Measurement of fictive temperature of silica glass optical fibers

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温度计量名词术语

MV_RR_CNG_0283 温度计量名词术语规范1. 温度计量名词术语说明编号JJF1007-1987名称(中文）温度计量名词术语(英文）归口单位起草单位主要起草人凌善康(中国计量科学研究院热工处)李而明(中国计量科学研究院热工处)批准日期实施日期替代规程号适用范围主要技术要求是否分级否检定周期（年）附录数目无出版单位中国计量出版社检定用标准物质相关技术文件备注2. 温度计量名词术语摘要一一般术语1 热平衡 (Thermal equilibrium)当物休吸收的热量等于放出的热量，物体各部分都具有相同的温度时，物体呈热平衡；或两个以及多个物体之间，通过热量交换，彼此都具有相同的温度时，物体间呈热平衡。

2 温度 (Temperature)温度是描述系统不同自由度之间能量分布状况的基本物理量。

温度是决定一系统是否与其他系统处于热平衡的宏观性质，一切互为热平衡的系统都具有相同的温度。

分子运动论以微观的角度来观察，温度是与大量分子的平均动能相联系，它标志着物体内部分子无规则运动的剧烈程度。

注：温度是七个基本物理量之一。

3 测温学 (Thermometry)研究温度测量的理论和方法。

4 温标 (Temperature scale)温度的数值表示法。

5 经验温标 (Experimental temperature scale)借助于某物质的物理参量与温度变化的关系，用实验方法或经验公式构成的温标。

例：现行的国际实用温标，曾采用过的摄氏温标和华氏温标等。

6 热力学温标 (Thermodynamic temperature scale)以热力学第二定律为基础的温标。

注：根据卡诺定理的推论可知，工作于两个恒定热源之间的一切可逆卡诺热机的效率与工作物质无关，只与两个热源的温度有关。

这样定义的温标称为热力学温标或开尔文温标。

7 热力学温度 (Thermodynamic temperature)按热力学原理所确定的温度。

MODIS Land Surface Temperature as

MODIS Land Surface Temperature as an index of surface air temperature for operational snowpack estimationEylon Shamir a ,⁎,Konstantine P.Georgakakos a ,ba Hydrologic Research Center,12555High Bluff Drive,Suite 255,San Diego,CA 92130,USA bScripps Institution of Oceanography,UCSD,La Jolla,CA 92037,USAa b s t r a c ta r t i c l e i n f o Article history:Received 26November 2013Received in revised form 26April 2014Accepted 1June 2014Available online 24June 2014Keywords:MODIS LSTLand Surface Temperature Surface air temperature Snow pack Snow 17Regional operational modeling systems that support forecasters for the real-time warning of ﬂash ﬂood events often suffer from lack of adequate real-time surface air temperature data to force their accumulation and ablation snow model.The Land Surface Temperature (LST)product from MODIS,which provides four instantaneous readings per day,was tested for its feasibility to be used in real-time to derive spatially distributed surface air temperature (T a )forcing for the operational snow model.The study was conducted in the Southeast region of Turkey using an atypically dense network of hourly T a ,daily snow depth,snow water equivalent (SWE),and rainfall datasets for the period:October 2002–September 2010.A comparison between the T a and the corre-sponding LST grid-cell data indicated close associations that are different in nature for periods with and without snow on the ground.The LST-derived T a was compared with that obtained from on-site gauge-based interpola-tion procedures and climatological time series.The LST-derived T a was found inferior only to the T a derived from the interpolation of the dense gauge network (31-gauges).Snow-pack simulations using estimated T a time series were compared to simulations that were forced by the observed T a at each site of 18sites.The LST-derived T a performed well in simulating snow mass and maximum SWE magnitude,while it did not represent well the timing of the annual peak of SWE and the duration of spring melt.Our study concluded that the MODIS/LST product can be a valuable additional source of real time forcing data for regional operational snow models,especially in remote mountainous areas with sparse telemetric data.©2014Elsevier Inc.All rights reserved.1.IntroductionSnow accumulation and ablation models that track the snowpack seasonal evolution of the energy and mass balance have been applied routinely worldwide to evaluate the snowpack and melt characteristics.In operational setups which require real-time measurements to repre-sent watershed scale snowpack characteristics,surface air temperature is often a key observed variable that serves as an index for a range of energy ﬂuxes in the atmosphere –snow pack interface and the internal snowpack (e.g.Anderson,1973and 2006).A major uncertainty source in the output of these snow models stems from the commonly insuf ﬁ-cient density of the in-situ meteorological observation network that is required to derive reliable and accurate estimates of energy ﬂuxes and their spatial variability.In mountainous regions with complex terrain and few gauges this uncertainty is expected to be larger (e.g.Bales et al.,2006).In addition,in complex terrain the use of a constant to describe the lapse rate and associate temperature in different elevations adds uncertainty,because in these regions the lapserate varies considerably,being dependent on the synoptic conditions (e.g.Lundquist &Cayan,2007).Snow model sensitivity to surface air temperature (T a )is well demonstrated in Fig.1.The upper panel of the ﬁgure compares simula-tions of snow water equivalent (SWE)for a selected meteorological station in Southeastern Turkey using observed and interpolated surface air temperatures from a relatively (and atypically)dense observation network (lower panel).The details about the snow model,air surface temperature dataset and the interpolation procedure will be further discussed in the following sections.Clearly,these two surface air temperature time series yield a substantial difference between the simulations of the snow water equivalent (SWE)during the winter accumulation and spring ablation time.The sensitivity of the snow model to the surface air temperature even during periods with small temperature differences is attributed to the nonlinear behavior of the snow model and the cumulative effect of the error with the progression of the snow season (e.g.Shamir &Georgakakos,2006).This uncertainty associated with the interpolation of surface air temperature is added to the uncertainty associated with the representa-tion of the energy ﬂuxes as functions of surface air temperature to yield the model simulation uncertainty.Remote Sensing of Environment 152(2014)83–98⁎Corresponding author.E-mail address:Eshamir@ (E.Shamir)./10.1016/j.rse.2014.06.0010034-4257/©2014Elsevier Inc.All rightsreserved.Contents lists available at ScienceDirectRemote Sensing of Environmentj o u r n a l h om e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /r s eIn this study we explore the applicability of the Moderate Resolution Imaging Spectroradiometer (MODIS)Land Surface Temperature (LST)product as a source of information to develop real-time surface air temperature forcing for the snow model.Our motivation to use the MODIS LST product as a proxy for surface air temperature is driven by its potential to resolve the ﬁner scale features of variability which are commonly not inferable from in-situ gauge networks in complex terrain.In the following we present a feasibility study conducted in South-east Turkey.To our knowledge,this is one of the handful studies of LST MODIS in snow environment conducted in latitudes lower than 40°N.Following literature review,introduction of the study area,data,and procedures (Section 2)we discuss and evaluate the association between the LST and observed surface air temperature.In Section 3the availability of valid LST reports for the study region is evaluated,and a comparison between surface air temperature derived from the LST product and other commonly available time series is presented.Section 4compares the effect of the interpolated T a on the simulation of snow pack.Study conclusions are provided in Section 5.1.1.Literature reviewEnergy exchange ﬂuxes at the land-surface are largely in ﬂuenced by T a ,LST and their difference.Unlike T a that is commonly measured at a 2m height,LST has not been routinely measured in meteorological stations.In the U.S.for example,less than 2%of the snow measuring automatic stations measure radiant LST (Raleigh,Landry,Hayashi,Quinton,&Lundquist,2013).The complicated interlinks between LST and T a can be demonstrated by examining the energy exchange equation between the land surface and the immediate atmosphere:1−αðÞR s ↓−R L ↑þR L ↓−G ¼H þλEð1Þwhere R S ↓is the incoming shortwave radiation,R L ↓and R L ↑are the incoming and outgoing longwave radiation,respectively,αis the surface albedo,G is the ground heat ﬂux,and H and λE are the sensible and latent heat ﬂuxes,respectively.The units of the energy ﬂuxes are in power per area (e.g.W m −2).All the energy ﬂux terms in Eq.(1)are dependent on LST,T a ,or their difference.The longwave radiation ﬂux association with temperature is explained by the Stephan –Boltzmann's equation,which ascribes R L ↓as a function of T a and the atmospheric emissivity,and R L ↑as a function of LST and the surface emissivity.The magnitude and direction of the turbulent latent and sensible heat ﬂuxes,as seen in the equations below,are controlled by the difference between T a and LST.H ¼C H U T a −LST ðÞð2ÞλE ¼C E U e a −e s ðÞð3Þwhere C H and C E are the bulk transfer coef ﬁcients for heat and moisture,respectively (kJ/m 3°C),U is the wind speed above the surface (m/s),and e s and e a are the vapor pressure (Pa)of the snow surface and the air surface,respectively.Notice that the vapor pressure is monotonically and positively associated with temperature.The ground ﬂux (G )is often estimated as a function of the LST,and the surface albedo is often associated with LST (Jin &Dickinson,2010),which determines the absorbed shortwave radiation at the land surface.As a general rule the land surface warms up in the morning to yield a positive LST −T a difference,whereas during the night LST cools faster and the difference is negative.In dry soil,calm air,and clear sky condi-tions the LST follows the radiation cycle with a short time lag (~1h).In similar conditions for wet soil,the LST is considerably reduced because of latent heat releases from evaporation.Vegetation canopy cover050100150200250300350400450S n o w W a t e r E q u i v a l e n t (m m )-30-20-10010206-Hour IntervalT a i r (o C )Fig.1.SWE simulation using observed (solid black)and interpolated (red)air temperatures for Gauge #17920(2005–2006).The interpolation was based on a network of 31gauges.Lower panel shows the observed (solid black)and interpolated (red)surface air temperatures.84 E.Shamir,K.P.Georgakakos /Remote Sensing of Environment 152(2014)83–98depends on type and the fractional cover changes the albedo and modulates the fraction of shortwave radiation absorbed at the surface. The dominant impact of vegetation however,is associated with its evaporative cooling.Plant canopy actively exchanges absorbed solar radiation through evaporation and thus maintains daytime canopy temperature that is close to the ambient T a(e.g.Nemani,Pierce, Running,&Band,1993).Remotely sensed LST measurements often represent a mixture of soil and vegetation canopy temperatures.The observed portion of soil and vegetation varies with the viewing angle and the fraction and type of vegetation.LST measurements in these mixed areas are also inﬂuenced by the lower atmosphere and the temperature difference between the vegetation canopy and the soil background(Weng,Lu,& Schubring,2004).In snow,because of its low thermal conductivity and insulating characteristics,the surface layer quickly reaches temperature equilibri-um with the atmosphere even for large differences between LST and T a(e.g.,Liston,1995).Snow pack LST cannot exceed melting temperature(0.0°C)except for cases of vegetation litter(e.g.,Hardy,Davis,Jordan, Ni,&Woodcock,1998)or dust(e.g.,Painter et al.,2007).During calm nights radiative cooling can reduce the LST below the T a(5–10°C) and cold surface temperature often causes near surface inverse stable conditions that reduces turbulent mixing.Warmer snow surface temperature,as might seem counter intuitive,in general,decreases the snowpack's melting rate.This is because sensible and latent heat ﬂuxes decrease as a consequence of smaller temperature and vapor pressure gradients(see Eqs.2and3),and increase of outgoing longwave radiation(e.g.Sade et al.,2011).During periods of complete areal snow cover it is reasonable to assume that horizontalﬂuxes between the grid cells are less dominant than the verticalﬂuxes.However,in patchy snow pack during melt season the intergrid cell differences in vertical energyﬂuxes between the snow covered and uncovered areas create considerable horizontal ﬂuxes that introduce large uncertainty to the energy balance equation (Liston,1995).The relationship between LST and surface air temperature was stud-ied by many,both from theoretical and empirical perspectives.A few large scale global studies concluded that this relationship is dependent on local variables such as land use/cover,soil moisture,snow cover, frozen ground,regional microclimate conditions,terrain and local landscape features(drexler,Zhao,&Running,2011;Jin& Dickinson,2010;Prihodko&Goward,1997;Sade,Rimmer,Litaor, Shamir,&Furman,2011).1.2.MODIS LSTDetails of the MODIS LST algorithm,its day–night split-window regression,and its theoretical basis can be found in Wan and Dozier (1996),Wan and Li(1997),Wan(2003)and Wan(2008).The MODIS LST product can be made operationally available in near real-time, within hours of the satellite overpass,from the MODIS Rapid Response System(Pinheiro et al.,2007).Land Surface Temperature(LST)is an instantaneous measurement of the skin temperature that is mapped from the radiometric(kinetic) temperature and derived from the thermal IR(TIR)radiation emitted from the land surface.Because TIR measures radiance at the top of the atmosphere,during cloudy conditions the measured signal is from the cloud-top and therefore the MODIS LST is retrieved only in clear-sky conditions.Sensible heatﬂuxes emitted from the earth surfaces are detected by the MODIS satellite and are used to estimate instantaneous LST.The LST generalized split-window algorithm depends on the MODIS brightness temperature bands(11and12μm channels31 and32)and surface emissivity estimates for these two channels.The emissivity in the thermal infrared is estimated using regression coefﬁcients that depend on land cover classiﬁcation(MOD12Q1)and daily binary snow cover(MOD10_L2).During snow and ice conditions the emissivity is set to0.993and0.99for bands31and32,respectively (Wan,2008).The algorithm also requires dynamic estimates of the atmospheric transmission,which is derived directly from the MOD07_L2product of vertical atmospheric temperature and vapor proﬁles and the MODIS cloud masking product(MOD35_L2).In addition to night and day LST estimates,the product also includes information on the emissivity,view-angle,cloud-cover,time of acquisi-tion,and quality-control assessment for each grid cell.Under clear sky conditions the accuracy of the MODIS/LST product was reported to be within1°C for a temperature range of−10to50°C.It was also report-ed to perform better in desert regions(Wan et al.,2004).The performance of MODIS LST in snow and ice covered areas and under clear sky conditions was reported to be accurate within +/−1°C(Wan,Zhang,Zhang,&Li,2002)for a temperature range of −15–0°C(Hall et al.,2008).The accuracy of MODIS LST in snow and ice conditions and temperature below−15°C is still unknown.For these conditions it is reasonable to assume+/−1°C accuracy as report-ed by Wan et al.(2002)(Hall et al.,2008).Although the accuracy is assumed reasonable,Westermann,Langer,and Boike(2012)claim that during clear sky conditions the snow surface temperature is usually colder than during cloudy conditions,and therefore the MODIS LST in snow and ice has a systematic cold bias.MODIS LST was used to detect the thermal regime of permafrost. Several studies conducted in the Arctic found MODIS LST to correspond well with permafrost and the detection of thawing(e.g.,Langer, Westermannb,Heikenfelda,Dorna,&Boikea,2013for the Lena River Deltain in Siberia;Hachem et al.,2012for Northern Quebec,Canada). Hall,Nghiem,Schaaf,DiGirolamo,and Neumann(2009)used the MODIS LST product to detect melting areas in Greenland's ice sheet. Compared with shallow ground based measurements,the LST was found to have better association with surface air temperature and reported to perform better during periods with snow cover(Hachem, Duguay,&Allard,2012).Another study from the Arctic that compared among various LST products derived from polar orbiter satellites con-cluded that the MODIS LST product had the best association with surface air temperature(Urban,Eberle,Hüttich,Schmullius,&Herold,2013). Tight association between monthly MODIS LST and T a was also reported at the Lambert Glacier basin in East Antarctica(Wang,Wang,&Zhao, 2013).All the above described validation studies for LST in snow,ice and permafrost environment were conducted in high latitude relatively homogeneous snow and ice surfaces.However,only a handful of studies evaluated the performance of MODIS LST in mid-latitude mountainous terrain with seasonal snow pack.One example is aﬁeld study from the Italian Alps that reported correlation between the skin temperatures of snow and observed surface air temperature to be greater than0.85 and0.89for day and night,respectively(Colombi,De Michele,Pep,& Rampini,2007).This strong association enables derivation of detailed maps for surface air temperature in snow dominated mountainous terrain that can potentially improve the estimation of the spatial variability of melt.2.Data2.1.Study regionThe study was conducted in the Southeast region of Turkey (black thick rectangular outline in Fig.2).The study domain (500km×330km)contains the headwaters of the Euphrates and Tigris Rivers and other east-ﬂowing rivers draining into the Caspian Sea.The domain expands across two continental climate zones:south-eastern Anatolia and Eastern Anatolia.In the western part of the domain is the Anti-Taurus mountain range with average peak elevation at 3000m;while the eastern part near the border with Armenia is the Armenian Highlands mountain range that peaks at Mount Ararat85E.Shamir,K.P.Georgakakos/Remote Sensing of Environment152(2014)83–98(5137m).Turkey's largest lake,Lake Van,is situated in the mountains at an elevation of 1546m.The Southern slopes of the Anti-Taurus Mountains constitute a region of rolling hills and a broad plateau surface that extends into Syria.The region experiences severe winters with frequent heavy snow-fall events and warm summers.The dominant land cover is grasslandwith patches of closed and open shrubland and extended areas of cultivated agricultural land.The MODIS LST product was extensively validated for these dominant land cover of grassland and cultivated agriculture by Wan et al.(2002)and Wan (2008),respectively.Because of therelativelyFig.2.A map of the study area.123456789101112MonthsV a l i d L S T R e p o r t s (F r a c t i o n )31-gauges Oct 2002-Sept 2010Fig.3.Aqua and Terra monthly summary of the valid day and night LST reports (Oct 2002–Sep 2010)for grid-cells that are associated with the 31gauges of surface air temperature.MONTHP E R C E N TAvg. Reports Binary Snow Product: Sept 2002 - Oct 2010Fig.4.Classi ﬁcation of the Snow Cover Area (SCA)reports from Aqua into valid reports (red),clouds (green)and no data (black).In addition,the valid reports that indicated snow cover are in blue.86 E.Shamir,K.P.Georgakakos /Remote Sensing of Environment 152(2014)83–98low vegetation canopy,the seasonal snow pack in such landscape is relatively homogeneous.Therefore,it is expected that during periods of snow cover the LST signal will represent well the snow surface temperature as reported in the validation studies mentioned in Section 1.2.2.In situ observationsMeteorological time series of observations for 1October 2002–30September 2010were received from the Turkish State Meteorological Service (TSMS).For the study domain we identi ﬁed 31stations with hourly surface air temperature and daily snow survey information,such as snow water equivalent and snow depth (white triangles in Fig.2).Eighteen of those locations also have daily precipitation records.The range of station elevations is 370–2300m,with a mean average el-evation of 1300m.Most of the stations are located in areas that were identi ﬁed as either cultivated crop or grassland.This dataset represents a fairly dense observation network with an average distance between nearest neighbors equal to 37km (range 11to 80km).Such network density is considered highly dense by operational network standards,especially for high mountains and rugged terrain regions,as in the study domain.2.3.MODIS LST data for the study areaThe LST product from the Aqua and Terra spacecraft MODIS sensors was retrieved from NASA's Earth Observing System Data and Informa-tion System for 1October 2002–30September 2010.We used version 5of the daily Aqua and Terra Land Surface Temperature/Emissivity L3which is available globally at 1km in a sinusoidal projection (MOD11A1and MYD11A1)and use the generalized split-window algorithm (Weng et al.,2004).The study area is covered by a single tile that includes 1200rows and columns (h21v05).Most overpasses for Terra [Aqua]occurred around 11:00and 23:00[13:00and 01:00]local time.2.3.1.LST product availabilityFor the study region and the duration of analysis the LST dataset has 505missing daily products (out of 6574),most having occurred prior to 2005.The availability of valid LST reports,which are cases with actual temperature reports,for the study duration and for the grid-cells that match the 31surface air temperature gauges was summarized by month and is presented in Fig.3.It is seen that valid LST products are available less than 40%of the time during November –April.The availability of valid LST products rises to about 60–80%during June–parison of MODIS LST and 31surface air temperature gauges.Black dots indicate gauges of snow measurement and gray are gauges with measurement of no snow.Red lines are regression estimates and con ﬁdence bounds (5%and 95%)for the snow and no snow separately.87E.Shamir,K.P.Georgakakos /Remote Sensing of Environment 152(2014)83–98September for Aqua and Terra,respectively.We note that only 2%and 0.5%of the missing LST products from both Terra and Aqua lasted longer than 15and 26consecutive days,respectively.Fig.4shows the status of the MODIS snow cover product for the same period and domain available from the Aqua 500m daily snow cover product (MYD10A1)(Hall,Riggs,&Salomonson,1995).As mentioned above,the snow cover product is being used as input to the MODIS LST algorithm.In Fig.4we consider the entire dataset as valid and invalid reports.Valid reports are considered as grid-cells that report snow cover,bare ground,or water;and invalid reports are grid-cells that considered as cloud masking and missing data that are ﬂagged by the quality assessment index.In addition,as a point of reference,we present the percent of snow cover reports (out of the total),which is also part of the valid report category.During November –April,the period with reported snow cover (blue line),the cloud cover was reported in 50–70%of the time (red line).On the other hand,cloud cover decreased considerably during the summer months,and valid daily reports of the product (green line)became abundant.Notice however,that for this period (summer)the number of snow cover reports is marginal (blue line).The black line,which ranges between 8and 12%,summarizes the periods in which the SCA product quality assessment index indicated a problem with-15-10-50510152025Days: 1 Aug 2005 - 31 July 2006T e m p e r a t u r e D i f f e r e n c e (L S T -T a )o CFig.6.An example of annual plot (August 2005–July 2006)of LST,T a ,and snow water equivalent from a gauge that is located in the southeast part of the study domain.The upper panels show the day and night Terra (left)and Aqua (right)LSTs (red and black circles,respectively),day and night gauge air surface temperatures (red and black stars,respectively)and snow water equivalent (cm)(black line).The differences between the LST and the T a are shown for Terra and Aqua (left and right,respectively)and for day and night red and black markers,respectively.88 E.Shamir,K.P.Georgakakos /Remote Sensing of Environment 152(2014)83–98the SCA product.The prevalence of cloud cover in the study region,which obscures the MODIS/SCA product during the snow accumulation season,was previously documented by Tekeli,Akyürek,Şorman,Şensoy,and Şorman (2005and 2006)and Tekeli,Şensoy,Şorman,Akyürek,and Şorman (2006).The analyses presented in Figs.3and 4indicate that the LST product is highly infrequent during the winter,when snow is likely to accumulate,and becomes available with higher frequency during spring –summer (melting period).2.3.2.LST correspondence with surface air temperatureThe correspondence between the LST and gauge surface air temper-ature for the study region is shown in Fig.5.The black [gray]dots in this ﬁgure indicate cases in which snow [no snow]was reported at the gauge locations.The red lines show the estimated linear regressions and the 5and 95percentile prediction con ﬁdence intervals,calculated separately for gauges with and without snow.The data in the ﬁgure was screened through the quality control procedure that is described in Section 3.3.Although there is an overall monotonic association between the gauges and the LST values,there is signi ﬁcant scatter in the association.It is also seen that the relationships during snow and no snow periods are different as seen by the slopes of the regressions.In general during periods of snow on the ground small changes in LST correspond with a larger range of surface air temperature values.During these periodsthe LST values are below or equal to 0°C,while the surface air temper-ature can possibly rise above freezing temperature.The intra-annual correspondence between LST from Terra and Aqua,gauge surface air temperature,and SWE is further demonstrated in Fig.6,for a high elevation meteorological station (~2300m)in a grass-land dominated land cover at the southeast corner of the study domain.During periods of no snow the LST day –night amplitude brackets the surface air temperature with LST being warmer [colder]than surface air temperature during the day [night](upper panels).During periods with snow measured at the gauge (black solid line),the day –night amplitudes of the LST and surface air temperature were comparable.The LST temperature remained consistently below zero while the surface air temperature occasionally increased above zero.Although snow was measured at the gauge as late as mid-March,the LST increased above zero about a month earlier.The lower panels,which depict the temperature differences between the LST and T a ,show that the daily LST was warmer than T a during no snow periods.This difference ranges 0–20°C with highest differences observed in the summer (June –September).During periods with snow on the ground the daily LST was occasionally colder than the T a .The night LST was consistently colder than T a throughout the year and about an additional 5°C colder than the T a during periods with snow cover.The daily LST values from both sensors were comparable for this location,and although one might expect a warmer Aqua LST because its overpass is closer to the daily maximum short wave irradiance,no-40-200204000 Local time-40-200204006 Local Time200400600-200204060 October 2002 -September 2004 (Days)12 Local Time200400600-40-200204018 Local Time-40-200204000 Local time-200204006 Local Time200400600-20204060October 2002 -September 2004 (Days)200400600-200204018 Local Time-40-200204000 Local time-40-200204006 Local Time-200204060October 2002 -September 2004 (Days) -200204018 Local Time -40-2002000 Local time-40-20204006 Local Time-20204060October 2002 -September 2004 (Days)-40-200204018 Local TimeT e m p e r a t u r e (o C )T e m p e r a t u r e (o C )T e m p e r a t u r e (o C )T e m p e r a t u r e (o C )Fig.7.Two years (1October 2002–30September 2004)of LST and surface air temperature at 00,06,12,and,18hour local time for four selected stations that represent different elevations.89E.Shamir,K.P.Georgakakos /Remote Sensing of Environment 152(2014)83–98distinct differences are apparent.The night time LST however,shows a persistent colder temperature (about 2°C)for the Aqua sensor.Spring LST values that exceeded 0°C although snow was measured at the gauge indicate considerable uncertainty in the association between LST and T a .This uncertainty is likely attributed to the patchi-ness of snow cover that is prevalent during spring times and the classi ﬁcation of the LST product as snow-free grid-cells while patches of snow existed in high elevations.During spring it is expected that in-situ snow reports will often misrepresent the patchiness of snow cover at their corresponding grid-cells.In addition,it is expected that during spring time when daily surface air temperature can rise to relatively warm temperatures the snow surface temperature can't rise above freezing.The generalized split-window algorithm for version 5ingests binary snow cover estimates and therefore grid cells that are fractionally covered with snow are assigned to either completely covered or not covered.This in turn increases the uncertainty in the LST estimates and likely to under (over)estimate in cases of low (high)snow fraction-al cover (Rittger,Painter,&Dozier,2012).The recent addition of the fractional snow cover to the MODIS operational products can potentially be incorporated to improve LST estimates in fractionally snow covered grid cells (Dozier,Painter,Rittger,&Frew,2008).Another depiction of the relationship between LST and surface air temperature is provided in Fig.7.Two years of LST and T a daily time series for 0,6,12,and 18hour local time are plotted from four gauges in a grassland environment that were selected in order to represent different elevations.The interpolation of the MODIS LST from the obser-vation times to these hours and for the periods for which LST valid reports are unavailable is described in Section 3.1.The general patterns among these selected gauges are similar except that in the higher-elevation gauges (lower panels)during the winters there are more missing LST values,and the reported LST values for these periods are based on climatological values for their estimates and thus appear as straight lines.The plot further demonstrates theStart t ing g tim m e Oc c tob b er 1 (6-h h our r tim m e int t erv v als)Fig.8.Sensitivity of simulated SWE to biased air temperature (+/−3°C)on each of the three processes:temperature threshold to distinguish between rain and snow (left),snow melt(middle)and snowpack energy balance during non-melt periods (right).-40-2002040MOD 11am-40-2002040MOD 22pm-40-2002040Surface Air Temperature (o C)MYD 13pm-40-2002040MYD 02amM O D I S L S T (o C )Fig.9.Scatter plots of observed hourly surface air temperature from 31gauges and the corresponding LST values for the day and night overpasses from Terra and Aqua satellites.The red dots indicate cases in which the difference between T a and LST exceeds 15°C.90 E.Shamir,K.P.Georgakakos /Remote Sensing of Environment 152(2014)83–98。

外文翻译室内环境温度监测(英文原文)

Sustainable Cities and Society 13(2014)57–68Contents lists available at ScienceDirectSustainable Cities andSocietyj o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /s csMonitoring building energy consumption,thermal performance,and indoor air quality in a cold climate regionTanzia Sharmin a ,Mustafa Gül a ,∗,Xinming Li a ,Veselin Ganev b ,Ioanis Nikolaidis b ,Mohamed Al-Hussein aa Department of Civil and Environmental Engineering,University of Alberta,9105116th Street,Edmonton,Alberta,Canada bDepartment of Computing Science,2-21Athabasca Hall,University of Alberta,Edmonton,Alberta,Canadaa r t i c l ei n f oKeywords:Sensor-based monitoring system Energy usageBuilding envelope thermal performance Indoor air qualityBuilding management systema b s t r a c tBuildings are major consumers of the world’s energy.Optimizing energy consumption of buildings during operation can signiﬁcantly reduce their impact on the global environment.Monitoring the energy usage and performance is expected to aid in reducing the energy consumption of occupants.In this regard,this paper describes a framework for sensor-based monitoring of energy performance of buildings under occupancy.Different types of sensors are installed at different locations in 12apartment units in a building in Fort McMurray,Alberta,Canada to assess occupant energy usage,thermal performance of the building envelope,and indoor air quality (IAQ).The relationship between heating energy consumption and the thermal performance of building envelope and occupant comfort level is investigated by analyzing the monitoring data.The results show that the extent of heat loss,occupant comfort level,and appliance usage patterns have signiﬁcant impacts on heating energy and electricity consumption.This study also identiﬁes the factors inﬂuencing the poor IAQ observed in some case-study units.In the long term,it is expected that the extracted information acquired from the monitoring system can be used to support intelligent decisions to save energy,and can be implemented by the building management system to achieve ﬁnancial,environmental,and health beneﬁts.©2014Elsevier Ltd.All rights reserved.1.IntroductionThe building sector accounts for about 30%of total green-house gas (GHG)emissions in Canada (NRC,2006).Furthermore,the construction and operation of buildings are responsible for over a third of the world’s energy consumption (Straube,2006).Data shows that energy consumption and GHG emissions in build-ing sector are growing at an advanced rate than in other sectors (Akashi &Hanaoka,2012).As a result,reducing energy consump-tion has become essential to planning,construction,and use of buildings from the environmental point of view (Stoy,Pollalis,&Fiala,2009).This also entails that the building sector has con-siderable potential for energy and energy-related CO 2emissionssavings (Gökc¸e &Gökc ¸e,2013).According to the International Energy Agency,the building sector can reduce energy consump-tion with an estimated energy savings of 1509Mtoe (million tonnes of oil equivalent)by 2050.Furthermore,through energy-efﬁcient building design,carbon dioxide (CO 2)emissions can be reduced,∗Corresponding author.Tel.:+17804923002.E-mail address:mustafa.gul@ualberta.ca (M.Gül).which can possibly mitigate 12.6Gt (gigatonnes)of CO 2emissions by 2050(International Energy Agency,2010).Energy consumption by built environments can be reduced through new designs,technologies,and materials;proper control;and the use of effective energy management systems by consider-ing factors such as building orientation,shape,wall–window ratio,insulation,use of high-efﬁciency windows,and natural ventila-tion (Dawood,Crosbie,Dawood,&Lord,2013).However,electrical loads,especially miscellaneous electrical loads (involving a range of products,devices,and electrical equipment in some combina-tion,common in every household)consume a signiﬁcant portion of total building energy (Hendron &Eastment,2006).In Canada,the residential building sector consumes approximately 16%of total secondary energy usage (NRC,2006).According to Statistics Canada,in 2007the average Canadian household consumed 106GJ (gigajoules)of energy,with the national total reaching 1,368,955TJ (terajoules)(Statistics Canada,2007).A substantial share of total energy consumption is due to improper use of appliances,and elim-inating this wastage can reduce the overall energy consumption by approximately 30%in buildings (US DOE Energy Information Administration,2003).Today it is important to focus on greater energy efﬁciency to reduce our impact on the environment by/10.1016/j.scs.2014.04.0092210-6707/©2014Elsevier Ltd.All rights reserved.58T.Sharmin et al./Sustainable Cities and Society13(2014)57–68reducing fossil fuel consumption(Gua,Sun,&Wennersten,2013; Sharmin,Li,Gökc¸e,Gül,&Al-Hussein,2012).Built environments also have a signiﬁcant impact on human health.The extent of a building’s impact on human health and the environment depends on the building design,materials,and the methods used for construction and operation(Vittori,2002). According to the Science Advisory Board of the United States Envi-ronmental Protection Agency(EPA),indoor environment stands among the topﬁve environmental risks to public health.In Canada, people spend an average of89%of their time indoors and66%of their time indoors at home(Leech,Wilby,McMullen,&Laporte, 1996),and there is a possibility that people with weak immune systems may suffer from asthmatic symptoms or other respiratory health problems as a result of exposure to poor indoor air quality (Vittori,2002).Considering the fact that human health is affected by poor indoor air quality(IAQ),it is important to maintain a healthy IAQ in the interest of occupant health.Continuous monitoring of indoor environmental quality(IEQ)can thus play a signiﬁcant role in maintaining healthy indoor environments.A signiﬁcant aspect of assessing the sustainability of a building is the monitoring of energy performance(Berardi,2012).Recent innovations in sensing,data logging,and computing technologies have improved monitoring of indoor environment and energy per-formance of buildings.“Real-time”energy performance and IEQ monitoring are signiﬁcant from the perspective of real-time feed-back to promote energy-saving behavior,and also for maintaining healthy IAQ.Proper targeting and monitoring of energy consump-tion and continuous energy management can be effective strategies for improved energy performance of buildings,and can result in reductions in operating costs of facilities(Lee&Augenbroe,2007; Sapri&Muhammad,2010).Research studies examining the effect of energy feedback information on occupant behavior have shown that real-time feedback can be a powerful impetus for behavioral change.McClelland and Cook(1980)ﬁrst tested the impact of con-tinuous energy feedback on electricity usage.The results showed that on average electricity usage was lowered by12%in the homes with continuous electricity usage feedback compared to the homes with no usage feedback system(as cited in Allen&Janda,2006). In another study,a technical research university has monitored energy usage to reduce energy costs through an energy awareness program that offered departments a chance to receive payments of up to30%of the savings achieved.The departments had accom-plished energy savings(saving about$300,000per year)after one and half years of monitoring through improved operations and maintenance procedures and reduced their usage from about44 million kWh to40million kWh(Energy Star,2002).Hutton,Mauser, Filiatrault,and Antola(1986)have shown how the feedback pro-vided by monitoring helped to conserve energy for over75%of the subjects in25households in three cities.In a case regarding water usage,the city of Boston,MA,USA was unable to account for the use of50%of the water used in its municipal water system and,after installing meters,water that was unaccounted for had dropped to 36%(Grisham&Fleming,1989).Another study has shown that an effective energy management system can identify problems in an operating system which might not otherwise have been identiﬁed (Mills&Mathew,2009).Yang and Wang(2013)has shown that energy management systems can also provide comfortable building environments with high energy efﬁciency.Literature reviews from the last ten years show that usage of energy can be reduced from0%to20%by using a variety of feed-back mechanisms(Abrahamse,Steg,Vlek,&Rothengatter,2005). However,despite the fact that providing appropriate feedback can signiﬁcantly reduce the overall energy consumption,relying only on occupants’awareness and behavioral change might not be an effective approach.In a recent study,wireless AC plug-load meters and light sensors were deployed in a computer science laboratory as a case study in energy monitoring.The study reported that more than30%energy savings were achieved immediately after installing a monitoring system,but that the savings were subse-quently reduced to less than4%of the week one level by the fourth week of the study.It light of this case,it might be considered that an effective solution for reducing energy consumption could be an automated energy management system,in addition to user coop-eration(Jiang,Van Ly,Taneja,Dutta,&Culler,2009).Major progress has been made in recent years in accomplish-ing greater awareness(Jiang et al.,2009),showing that advanced measurement of energy usage enables reduction of energy con-sumption.While the approach of monitoring energy usage is useful to achieveﬁnancial beneﬁts,a holistic monitoring of the perfor-mance of the building system can also be used to identify the factors inﬂuencing irregular energy usage or non-standard IEQ.Any information pertaining to irregularity of building system perfor-mance can contribute to building management systems intended to support operational improvement,and can also provide the infor-mation needed to encourage behavioral and operational changes by building occupants and operators.Monitoring is essential to achieving an energy-efﬁcient building management system,but sensor-based monitoring is sometimes costly.In recent years more cost-effective high performance sensor technologies have been introduced,such that the beneﬁts of utilizing this technology outweigh the associated costs.Continuous collection of the indi-vidualized energy use information would translate into increased energy use awareness,identiﬁcation of problems in the building management system,and notiﬁcation of irregular energy usage and non-standard indoor environmental parameters,all of which can lead to more sustainable building operations.However,it remains an open question whether the apparent additional understanding would be enough to justify the cost of installation,maintenance, and calibration of sensors.This paper thus offers a methodological approach by which to extract useful information by establishing relationships and studying patterns across different components of a building management system,facilitated by the installation of various sensors in a case study,the“Stony Mountain Plaza”project in Fort McMurray,Alberta,Canada.1.1.Objective and scopeThe objective of the sensor-based monitoring system adopted in this research is to provide relevant information regarding effec-tive management of building systems in cold-climate regions.The implemented monitoring system can be used for increasing energy performance and occupant comfort while reducing energy and water consumption.In this study,the ASHRAE standard specifying environmental parameter ranges(indoor air temperature,RH,CO2 level)has been used to deﬁne occupant comfort.A holistic exam-ination of the performance of the building system(energy usage, thermal performance,and IEQ)helps to determine whether or not the system is working efﬁciently by identifying correlations across different monitoring components.A more advanced understand-ing of the recorded data is expected to result in changes in building operations through the use of intelligent controls that automati-cally adjust to environmental requirements.It is expected that the extracted information and strategies acquired from the monitor-ing system can be implemented within the building management system to achieveﬁnancial,environmental,and health beneﬁts. 2.Methodological approachIn order to conduct a holistic examination of the performance of the building system under consideration,operating energy usage (e.g.,electrical energy usage,space heating energy usage,andT.Sharmin et al./Sustainable Cities and Society13(2014)57–6859Fig.1.Objective and methodological approach.household water usage);thermal performance of the building; and IAQ under occupancy are monitored.Twelve sample units are chosen in the building to be monitored for energy performance. Different types of sensors are installed in these individual units in order to monitor different components.Finally,recorded data are analyzed in order to extract useful information.Fig.1shows the objective and the monitored components for building energy performance under occupancy.2.1.Sample case-study unitTwo four-storey residential buildings have been constructed as part of the“Stony Mountain Plaza”project in Fort McMurray, Alberta,Canada.Both buildings are oriented with their longer axis facing north and south.Building1has70units while building2has 55units.There are two types of units in building1:one-bedroom and two-bedroom units.For monitoring building energy perfor-mance,three case-study units in eachﬂoor of building1with the same relativeﬂoor plan position are selected:(1)Type‘A’unit (one-bedroom)facing north,(2)Type‘A’unit(one-bedroom)facing south,and(3)Type‘B’unit(two-bedroom)facing south.The sam-ple households are assigned code numbers1–12,and the speciﬁc locations of the units in theirﬂoors are not revealed for the sake of privacy.Fig.2displays the12case-study units.2.2.Types and locations of installed sensorsDifferent types of sensors are used for different types of required information in this assessment of building energy performance under occupancy.For electrical energy usage,Brultech ECM-1240 power meters are used.Each apartment receives power from two phases(phases A and B).Two power meters,one for each phase, recording the total energy for each load(in Ws)are therefore installed in each case-study unit.One Kamstrup MULTICAL601 heating meter is used for monitoring the energy from the water circulation heating system.Three sensors are also used for this purpose:oneﬂow meter and two temperature probes(for supply temperature,T s,and return temperature,T r).The heating meter records the total volume(L),total mass(g),currentﬂow(L/s),cur-rent T s and T r(◦C),and total energy(Wh).The energy consumed by the water circulation heating system can be calculated satisfying Eq.(1).E=V(T s−T r)k(1) where V:volume;T s:supply temperature;T r:return temperature; k:thermal coefﬁcient.For monitoring household water usage,Minomess130water meters are used.There are two water meters in each apartment, one monitoring total incoming water and one monitoring output (cumulative hot water usage in the apartment)of the hot water tank.Two heatﬂux sensors(HFT3Soil Heat Flux Plate)are used for monitoring thermal performance of the building envelope:one measuring the heatﬂux(W/m2)through the studs and the other measuring the heatﬂux through the insulation.The sensor used for IAQ measurement is the IAQ Point air monitoring device man-ufactured by Honeywell Analytics.This device records real-time values of CO2(ppm),RH(%),and temperature(◦C)(Sharmin et al., 2012).The locations of the sensors for one-bedroom units and two-bedroom units are as shown in Fig.3.2.3.Development of system architectureThe power consumption meters(Brultech ECM-1240)commu-nicate using ZigBee with four EtherBee gateways(one on each ﬂoor),which are connected by a CAT5Ethernet cable to a single-board computer through a5-port switch.The energy meter andthe Fig.2.Case-study building and selection of case-study units.60T.Sharmin et al./Sustainable Cities and Society 13(2014)57–68Fig.3.Location of sensors in case-study units.IAQ sensor use the LonTalk protocol to communicate with an iLON smart server,which is also connected to the single-board computer where the data are being encrypted and transmitted to a database server through a secured connection over the Internet.The heat ﬂux sensors are connected to the CR1000data logger (Campbell Scientiﬁc,Inc.)through a Solid State Multiplexer (Campbell Scien-tiﬁc,Inc.),which makes it possible to connect all 24of the heat ﬂux sensors to a single data logger.The data logger converts the ana-log signal from the heat ﬂux sensors into digital values and sends these values to the SBC through an Ethernet interface (Sharminet al.,2012).Fig.4provides a ﬂowchart of the data collection system adopted in this project.3.Data analysisThis section discusses ﬁndings based on the collected data to assess building energy performance under occupancy.The data sets used for the analysis presented in this paper have been collected during regular operation of thebuilding.Fig.4.System architecture for data collection.T.Sharmin et al./Sustainable Cities and Society13(2014)57–6861Fig.5.Data analysis framework for electrical energy consumption.3.1.Measurement of electrical energy usageAccording to Statistics Canada(2007),Alberta’s average per household use of electricity in2007was the lowest among all provinces(26GJ).A possible reason for this low electricity con-sumption might be the comparably high rate of natural gas consumption in Alberta due to the low price of natural gas.In this paper,26GJ is set as the annual per household usage threshold. We consider the electricity consumption for individual appliances and the total electricity consumption for the case-study units. By measuring the electricity consumption of occupants,building management can pursue appropriate measures(i.e.,setting an opti-mum usage limit)if the electricity usage continuously exceeds the threshold of electricity usage established.Fig.5shows the data analysis framework for electrical energy consumption,while Fig.6shows the total electricity consump-tion by case-study unit(except unit8,because of missing data). It is observed in Fig.6that the electricity consumption by units7 (Type A)and9(Type A)in2012exceeds the26GJ threshold.Even though units7and9are type A(one-bedroom)units,the electric-ity consumption of these units is higher than the other case-study units.The data analysis framework(Fig.5)adopted in this study identi-ﬁes factors that inﬂuence higher electricity consumption by a given unit by comparing the electricity consumption of different appli-ances of the selected unit with the average electricity consumption of individual appliances of all the case-study units.Fig.7presents the inﬂuencing factors for higher electricity consumption of3case-study units(units7,9and10).These three units are chosen as examples since two of them(units7and9)exceed the26-GJ thresh-old and the other unit(unit10)has comparatively higher electricity usage but appears to be inﬂuenced by different factors than units7 and9.Our data analysis shows that the primary factors inﬂuencing the higher electricity consumption in unit7are the bedroom appli-ances,electrical duct heating,kitchen plug,and kitchen-bathroom lighting,since electricity consumption by these appliances in unit 7is much higher than the average of the11case-study units for these appliances.A possible reason for higher electricity consump-tion in the bedroom of unit7may be the use of electrical heating radiators by occupants.On the other hand,bedroom appliances and oven usage for unit9and hot water tank and refrigerator usage for unit10are identiﬁed as the primary inﬂuencing factors accounting for the higher electricity consumption of the respective units.It is worth noting that household energy use can vary based on a number of factors,including the number of occupants,lifestyle, and usage of different appliances.With the continuous monitor-ing of electrical energy consumption,it is possible to identify the inﬂuencing factors of higher electricity consumption of occupants and to set an optimum value for electrical energy usage accord-ingly.Based on the monitoring of electricity usage carried out in this study,building management can set an appropriate optimum range of yearly energy usage by occupants.3.2.Measuring thermal performance of building envelope and space heating energy usageFor this research,the heatﬂux—the rate of heat energy transfer—through studs and insulation is also monitored.Since studs(working as thermal bridges between outdoor and indoor environments)lose more heat than does insulation,this research measures heatﬂux through studs and insulation separately.In order to assess the impact of orientation on heatﬂux for the case-study units,annual average heatﬂux through studs and annual average heatﬂux through insulation are compared for north-facing and south-facing units.At eachﬂoor level,one north-facing unit and one south-facing type A(one-bedroom)unit are selected in order to compare heatﬂux.As expected,the collected data in Fig.8shows that north-facing units have greater heat loss than south-facing units when considering the2nd and3rdﬂoor.However,contrary to expectations,at the ground(stud)and topﬂoor,south-facing units have greater heat loss than north-facing units.The recorded data in Fig.8gives an inconclusive result.In order to identify long-term patterns(if any)of heatﬂux for different orientations,it is impor-tant to monitor the data for a few years.If patterns of heatﬂux for differentﬂoor levels(variations with respect to height)or differ-ent orientations are identiﬁed,measures(i.e.,increasedinsulation) Fig.6.Electricity consumption for case-study units.62T.Sharmin et al./Sustainable Cities and Society 13(2014)57–68Fig.7.Electricity consumption of individual appliances by units 7,9and10.Fig.8.Heat ﬂux for different orientations and ﬂoor levels in 2012.can be taken to reduce heat ﬂux for the units with higher rates.Increasing the thermal performance of the building envelope also provides an opportunity to reduce signiﬁcantly the heating loss of a building,but this is beyond the scope of this study.Fig.9shows the data analysis framework adopted in this study for heating energy consumption.The framework examines the impact of heat ﬂux and outdoor temperature on heating energy consumption.The indoor air temperature maintained in the unit is also compared with the standard indoor temperature range in order to gain understanding of the relationship between occupant comfort level and heating energy consumption.As expected,the recorded data (Fig.10)shows that apart-ments consume more heating energy as the outside temperature decreases.Fig.10also shows the relationship between heat ﬂux and heating energy consumption such that units with higher heat ﬂux in general have higher heating energy consumption,with some exceptions,e.g.,unit 12in October and unit 7in January;(in these exceptions,even though heat loss was high,heating energy con-sumption was comparatively low).In general,variations in theoccupancy,such as vacations and other absences,can directly impact the energy consumption,and the absence of residents ren-ders the heat comfort level of individuals irrelevant with respect to its impact on energy consumption over these periods of absence.Another exception is with respect to unit 7in November and December.Data shows that even though heat ﬂux was lower in unit 7,heating energy consumption was higher (compared to unit 12)in November and December.There is a possibility that occupant comfort level with a higher temperature range may have resulted in higher heating consumption in unit 7.Recorded data indicates that the indoor air temperature in unit 7has always been maintained at a higher level (sometimes exceeding the standard temperature range)compared to unit 12,indicating that occupant preference for a higher temperature range may be the reason for higher heat-ing consumption during October-December in unit 7,even though heat loss was less than for unit 12.It should be noted that occupant lifestyle and comfort level may affect the heating energy consump-tion signiﬁcantly.In order to manage heating energy effectively,it is necessary to monitor and analyze the heating energy usageT.Sharmin et al./Sustainable Cities and Society 13(2014)57–6863Fig.9.Data analysis framework for heating energyconsumption.Fig.10.Heat ﬂux and heating energy consumption in north-(unit 7)and south-facing (unit 12)units.regularly and to set realistic targets for improving energy efﬁ-ciency.3.3.Measurement of household water usageHousehold water usage is also being monitored as part of this study.According to Environment Canada ,in 2009average resi-dential water use was 72.38gallons per capita per day,which corresponds to 26,420gallons per capita per year (Municipal Water Use Report,2011).Fig.11shows the water consumption by case-study unit in 2012.The results indicate that even though unit 9is a one-bedroom unit (assumed to be accommodating fewer residents than two-bedroom units),it exhibits the highest water consumption.By measuring the water usage of occupants,build-ing management can pursue appropriate measures (i.e.,optimum usage range)if the water usage per person for a particular unit is continuously higher than the Canadian average residential water usage per capita per day.The recorded data in Fig.11shows that hot water consumption typically accounts for more than 30%of total water consumption in the case-study units,with the exception of unit 11.Since in thisproject energy is drawn from used hot water through drain water heat recovery (DWHR),there is a possibility that this gray water could be used for toilet ﬂushing.It should be noted that the use of gray water in the case-study units is beyond the scope of this study.3.4.Indoor air quality (CO 2concentration and relative humidity)measurementElevated CO 2levels affect occupant comfort and IAQ.With ele-vated CO 2levels,occupants may complain of perceived poor air quality and may face health problems such as headaches,fatigue,and eye and throat irritation.Poor air quality may reduce the efﬁ-ciency of the occupants (Wyon &Wargocki,2006)and this loss can be reduced through proper design strategy (Wyon,1996).The rela-tionship between indoor CO 2concentration and IAQ is in terms of the impact of elevated CO 2on comfort,and the correlation between CO 2and ventilation (Aglan,2003).According to the American Soci-ety of Heating,Refrigerating and Air-conditioning Engineers Inc.(ASHRAE),buildings with proper ventilation should have CO 2lev-els not in excess of 1000ppm (Quinn,2011).Exceeding this level is likely indicative of inadequate ventilation.In consideration of this,64T.Sharmin et al./Sustainable Cities and Society13(2014)57–68Fig.11.Total water consumption of case-study units in2012.Fig.12.IAQ data analysis framework for CO2.Fig.13.IAQ data analysis framework for RH.T.Sharmin et al./Sustainable Cities and Society 13(2014)57–6865Fig.14.Monthly average CO 2concentration level in case-studyunits.Fig.15.Average CO 2level and ERV electricity consumption in case-study units for February and March,2012.Figs.12and 13show the framework of IAQ data analysis (CO 2and RH,respectively)considered in this project.The results of data analysis (Fig.14)show that CO 2concentra-tion levels exceed the 1000ppm threshold in units 1,3,4,5,8,and 9for several months of 2012.In order to determine if lack of energy recovery ventilation (ERV)usage is the reason for the elevated level of CO 2,electricity consumption by the ERV is inves-tigated for the case-study units for February and March,2012.These two months are chosen as examples since most of the units exceed the threshold during these two months.Fig.15shows the CO 2con-centration and ERV electricity consumption by unit,exhibiting that the units with higher ERV usage have in general relatively lowerCO 2concentration (units 7,10,and 11),while units with lower ERV usage have higher CO 2concentration (units 1,3,4,5,and 9).An improper heating,ventilation,and air conditioning system (HVAC),as well as unvented appliances (space heaters,dryers,stoves,and any other unvented gas appliances)in a house,can lead to high levels of indoor CO 2(Health Canada,1995).Complementing the recorded data (ERV usage record),interviews with occupants may be helpful for identifying the factors inﬂuencing higher CO 2levels in the identiﬁed units.Once the causal factors are identiﬁed,necessary steps (e.g.,imposing the use of ERV,proper maintenance of HVAC system and appliances)should be taken in the interest of occupant health.。

规范ISO7726

INTERNATIONAL STANDARD
COPYRIGHT © Danish Standards. NOT FOR COMMERCIAL USE OR REPRODUCTION
ISO 7726
Second edition 1998-11-01
Ergonomics of the thermal environment — Instruments for measuring physical quantities
1 Scope
This International Standard specifies the minimum characteristics of instruments for measuring physical quantities characterizing an environment as well as the methods for measuring the physical quantities of this environment. It does not aim to define an overall index of comfort or thermal stress but simply to standardize the process of recording information leading to the determination of such indices. Other International Standards give details of the methods making use of the information obtained in accordance with this standard. This International Standard is used as a reference when establishing a) b) specifications for manufacturers and users of instruments for measuring the physical quantities of the environment; a written contract between two parties for the measurement of these quantities.

测绘专业术语

测量专业术语中英文对照及解析发布时间：2010-04-14 16:24 来自：测量meas uremen t以确定量值为目的的操作。

静态测量s tatic meas urement对测量期间其值可认为是恒定的量的测量。

注：“静态”一词适用于被测量，不适用于测量方法。

动态测量d ynamic meas ur eme nt对[变]量的瞬时值或随时间的变化值的测量。

注：“动态”一词适用于被测量，不适合于测量方法。

测量原理p rinc ip le o f meas urement测量方法的科学基础。

例如：应用于电压测量的约瑟夫森效应。

测量方法metho d o f meas ureme nt根据给定的原理，在实施测量中所涉及的理论运算和实际操作的方法。

测量步骤meas ureme nt p ro c ed ure根据给定的方法，在实施测量中所涉及的理论运算和实际操作的步骤。

被测量meas urand，meas ured q uant ity，q uant it y to b e meas ured受到测量的量。

被测变量meas ured var iab le受到测量的变量。

输入变量inp ut var iab le输入到仪器仪表的变量。

输出变量o utp ut variab le由仪器仪表输出的变量。

被测值meas ured valud在规定条件的瞬间，相当于由测量装置获得的信息，并以数值和测量单位表示的量值。

[被测量的]变换值trans fo rmed [o f a meas urand]表示与被测量有函数关系的量值。

例如：压力传感器的电输出信号值。

注：变换值可以是测量系统内部的值，或者是从系统中提供的输出。

影响量inf lue nc e q uant ity不属于被测量但却影响被测值或测量仪器仪表表示值的量。

例如：环境温度、被测交流电压的频率。

信号s igna l载有由一个或几个参数表示的一个或几个变量的信息的物理变量。

仪器仪表常用词汇英语翻译

仪器仪表常用词汇英语翻译pH计 pH meterX射线衍射仪 X-ray diffractometerX射线荧光光谱仪 X-ray fluorescence spectrometer 力测量仪表 force measuring instrument孔板 orifice plate文丘里管 venturi tube水表 water meter加速度仪 accelerometer可编程序控制器 programmable controller平衡机 balancing machine皮托管 Pitot tube皮带秤 belt weigher光线示波器 light beam oscillograph光学高温计 optical pyrometer光学显微镜 optical microscope光谱仪器 optical spectrum instrument吊车秤 crane weigher地中衡 platform weigher字符图形显示器 character and graphic display位移测量仪表 displacement measuring instrument 巡迴检测装置 data logger波纹管 bellows长度测量工具 dimensional measuring instrument长度传感器 linear transducer厚度计 thickness gauge差热分析仪 differential thermal analyzer扇形磁场质谱计 sector magnetic field mass spectrometer 料斗秤 hopper weigher核磁共振波谱仪 nuclear magnetic resonance spectrometer 气相色谱仪 gas chromatograph浮球调节阀 float adjusting valve真空计 vacuum gauge动圈仪表 moving-coil instrument基地式调节仪表 local-mounted controller密度计 densitometer液位计 liquid level meter组装式仪表 package system减压阀 pressure reducing valve测功器 dynamometer紫外和可见光分光光度计 ultraviolet-visible spectrometer 顺序控制器 sequence controller微处理器 microprocessor温度调节仪表 temperature controller煤气表 gas meter节流阀 throttle valve电子自动平衡仪表 electronic self-balance instrument 电子秤 electronic weigher电子微探针 electron microprobe电子显微镜 electron microscope弹簧管 bourdon tube数字式显示仪表 digital display instrument热流计 heat-flow meter热量计 heat flux meter热电阻 resistance temperature热电偶 thermocouple膜片和膜盒 diaphragm and diaphragm capsule调节阀 regulating valve噪声计 noise meter应变仪 strain measuring instrument湿度计 hygrometer声级计 sound lever meter黏度计 viscosimeter转矩测量仪表 torque measuring instrument转速测量仪表 tachometer露点仪 dew-point meter变送器 transmitter仪器仪表常用术语中英文对照带注释版性能特性performance characteristic：确定仪器仪表功能和能力的有关参数及其定量的表述。

药物分析专业英语

(dissolution) vessel 溶出杯(FTIR) 傅里叶变换红外光谱仪13C-NMR spectrum,13CNMR 碳-13核磁共振谱1ength basis 长度基准1H-NMR 氢谱2D-NMR 二维核磁共振谱：2D-NMR3D-spectrochromatogram 三维光谱－波谱图Aa stream of nitrogen 氮气流a wide temperature range 宽的温度范围absolute detector response 检测器绝对响应(值)absolute entropy 绝对熵absolute error 绝对误差absolute reaction rate theory 绝对反应速率理论absolute temperature scale 绝对温标absorbance 吸光度，而不是吸收率（absorptance）。

当我们忽略反射光强时，透射率（T）与吸光度（A）满足如下关系式：A=lg(1/T)。

absorbance noise, absorbing noise 吸光度噪音。

也称光谱的稳定性，是指在确定的波长范围内对样品进行多次扫描，得到光谱的均方差。

吸光度噪音是体现仪器稳定性的重要指标。

将样品信号强度与吸光度噪音相比可计算出信噪比。

absorbed water 吸附水absorptance 吸收率absorptant 吸收剂absorption band 吸收带absorption cell 吸收池absorption curve 吸收光谱曲线/光吸收曲线absorption tube 吸收管abundance 丰度。

即具有某质荷比离子的数量accelerated solvent extraction(ASE) 加速溶剂萃取accelerated testing 加速试验accelerating decomposition 加速破坏acceptance limit，acceptance criterion 验收限度，合格标准accidental error 随机误差accuracy 准确度。

化学及化工专业英语词汇（F）

化学及化工专业英语词汇(F)f acid f 酸f distribution f 分布fabric 织物fabric filler 织物填料fabrication 制造face centered cubic lattice 面心立方晶格facet 面factice 油膏factor 因数factorial design 因子设计factorial development 系数显影法factory test 工厂试验facultative anaerobe 嫌气性细菌fadeometer 褪色计fahrenheit scale 华氏温标fall velocity 沉降速度falling ball viscometer 落球粘度计falling drop method 落滴法falling rate drying 降速率干燥false setting 异常凝固fan 风扇fan belt 风扇皮带farad 法拉faraday constant 法拉第常数faraday effect 法拉第效应faraday's law of electrolysis 法拉第电解定律farinometer 面粉谷胶测定器farnesol 法呢醇fashioning 成形fast color 不褪色颜色fast powder 高速炸药fastness 坚牢度fastness test 坚牢度试验fastness to rubbing 耐摩擦坚牢度fastness to water 耐水性fat 脂肪fat and oil 油脂fat content 脂肪含量fat hardening 油脂硬化fat hydrolyzing process 油脂水解法fat lime 富石灰fat soluble vitamins 脂溶性维生素fat solvent 油脂溶剂fat splitting agent 油脂水解剂fatigue 疲劳fatigue limit 疲劳限度fatigue test 疲劳试验fatty acid 脂肪酸fatty acid anhydride 脂肪酸酐fatty acid pitch 脂肪酸沥青fatty alcohol 脂族醇fatty matter 脂肪性物质fatty oil 脂油fatty substance 脂肪性物质favorskii rearrangement 法沃斯基重排酌febrifuge 解热药feed hopper 装料斗feed preparation unit 原料制备单元feeder 加料器供给装置fehling's reagent 费林试剂fehling's solution 非林液feldspar 长石feldspathic porcelain 长石瓷felspar 长石female sex hormone 女性激素fenchol 葑醇fenchyl alcohol 葑醇fenethazine 乙嗪fennel oil 茴香油fenson 除螨酯fentiazon 叶噻灵ferbam 福美铁ferberite 钨铁矿fergusonite 褐钇钽矿ferment 酶fermentation 发酵fermentation accelerator 发酵加速剂fermentation alcohol 发酵酒精fermentation amylalcohol 发酵戊醇fermentation butyric acid 发酵酪酸fermentation degree 发酵度fermentation lactic acid 发酵乳酸fermentation organisms 发酵微生物fermenter 发酵槽fermenting enzyme 发酵酶fermenting power 发酵力fermi level 费米能级fermium 镄ferric acid 高铁酸ferric ammonium sulfate 硫酸铁铵ferric chloride 氯化铁ferric dimethyldithiocarbamate 福美铁ferric lactate 乳酸铁ferric nitrate 硝酸铁ferric oxalate 草酸铁ferric oxide 氧化铁ferric resinate 尸酸铁ferric salt 铁盐ferricyanide 铁氰化物ferriporphyrin 铁卟啉ferrite 铁酸盐ferrocene 二茂铁ferrochrome 铬铁合金ferrochromium 铬铁合金ferrocoke 铁焦炭ferrocyanic acid 氰亚铁酸ferrocyanide 亚铁氰化物ferrocyanide process 亚铁氰化物法ferroelectric liquid crystals 铁电液晶ferroelectric polymers 铁电聚合物ferroelectric substance 铁电体ferrofluid 铁磁铃ferromagnetic body 铁磁物质ferromagnetic substance 铁磁物质ferromagnetism 铁磁性ferromanganese 锰铁ferromolybdenum 钼铁ferrosilicon 硅铁ferrous chloride 氯化亚铁ferrous iodide 碘化亚铁ferrous lactate 乳酸亚铁ferrous oxalate 草酸亚铁ferrous salt 亚铁盐ferrovanadium 钒铁fertility 肥度fertilizer 肥料fertilizer analysis 肥料分析fiber 纤维fiber axis 纤维轴fiber board 纤维板fiber diagram 纤维图fiber forming property 纤维形成能fiber period 纤维周期fiber stress 纤维强度fiber structure 纤维结构fiber texture 纤维组织fiberboard 纤维板fibreboard 纤维板fibril 细纤维fibrin 纤维蛋白fibrin adhesive 纤维蛋白粘着剂fibrinogen 纤朊原fibrinoid 类纤维蛋白fibroin 丝蛋白fibrous material 纤维材料fibrous protein 纤维状蛋白质ficin 无花果朊酶fictive temperature 假想温度fiducial temperature 基准温度field emission 电场发射field evaporation 场致蒸发field laboratory 野外试验室field of force 力场figured glass 压花玻璃filament 丝filler 填充物filler of rubber 橡胶填料filling 填充filling hopper 装料斗film 照相软片film base 片基film coefficient 膜系数film coefficient of heat transfer 薄膜导热系数film condensation 薄膜冷凝film former 成膜物film forming ability 成膜能film forming matter 成膜物film support 片基filter 过滤器filter bed 过滤层filter cake 滤饼filter cake washing 滤饼洗涤filter chamber 过滤室filter cloth 滤布filter cone 滤斗filter crucible 滤埚filter flask 过滤瓶filter glass 滤光玻璃filter medium 过滤介质filter paper 滤纸filter paper for chromatography 色谱滤纸filter plate 滤板filter press 压力过滤器filter pump 滤泵filter stand 漏斗架filter stick 滤棒filter support 漏斗架filter tube 滤管filtering 过滤filtering basin 过滤池filtering surface 过滤面filtrate 滤液filtration 过滤filtration chamber 过滤室final product 最终产品final state 最终状态fine chemistry 精细化学fine coal 粉煤fine grain 微粒fine grinding 碾成细末fine powder 细粉fine pulverizer 精细磨粉机fine spinning 高支数纺纱fine structure 精细结构fine structure of spectral line 谱线精细结构fineness 细度fines 细料fining agent 澄清剂finish 完成finished product 最终产品finishing coating 修饰涂料finishing compound 整饰化合物finite element method 有限单元法fir balsam 加拿大胶fire box 火箱fire brick 耐火砖fire chamber 火箱fire clay 耐火粘土fire extinguisher 灭火器fire foam 泡沫灭火剂fire point 燃烧点fire proof material 耐火材料fire proof mortar 耐火砂浆fire proof paint 防火油漆fire resistance 耐火性fire shrinkage 焙烧收缩firedamp 坑气fireproof 耐火的first coat 底涂first law of newton 牛顿第一定律first law of thermodynamics 热力学第一定律first order reaction 一级反应fischer tropsch process 费希尔特罗普希法fischer's indole synthesis 费希尔吲哚合成fish oil 鱼油fissile material 可裂变物质fissiochemistry 裂变化学fission product 核裂产物fissionability 可裂变性fissionable material 可裂变物质fitness test 适合性试验fittig reaction 菲提希反应fittings 配件fix 固着fixation 固着fixation of atmospheric nitrogen 大气氮素固定fixative 固定剂fixative bath 固着浴fixative salt 定影剂fixed ammonia 固定氨fixed bed 固定床fixed bed hydroforming 固定床氢重整fixed bed ion exchange 固定床离子交换fixed bed operation 固定床操作fixed carbon 固定碳fixed catalyst process 固定催化过程fixed electron 束缚电子fixed ion 固定离子fixed oil 不挥发性油fixed point of temperature 温度定点fixed resistor 固定电阻器fixer 固定剂fixing 固着fixing bath 固着浴fixing salt 定影剂fixing solution 固定液flake 小片flake graphite 片状石墨flaking 剥落flaky crystal 片状结晶flame 火焰flame analysis 火焰分析flame coloration 焰色flame photometer 火焰光度计flame reaction 焰色反应flame retarded resin 阻燃尸flame spectrophotometer 火焰分光光度计flame spectrophotometry 火焰分光光度测定法flame spectrum 火焰光谱flame spraying 火焰喷射flammability 可燃性flammable liquid 可燃液体flash distillation 快速蒸馏flash dry 急骤干燥flash photolysis 闪光光解flash point 闪点flash point tester 闪点测定器flash vaporization 闪蒸flask 烧瓶flat bottom flask 平底烧瓶flat glass 平板玻璃flat paint 无光油漆flatting agent 消光剂flavanone 黄烷酮flavanthrene 黄烷士林flavianic acid 黄胺酸flavin 黄素flavin enzyme 黄素酶flavone 黄酮flavonoid 黄酮类flavonol 黄酮醇flavoprotein 黄素蛋白flavouring 刀剂flexibility 展曲性flexure 挠曲flint 打火石flint glass 铅玻璃flint mill 燧石磨机flint paper 粗砂纸floating battery 浮置电池组floating soap 浮水皂floc 絮凝物floc point 絮凝点flocculant 絮凝剂flocculate 絮凝物flocculating agent 絮凝剂flocculation 凝聚flocculation agent 絮凝剂flocculation value 凝结值flocculent 絮凝的flooding 溢流液阻现象flooding velocity 溢临度flotation 浮选flotation agent 浮选剂flotation process 浮选法flourescent lamp 荧光灯flow birefringence 怜双折射flow circulation reactor 怜循环反应器flow conveyor 连续了输机flow diagram 撂图flow limit 怜极限flow mark 波鳞flow measurement 量测定flow rate 量flow reactor 怜反应器flow sheet 撂图flower of sulfur 硫黄华flowmeter 量计fluctuation 起伏flue 烟道flue dust 烟道灰flue gas analysis 烟气分析flue gases 烟道气fluid 铃fluid bed catalytic process 怜床催化过程fluid catalyst 怜催化剂fluid catalytic cracker 怜催化裂解装置fluid mechanics 铃力学fluid rubber 液态橡胶fluidity 寥fluidization 怜化fluidization tower 怜柱fluidized adsorption 怜吸附fluidized bed 怜床fluidized drying 怜干燥fluidized gas producer 怜床气化炉fluorene 芴fluorenol 芴醇fluorescein 荧光素fluorescence 荧光fluorescence indicator 荧光指示剂fluorescence spectrum 荧光光谱fluorescent brightening agent 荧光增白剂fluorescent color 荧光染料fluorescent dye 荧光染料fluorescent pigment 荧光颜料fluorescent screen 荧光膜fluorescent substance 荧光物质fluorescent x rays 荧光 x 射线fluoride 氟化物fluoride glass 氟化物玻璃fluorimetry 荧光测定fluorination 氟化fluorine 氟fluorite 荧石fluoroacetic acid 氟乙酸fluoroalkane 氟代烷fluorobenzene 氟苯fluorocarbon 碳氟化合物fluorometer 荧光光度计fluorometric analysis 荧光测定fluoronitrobenzene 氟硝基苯fluorophore 荧光团fluorosilicate 氟硅酸盐fluorotoluene 氟代甲苯fluorspar 荧石fluosilicic acid 氟硅酸fluothane 氟烷fluphenazine 氟奋乃静flurenol 抑草丁flux 量flux line 液面线fly ash 飞灰fly paper 粘蝇纸foam 泡沫foam analysis 发泡分析foam breaker 消泡剂foam extinguisher 泡沫灭火器foam glass 泡沫玻璃foam inhibitor 消泡剂foam rubber 沉沫橡皮foam separator 沉沫分离器foam suppressor 消泡剂foamed plastics 泡沫塑料foaming agent 起沫剂foaming test 起泡试验focal distance 焦距focal length 焦距focal point 焦点focus 焦点fog chamber 云室folded filter 折纸漏斗folic acid 叶酸follicular cell 卵泡细胞follicular hormone 卵泡激素fontactoscope 温泉测氡计food 食品food analysis 食品分析food chemistry 食物化学food color 食用染料food dye 食用染料forbidden line 禁线forced convection 强制对流forced draft 强制通风forced vibration 强制振动forceps 钳子forehearth 前炉foreign matter 异物forensic analysis 法医检定法forensic chemistry 法医化学form 形form factor 形状因数formal 福马尔formal charge 形式电荷formaldehyde 甲醛formaldoxime 甲醛肟formalin 甲醛水formamide 甲酰胺formanilide 甲酰苯胺formate 甲酸盐formation 形成formic acid 甲酸formin 甲酸精forming 成形forming of glass 玻璃成形formol titration 甲醛滴定formose 甲醛聚糖formula weight 式量formulation of pesticide 农药配方formyl fluoride 氟化甲酰forsterite brick 镁橄榄石砖forsterite porcelain 镁橄榄石瓷fossil resin 火石尸fossil wax 木炭fouling factor 生垢因数founding 澄清foundry coke 铸造用焦炭fourcault process 弗克法fourier analysis of crystal structure 晶体结构傅里叶分析法fourier number 傅里叶数fourier series 傅里叶级数fraction 馏分fraction collector 馏分收集器fractional composition of petroleum 石油馏分组成fractional crystallization 分步结晶fractional decomposition 分级分解fractional dissolution 分级溶解fractional distillation 分馏fractional extraction 分馏萃取fractional neutralization 分级中和fractional precipitation 分级沉淀fractional sterilization 间歇杀菌fractional sublimation 分级升华fractionating column 分馏柱fractionating flask 分馏瓶fractionating tower 分馏柱fractionating tube 分馏管fractionation 分馏frame filter press 框式压滤机francium 钫franck hertz's experiment 弗兰克赫茨实验free acid 游离酸free alkali 游离碱free carbon 单体碳free convection 自然对流free electron model 自由电子模型free energy 自由能free energy at constant pressure 定压自由能free energy of activation 活化自由能free expansion 自由膨胀free heat convection 自然对粱热free moisture 游离水分free path 自由程free radical 自由基free radical initiation 游离基开始反应free radical reaction 游离基反应free sulfur 单体硫free surface 自由液面free valence 自由价free volume 自由体积free water 自由水freeze drying 冷冻干燥freezing mixture 致冷混合物freezing point 冰点freon 氟利昂frequency 频率frequency factor 频率因子frequency meter 频率计fresh air 新鲜空气fresh water 淡水freund's acid 弗罗因德酸freundlich's adsorption formula 弗罗因德利奇吸附公式friability 脆性friction 摩擦friction calender 擦胶压延机friction compound 擦胶剂friction press 摩擦压力机friction tape 摩擦带frictional coefficient of fiber 纤维摩擦系数frictional loss 摩擦损失frictional resistance 摩擦阻力friedel crafts reaction 弗里德尔克拉夫特反应fries reaction 弗里斯反应frit 玻璃料frit furnace 弗里特窑frit kiln 弗里特窑fritting 熔化front view 正视图frontal analysis 前端分析frontal chromatography 前端分析frosted glass 毛玻璃froth flotation 浮选froth promoter 泡沫促进剂frother 起沫剂froude number 弗劳德数frozen food 冷冻食品fructose 果糖fruit sugar 果糖fuchsin 品红色fuchsine base 品红盐基fuchsine test 品红试验fucose 岩藻糖fucosterol 墨角藻甾醇fuel 燃料fuel cell 燃料电池fuel consumption 燃料消耗fuel gas 气体燃料fuel injection pump 燃油喷射泵fuel oil 燃料油fuel ratio 燃料比fugacity 逸度fulcrum 支点full load 全载重fuller's earth 漂白土fulling 缩绒fulminate 雷酸盐fulminating mercury 雷汞fulminic acid 雷酸fumarase 富马酸酶fumaric acid 富马酸fume cupboard 通风橱fumigant 熏蒸剂fumigation 熏蒸fuming nitric acid 发烟硝酸fuming sulfuric acid 发烟硫酸function of hybridized orbital 杂化轨道函数function space 函数空间functional determinant 函数行列式functional group 功能基functional ion exchange resin 功能性离子交换尸functional membrane 功能性膜functional particle 机能性粒子functional polymer 功能聚合物functionality 官能度fundamental frequency 基频fundamental unit 基本单位fungicide 杀菌剂fungistat 抑菌剂funnel 漏斗funnel stand 漏斗架funnel support 漏斗架furan 呋喃furan carboxylic acid 糠酸furan resin 呋喃尸furanose 呋喃糖furfural 糖醛furfuran 呋喃furfurol 糖醛furfuryl alcohol 糠醇furnace 炉furnace black 炉法炭黑furnace gas 炉气furoic acid 糠酸furoin 糠偶姻fusain 丝炭fuse 导火线fused alumina 熔融氧化铝fused aromatic ring 稠合芳族环fused cement 熔融水泥fused electrolyte 熔融电解质fused phosphate fertilizer 熔融磷酸肥料fused quartz 石英玻璃fused ring 稠环fused silica 石英玻璃fusel oil 杂醇油fusibility 可熔性fusible alloy 易熔合金fusing agent 熔剂fusing assistant 助熔剂fusing point 熔点fusion 熔融fusion tube 熔管。

用LID测量193nm弱吸收

Measurement of initial absorption of fused silica at 193nm using laserinduced deflection technique (LID)Dörte Schönfeld a, Ursula Klett a, Christian Mühlig b, Stephan Thomas aa Heraeus Quarzglas GmbH & Co. KG, Quarzstrasse 8, 63450 Hanau, Germany;b Institut für Photonische Technologien e.V.; Albert-Einstein-Str. 9, 07745 Jena, GermanyABSTRACTThe ongoing development in microlithography towards further miniaturization of structures creates a strong demand for lens material with nearly ideal optical properties. Beside the highly demanding requirements on homogeneity and stress induced birefringence (SIB), low absorption is a key factor. Even a small absorption is associated with a temperature increase and results in thermally induced local variations of refractive index and SIB. This could affect the achievable resolution of the lithographic process.The total absorption of the material is composed of initial absorption and of absorption induced during irradiation. Thus, the optimization of both improves the lifetime of the material.In principal, it is possible to measure transmission and scattering with a suitable spectrometer assembly and calculate absorption from them. However, owing to the influence of sample surfaces and errors of measurement, these methods usually do not provide satisfactory results for highly light-transmissive fused silica. Therefore, it is most desirable to find a technique that is capable of directly measuring absorption coefficients in the range of (1...10)·10-4 cm-1 (base 10) directly.We report our first results for fused silica achieved with the LID technique. Besides a fused silica grade designed for 193 nm applications, grades with higher absorption at 193 nm were measured to test the LID technique. A special focus was set on the possibility of measuring initial absorption without the influence of degradation effects.Keywords: fused silica, initial absorption, DUV1.INTRODUCTIONMaterial for lens blanks has to fulfil increasingly ambitious requirements in order to follow Moore’s Law of the continuous miniaturization of lithographic structures. It is no longer sufficient to “simply” produce material with outstanding homogeneity of refractive index and stress induced birefringence (SIB). At the same time, the material must be extremely resistant against changes of optical properties during lens lifetime.Such changes may occur as a result of absorption. The exposure of a lens element to laser light in a wafer scanner results in more or less lens heating depending on the material properties. The locally increased temperature induces an additional refractive index inhomogeneity via the thermo optical coefficient of d n/d T≈10 ppm K-1 for fused silica and will superpose the material inherent properties. Depending on the amount of absorption and the specification for the refractive index homogeneity this effect can generate a total inhomogeneity much larger than that of the initial lens material. Thus, the improvement of material absorption is one key parameter for the further material improvement for microlithography.The total absorption k total of a material is the sum of two contributions: a material inherent absorption k initial and an induced absorption k induced. Whereas established setups exist for measuring the induced absorption, the situation is different in the case of initial absorption measurements.Fig. 1. Scheme of LID-principle. The deflection angle of the probe beam depends onabsorption, thermal conductivity and thethermo optical coefficient d n/d T.For very pure material, initial absorption coefficients as low as 1·10-4 cm-1 were found. To our knowledge, there has been no investigation up to now presenting such low measured values for the initial absorption of fused silica material.REFERENCES[1]S. Thomas, B. Kühn, KrF Laser induced absorption in synthetic fused silica, in H. E. Bennett, A. H. Guenther,M. R. Kozlowski, B. E. Newnam, M. J. Soileau (eds.), Laser-induced damage in optical materials, Proc. of SPIE 2966, 56 (1996)[2]N. Leclerc, C. Pfleiderer, H. Hitzler, J. Wolfrum, K.-O. Greulich, S. Thomas, H. Fabian, R. Takke, W. Englisch,Transient 210-nm absorption in fused silica induced by high-power UV laser irradiation, Opt.Lett., 16(12), 940-942 (1991)[3]S. Thomas, W. Englisch, R. Takke, Effect of excimer laser radiation on the optical properties of synthetic fusedsilica, Glass Sci. Techn., 67 C, 19 (1994)[4]ISO/TC 172/SC 9, Test method for absorptance of optical laser components,ISO/DIS 11551 (1994)[5]U. Willamowski, T. Groß, D. Ristau, H. Welling, Calorimetric measurement of optical absorption andtransmissivity with sub ppm sensitivity, SPIE 2775, 148-158 (1996)[6]S. Logunov, S. Kuchinsky, Scattering losses in fused silica and CaF2 for DUV applications, in A. Yen (ed.),Optical Microlithography XVI, Proc. SPIE 5040, 1396-1407 (2003)[7]S. Schröder, M. Kamprath, A. Duparré, A. Tünnermann, Bulk scattering properties of synthetic fused silica at193 nm, Opt. Express 14(22), 10537-10549 (2006)[8] E. Welsch, K. Ettrich, H. Blaschke, P. Thomson-Schmidt, D. Schäfer, N. Kaiser, Investigation of the absorptioninduced damage in ultraviolet dielectric thin films, Opt.Eng. 36, 504-514 (1997)[9] A. L. Alexandrovski, M. M. Fejer, R. P. Route, R. L. Byer, Photothermal absorption measurements in opticalmaterials, in Conference on Lasers and Electro-Optics (CLEO 2000), TOPS 39 , 320-321 (2000)[10] F. Coriand, S. Kufert, Ch. Mühlig, W. Triebel, Anordnung zur optischen Bestimmung der Absorption, DE 10139 906, patent pending: 15.8.2001, disclosure: 6.6.2002[11]M. Guntau, W. Triebel, Novel method to measure bulk absorption in optically transparent materials, Rev. Sci.Instrum. 71, 2279-2282 (2000)[12]K. Mann, S. Kranzusch, G. Eckert, C. Görling, U. Leinhos, C. Peth, B. Schäfer, Optical metrology in the VUVand EUV spectral range, Proc.SPIE 4779, 31-40 (2002)[13]K. Mann, U. Leinhos, B. Schäfer, Characterization of absorption losses in deep UV optical materials, in G. J.Exarhos, A. H. Guenther, K. L. Lewis, D. Ristau, M. J. Soileau, C. J. Stolz (eds.), Laser-Induced Damage in Optical Materials, Proc. of SPIE 6403, 64031J-1 - 64031J-10 (2007)[14] E. Eva, K. Mann, High-resolution calorimetric absorption measurement on optical components for excimerlasers in H. E. Bennett, A. H. Guenther, M. R. Kozlowski, B. E. Newnam, M. J. Soileau (eds.), Laser-induced damage in optical materials, Proc. of SPIE 2966, 48-55 (1997)[15] C. Görling, U. Leinhos, K. Mann, Surface and Bulk Absorption in CaF2 at 193nm and 157nm, OpticsCommunications 249(1), 319-328 (2005)[16]W. Triebel, Ch. Mühlig, S. Kufert, Application of the laser induced deflektion (LID) technique for lowabsorption measurements in bulk materials and coatings, in A. Duparré, R. Geyl, L. Wang (eds.), Optical Fabrication, Testing, and Metrology II, Proc. of SPIE 5965, 59651J-1- p59651J-10 (2005)。

化学及化工专业英语词汇(F)

化学及化工专业英语词汇(F)化学及化工专业英语词汇(F)化学及化工专业英语词汇(F)f acid f 酸f distribution f 分布fabric 织物fabric filler 织物填料fabrication 制造face centered cubic lattice 面心立方晶格facet 面factice 油膏factor 因数factorial design 因子设计factorial development 系数显影法factory test 工厂试验facultative anaerobe 嫌气性细菌fadeometer 褪色计fahrenheit scale 华氏温标fall velocity 沉降速度falling ball viscometer 落球粘度计falling drop method 落滴法falling rate drying 降速率干燥false setting 异常凝固fan 风扇fan belt 风扇皮带farad 法拉faraday constant 法拉第常数faraday effect 法拉第效应faraday's law of electrolysis 法拉第电解定律farinometer 面粉谷胶测定器farnesol 法呢醇fashioning 成形fast color 不褪色颜色fast powder 高速炸药fastness 坚牢度fastness test 坚牢度试验fastness to rubbing 耐摩擦坚牢度fastness to water 耐水性fat 脂肪fat and oil 油脂fat content 脂肪含量fat hardening 油脂硬化fat hydrolyzing process 油脂水解法fat lime 富石灰fat soluble vitamins 脂溶性维生素fat solvent 油脂溶剂fat splitting agent 油脂水解剂fatigue 疲劳fatigue limit 疲劳限度fatigue test 疲劳试验fatty acid 脂肪酸fatty acid anhydride 脂肪酸酐fatty acid pitch 脂肪酸沥青fatty alcohol 脂族醇fatty matter 脂肪性物质fatty oil 脂油fatty substance 脂肪性物质favorskii rearrangement 法沃斯基重排酌febrifuge 解热药feed hopper 装料斗feed preparation unit 原料制备单元feeder 加料器供给装置fehling's reagent 费林试剂fehling's solution 非林液feldspar 长石feldspathic porcelain 长石瓷felspar 长石female sex hormone 女性激素fenchol 葑醇fenchyl alcohol 葑醇fenethazine 乙嗪fennel oil 茴香油fenson 除螨酯fentiazon 叶噻灵ferbam 福美铁ferberite 钨铁矿fergusonite 褐钇钽矿ferment 酶fermentation 发酵fermentation accelerator 发酵加速剂fermentation alcohol 发酵酒精fermentation amylalcohol 发酵戊醇fermentation butyric acid 发酵酪酸fermentation degree 发酵度fermentation lactic acid 发酵乳酸fermentation organisms 发酵微生物fermenter 发酵槽fermenting enzyme 发酵酶fermenting power 发酵力fermi level 费米能级fermium 镄ferrate 铁酸盐ferric acid 高铁酸ferric ammonium sulfate 硫酸铁铵ferric chloride 氯化铁ferric dimethyldithiocarbamate 福美铁ferric lactate 乳酸铁ferric nitrate 硝酸铁ferric oxalate 草酸铁ferric oxide 氧化铁ferric resinate 尸酸铁ferric salt 铁盐ferricyanide 铁氰化物ferriporphyrin 铁卟啉ferrite 铁酸盐ferrocene 二茂铁ferrochrome 铬铁合金ferrochromium 铬铁合金ferrocoke 铁焦炭ferrocyanic acid 氰亚铁酸ferrocyanide 亚铁氰化物ferrocyanide process 亚铁氰化物法ferroelectric liquid crystals 铁电液晶ferroelectric polymers 铁电聚合物ferroelectric substance 铁电体ferrofluid 铁磁铃ferromagnetic body 铁磁物质ferromagnetic substance 铁磁物质ferromagnetism 铁磁性ferromanganese 锰铁ferromolybdenum 钼铁ferronickel 镍铁ferrosilicon 硅铁ferrous chloride 氯化亚铁ferrous iodide 碘化亚铁ferrous lactate 乳酸亚铁ferrous oxalate 草酸亚铁ferrous salt 亚铁盐ferrovanadium 钒铁fertility 肥度fertilizer 肥料fertilizer analysis 肥料分析fiber 纤维fiber axis 纤维轴fiber board 纤维板fiber diagram 纤维图fiber forming property 纤维形成能fiber period 纤维周期fiber stress 纤维强度fiber structure 纤维结构fiber texture 纤维组织fiberboard 纤维板fibreboard 纤维板fibril 细纤维fibrin 纤维蛋白fibrin adhesive 纤维蛋白粘着剂fibrinogen 纤朊原fibrinoid 类纤维蛋白fibroin 丝蛋白fibrous material 纤维材料fibrous protein 纤维状蛋白质ficin 无花果朊酶fictive temperature 假想温度fiducial temperature 基准温度field emission 电场发射field evaporation 场致蒸发field laboratory 野外试验室field of force 力场figured glass 压花玻璃filament 丝filler 填充物filler of rubber 橡胶填料filling 填充filling hopper 装料斗film 照相软片film base 片基film coefficient 膜系数film coefficient of heat transfer 薄膜导热系数film condensation 薄膜冷凝film former 成膜物film forming ability 成膜能film forming matter 成膜物film support 片基filter 过滤器filter bed 过滤层filter cake washing 滤饼洗涤filter chamber 过滤室filter cloth 滤布filter cone 滤斗filter crucible 滤埚filter flask 过滤瓶filter glass 滤光玻璃filter medium 过滤介质filter paper 滤纸filter paper for chromatography 色谱滤纸filter plate 滤板filter press 压力过滤器filter pump 滤泵filter stand 漏斗架filter stick 滤棒filter support 漏斗架filter tube 滤管filtering 过滤filtering basin 过滤池filtering surface 过滤面filtrate 滤液filtration chamber 过滤室final product 最终产品final state 最终状态fine chemistry 精细化学fine coal 粉煤fine grain 微粒fine grinding 碾成细末fine powder 细粉fine pulverizer 精细磨粉机fine spinning 高支数纺纱fine structure 精细结构fine structure of spectral line 谱线精细结构fineness 细度fines 细料fining agent 澄清剂finish 完成finished product 最终产品finishing coating 修饰涂料finishing compound 整饰化合物finite element method 有限单元法fir balsam 加拿大胶fire box 火箱fire brick 耐火砖fire chamber 火箱fire clay 耐火粘土fire extinguisher 灭火器fire foam 泡沫灭火剂fire point 燃烧点fire proof material 耐火材料fire proof mortar 耐火砂浆fire proof paint 防火油漆fire resistance 耐火性fire shrinkage 焙烧收缩firedamp 坑气fireproof 耐火的first coat 底涂first law of newton 牛顿第一定律first law of thermodynamics 热力学第一定律first order reaction 一级反应fischer tropsch process 费希尔特罗普希法fischer's indole synthesis 费希尔吲哚合成fish oil 鱼油fissile material 可裂变物质fissiochemistry 裂变化学fission product 核裂产物fissionability 可裂变性fissionable material 可裂变物质fitness test 适合性试验fittig reaction 菲提希反应fittings 配件fix 固着fixation 固着fixation of atmospheric nitrogen 大气氮素固定fixative 固定剂fixative bath 固着浴fixative salt 定影剂fixed ammonia 固定氨fixed bed 固定床fixed bed hydroforming 固定床氢重整fixed bed ion exchange 固定床离子交换fixed bed operation 固定床操作fixed carbon 固定碳fixed catalyst process 固定催化过程fixed electron 束缚电子fixed ion 固定离子fixed oil 不挥发性油fixed point of temperature 温度定点fixed resistor 固定电阻器fixer 固定剂fixing 固着fixing bath 固着浴fixing salt 定影剂fixing solution 固定液flake 小片flake graphite 片状石墨flaking 剥落flaky crystal 片状结晶flame 火焰flame analysis 火焰分析flame coloration 焰色flame photometer 火焰光度计flame reaction 焰色反应flame retarded resin 阻燃尸flame spectrophotometer 火焰分光光度计flame spectrophotometry 火焰分光光度测定法flame spectrum 火焰光谱flame spraying 火焰喷射flammability 可燃性flammable liquid 可燃液体flash distillation 快速蒸馏flash dry 急骤干燥flash photolysis 闪光光解flash point 闪点flash point tester 闪点测定器flash vaporization 闪蒸flask 烧瓶flat bottom flask 平底烧瓶flat glass 平板玻璃flat paint 无光油漆flatting agent 消光剂flavanone 黄烷酮flavanthrene 黄烷士林flavianic acid 黄胺酸flavin 黄素flavin enzyme 黄素酶flavone 黄酮flavonoid 黄酮类flavonol 黄酮醇flavoprotein 黄素蛋白flavouring 刀剂flexibility 展曲性flexure 挠曲flint 打火石flint glass 铅玻璃flint mill 燧石磨机flint paper 粗砂纸floating battery 浮置电池组floating soap 浮水皂floc 絮凝物floc point 絮凝点flocculant 絮凝剂flocculate 絮凝物flocculating agent 絮凝剂flocculation 凝聚flocculation agent 絮凝剂flocculation value 凝结值flocculent 絮凝的flooding 溢流液阻现象flooding velocity 溢临度flotation 浮选flotation agent 浮选剂flotation process 浮选法flourescent lamp 荧光灯flow birefringence 怜双折射flow circulation reactor 怜循环反应器flow conveyor 连续了输机flow diagram 撂图flow limit 怜极限flow mark 波鳞flow measurement 量测定flow rate 量flow reactor 怜反应器flow sheet 撂图flower of sulfur 硫黄华flowmeter 量计fluctuation 起伏flue 烟道flue dust 烟道灰flue gas analysis 烟气分析flue gases 烟道气fluid 铃fluid bed catalytic process 怜床催化过程fluid catalyst 怜催化剂fluid catalytic cracker 怜催化裂解装置fluid mechanics 铃力学fluid rubber 液态橡胶fluidity 寥fluidization 怜化fluidization tower 怜柱fluidized adsorption 怜吸附fluidized bed 怜床fluidized drying 怜干燥fluidized gas producer 怜床气化炉fluorene 芴fluorenol 芴醇fluorescein 荧光素fluorescence 荧光fluorescence indicator 荧光指示剂fluorescence spectrum 荧光光谱fluorescent brightening agent 荧光增白剂fluorescent color 荧光染料fluorescent dye 荧光染料fluorescent pigment 荧光颜料fluorescent screen 荧光膜fluorescent substance 荧光物质fluorescent x rays 荧光x 射线fluoride 氟化物fluoride glass 氟化物玻璃fluorimetry 荧光测定fluorination 氟化fluorine 氟fluorite 荧石fluoroacetic acid 氟乙酸fluoroalkane 氟代烷fluorobenzene 氟苯fluorocarbon 碳氟化合物fluorometer 荧光光度计fluorometric analysis 荧光测定fluoronitrobenzene 氟硝基苯fluorophore 荧光团fluorosilicate 氟硅酸盐fluorotoluene 氟代甲苯fluorspar 荧石fluosilicic acid 氟硅酸fluothane 氟烷fluphenazine 氟奋乃静flurenol 抑草丁flux 量flux line 液面线fly ash 飞灰fly paper 粘蝇纸foam 泡沫foam analysis 发泡分析foam breaker 消泡剂foam extinguisher 泡沫灭火器foam glass 泡沫玻璃foam inhibitor 消泡剂foam rubber 沉沫橡皮foam separator 沉沫分离器foam suppressor 消泡剂foamed plastics 泡沫塑料foaming agent 起沫剂foaming test 起泡试验focal distance 焦距focal length 焦距focal point 焦点focus 焦点fog chamber 云室folded filter 折纸漏斗folic acid 叶酸follicular cell 卵泡细胞follicular hormone 卵泡激素fontactoscope 温泉测氡计food 食品food analysis 食品分析food chemistry 食物化学food color 食用染料food dye 食用染料forbidden line 禁线forced convection 强制对流forced draft 强制通风forced vibration 强制振动forceps 钳子forehearth 前炉foreign matter 异物forensic analysis 法医检定法forensic chemistry 法医化学form 形form factor 形状因数formal 福马尔formal charge 形式电荷formaldehyde 甲醛formaldoxime 甲醛肟formalin 甲醛水formamide 甲酰胺formanilide 甲酰苯胺formate 甲酸盐formation 形成formic acid 甲酸formin 甲酸精forming 成形forming of glass 玻璃成形formol titration 甲醛滴定formose 甲醛聚糖formula weight 式量formulation of pesticide 农药配方formyl fluoride 氟化甲酰forsterite brick 镁橄榄石砖forsterite porcelain 镁橄榄石瓷fossil resin 火石尸fossil wax 木炭fouling factor 生垢因数founding 澄清foundry coke 铸造用焦炭fourcault process 弗克法fourier analysis of crystal structure 晶体结构傅里叶分析法fourier number 傅里叶数fourier series 傅里叶级数fraction 馏分fraction collector 馏分收集器fractional composition of petroleum 石油馏分组成fractional crystallization 分步结晶fractional decomposition 分级分解fractional dissolution 分级溶解fractional distillation 分馏fractional extraction 分馏萃取fractional neutralization 分级中和fractional precipitation 分级沉淀fractional sterilization 间歇杀菌fractional sublimation 分级升华fractionating column 分馏柱fractionating flask 分馏瓶fractionating tower 分馏柱fractionating tube 分馏管fractionation 分馏frame filter press 框式压滤机francium 钫franck hertz's experiment 弗兰克赫茨实验free acid 游离酸free alkali 游离碱free carbon 单体碳free convection 自然对流free electron model 自由电子模型free energy 自由能free energy at constant pressure 定压自由能free energy of activation 活化自由能free expansion 自由膨胀free heat convection 自然对粱热free moisture 游离水分free path 自由程free radical 自由基free radical initiation 游离基开始反应free radical reaction 游离基反应free sulfur 单体硫free surface 自由液面free valence 自由价free volume 自由体积free water 自由水freeze drying 冷冻干燥freezing mixture 致冷混合物freezing point 冰点freon 氟利昂frequency 频率frequency factor 频率因子frequency meter 频率计fresh air 新鲜空气fresh water 淡水freund's acid 弗罗因德酸freundlich's adsorption formula 弗罗因德利奇吸附公式friability 脆性friction 摩擦friction calender 擦胶压延机friction compound 擦胶剂friction press 摩擦压力机friction tape 摩擦带frictional coefficient of fiber 纤维摩擦系数frictional loss 摩擦损失frictional resistance 摩擦阻力friedel crafts reaction 弗里德尔克拉夫特反应fries reaction 弗里斯反应frit 玻璃料frit furnace 弗里特窑frit kiln 弗里特窑fritting 熔化front view 正视图frontal analysis 前端分析frontal chromatography 前端分析frosted glass 毛玻璃froth flotation 浮选froth promoter 泡沫促进剂frother 起沫剂froude number 弗劳德数frozen food 冷冻食品fructose 果糖fruit sugar 果糖fuchsin 品红色fuchsine base 品红盐基fuchsine test 品红试验fucose 岩藻糖fucosterol 墨角藻甾醇fuel 燃料fuel cell 燃料电池fuel consumption 燃料消耗fuel gas 气体燃料fuel injection pump 燃油喷射泵fuel oil 燃料油fuel ratio 燃料比fugacity 逸度fulcrum 支点full load 全载重fuller's earth 漂白土fulling 缩绒fulminate 雷酸盐fulminating mercury 雷汞fulminic acid 雷酸fumarase 富马酸酶fumaric acid 富马酸fume cupboard 通风橱fumigant 熏蒸剂fumigation 熏蒸fuming nitric acid 发烟硝酸fuming sulfuric acid 发烟硫酸function of hybridized orbital 杂化轨道函数function space 函数空间functional determinant 函数行列式functional group 功能基functional ion exchange resin 功能性离子交换尸functional membrane 功能性膜functional particle 机能性粒子functional polymer 功能聚合物functionality 官能度fundamental frequency 基频fundamental unit 基本单位fungicide 杀菌剂fungistat 抑菌剂funnel 漏斗funnel stand 漏斗架funnel support 漏斗架furan 呋喃furan carboxylic acid 糠酸furan resin 呋喃尸furanose 呋喃糖furfural 糖醛furfuran 呋喃furfurol 糖醛furfuryl alcohol 糠醇furnace 炉furnace black 炉法炭黑furnace gas 炉气furoic acid 糠酸furoin 糠偶姻fusain 丝炭fuse 导火线fused alumina 熔融氧化铝fused aromatic ring 稠合芳族环fused cement 熔融水泥fused electrolyte 熔融电解质fused phosphate fertilizer 熔融磷酸肥料fused quartz 石英玻璃fused ring 稠环fused silica 石英玻璃fusel oil 杂醇油fusibility 可熔性fusible alloy 易熔合金fusing agent 熔剂fusing assistant 助熔剂fusing point 熔点fusion 熔融fusion tube 熔管化学及化工专业英语词汇(F) 相关内容:。

The absorption spectrum of V838 Mon in 2002 February - March. I. Atmospheric parameters and

a r X i v :a s t r o -p h /0411032v 1 1 N o v 2004Mon.Not.R.Astron.Soc.000,1–7(2004)Printed 2February 2008(MN L A T E X style ﬁle v2.2)The absorption spectrum of V838Mon in 2002February -March.I.Atmospheric parameters and iron abundance.⋆Bogdan M.Kaminsky 1†,Yakiv V.Pavlenko 1‡1Main Astronomical Observatory of Ukrainian Academy of Sciences,Golosiiv woods,03680Kyiv-127,UkraineReceived ;acceptedABSTRACTWe present a determination of the eﬀective temperatures,iron abundances,and mi-croturbulent velocities for the pseudophotosphere of V838Mon on 2002February 25,and March 2and 26.Physical parameters of the line forming region were obtained in the framework of a self-consistent approach,using ﬁts of synthetic spectra to observed spectra in the wavelength range 5500-6700˚A .We obtained T eﬀ=5330±300K,5540±270K and 4960±190K,for February 25,March 2,and March 26,respectively.The iron abundance log N (Fe)=−4.7does not appear to change in the atmosphere of V838Mon from February 25to March 26,2002.Key words:stars:atmospheres –stars:abundances –stars:individual:V838Mon1INTRODUCTIONThe peculiar variable star V838Mon was discovered during an outburst in the beginning of 2002January (Brown 2002).Two further outbursts were then observed in 2002February (Munari et al.2002a;Kimeswenger et al.2002;Crause et al.2003)and in general the optical brightness in V-band of the star increased by 9mag.Since 2002March,a gradual fall in V-magnitude began which,by 2003January,was re-duced by 8mag.The suspected progenitor of V838Mon was identiﬁed by Munari et al.(2002a)as a 15mag F-star on the main sequence.Possibly V838Mon might have a B3V companion (Desidera &Munari 2002),but it could be a background star.The discovery of a light echo (Henden et al.2002)allowed an estimate of the distance to V838Mon and,according to recent works based on HST data (Bond et al.2003;Tylenda 2004)its distance is 5-6kpc.If these estimations are correct,at the time of maximum brightness V838Mon was the most luminous star in our Galaxy.Details of the spectral evolution of the star are described in Kolev et al.2002;Wisniewski et al.2003;Osiwala et al.2002).During outbursts (except for the last)the spec-trum displayed numerous emission lines with P Cyg pro-ﬁles,formed in the expanding shell and around an F-or A-star (Kolev et al.2002).On the other hand,absorption spectra appropriate to a red giant or supergiant were ob-served in quiescent periods.Strong lines of hydrogen,D lines of sodium,triplets of calcium and other elements show P⋆Based in part on observations collected with the 1.83m tele-scope of the Astronomical Observatory in Asiago,Italy †E-mail:bogdan@mao.kiev.ua ‡E-mail:yp@mao.kiev.uaCyg proﬁles.They have similar proﬁles and velocities vary-ing from −500km s −1in late January to −280km s −1in late March (Munari et al.2002a).Since the middle of 2002March,the emissions are considerably weakened and the spectrum of V838Mon evolved to later spectral classes.In middle of 2002April,there were present some lines of TiO;in May the spectrum evolved to the“very cold”M-giant (Banerjee &Ashok 2002).In October Evans et al.(2003)characterized it as a L-supergiant.Recently Kipper et al.(2004)found for iron group ele-ments [m/H]=−0.4,while abundances of lithium and some s-process elements are clearly enhanced.This results was obtain using the static LTE model.These results are very dependent on the model atmo-sphere and spectrum synthesis assumptions.The nature of the outbursts remains a mystery.Possible explanations include various thermonuclear processes (very slow nova,ﬂare post-AGB),and the collision of two stars (Soker &Tylenda 2003).Munari et al.(2002a)suggested that V838Mon is a new type of a variable star,because comparison with the closely analogous V4334Sgr and M31RV has shown signiﬁcant enough diﬀerences in the observed parameters.In this paper we discuss the results of the determina-tion of iron abundance and atmospheric parameters of V838Mon.These we obtained from an analysis of absorption spec-tra of V838Mon on 2002February 25and March 2and 26.The complexity and uniqueness of the observed character-istics of V838Mon practically excluded a deﬁnition of the parameters of the atmosphere using conventional methods,based on calibration on photometric indices,ionization bal-ance,proﬁles of hydrogen lines.Indeed,the presence around the star of a dust shell,and the uncertain determination of2Bogdan M.Kaminsky,Yakiv V.Pavlenko interstellar reddening(from E B−V=−0.25to E B−V=−0.8 Munari et al.2002a),aﬀects the U−B and B−V colours. Emission in the hydrogen lines provides severe problems for their application in the estimation of eﬀective temperature. Moreover,both the macroturbulent motions and expansion of the pseudophotosphere merges the numerous lines in wide blends.As a result,a single unblended line in the spectrum of V838Mon cannot be found at all,and any analysis based on measurements of equivalent widths is completely excluded.The observational data used in this paper are described in section2.Section3explains some background to our work and some details of the procedure used.We attempt to de-termine T eﬀ,the microturbulent velocity V t and the iron abundance log N(Fe)in the atmosphere of V838Mon in theframework of the self-consistent approach in section4.Some results are discussed in section5.2OBSER V ATIONSSpectra of V838Mon were obtained on2002February25 and March26with the Echelle+CCD spectrograph on the 1.82m telescope operated by Osservatorio Astronomico di Padova on Mount Ekar(Asiago),and freely available to the community from http://ulisse.pd.astro.it/V838Mon/.A 2arcsec slit was used withﬁxed E-W orientation,produc-ing a PSF with a FWHM of1.75pixels,corresponding to a resolving power close to20000.The detector was a UV coated Thompson CCD1024×1024pixel,19micron square size,covering in one exposure the wavelength range4500to 9480˚A(echelle orders#49to#24).The short wavelength limit is set by a2mm OG455long-passﬁlter,inserted in the optical train to cut the second order from the cross-disperser. The wavelength range is covered without gaps between ad-jacent echelle orders up to7300˚A.The spectra have been extracted and calibrated using IRAF software running un-der Linux operating system.The spectra are sky-subtracted andﬂat-ﬁelded.The wavelength solution was derived simul-taneously for all26echelle orders,with an average r.m.s of 0.18km s−1.The8480-8750˚A wavelength range of these Asi-ago spectra has been described in Munari et al.(2002a,b).Another set of spectra(R∼32000)for March2was obtained with the echelleﬁbre-fed spectrograph on the1.9-m SAAO telescope kindly provided for us by Dr.Lisa Crause (see Crause et al.2003for details).3PROCEDURETo carry out our analysis of V838Mon we used the spectral synthesis techniques.Our synthetic spectra were computed in the framework of the classical approach:LTE,plane-parallel media,no sinks and sources of energy inside the atmosphere,and transfer of energy provided by the radia-tionﬁeld and by convection.Strictly speaking,none of these assumptions is100% valid in atmosphere of V838Mon.Clearly we have non-static atmosphere which may well have shock waves mov-ing trough it.Still we assumed that in any moment the structure of model atmosphere of V838Mon is similar to model atmospheres of supergiants.Indeed,temporal changes of the absorption spectra on the days were rather marginal.0.00050.0010.00150.0020.00250.0030.00350.004-200-150-100-50 0 50 100 150 200Velocity (km s-1)V exp=160 km s-1V*sin i=80 km s-1V macro=50 km s-1parison of expansion(V exp=160km s−1),rota-tional(v∗sin i=80km s−1)and macroturbulent(V macro=50 km s−1)proﬁles used in this paper to convolve synthetic spectra.Most probably,for this object,we see only a pseudophoto-sphere,which is the outermost part of an expanding enve-lope.Therefore,ourﬁrst goal was to determine whether it is possible toﬁt our synthetic spectra to the observed V838 Mon spectra.At the time of the observations the spectral class of V838Mon was determined as K-type(Kolev et al.2002). Absorption lines in spectrum of V838Mon form compara-tively broad blends.Generally speaking,there may be a number of broad-ening mechanisms:•Microturbulence,which is formed by small scale(i.e τ≪1)motions in the atmosphere.In the case of a super-giant,V t usualy does not exceed10km s−1.In our analysis we determined V t from a comparison of observed and com-puted spectra.•Stellar rotation.Our analysis shows that,in the case of V838,we should adopt v∗sin i=80km s−1toﬁt the observed spectra.This value is too high for the later stages of stellar evolution,for obvious reasons.In reality rotation cannot contribute much to the broadening of lines observed in spectra of most supergiants.•Expansion of the pseudophotosphere of the star.Asym-metrical proﬁles of expansion broadening can be described, to aﬁrst approximation,by the formulaG(v,λ,∆λ)=const∗∆λThe absorption spectrum of V838Mon3−0.50.511.522.5566056705680569057005710N o r m a l i s e d F l u xWavelength (Å)February 3February 25March 2March 26Figure 2.Spectra of V838Mon observed on February 3,Febru-ary 25,March 2and March 262002emission:many lines are observed in emission.This demon-strates that eﬀects of the radial expansion of the line-forming layers were not signiﬁcant for the dates of our data and for-mally obtained value V exp =160km s −1is not real.•Macroturbulence.After the large increase of luminos-ity in 2002January-February,large scale (i.e.of magnitude τ>1)macroturbulent motions should be very common in the disturbed atmosphere of V838Mon.Our numerical ex-periments showed that,to get appropriate ﬁts to the ob-served spectra taking into account only macroturbulent ve-locities,we should adopt V macro ∼50km s −1.In any case,for the times of our observations the spectra of V838Mon resemble the spectra of “conventional”super-giants.Our V838Mon spectra for February 25,March 2and 26agree,at least qualitatively,with the spectrum of Arcturus (K2III),convolved with macroturbulent velocity proﬁle,given by a gaussian of half-width V macro =50km s −1(Fig.3).The observed emissions in the cores of the strongest lines are formed far outside,perhaps at the outer boundary of the expanding envelope,i.e.in the region which is heated by shock wave dissipation.As result of our ﬁrst numerical experiments,we con-cluded that the spectra of V838Mon in 2002February -March were similar to the spectrum of a normal late (su-per)giant,broadened by strong macroturbulence motions and/or expansion of its pseudophotosphere.Unfortunately we cannot,from the observed spectra,distinguish between broadening due to the macroturbulence and expansion (see next section).It is worth noting that the observed spectra of V838Mon are formed in a medium with decreasing temperature to the outside,i.e.in the local co-moving system of co-ordinates the atmosphere,to a ﬁrst approximation,can be described by a “normal”model,at least in the region of formation of weak or intermediate strength atomic lines.0.10.20.3 0.4 0.5 0.6 0.7 0.8 0.91 1.1 570057105720573057405750N o r m a l i s e d F l u xWavelength (Å)V 838 Mon ArcturusArcturus conv. V macro =50 km s −1Figure parison of the spectrum of V838Mon and that of Arcturus,convolved with macroturbulent proﬁle V macro =50km s −13.1Fits to observed spectraWe computed a sample of LTE synthetic spectra for a grid of Kurucz (1993)model atmospheres with T eﬀ=4000–6000K using the WITA612program (Pavlenko 1997).Synthetic spectra were computed with wavelength step 0.02˚A ,micro-turbulent velocities 2–18km s −1with a step 1km s −1,iron abundances log N (Fe)=−5.6→−3.6dex 1,with a step 0.1dex.Then,due to the high luminosity of the star,we formally adopt log g =0.Synthetic spectra were computed using the VALD (Kupka et al.1999)line list.For atomic lines the line broadening constants were taken from VALD or computed following Unsold (1955).For the dates of our observations lines of neutral iron dominate in the spectra.Fortunately,they show rather weak gravity/pressure dependence,therefore the uncertainty in the choice of log g will not be important in determining our main results;the dependence of the computed spectra on T eﬀis more signiﬁcant (see Fig.4).The computed syn-thetic spectra were convolved with diﬀerent proﬁles,and then ﬁtted to the observed spectra following the numeri-cal scheme described in Jones et al.(2002)and Pavlenko &Jones (2002).In order to determine the best ﬁt parameters,we com-pared the observed residual ﬂuxes r obsλwith computed values H theorλ+f s .We let H obs λ= F theor x −y ∗G (y )∗dy ,where F theor λis the theoretical ﬂux and G (y )is the broadening proﬁle.In our case G (y )may be wavelength dependent.To get the best ﬁt we ﬁnd the minima per point of the 2D functionS (f s ,f g )=Σ(1−H synt /H obs )2.We calculated these minimization parameters for our grid of synthetic spectra to determine a set of parameters f s (wavelength shift parameter)and f g (convolution parame-ter).The theoretical spectra were convolved with a gaussian proﬁle.Our convolution proﬁle is formed by both expan-sion and macroturbulent motions.We cannot distinguish between them in our spectra.To get a numerical estimate1in the paper we use the abundance scaleN i =14Bogdan M.Kaminsky,Yakiv V.Pavlenko0.60.650.7 0.75 0.8 0.85 0.90.95 1 6306 6308 6310 6312 6314 6316 6318 6320 6322 6324N o r m a l i s e d F l u xWavelength (Å)T eff =4000 KT eff =5000 K logg=0T eff =5000 K logg=1T eff =6000 KFigure 4.Dependence of computed spectra on T eﬀand log gof the broadening processes in the pseudophotosphere,we use a formal parameter V g ,which describes the cumulative eﬀect of broadening/expansion motions.The parameters f s and f g were determined by the min-imization procedure;the procedure was carried out for dif-ferent spectral regions.We selected for analysis 6spectral orders in the interval 5600-6700˚A .In the red,spectral lines are blended by telluric spectra,and are of lower S/N.In the blue the blending of the spectra are rather high.Our main intention was to obtain a self-consistent solution sep-arately for diﬀerent echelle orders,and then compare them.If we could obtain similar parameters from diﬀerent spec-tral regions it can be evidence of the reality of the obtained solution.4RESULTS 4.1The SunTo be conﬁdent in our procedure,we carried out a similar analysis for the Sun.For this case we know the solar abun-dances and other basic parameters,therefore our analysis provides an independent estimation of the quality of our procedure:•From the solar atlas of Kurucz et al (1984)we ex-tract spectral regions corresponding to our observed orders of V838Mon;•we convolve the solar spectra with a gaussian of V macro =50km s −1.•we carried out a spectral analysis of the spectral regions with our procedure;again,model atmospheres from Kurucz (1993)with a grid of diﬀerent log g ,T eﬀ,log N (Fe)were used.The results of our “re-determination”of parameters of the solar atmosphere are given in Table 1.The best ﬁt to one spectral region is shown in Fig.5.From our analysis of the solar spectrum we obtained T eﬀ=5625±125K,log N (Fe)=−4.48±0.15dex,V t =1.2±0.4km s −1.Here and below we used the standard deviation for error esti-mates.All these parameters are in good agreement with theTable 1.Parameters of the solar atmosphere116480–668555001-4.545.8126300–649057502-4.646.4136125–631557501-4.442.9145960–614557501-4.244.1165660–581055001-4.643.9175520–567055001-4.642.9Averaged56251.2-4.4844.3The absorption spectrum of V838Mon5–For February25we obtained T eﬀ=5330±300K,log N(Fe)=−4.7±0.14dex and V t=13.±2.8km s−1.–For the March26data the mean values are T eﬀ=4960±270K,log N(Fe)=−4.68±0.11dex,V t=12.5±1.7km s−1.–And for March2the mean values are T eﬀ=5540±190K,log N(Fe)=−4.75±0.14dex,V t=13.3±3.2kms−1.–We obtained V g=54±3,47±3and42±5km s−1for February25,March2and March26,respectively.–The f s parameter provides the heliocentric velocity ofV838Mon.We obtained V radial=−76±3,−70±3and−65±3km s−1for February25,March2and March26,respectively.Most probably,we see some reduction in theexpansion velocity of the envelope.5DISCUSSIONFrom a comparison of our results for all three dates we see that:•The eﬀective temperature for March26is somewhat lower then for the previous dates.This is an expected re-sult,in view of the gradual cooling of envelope.However, for March2we found a slightly higher value of temperature than for February25.A possible explanation is the heating of the pseudophotosphere as result of the third outburst.•The microturbulent velocities are very similar and ex-tremely high for all three dates.•Our analysis shows a lower value of V g for the later dates:the eﬀects of expansion and macroturbulence were weakened at the later stages of evolution of the pseudopho-tosphere of V838Mon.•The iron abundances log N(Fe)=-4.7±0.14are similar for all dates.Our estimates of eﬀective temperature are in a good agreement with Kipper et al.(2004),although we used dif-ferent procedures of analysis.The iron abundance([Fe/H]=−0.4)and microturbulent velocity(V t=12km s−1)found by Kipper et al.(2004)for March18are in agreement with our results.Our deduced“eﬀective temperatures”as well as those in Kipper et al(2004)do not correspond with values ob-tained from photometry(T eﬀ∼4200K).We assume that in our analysis we deal with temperatures in the line forming region,rather than with the temperatures at photospheric levels which determine the spectral energy distribution of V838Mon and the photometric indices.Indeed,the formally determined microturbulent velocity V t=13km s−1exceeds the sound velocity in the atmosphere(4-5km s−1).This means that the region of formation of atomic lines should be heated by dissipation of supersonic motions:the temper-ature there should be higher than that given in a plane-parallel atmosphere of T eﬀ∼4200K.Certainly the eﬀect cannot be explained by sphericity eﬀects:the temperature gradients in the extended atmo-spheres should be steeper(see Mihalas1978),therefore tem-peratures in the line forming regions should be even lower, in contradiction with our results.Strong deviations from LTE are known to occur during the photospheric stages of the evolution of novae and super-0.40.50.60.70.80.911.16480 6500 6520 6540 6560 6580 6600 6620 6640 6660 6680 6700 NormalisedFluxWavelength (Å)V 838 MonT eff=5250 KT eff=4500 K0.40.50.60.70.80.911.16300 6320 6340 6360 6380 6400 6420 6440 6460 6480 6500 NormalisedFluxWavelength (Å)V 838 MonT eff=5000 KT eff=4500 K0.40.50.60.70.80.911.16120 6140 6160 6180 6200 6220 6240 6260 6280 6300 6320 NormalisedFluxWavelength (Å)V 838 MonT eff=5250 KT eff=4500 KFigure6.The bestﬁts of synthetic spectra to11-13orders of the observed spectrum of V838Mon on February25,found by the minimization procedure.novae.The main eﬀect there should be caused by deviations from LTE in the ionization balance.However,in our case we used lines of the neutral iron,which dominate by number. We cannot expect a reduction in the density of Fe I atoms in the comparatively cool atmosphere of the star.Further-more,we exclude from our analysis strong lines with P Cyg proﬁles.Lines of interest in our study have normal proﬁles.6Bogdan M.Kaminsky,Yakiv V.PavlenkoTable2.Atmospheric parameters for V838MonAsiago spectraFebruary25116480–6685525015-4.753.2-79.6126300–6490500014-4.954.5-76.3136125–6315525010-4.756.0-82.7145960–6145575017-4.552.5-79.5165660–581050009-4.960.7-67.1175520–5670575014-4.751.1-73.6Averaged533013.2-4.7354.7-76.5March26116480–6685475012-4.843.7-67.3126300–6490475014-4.844.7-68.3136125–6315475010-4.546.0-74.3145960–6145500015-4.842.1-65.8165660–5810500011-4.738.8-52.2175520–5670550013-4.539.7-63.6Average496012.5-4.6842.5-65.2SAAO spectraMarch2116480–6685550012-4.645.3-80.6126300–6490525016-4.955.8-77.3136125–631552507-4.642.8-78.9145960–6145575014-4.849.0-80.6165660–5810550015-4.951.7-68.1175520–5670600016-4.742.1-80.0Average554013.3-4.7547.8-77.6The absorption spectrum of V838Mon70.40.50.6 0.7 0.8 0.9 1 1.1 5960 5980 6000 6020 6040 6060 6080 6100 6120 6140 6160N o r m a l i s e d F l u xWavelength (Å)V 838 Mon T eff =5750 K T eff =4500 K0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 5660 5680570057205740576057805800N o r m a l i s e d F l u xWavelength (Å)V 838 Mon T eff =5000 K T eff =4500 K0.40.50.6 0.7 0.8 0.9 1 1.1 5500 5520 5540 5560 5580 5600 5620 5640 5660 5680N o r m a l i s e d F l u xWavelength (Å)V 838 Mon T eff =5750 K T eff =4500 K Figure 7.The best ﬁts of synthetic spectra to orders 14,16and 17of the observed spectrum of V838Mon on February 25,found by the minimization procedure.•most probably,the line-forming region is heated by su-personic motions –our spectroscopic temperatures exceed photometrically determined T eﬀby ∼1000K;•we do not ﬁnd any signiﬁcant change in the iron abun-dance in atmosphere V838from February 25to March 26.•we derived a moderate deﬁcit of iron log N (Fe)∼−4.7in the atmosphere of V838Mon.ACKNOWLEDGMENTSWe thank Drs.Ulisse Munari,Lisa Crause,Tonu Kipper and Valentina Klochkova for providing spectra and for discus-sions of our results.We thank Dr.Nye Evans for improving text of paper.We thank unknown referee for many helpful remarks.This work was partially supported by a PPARC visitors grants from PPARC and the Royal Society.YPs studies are partially supported by a Small Research Grant from American Astronomical Society.This research has made use of the SIMBAD database,operated at CDS,Strasbourg,France.REFERENCESAllen C.W.,1973,Astrophysical quantities,3rd edition,TheAthlone Press,LondonBanerjee D.P.K.,Ashok N.M.,2002,A&A,395,161Bond H.E.,et al.,2003,Natur,422,405Brown N.J.,2002,IAU Circ,7785,1Crause L.A.,Lawson W.A.,Kilkenny D.,van Wyk F.,MarangF.,Jones A.F.,2003,MNRAS,341,785Desidera,S.,Munari,U.,2002,IAU Circ,7982,1Evans A.,Geballe T.R.,Rushton M.T.,Smalley B.,van LoonJ.Th.,Eyres S.P.S.,Tyne V.H.,2003,MNRAS,343,1054Henden A.,Munari U.,Schwartz M.B.,2002,IAU Circ,7859Jones H.R.A.,Pavlenko Ya.,Viti S.,Tennyson J.,2002,MNRAS,330,675JKimeswenger S.,Ledercle C.,Schmeja S.,Armsdorfer B.,2002,MNRAS,336,L43Kipper T.,et al.,2004,A&A,416,1107Kolev D.,Mikolajewski M.,Tomow T.,Iliev I.,Osiwala J.,Nirski J.,Galan C.,2002,Collected Papers,Physics (Shu-men,Bulgaria:Shumen University Press),147Kupka F.,Piskunov N.,Ryabchikova T.A.,Stempels H.C.,WeissW.W.,1999,A&AS,138,119Kurucz R.L.,Furenlid I.,Brault J.,Testerman L.,1984,Nationalsolar obs.-Sunspot,New Mexico Kurucz R.L.,1993,CD-ROM 13Mihalas D.,1978,Stellar atmospheres,Freeman &Co.Munari U.,et al.,2002a,A&A,389,L51Munari U.,Henden A.,Corradi R.M.L,Zwitter T.,2002b,in”Classical Nova Explosions”,M.Hernanz and J.Jos´e eds.,AIP Conf.Ser.637,52Osiwala J.P.,Mikolajewski M.,Tomow T.,Galan C.,Nirski J.,2003,ASP Conf.Ser.,303,in pressPavlenko Y.V.,1997,Astron.Reps,41,537Pavlenko Ya.V.,Jones H.R.A.,2002.A&A,397,967Pavlenko Ya.V.,2003.Astron.Reps,47,59Soker N.,Tylenda R.,2003,ApJ,582,L105Tylenda R.,2004,A&A,414,223Unsold A.,1955Physik der Sternatmospheren,2nd ed.Springer.BerlinWisniewski J.P.,Morrison N.D.,Bjorkman K.S.,MiroshnichenkoA.S.,Gault A.C.,Hoﬀman J.L.,Meade M.R.,Nett J.M.,2003,ApJ,588,486This paper has been typeset from a T E X/L A T E X ﬁle preparedby the author.。

辐射强度与波长与温度的关系英文解释

辐射强度与波长与温度的关系英文解释Radiation is a fundamental aspect of physics and plays a crucial role in various scientific phenomena. One of the key properties of radiation is its intensity, which is directly related to the wavelength and temperature of the radiating body.The intensity of radiation is a measure of the amount of energy emitted per unit area and time by a radiating body. It is usually denoted as I and is expressed in units of watts per square meter (W/m2). The intensity of radiation is directly proportional to the fourth power of the temperature of the radiating body, known as the Stefan-Boltzmann law. This means that as the temperature of the radiating body increases, the intensity of radiation emitted also increases significantly.Another important parameter that influences the intensity of radiation is the wavelength of the radiation. The relationship between the intensity of radiation and the wavelength is described by Wien's displacement law, which states that the peak wavelength of radiation emitted by a blackbody is inversely proportional to its temperature. In other words, as the temperature of the radiating body increases, the peak wavelength of radiation shifts to shorter wavelengths.The relationship between the intensity of radiation, wavelength, and temperature can be further explained by the Planck radiation law, which describes the spectral distribution of radiation emitted by a blackbody at a given temperature. According to this law, the intensity of radiation at a specific wavelength is determined by the temperature of the radiating body and the wavelength of the radiation.In practical terms, these relationships have important implications for various fields of science and technology. For example, in astronomy, the intensity of radiation emitted by stars at different wavelengths can provide valuable insight into their temperature and composition. In engineering, the knowledge of radiation intensity is critical for the design of thermal systems and the development of energy-efficient technologies.In conclusion, the intensity of radiation is closely linked to the wavelength and temperature of the radiating body. By understanding these relationships and laws governing radiation, scientists and engineers can better manipulate and harness radiation for various applications and advancements in science and technology.。

无损检测术语(中英文对照)

无损检测名词术语中英文对照A1/3——该表节选自《中英文无损检测名词术语查询系统（NDTGP）》A.C magnetic saturation 交流磁饱和Absorbed dose 吸收剂量Absorbed dose rate 吸收剂量率Acceptanc limits 验收范围Acceptance level 验收水平Acceptance standard 验收标准Accumulation test 累积检测Acoustic emission count（emission count）声发射计数（发射计数）Acoustic emission transducer 声发射换能器（声发射传感器）Acoustic emission(AE) 声发射Acoustic holography 声全息术Acoustic impedance 声阻抗Acoustic impedance matching 声阻抗匹配Acoustic impedance method 声阻法Acoustic wave 声波Acoustical lens 声透镜Acoustic—ultrasonic 声-超声（AU）Activation 活化Activity 活度Adequate shielding 安全屏蔽Ampere turns 安匝数Amplitude 幅度Angle beam method 斜射法Angle of incidence 入射角Angle of reflection 反射角Angle of spread 指向角Angle of squint 偏向角Angle probe 斜探头Angstrom unit 埃(A)Area amplitude response curve 面积幅度曲线Area of interest 评定区Arliflcial disconlinuity 人工不连续性Artifact 假缺陷Artificial defect 人工缺陷Artificial discontinuity 标准人工缺陷A-scan A型扫描A-scope; A-scan A型显示Attenuation coefficient 衰减系数Attenuator 衰减器Audible leak indicator 音响泄漏指示器Automatic testing 自动检测Autoradiography 自射线照片A valuation 评定Barium concrete 钡混凝土Barn 靶Base fog 片基灰雾Bath 槽液Bayard- Alpert ionization gage B- A型电离计Beam 声束Beam ratio 光束比Beam angle 束张角Beam axis 声束轴线Beam index 声束入射点Beam path location 声程定位Beam path; path length 声程Beam spread 声束扩散Betatron 电子感应加速器Bimetallic strip gage 双金属片计Bipolar field 双极磁场Black light filter 黑光滤波器Black light; ultraviolet radiation 黑光Blackbody 黑体Blackbody equivalent temperature 黑体等效温度Bleakney mass spectrometer 波利克尼质谱仪Bleedout 渗出Bottom echo 底面回波Bottom surface 底面Boundary echo(first) 边界一次回波Bremsstrahlung 轫致辐射Broad-beam condition 宽射束Brush application 刷涂B-scan presenfation B型扫描显示B-scope;B-scan B型显示C- scan C型扫描Calibration,instrument 设备校准Capillary action 毛细管作用Carrier fluid 载液Carry over of penetrate 渗透剂移转Cassette 暗合Cathode 阴极Central conductor 中心导体Central conductor method 中心导体法Characteristic curve 特性曲线Characteristic curve of film 胶片特性曲线Characteristic radiation 特征辐射Chemical fog 化学灰雾Cine-radiography 射线(活动)电影摄影术Cintact pads 接触垫Circumferential coils 圆环线圈Circumferential field 周向磁场Circumferential magnetization method 周向磁化法Clean 清理Clean- up 清除Clearing time 定透时间Coercive force 矫顽力Coherence 相干性Coherence length 相干长度（谐波列长度）Coi1，test 测试线圈Coil size 线圈大小Coil spacing 线圈间距Coil technique 线圈技术Coil method 线圈法Coilreference 线圈参考Coincidence discrimination 符合鉴别Cold-cathode ionization gage 冷阴极电离计Collimator 准直器Collimation 准直Collimator 准直器Combined colour comtrast and fluorescent penetrant 着色荧光渗透剂Compressed air drying 压缩空气干燥Compressional wave 压缩波Compton scatter 康普顿散射Continuous emission 连续发射Continuous linear array 连续线阵Continuous method 连续法Continuous spectrum 连续谱Continuous wave 连续波Contract stretch 对比度宽限Contrast 对比度Contrast agent 对比剂Contrast aid 反差剂Contrast sensitivity 对比灵敏度Control echo 监视回波Control echo 参考回波Couplant 耦合剂Coupling 耦合Coupling losses 耦合损失Cracking 裂解Creeping wave 爬波Critical angle 临界角Cross section 横截面Cross talk 串音Cross-drilled hole 横孔Crystal 晶片C-scope;C-scan C型显示Curie point 居里点Curie temperature 居里温度Curie(Ci) 居里Current flow method 通电法Current induction method 电流感应法Current magnetization method 电流磁化法Cut－off level 截止电平Dead zone 盲区Decay curve 衰变曲线Decibel(dB) 分贝Defect 缺陷Defect resolution 缺陷分辨力Defect detection sensitivity 缺陷检出灵敏度Defect resolution 缺陷分辨力Definition 清晰度Definition，image definition 清晰度，图像清晰度Demagnetization 退磁Demagnetization factor 退磁因子Demagnetizer 退磁装置Densitometer 黑度计Density 黑度（底片）Density comparison strip 黑度比较片Detecting medium 检验介质Detergent remover 洗净液Developer 显像剂Developer station 显像工位Developer，agueons 水性显象剂Developer，dry 干显象剂Developer，liquid film 液膜显象剂Developer，nonaqueous（sus- pendible）非水（可悬浮）显象剂Developing time 显像时间Development 显影Diffraction mottle 衍射斑Diffuse indications 松散指示Diffusion 扩散Digital image acquisition system 数字图像识别系统Dilatational wave 膨胀波Dip and drain station 浸渍和流滴工位Direct contact magnetization 直接接触磁化Direct exposure imaging 直接曝光成像Direct contact method 直接接触法Directivity 指向性Discontinuity 不连续性Distance- gain- size-German A VG 距离- 增益- 尺寸（DGS德文为A VG）Distance marker; time marker 距离刻度Dose equivalent 剂量当量Dose rate meter 剂量率计Dosemeter 剂量计Double crystal probe 双晶片探头Double probe technique 双探头法Double transceiver technique 双发双收法Double traverse technique 二次波法Dragout 带出Drain time 滴落时间Drain time 流滴时间Drift 漂移Dry method 干法Dry powder 干粉Dry technique 干粉技术Dry developer 干显像剂Dry developing cabinet 干显像柜Dry method 干粉法Drying oven 干燥箱Drying station 干燥工位Drying time 干燥时间D-scope;D-scan D型显示Dual search unit 双探头Dual-focus tube 双焦点管Duplex-wire image quality indicator 双线像质指示器Duration 持续时间Dwell time 停留时间Dye penetrant 着色渗透剂Dynamic leak test 动态泄漏检测Dynamic leakage measurement 动态泄漏测量Dynamic range 动态范围Dynamic radiography 动态射线透照术Echo 回波Echo frequency 回波频率Echo height 回波高度Echo indication 回波指示Echo transmittance of sound pressure 往复透过率Echo width 回波宽度Eddy current 涡流Eddy current flaw detector 涡流探伤仪Eddy current testiog 涡流检测Edge 端面Edge effect 边缘效应Edge echo 棱边回波Edge effect 边缘效应Effective depth penetration（EDP）有效穿透深度Effective focus size 有效焦点尺寸Effective magnetic permeability 有效磁导率Effective permeability 有效磁导率Effective reflection surface of flaw 缺陷有效反射面Effective resistance 有效电阻Elastic medium 弹性介质Electric displacement 电位移Electrical center 电中心Electrode 电极Electromagnet 电磁铁Electro-magnetic acoustic transducer 电磁声换能器Electromagnetic induction 电磁感应Electromagnetic radiation 电磁辐射Electromagnetic testing 电磁检测Electro-mechanical coupling factor 机电耦合系数Electron radiography 电子辐射照相术Electron volt 电子伏恃Electronic noise 电子噪声Electrostatic spraying 静电喷涂Emulsification 乳化Emulsification time 乳化时间Emulsifier 乳化剂Encircling coils 环绕式线圈End effect 端部效应Energizing cycle 激励周期Equalizing filter 均衡滤波器Equivalent 当量Equivalent I．Q. I.Sensitivity 象质指示器当量灵敏度Equivalent nitrogen pressure 等效氮压Equivalent penetrameter sensifivty 透度计当量灵敏度Equivalent method 当量法Erasabl optical medium 可探光学介质Etching 浸蚀Evaluation 评定Evaluation threshold 评价阈值Event count 事件计数Event count rate 事件计数率Examination area 检测范围Examination region 检验区域Exhaust pressure/discharge pressure 排气压力Exhaust tubulation 排气管道Expanded time-base sweep 时基线展宽Exposure 曝光Exposure table 曝光表格Exposure chart 曝光曲线Exposure fog 曝光灰雾Exposure，radiographic exposure 曝光，射线照相曝光Extended source 扩展源Facility scattered neutrons 条件散射中子False indication 假指示Family 族Far field 远场Feed-through coil 穿过式线圈Field，resultant magnetic 复合磁场Fill factor 填充系数Film speed 胶片速度Film badge 胶片襟章剂量计Film base 片基Film contrast 胶片对比度Film gamma 胶片γ值Film processing 胶片冲洗加工Film speed 胶片感光度Film unsharpness 胶片不清晰度Film viewing screen 观察屏Filter 滤波器/滤光板Final test 复探Flat-bottomed hole 平底孔Flat-bottomed hole equivalent 平底孔当量Flaw 伤Flaw characterization 伤特性Flaw echo 缺陷回波Flexural wave 弯曲波Floating threshold 浮动阀值Fluorescence 荧光Fluorescent examination method 荧光检验法Fluorescent magnetic particle inspection 荧光磁粉检验Fluorescent dry deposit penetrant 干沉积荧光渗透剂Fluorescent light 荧光Fluorescent magnetic powder 荧光磁粉Fluorescent penetrant 荧光渗透剂Fluorescent screen 荧光屏Fluoroscopy 荧光检查法Flux leakage field 磁通泄漏场Flux lines 磁通线Focal spot 焦点Focal distance 焦距Focus length 焦点长度Focus size 焦点尺寸Focus width 焦点宽度Focus(electron) 电子焦点Focused beam 聚焦声束Focusing probe 聚焦探头Focus-to-film distance(f.f.d) 焦点-胶片距离（焦距）Fog 底片灰雾Fog density 灰雾密度Footcandle 英尺烛光Freguency 频率Frequency constant 频率常数Fringe 干涉带Front distance 前沿距离Front distance of flaw 缺陷前沿距离Full- wave direct current（FWDC）全波直流Fundamental frequency 基频Furring 毛状迹痕Gage pressure 表压Gain 增益Gamma radiography γ射线透照术Gamma ray source γ射线源Gamma ray source container γ射线源容器Gamma rays γ射线Gamma-ray radiographic equipment γ射线透照装置Gap scanning 间隙扫查Gas 气体Gate 闸门Gating technique 选通技术Gauss 高斯Geiger-Muller counter 盖革.弥勒计数器Geometric unsharpness 几何不清晰度Gray(Gy) 戈瑞Grazing incidence 掠入射Grazing angle 掠射角Group velocity 群速度Half life 半衰期Half- wave current（HW）半波电流Half-value layer(HVL) 半值层Half-value method 半波高度法Halogen 卤素Halogen leak detector 卤素检漏仪Hard X-rays 硬X射线Hard-faced probe 硬膜探头Harmonic analysis 谐波分析Harmonic distortion 谐波畸变Harmonics 谐频Head wave 头波Helium bombing 氦轰击法Helium drift 氦漂移Helium leak detector 氦检漏仪Hermetically tight seal 气密密封High vacuum 高真空High energy X-rays 高能X射线Holography (optical) 光全息照相Holography，acoustic 声全息Hydrophilic emulsifier 亲水性乳化剂Hydrophilic remover 亲水性洗净剂Hydrostatic text 流体静力检测Hysteresis 磁滞Hysteresis 磁滞IACS IACSID coil ID线圈Image definition 图像清晰度Image contrast 图像对比度Image enhancement 图像增强Image magnification 图像放大Image quality 图像质量Image quality indicator sensitivity 像质指示器灵敏度Image quality indicator(IQI)/image quality indication 像质指示器Imaging line scanner 图像线扫描器Immersion probe 液浸探头Immersion rinse 浸没清洗Immersion testing 液浸法Immersion time 浸没时间Impedance 阻抗Impedance plane diagram 阻抗平面图Imperfection 不完整性Impulse eddy current testing 脉冲涡流检测Incremental permeability 增量磁导率Indicated defect area 缺陷指示面积Indicated defect length 缺陷指示长度Indication 指示Indirect exposure 间接曝光Indirect magnetization 间接磁化Indirect magnetization method 间接磁化法Indirect scan 间接扫查Induced field 感应磁场Induced current method 感应电流法Infrared imaging system 红外成象系统Infrared sensing device 红外扫描器Inherent fluorescence 固有荧光Inherent filtration 固有滤波Initial permeability 起始磁导率Initial pulse 始脉冲Initial pulse width 始波宽度Inserted coil 插入式线圈Inside coil 内部线圈Inside- out testing 外泄检测Inspection 检查Inspection medium 检查介质Inspection frequency/ test frequency 检测频率Intensifying factor 增感系数Intensifying screen 增感屏Interal,arrival time（Δtij)/arrival time interval（Δtij）到达时间差(Δtij) Interface boundary 界面Interface echo 界面回波Interface trigger 界面触发Interference 干涉Interpretation 解释Ion pump 离子泵Ion source 离子源Ionization chamber 电离室Ionization potential 电离电位Ionization vacuum gage 电离真空计Ionography 电离射线透照术Irradiance， E 辐射通量密度， EIsolation 隔离检测Isotope 同位素K value K值Kaiser effect 凯塞(Kaiser)效应Kilo volt kv千伏特Kiloelectron volt keV千电子伏特Krypton85 氪85L／D ratio L/D比Latent image 潜象Lateral scan 左右扫查Lateral scan with oblique angle 斜平行扫查Latitude (of an emulsion) 胶片宽容度Lead screen 铅屏Leak 泄漏孔Leak artifact 泄漏器Leak detector 检漏仪Leak testtion 泄漏检测Leakage field 泄漏磁场Leakage rate 泄漏率Leechs 磁吸盘Lift-off effect 提离效应Light intensity 光强度Limiting resolution 极限分辨率Line scanner 线扫描器Line focus 线焦点Line pair pattern 线对检测图Line pairs per millimetre 每毫米线对数Linear (electron) accelerator(LINAC) 电子直线加速器Linear attenuation coefficient 线衰减系数Linear scan 线扫查Linearity（time or distance）线性（时间或距离）Linearity，anplitude 幅度线性Lines of force 磁力线Lipophilic emulsifier 亲油性乳化剂Lipophilic remover 亲油性洗净剂Liquid penetrant examination 液体渗透检验Liquid film developer 液膜显像剂Local magnetization 局部磁化Local magnetization method 局部磁化法Local scan 局部扫查Localizing cone 定域喇叭筒Location 定位Location accuracy 定位精度Location computed 定位，计算Location marker 定位标记Location upon delta-T 时差定位Location，clusfer 定位，群集Location，continuous AE signal 定位，连续AE信号Longitudinal field 纵向磁场Longitudinal magnetization method 纵向磁化法Longitudinal resolution 纵向分辨率Longitudinal wave probe 纵波探头Longitudinal wave technique 纵波法Loss of back reflection 背面反射损失Loss of back reflection 底面反射损失Love wave 乐甫波Low energy gamma radiation 低能γ辐射Low－enerugy photon radiation 低能光子辐射Luminance 亮度Luminosity 流明Lusec 流西克Maga or million electron volts MeV兆电子伏特Magnetic history 磁化史Magnetic hysteresis 磁性滞后Magnetic particle field indication 磁粉磁场指示器Magnetic particle inspection flaw indications 磁粉检验的伤显示Magnetic circuit 磁路Magnetic domain 磁畴Magnetic field distribution 磁场分布Magnetic field indicator 磁场指示器Magnetic field meter 磁场计Magnetic field strength 磁场强度(H)Magnetic field/field，magnetic 磁场Magnetic flux 磁通Magnetic flux density 磁通密度Magnetic force 磁化力Magnetic leakage field 漏磁场Magnetic leakage flux 漏磁通Magnetic moment 磁矩Magnetic particle 磁粉Magnetic particle indication 磁痕Magnetic particle testing/magnetic particle examination 磁粉检测Magnetic permeability 磁导率Magnetic permeability 磁导率Magnetic pole 磁极Magnetic saturataion 磁饱和Magnetic saturation 磁饱和Magnetic slorage meclium 磁储介质Magnetic writing 磁写Magnetizing 磁化Magnetizing current 磁化电流Magnetizing coil 磁化线圈Magnetostrictive effect 磁致伸缩效应Magnetostrictive transducer 磁致伸缩换能器Main beam 主声束Manual testing 手动检测Markers 时标MA-scope;MA-scan MA型显示Masking 遮蔽Mass attcnuation coefficient 质量吸收系数Mass number 质量数Mass spectrometer（M.S.）质谱仪Mass spectrometer leak detector 质谱检漏仪Mass spectrum 质谱Master/slave discrimination 主从鉴别MDTD 最小可测温度差Mean free path 平均自由程Medium vacuum 中真空Mega or million volt MV兆伏特Micro focus X - ray tube 微焦点X 光管Microfocus radiography 微焦点射线透照术Micrometre 微米Micron of mercury 微米汞柱Microtron 电子回旋加速器Milliampere 毫安（mA）Millimetre of mercury 毫米汞柱Minifocus x- ray tube 小焦点调射线管Minimum detectable leakage rate 最小可探泄漏率Minimum resolvable temperature difference（MRTD）最小可分辨温度差（MRDT）Mode 波型Mode conversion 波型转换Mode transformation 波型转换Moderator 慢化器Modulation transfer function（MTF）调制转换功能（MTF）Modulation analysis 调制分析Molecular flow 分子流Molecular leak 分子泄漏Monitor 监控器Monochromatic 单色波Movement unsharpness 移动不清晰度Moving beam radiography 可动射束射线透照术Multiaspect magnetization method 多向磁化法Multidirectional magnetization 多向磁化Multifrequency eddy current testiog 多频涡流检测Multiple back reflections 多次背面反射Multiple reflections 多次反射Multiple back reflections 多次底面反射Multiple echo method 多次反射法Multiple probe technique 多探头法Multiple triangular array 多三角形阵列Narrow beam condition 窄射束NC NCNear field 近场Near field length 近场长度Near surface defect 近表面缺陷Net density 净黑度Net density 净(光学)密度Neutron 中子Neutron radiograhy 中子射线透照Neutron radiography 中子射线透照术Newton（N）牛顿Nier mass spectrometer 尼尔质谱仪Noise 噪声Noise 噪声Noise equivalent temperature difference（NETD）噪声当量温度差（NETD）Nominal angle 标称角度Nominal frequency 标称频率Non-aqueous liquid developer 非水性液体显像剂Noncondensable gas 非冷凝气体Nondcstructivc Examination（NDE）无损试验Nondestructive Evaluation（NDE）无损评价Nondestructive Inspection（NDI）无损检验Nondestructive Testing（NDT）无损检测Nonerasble optical data 可固定光学数据Nonferromugnetic material 非铁磁性材料Nonrelevant indication 非相关指示Non-screen-type film 非增感型胶片Normal incidence 垂直入射（亦见直射声束）Normal permeability 标准磁导率Normal beam method; straight beam method 垂直法Normal probe 直探头Normalized reactance 归一化电抗Normalized resistance 归一化电阻Nuclear activity 核活性Nuclide 核素Object plane resolution 物体平面分辨率Object scattered neutrons 物体散射中子Object beam 物体光束Object beam angle 物体光束角Object-film distance 被检体-胶片距离Object一film distance 物体- 胶片距离Over development 显影过度Over emulsfication 过乳化Overall magnetization 整体磁化Overload recovery time 过载恢复时间Overwashing 过洗Oxidation fog 氧化灰雾P PPair production 偶生成Pair production 电子对产生Pair production 电子偶的产生Palladium barrier leak detector 钯屏检漏仪Panoramic exposure 全景曝光Parallel scan 平行扫查Paramagnetic material 顺磁性材料Parasitic echo 干扰回波Partial pressure 分压Particle content 磁悬液浓度Particle veloc ity 质点(振动)速度Pascal（Pa）帕斯卡（帕）Pascal cubic metres per second 帕立方米每秒（Pa·m3/s ）Path length 光程长Path length difference 光程长度差Pattern 探伤图形Peak current 峰值电流Penetrameter 透度计Penetrameter sensitivity 透度计灵敏度Penetrant 渗透剂Penetrant comparator 渗透对比试块Penetrant flaw detection 渗透探伤Penetrant removal 渗透剂去除Penetrant station 渗透工位Penetrant，water- washable 水洗型渗透剂Penetration 穿透深度Penetration time 渗透时间Permanent magnet 永久磁铁Permeability coefficient 透气系数Permeability，a-c 交流磁导率Permeability，d－c 直流磁导率Phantom echo 幻象回波Phase analysis 相位分析Phase angle 相位角Phase controlled circuit breaker 断电相位控制器Phase detection 相位检测Phase hologram 相位全息Phase sensitive detector 相敏检波器Phase shift 相位移Phase velocity 相速度Phase-sensitive system 相敏系统Phillips ionization gage 菲利浦电离计Phosphor 荧光物质Photo fluorography 荧光照相术Photoelectric absorption 光电吸收Photographic emulsion 照相乳剂Photographic fog 照相灰雾Photostimulable luminescence 光敏发光Piezoelectric effect 压电效应Piezoelectric material 压电材料Piezoelectric stiffness constant 压电劲度常数Piezoelectric stress constant 压电应力常数Piezoelectric transducer 压电换能器Piezoelectric voltage constant 压电电压常数Pirani gage 皮拉尼计Pirani gage 皮拉尼计Pitch and catch technique 一发一收法Pixel 象素Pixel size 象素尺寸Pixel，disply size 象素显示尺寸Planar array 平面阵(列)Plane wave 平面波Plate wave 板波Plate wave technique 板波法Point source 点源Post emulsification 后乳化Post emulsifiable penetrant 后乳化渗透剂Post-cleaning 后清除Post-cleaning 后清洗Powder 粉未Powder blower 喷粉器Powder blower 磁粉喷枪Pre-cleaning 预清理Pressure difference 压力差Pressure dye test 压力着色检测Pressure probe 压力探头Pressure testing 压力检测Pressure- evacuation test 压力抽空检测Pressure mark 压痕Pressure,design 设计压力Pre-test 初探Primary coil 一次线圈Primary radiation 初级辐射Probe gas 探头气体Probe test 探头检测Probe backing 探头背衬Probe coil 点式线圈Probe coil 探头式线圈Probe coil clearance 探头线圈间隙Probe index 探头入射点Probe to weld distance 探头-焊缝距离Probe/ search unit 探头Process control radiograph 工艺过程控制的射线照相Processing capacity 处理能力Processing speed 处理速度Prods 触头Projective radiography 投影射线透照术Proportioning probe 比例探头Protective material 防护材料Proton radiography 质子射线透照Pulse 脉冲波Pulse 脉冲Pulse echo method 脉冲回波法Pulse repetition rate 脉冲重复率Pulse amplitude 脉冲幅度Pulse echo method 脉冲反射法Pulse energy 脉冲能量Pulse envelope 脉冲包络Pulse length 脉冲长度Pulse repetition frequency 脉冲重复频率Pulse tuning 脉冲调谐Pump- out tubulation 抽气管道Pump-down time 抽气时间Q factor Q值Quadruple traverse technique 四次波法Quality (of a beam of radiation) 射线束的质Quality factor 品质因数Quenching 阻塞Quenching of fluorescence 荧光的猝灭Quick break 快速断间Rad(rad) 拉德Radiance，L 面辐射率，LRadiant existence，M 幅射照度MRadiant flux；radiant power，ψe 辐射通量、辐射功率、ψe Radiation 辐射Radiation does 辐射剂量Radio frequency（r- f）display 射频显示Radio- frequency mass spectrometer 射频质谱仪Radio frequency(r-f) display 射频显示Radiograph 射线底片Radiographic contrast 射线照片对比度Radiographic equivalence factor 射线照相等效系数Radiographic exposure 射线照相曝光量Radiographic inspection 射线检测Radiographic inspection 射线照相检验Radiographic quality 射线照相质量Radiographic sensitivity 射线照相灵敏度Radiographic contrast 射线底片对比度Radiographic equivalence factor 射线透照等效因子Radiographic inspection 射线透照检查Radiographic quality 射线透照质量Radiographic sensitivity 射线透照灵敏度Radiography 射线照相术Radiological examination 射线检验Radiology 射线学Radiometer 辐射计Radiometry 辐射测量术Radioscopy 射线检查法Range 量程Rayleigh wave 瑞利波Rayleigh scattering 瑞利散射Real image 实时图像Real-time radioscopy 实时射线检查法Rearm delay time 重新准备延时时间Rearm delay time 重新进入工作状态延迟时间Reciprocity failure 倒易律失效Reciprocity law 倒易律Recording medium 记录介质Recovery time 恢复时间Rectified alternating current 脉动直流电Reference block 参考试块Reference beam 参考光束Reference block 对比试块Reference block method 对比试块法Reference coil 参考线圈Reference line method 基准线法Reference standard 参考标准Reflection 反射Reflection coefficient 反射系数Reflection density 反射密度Reflector 反射体Refraction 折射Refractive index 折射率Refrence beam angle 参考光束角Reicnlbation 网纹Reject; suppression 抑制Rejection level 拒收水平Relative permeability 相对磁导率Relevant indication 相关指示Reluctance 磁阻Rem(rem) 雷姆Remote controlled testing 机械化检测Replenisers 补充剂Representative quality indicator 代表性质量指示器Residual magnetic field/field，residual magnetic 剩磁场Residual technique 剩磁技术Residual magnetic method 剩磁法Residual magnetism 剩磁Resistance（to flow）气阻Resolution 分辨力Resonance method 共振法Response factor 响应系数Response time 响应时间Resultant field 复合磁场Resultant magnetic field 合成磁场Resultant magnetization method 组合磁化法Retentivity 顽磁性Reversal 反转现象Ring-down count 振铃计数Ring-down count rate 振铃计数率Rinse 清洗Rise time 上升时间Rise-time discrimination 上升时间鉴别Rod-anode tube 棒阳极管Roentgen(R) 伦琴Roof angle 屋顶角Rotational magnetic field 旋转磁场Rotational magnetic field method 旋转磁场法Rotational scan 转动扫查Roughing 低真空Roughing line 低真空管道Roughing pump 低真空泵S SSafelight 安全灯Sampling probe 取样探头Saturation 饱和Saturation，magnetic 磁饱和Saturation level 饱和电平Scan on grid lines 格子线扫查Scan pitch 扫查间距Scanning 扫查Scanning index 扫查标记Scanning directly on the weld 焊缝上扫查Scanning path 扫查轨迹Scanning sensitivity 扫查灵敏度Scanning speed 扫查速度Scanning zone 扫查区域Scattared energy 散射能量Scatter unsharpness 散射不清晰度Scattered neutrons 散射中子Scattered radiation 散射辐射Scattering 散射Schlieren system 施利伦系统Scintillation counter 闪烁计数器Scintillator and scintillating crystals 闪烁器和闪烁晶体Screen 屏Screen unsharpness 荧光增感屏不清晰度Screen-type film 荧光增感型胶片SE probe SE探头Search-gas 探测气体Second critical angle 第二临界角Secondary radiation 二次射线Secondary coil 二次线圈Secondary radiation 次级辐射Selectivity 选择性Semi-conductor detector 半导体探测器Sensitirity va1ue 灵敏度值Sensitivity 灵敏度Sensitivity of leak test 泄漏检测灵敏度Sensitivity control 灵敏度控制Shear wave 切变波Shear wave probe 横波探头Shear wave technique 横波法Shim 薄垫片Shot 冲击通电Side lobe 副瓣Side wall 侧面Sievert(Sv) 希(沃特)Signal 信号Signal gradient 信号梯度Signal over load point 信号过载点Signal overload level 信号过载电平Signal to noise ratio 信噪比Single crystal probe 单晶片探头Single probe technique 单探头法Single traverse technique 一次波法Sizing technique 定量法Skin depth 集肤深度Skin effect 集肤效应Skip distance 跨距Skip point 跨距点Sky shine(air scatter) 空中散射效应Sniffing probe 嗅吸探头Soft X-rays 软X射线Soft-faced probe 软膜探头Solarization 负感作用Solenoid 螺线管Soluble developer 可溶显像剂Solvent remover 溶剂去除剂Solvent cleaners 溶剂清除剂Solvent developer 溶剂显像剂Solvent remover 溶剂洗净剂Solvent-removal penetrant 溶剂去除型渗透剂Sorption 吸着Sound diffraction 声绕射Sound insulating layer 隔声层Sound intensity 声强Sound intensity level 声强级Sound pressure 声压Sound scattering 声散射Sound transparent layer 透声层Sound velocity 声速Source 源Source data label 放射源数据标签Source location 源定位Source size 源尺寸Source-film distance 射线源-胶片距离Spacial frequency 空间频率Spark coil leak detector 电火花线圈检漏仪Specific activity 放射性比度Specified sensitivity 规定灵敏度Standard 标准Standard 标准试样Standard leak rate 标准泄漏率Standard leak 标准泄漏孔Standard tast block 标准试块Standardization instrument 设备标准化Standing wave; stationary wave 驻波Step wedge 阶梯楔块Step- wadge calibration film 阶梯楔块校准底片Step- wadge comparison film 阶梯楔块比较底片Step wedge 阶梯楔块Step-wedge calibration film 阶梯-楔块校准片Step-wedge comparison film 阶梯-楔块比较片Stereo-radiography 立体射线透照术Subject contrast 被检体对比度Subsurface discontinuity 近表面不连续性Suppression 抑制Surface echo 表面回波Surface field 表面磁场Surface noise 表面噪声Surface wave 表面波Surface wave probe 表面波探头Surface wave technique 表面波法Surge magnetization 脉动磁化Surplus sensitivity 灵敏度余量Suspension 磁悬液Sweep 扫描Sweep range 扫描范围Sweep speed 扫描速度Swept gain 扫描增益Swivel scan 环绕扫查System exanlillatien threshold 系统检验阈值System inclacel artifacts 系统感生物System noise 系统噪声Tackground，target 目标本底Tandem scan 串列扫查Target 耙Target 靶Television fluoroscopy 电视X射线荧光检查Temperature envelope 温度范围Tenth-value-layer(TVL) 十分之一值层Test coil 检测线圈Test quality level 检测质量水平Test ring 试环Test block 试块Test frequency 试验频率Test piece 试片Test range 探测范围Test surface 探测面Testing，ulrasonic 超声检测Thermal neutrons 热中子Thermocouple gage 热电偶计Thermogram 热谱图Thermography，infrared 红外热成象Thermoluminescent dosemeter(TLD) 热释光剂量计Thickness sensitivity 厚度灵敏度Third critiical angle 第三临界角Thixotropic penetrant 摇溶渗透剂Thormal resolution 热分辨率Threading bar 穿棒Three way sort 三档分选Threshold setting 门限设置Threshold fog 阈值灰雾Threshold level 阀值Threshotd tcnet 门限电平Throttling 节流Through transmission technique 穿透技术Through penetration technique 贯穿渗透法Through transmission technique; transmission technique 穿透法Through-coil technique 穿过式线圈技术Throughput 通气量Tight 密封Total reflection 全反射Totel image unsharpness 总的图像不清晰度Tracer probe leak location 示踪探头泄漏定位Tracer gas 示踪气体Transducer 换能器/传感器Transition flow 过渡流Translucent base media 半透明载体介质Transmission 透射Transmission densitomefer 发射密度计Transmission coefficient 透射系数Transmission point 透射点Transmission technique 透射技术Transmittance，τ透射率τTransmitted film density 检测底片黑度Transmitted pulse 发射脉冲Transverse resolution 横向分辨率Transverse wave 横波Traveling echo 游动回波Travering scan; depth scan 前后扫查Triangular array 正三角形阵列Trigger/alarm condition 触发/报警状态Trigger/alarm level 触发/报警标准Triple traverse technique 三次波法True continuous technique 准确连续法技术Trueattenuation 真实衰减Tube current 管电流Tube head 管头Tube shield 管罩Tube shutter 管子光闸Tube window 管窗Tube-shift radiography 管子移位射线透照术Two-way sort 两档分选Ultra- high vacuum 超高真空Ultrasonic leak detector 超声波检漏仪Ultrasonic noise level 超声噪声电平Ultrasonic cleaning 超声波清洗Ultrasonic field 超声场Ultrasonic flaw detection 超声探伤Ultrasonic flaw detector 超声探伤仪Ultrasonic microscope 超声显微镜Ultrasonic spectroscopy 超声频谱Ultrasonic testing system 超声检测系统Ultrasonic thickness gauge 超声测厚仪Ultraviolet radiation 紫外辐射Under development 显影不足Unsharpness 不清晰Useful density range 有效光学密度范围UV-A A类紫外辐射UV-A filter A类紫外辐射滤片V acuum 真空V acuum cassette 真空暗盒V acuum testing 真空检测V acuum cassette 真空暗合V an de Graaff generator 范德格喇夫起电机V apor pressure 蒸汽压V apour degreasing 蒸汽除油V ariable angle probe 可变角探头V ee path V型行程V ehicle 载体V ertical linearity 垂直线性V ertical location 垂直定位Visible light 可见光Vitua limage 虚假图像V oltage threshold 电压阈值V oltage threshold 阈值电压Wash station 水洗工位Water break test 水膜破坏试验Water column coupling method 水柱耦合法Water column probe 水柱耦合探头Water path; water distance 水程Water tolerance 水容限Water-washable penetrant 可水洗型渗透剂Wave 波Wave guide acoustic emission 声发射波导杆Wave train 波列Wave from 波形Wave front 波前Wave length 波长Wave node 波节Wave train 波列Wedge 斜楔Wet slurry technique 湿软磁膏技术Wet technique 湿法技术Wet method 湿粉法Wetting action 润湿作用Wetting action 润湿作用Wetting agents 润湿剂Wheel type probe; wheel search unit 轮式探头White light 白光White X-rays 连续X射线Wobble 摆动Wobble effect 抖动效应Working sensitivity 探伤灵敏度Wrap around 残响波干扰Xeroradiography 静电射线透照术X-radiation X射线X-ray controller X射线控制器X-ray detection apparatus X射线探伤装置X-ray film 射线胶片X-ray paper X射线感光纸X-ray tube X射线管X-ray tube diaphragm X射线管光阑Y oke 磁轭Y oke magnetization method 磁轭磁化法Zigzag scan 锯齿扫查。

红外温度测试仪中英文翻译讲课讲稿

附录一：英文技术资料翻译英文原文：Emerg Infect Dis. 2008 August; 14(8): 1255–1258.doi: 10.3201/eid1408.080059PMCID: PMC2600390Cutaneous Infrared Thermometry for Detecting Febrile PatientsPierre Hausfater, Yan Zhao, Stéphanie Defrenne, Pascale Bonnet, and Bruno Riou* Author information Copyright and License informationThis article has been cited by other articles in PMC.AbstractWe assessed the accuracy of cutaneous infrared thermometry, which measures temperature on the forehead, for detecting patients with fever in patients admitted to an emergency department. Although negative predictive value was excellent (0.99), positive predictive value was low (0.10). Therefore, we question mass detection of febrile patients by using this method.Keywords: Fever, mass detection, cutaneous infrared thermometry, infectious diseases, emergency, dispatchRecent efforts to control spread of epidemic infectious diseases have prompted health officials to develop rapid screening processes to detect febrile patients. Such screening may take place at hospital entry, mainly in the emergency department, or at airports to detect travelers with increased body temperatures (1–3). Infrared thermal imaging devices have been proposed as a noncontact and noninvasive method for detecting fever (4–6). However, few studies have assessed their capacity for accurate detection of febrile patients in clinical settings. Therefore, we undertook a prospective study in an emergency department to assess diagnostic accuracy of infrared thermal imaging.The StudyThe study was performed in an emergency department of a large academic hospital (1,800 beds) and was reviewed and approved by our institutional review board (Comitéde Protection des Personnes se Prêtant àla Recherche Biomédicale Pitié-Salpêtrière, Paris, France). Patients admitted to the emergency department were assessed by a trained triage nurse, and several variables were routinely measured, including tympanic temperature by using an infrared tympanic thermometer (Pro4000; Welch Allyn, Skaneateles Falls, NY, USA), systolic and diastolic arterial blood pressure, and heart rate.Tympanic temperature was measured twice (once in the left ear and once in the right ear). This temperature was used as a reference because it is routinely used in our emergency department and is an appropriate estimate of central core temperature (7–9). Cutaneous temperature was measured on the forehead by using an infrared thermometer (Raynger MX; Raytek, Berlin, Germany) (Figure 1). Rationale for an infrared thermometer device instead of a larger thermal scanner was that we wanted to test a method (i.e., measurement of forehead cutaneous temperature by using a simple infrared thermometer) and not a specific device. The forehead region was chosen because it is more reliable than the region behind the eyes (5,10). The latter region may not be appropriate for mass screening because one cannot accurately measure temperature through eyeglasses, which are worn by many persons. Outdoor and indoor temperatures were also recorded.Figure 1Measurement of cutaneous temperature with an infrared thermometer. A) The device is placed 20 cm from the forehead. B) As soon as the examiner pulls the trigger, the temperature measured is shown on the display. Used with permission.The main objective of our study was to assess diagnostic accuracy of infrared thermometry for detecting patients with fever, defined as a tympanic temperature >38.0°C. The second objective was to compare measurements of cutaneous temperature and tympanic temperature, with the latter being used as a reference point. Data are expressed as mean ± standard deviation (SD) or percentages and their 95% confidence intervals (CIs). Comparison of 2 means was performed by using the Student t test, and comparison of 2 proportions was performed by using the Fisher exact method. Bias, precision (in absolute values and percentages), and number of outliers (defined as a difference >1°C) were also recorded. Correlation between 2 variables was assessed by using the least square method. The Bland and Altman method was used to compare 2 sets of measurements, and the limit of agreement was defined as ±2 SDs of the differences (11). We determined the receiver operating characteristic (ROC) curves and calculated the area under the ROC curve and its 95% CI. The ROC curve was used to determine the best threshold for the definition of hyperthermia for cutaneous temperature to predict a tympanic temperature >38°C. We performed multivariate regression analysis to assess variables associated with thedifference between tympanic and infrared measurements. All statistical tests were 2-sided, and a p value <0.05 was required to reject the null hypothesis. Statistical analysis was performed by using Number Cruncher Statistical Systems 2001 software (Statistical Solutions Ltd., Cork, Ireland).A total of 2,026 patients were enrolled in the study: 1,146 (57%) men and 880 (43%) women 46 ± 19 years of age (range 6–103 years); 219 (11%) were >75 years of age, and 62 (3%) had a tympanic temperature >38°C. Mean tympanic temperature was 36.7°C ± 0.6°C (range 33.7°C–40.2°C), and mean cutaneous temperature was 36.7°C ± 1.7°C (range 32.0°C–42.6°C). Mean systolic arterial blood pressure was 130 ± 19 mm Hg, mean diastolic blood pressure was 79 ± 13 mm Hg, and mean heart rate was 86 ± 17 beats/min. Mean indoor temperature was 24.8°C ± 1.1°C (range 20°C–28°C), and mean outdoor temperature was 10.8°C ± 6.8°C (range 0°C–32°C). Reproducibility of infrared measurements was assessed in 256 patients. Bias was 0.04°C ± 0.35°C, precision was 0.22°C ± 0.27°C (i.e., 0.6 ± 0.7%), and percentage of outliers >1°C was 2.3%.Diagnostic performance of cutaneous temperature measurement is shown in Table 1. For the threshold of the definition of tympanic hyperthermia definition used (37.5°C, 38°C, or 38.5°C), sensitivity of cutaneous temperature was lower than that expected and positive predictive value was low. We attempted to determine the best threshold (definition of hyperthermia) by using cutaneous temperature to predict a tympanic temperature >38°C (Figure 2, panel A). Area under the ROC curve was 0.873 (95% CI 0.807–0.917, p<0.001). The best threshold for cutaneous hyperthermia definition was 38.0°C, a condition already assessed in Table 1. Figure 2, panels B and C shows the correlation between cutaneous and tympanic temperature measurements (Bland and Altman diagrams). Correlation between cutaneous and tympanic measurements was poor, and the infrared thermometer underestimated body temperature at low values and overestimated it at high values. Multiple regression analysis showed that 3 variables (tympanic temperature, outdoor temperature, and age) were significantly (p<0.001) and independently correlated with the magnitude of the difference between cutaneous and tympanic measurements (Table 2).Table 1Assessment of diagnostic performance of cutaneous temperature inpredicting increased tympanic temperature*Figure 2A) Comparison of receiver operating characteristic (ROC) curves showing relationship between sensitivity (true positive) and 1 – specificity (true negative) in determining value of cutaneous temperature for predicting various thresholds of hyperthermia ...Table 2Variables correlated with magnitude of the difference between cutaneous and tympanic temperature measurements*ConclusionsInfrared thermometry does not reliably detect febrile patients because its sensitivity was lower than that expected and the positive predictive value was low, which indicated a high proportion of false-positive results. Ng et al. (5) studied 502 patients, concluded that an infrared thermal imager can appropriately identify febrile patients, and reported a high area under the ROC curve value (0.972), which is similar to the area we found in the present study (0.925). However, such global assessment is of limited value because of low incidence of fever in the population. Rather than looking at positive predictive value or accuracy, one should determine negative predictive value. This determination might be of greater consequence if one considers an air traveler population or a population entering a hospital.Ng et al. (5) identified outdoor temperature as a confounding variable in cutaneous temperature measurement. Our study identified age as a variable that interferes with cutaneous measurement, but the role of gender is less obvious. Older persons showed impaired defense (stability) of core temperatures during cold and heat stresses, and their cutaneous vascular reactivity was reduced (12,13).Use of a simple infrared thermometry, rather than sophisticated imaging, should not be considered a limitation because this method concerns the relationship between cutaneous and central core temperatures. We can extrapolate our results to any devices that estimate cutaneous temperature and the software used to average it. Our study attempted to detect febrile patients, not infected patients. For mass detection of infection, focusing on fever means that nonfebrile patients are not detected. This last point is useful because fever is not a constant phenomenon during an infectious disease, antipyretic drugs may have been taken by patients, and a hypothermic ratherthan hyperthermic reaction may occur during an infectious process.In conclusion, we observed that cutaneous temperature measurement by using infrared thermometry does not provide a reliable basis for screening outpatients who are febrile because the gradient between cutaneous and core temperatures is markedly influenced by patient’s age and environmental characteristics. Mass detection of febrile patients by using this technique cannot be envisaged without accepting a high rate of false-positive results.AcknowledgmentWe thank David Baker for reviewing the manuscript.This study was supported by the Direction Générale de la Santé, Ministère de la Santé et de la Solidarité, Paris, France. Biography• Dr Hausfater is an internal medicine specialist in the emergency department of Centre Hospitalier Universitaire Pitié-Salpêtrière in Paris. His primary research interests are biomarkers of infection and inflammatory and infectious diseases. References1. Kaydos-Daniels SC, Olowokure B, Chang HJ, Barwick RS, Deng JF, Kuo SH, et al. ; SARS International Field Team. Body temperature monitoring and SARS fever hotline. Emerg Infect Dis2004;10:373–6. [PMC free article] [PubMed]2. Chng SY, Chia F, Leong KK, Kwang YPK, Ma S, Lee BW, et al. Mandatory temperature monitoring in schools during SARS. Arch Dis Child 2004;89:738–9. doi: 10.1136/adc.2003.047084. [PMC free article][PubMed] [Cross Ref]3. St John RK, King A, de Jong D, Brodie-Collins M, Squires SG, Tam TW Border screening for SARS.Emerg Infect Dis 2005;11:6–10. [PMC free article] [PubMed]4. Hughes WT, Patterson GG, Thronton D, Williams BJ, Lott L, Dodge R Detection of fever with infrared thermometry: a feasibility study. J Infect Dis 1985;152:301–6. [PubMed]5. Ng EY, Kaw GJ, Chang WM Analysis of IR thermal imager for mass blind fever screening. Microvasc Res 2004;68:104–9. doi: 10.1016/j.mvr.2004.05.003. [PubMed] [Cross Ref]6. Erickson RS, Meyer LT Accuracy of infrared ear thermometry and other temperature methods in adults. Am J Crit Care 1994;3:40–54. [PubMed]中文译文：新发传染性疾病.2008八月；14（8）：1255–1258.DOI：10.3201/eid1408.080059PMCID: PMC2600390 红外测温仪检测发热患者的皮肤彼埃尔侯司法特，赵岩，史蒂芬妮德弗雷纳，帕斯卡尔，和布鲁诺里乌摘要我们评估皮肤红外测温的准确性，通过病人的额头检测温度，发热病人进入急科室进行检测。

关于测温的英文综述

关于测温的英文综述英文回答：Thermometry is the measurement of temperature. It is a fundamental science that has applications in various fields such as physics, chemistry, biology, and medicine. Thefield of thermometry has evolved significantly over the centuries, with the development of new and more accurate methods for measuring temperature.One of the earliest methods of thermometry was the use of a mercury thermometer. Mercury thermometers consist of a glass tube with a bulb at one end. The bulb is filled with mercury, which expands or contracts when the temperature changes. The expansion or contraction of the mercury can be measured on a scale to determine the temperature. Mercury thermometers are still widely used today, but they are being replaced by other types of thermometers, such as digital thermometers and infrared thermometers.Digital thermometers use a thermistor to measure temperature. A thermistor is a semiconductor whose resistance changes with temperature. By measuring the resistance of the thermistor, the temperature can be determined. Digital thermometers are more accurate than mercury thermometers and they are also more convenient to use.Infrared thermometers measure temperature by detecting the infrared radiation emitted by an object. The intensity of the infrared radiation is proportional to the temperature of the object. By measuring the intensity of the infrared radiation, the temperature can be determined. Infrared thermometers are non-contact thermometers, which means that they can measure the temperature of an object without touching it. This makes them ideal for measuring the temperature of objects that are difficult or dangerous to touch, such as electrical equipment or hot surfaces.The field of thermometry is constantly evolving, with the development of new and more accurate methods for measuring temperature. These new methods are making itpossible to measure temperature with greater precision and accuracy than ever before.中文回答：测温。

第二部分温度的测量

如：实际气温每小时升温 3 ℃ ，热滞系数小于300秒的元件，滞差达 0.25 ℃ ；当热滞系数小于60秒时，滞差可环境温度呈周期性变化时的滞差
如果1.5米高处百叶箱的气温日变化看作日振幅 5 ℃ 的周期性变化，要保证纪录下来的日振幅误差小于 0.05 ℃ ，则测温元件的热滞系数应小于2000秒。
如同时要求最高（最低）温度出现的时刻相应落后所引起的误差不超过5分钟，则测温元件的热滞系数应小于300秒。
24
进行气象观测时应规定元件的热滞系数。 WMO对地面观测中测温元件要求为：当通
风速度为 5 m/s 时，热滞系数在 30~60s 之间。
25
2.3.5 热滞系数和风速的关系
成反比：
百叶片宽26毫米，厚6毫米。百叶箱门朝北，安置在固定的架子上，架底高出地面1.25米。箱门前面安置一个小矮梯。
整个箱子涂上白漆，使它具有良好反射率。
29
2.4.1 百叶箱（续）
百叶箱有两种规格。
较大的：高 612mm、宽 460mm、深 460mm 安放：温度、湿度自记仪器
较小的：高 537mm、宽 460mm、深 290mm 安放：干湿温度表、最高温度表、最低温度表、毛发湿度表
T90 ：热力学温度。单位为K。 dT/dp：温度随气压的变化。单位：10-8K/Pa W (T90) ：比电阻，等于R(T90)/R(273.16K)，
即该温度下的电阻值与水三相点温度下的铂电阻值之比。
5
2.1 ITS—90（续）
ITS—90测温标准系列由三个关节组成：
1. 定出一系列的测温参考点 2. 制作出国际标准铂电阻温度表 3. 各国计量部门制作出各自的铂电阻温度表，
1. 温度一次项系数大 2. 电阻与温度关系的二次项系数远小于一次项

示差扫描量热法英文

示差扫描量热法英文Differential Scanning CalorimetryDifferential scanning calorimetry (DSC) is a widely used thermal analysis technique that provides valuable information about the physical and chemical properties of materials. It is a powerful tool for studying a variety of materials, including polymers, metals, ceramics, and biological samples. The fundamental principle of DSC is to measure the difference in the amount of heat required to increase the temperature of a sample and a reference material as a function of temperature or time. This information can be used to characterize phase transitions, chemical reactions, and other thermal events that occur in the sample.The basic setup of a DSC instrument consists of two identical sample holders, one for the sample and one for a reference material. These holders are placed in a temperature-controlled environment, such as a furnace or a cryogenic chamber, and are connected to a sensitive heat-measuring device. As the temperature of the system is increased or decreased at a controlled rate, the difference in the amount of heat required to maintain the same temperature between the sample and the reference is measured and recorded.The resulting DSC curve, which is a plot of the heat flow (or heat capacity) as a function of temperature or time, provides a wealth of information about the sample. Endothermic events, such as melting or glass transitions, appear as peaks in the DSC curve, while exothermic events, such as crystallization or chemical reactions, appear as downward peaks. The position, shape, and area of these peaks can be used to determine various thermal properties of the sample, including the transition temperatures, the enthalpy (heat) of the transition, and the specific heat capacity.One of the key advantages of DSC is its ability to provide quantitative information about the thermal events in a sample. By comparing the DSC curve of the sample to that of a known reference material, it is possible to determine the absolute values of the thermal properties, such as the melting point or the heat of fusion. This information is particularly valuable in materials science, where the thermal behavior of a material is often a critical factor in its performance and application.Another important aspect of DSC is its versatility. The technique can be used to study a wide range of materials, from simple organic compounds to complex polymeric systems and biological samples. Additionally, DSC can be combined with other analytical techniques, such as X-ray diffraction or infrared spectroscopy, to provide a morecomprehensive understanding of the sample's structure and properties.One of the most common applications of DSC is in the study of polymers. Polymers are complex materials that can undergo a variety of thermal transitions, including melting, glass transitions, and crystallization. DSC is widely used to characterize these transitions, which are crucial in determining the mechanical, thermal, and processing properties of polymers. For example, the glass transition temperature (Tg) of a polymer is an important parameter that determines its flexibility and toughness at different temperatures, and DSC is the primary technique used to measure this property.In addition to polymers, DSC is also widely used in the study of other materials, such as metals, ceramics, and pharmaceuticals. In the case of metals, DSC can be used to detect phase transformations, such as the melting and solidification of alloys, which are important in the processing and heat treatment of these materials. In the field of ceramics, DSC is used to study the thermal stability and phase changes of ceramic materials, which are crucial in the development of advanced ceramic products. In the pharmaceutical industry, DSC is a crucial tool for the characterization of drug substances and formulations, as it can provide information about the purity, stability, and compatibility of these materials.Overall, differential scanning calorimetry is a powerful and versatile analytical technique that has a wide range of applications in materials science, chemistry, and other fields. Its ability to provide quantitative information about the thermal properties of a wide variety of materials makes it an indispensable tool for researchers and engineers working in these areas.。

1 This work was supported by the German Bundesministerium fr Bildung

Re-examination of Physical Models in theTemperature Range300K–700KAndreas Schenk1Technical Report No.99/011This work was supported by the German Bundesministerium für Bildung und Forschung under contract01M3034A.The authors are responsible for the contents of this publication.AbstractIn the PARASITICS project physical models used in device simulation are to be veriﬁed for the temperature range300K–700K(lattice temperature)by compari-son between simulation and electrical characterization of suitable test structures.A pre-evaluation of the decisive models in DESSIS ISE showed good agreement with existing experimental data up to500K and normal physical behavior up to1000K. The mobility model of Schenk[1]wasﬁne-tuned by means of a careful analysis of all existing data on the temperature dependence of the mobility.Drift velocity satu-ration is now perfectly reproduced for both electrons and holes,provided the energy relaxation times are given the valuesτE n075ps,τE p017ps in the simulation.A complete device analysis of DIODE24_BL from MOD_B_BOSCH based on dop-ing proﬁles by ST and measured IV-characteristics in the temperature range300K –700K with the device simulator DESSIS ISE produced the following results:At all temperatures the forward-bias range is dominated by SRH recombination up to a current of1105A,and by trap-assisted Auger(TAA)recombination above.The latter is the sum of temperature-dependent contributions from p-region,n-region, and buried layer.The measured temperature dependence of the high-injection range of the IV-curves is possibly due to the TAA coefﬁcients,which could not be worked out since DESSIS ISE did not converge there.All alternative possibilities-band gap,carrier statistics,BGN model,surface recombination,and band-to-band Auger recombination could be systematically ruled out.The temperature dependence of the reverse-bias IV-curves results from the changing contributions of p-region,n-region,and buried layer,respectively,to the total SRH generation ing theﬁt parameters of the lifetime models in DESSIS ISE,reasonable overall agreement was achieved without any hypothetical temperature dependence of the minority carrier lifetimes.A good match to the measured breakdown voltages was obtained for all temperatures with a modiﬁcation of the vanOverstraeten model of the impact ioniza-tion coefﬁcient of the formαconstγE g300KFE g TZusammenfassungZiel des Projekts ist die Veriﬁzierung der physikalischen Modelle im Temperaturbe-reich300K–700K(Gittertemperatur)durch Vergleich von Simulation und elektri-scher Charakterisierung geeigneter Teststrukturen.Dazu wurden im V orfeld die wichtigsten Modelle in DESSIS ISE auf ihr Verhalten bis1000K Gittertemperatur hin untersucht.Alle Modelle zeigten guteÜbereinstimmung mit vorhandenen Mess-ergebnissen(bis max.500K)sowie normales physikalisches Verhalten bis1000K.Ein Schwerpunkt des Projekts ist der Test des physik-basierten Silizium Bulk-Beweglichkeitsmodells von Schenk[1]bei hohen Temperaturen.Zur V orbereitung der Hochtemperatur-Hall-Messungen wurde das Modell mit sämtlichen vorhande-nen Messungen der Abhängigkeit von Gitter-und Ladungsträgertemperatur ver-glichen.Die existierenden Datenüber die Sättigung der Driftgeschwindigkeit(bis max.370K)wurden benutzt,um eine Feinanpassung der funktionalen Form zu erhalten,nach der sich perfekte Sättigung der Driftgeschwindigkeit für Elektronen und Löcher ergibt.Die optimalen Energie-Relaxationszeiten für die beste Anpas-sung an experimentelle Daten wurden ermittelt(τE n075ps,τE p017ps).Die benötigten Hall-Faktoren bis700K für alle relevanten Dotierungen der im Projekt gegebenen Teststrukturen wurden bereitgestellt.Eine vollständige Bauelemente-Analyse der DIODE24_BL von MOD_B_BOSCH (laterale pPlus/nWell smart-power Diode)wurde basierend auf Dotierproﬁlen von ST und Kennlinien-Messungen im Temperaturbereich300K–700K mit dem Bauele-mente-Simulator DESSIS ISE durchgeführt.Wegen der grossen Komplexität dieses Bauelements(laterale pn-Übergänge,Durchbruch an der Si-SiO2-Grenzﬂäche, hochdotierte vergrabene Schicht)sind die Ergebnisse mit gewissen Unsicherheiten behaftet.Sie setzen insbesondere voraus,dass die lateralen Dotierproﬁle korrekt sind und der Avalanche-Durchbruch nicht wesentlich durch die Grenzﬂäche beeinﬂusst wird.Die Analyse der V orwärts-Kennlinien erbrachte folgende Resultate:SRH-Re-kombination dominiert bis zu einer Stromstärke von1105A im gesamten Tem-peraturbereich,wobei der Beitrag des n-Gebiets mit steigender Temperatur zunimmt. Oberhalb1105A ist trap-assistierte Auger-Rekombination(TAA)der einzig wichtige Rekombinationsmechanismus,wobei in Abängigkeit von der Temperatur alle drei Gebiete–p-Gebiet,n-Gebiet und vergrabene Schicht–Anteile liefern. Band-Band-Auger-Rekombination würde um drei Grössenordnungen zu grosse Auger-Koefﬁzienten erfordern.Die starke Temperatur-Abhängigkeit der Kennli-nien im Hochinjektionsbereich könnte nurüber die TAA-Koefﬁzienten erklärt wer-den.Eine entsprechende Anpassung konnte jedoch nicht erfolgen,weil DESSIS ISE in diesem Bereich nicht konvergierte.Sämtliche alternativen Möglichkeiten für den gemessenen Temperatur-Einﬂuss–Energielücke,Ladungsträgerstatistik,BGN-Modell und Oberﬂächen-Rekombination–konnten systematisch ausgeschlossen werden.Die Dominanz der TAA-Rekombination resultiert aus der Tatsache,dass die Implantation der vergrabenen Schicht ein voluminöses Gebiet mit sowohl ho-her Elektronendichte(was einen Auger-Prozess begünstigt)als auch mit hoher Trap-Dichte erzeugt(was einen SRH-Prozess begünstigt).Die V orwärts-Kennlinien sind demnach wesentlich durch Eigenschaften der vergrabenen Schicht bestimmt.Die Temperatur-Abhängigkeit der Sperrströme ist durch die wechselndenBeiträge der einzelnen Gebiete–p n-Übergang,n-Gebiet und vergrabene Schicht –zur totalen SRH-Rate bestimmt.Eine genaue Anpassung würde die Kenntnis der Lebensdauerproﬁle im gesamten Bauelement erfordern.Jedoch gelingt bereits mit sinnvollen Variationen der Lebensdauer-Modellparameter eine gute Simula-tion der Sperrströme,ohne jegliche(hypothetische)Temperatur-Abhängigkeit der Minoritätsladungsträgerlebensdauern.Insbesondere kann die charakteristischeÄn-derung der Form der Sperr-Kennlinien zu einem“rechteckigen"Verlauf ab etwa 350K erklärt werden.Die Durchbruchspannungen bei hohen Temperaturen können zwanglos mit dem Lokalfeldmodell der Stossionisationsrate simuliert werden,wenn für die Schwellenenergie die temperaturabhängige Energielücke benutzt wird.Diese wurde ins vanOverstraeten-Modell implementiert,so dass sichαconstγE g300KFE g TFigure1:Temperature dependence of the indirect band gap in silicon.See the DESSIS ISE manual for the E g T L formula.Figure2:Impact ionization coefﬁcient for electrons as function of electricﬁeld as it turns out from Lackner’s model.given by the band gap and,therefore,should exhibit the(strong)temperature depen-dence of the latter.This will be detailed below.The drift velocity saturation for electrons at different lattice temperatures from Canali’s model[2],(p.65)is shown in Fig.3.It decreases with rising temperature at aﬁxedﬁeld strength in the Ohmic regime.In the saturation range the spacing between different curves becomes narrower with increasing temperature.This indicates that the relative decrease of the saturation velocity declines at higher temperatures.Figure3:Electron drift velocity as function of electricﬁeld for different lattice tem-peratures as it turns out from Canali’s model.In Fig.4the bulk mobility of Schenk[2],(p.127)is compared with the DESSIS ISE default model and experimental data in the entire temperature range up to1000K.Despite the good coincidence,the range between500K and1000K requires further investigations.The physics-based Schenk mobility model allows conclusions about the scatter-ing of hot carriers in doped(bulk)silicon.Fig.5depicts the electron mobility as function of the electricﬁeld at different doping levels.In the300K case an inter-esting behavior is observed which can be explained as follows:When the carrier temperature reaches a certain value,the Coulomb scattering at ionized dopants be-comes less important and the mobility increases.Further carrier heating,however, immediately leads to the common saturation effect due to the balance between en-ergy gain by the electricﬁeld and energy loss by emission of optical phonons.At the highest doping concentrations,the increase of the mobility only sets in after velocity saturation had already started to be effective.The latter behavior was only found for electrons but not for holes.In the right part of Fig.5results for700K are shown on the same scale.One observes that at high lattice temperatures the described effects do not occur because the saturation mechanism dominates.Figure4:Electron bulk mobility as function of lattice temperature as it turns out from Schenk’s model compared to experimental data and the DESSIS ISE default model.Figure5:Electron bulk mobility as function of electricﬁeld for different doping concentrations as it turns out from Schenk’s model.Left:T L300K,right:T L 700K2Drift velocity saturation in Schenk’s bulk mobility model2.1Simulation of n-type resistorIt is commonly believed that the drift velocity in bulk silicon perfectly saturates both in the case of electrons and holes,if the local electricﬁeld exceeds2105V/cm.Thebulk mobility model as published in Ref.[1]was slightly modiﬁed to reproduce this perfect velocity saturation.For this,the integral factor I ac T c2112αk B T c in the expressions describing phonon scattering had to be changed to2Figure7:Electron drift velocity at room temperature.Experimental data points arefor different substrate orientations(100or111).(blue curve).The red curve represents the result of the terminal extraction method which yields a perfectﬁt in the Ohmic regime(this has to be so,since deformationpotentials and phonon energies had beenﬁxed to reproduce the Ohmic mobility).The above mentioned effect of carrier injection becomes visible at approximately4103V/cm.If the third method is applied,the red curve merges with the blue one at about1104V/cm.From this exercice we draw the conclusion that the only change to be made in theset of parameters is the choiceτE n075ps.2.2Simulation of p-type resistorExchanging n by p in Fig.6deﬁnes the p-type resistor used to optimize the param-eters for the hole drift velocity.In Fig.8the green curve again represents the resultobtained with default values.In order to match the data of Smith,αp would have to be further reduced.However,the low valueαp015eV1had already been a concession to a reasonableﬁt of the drift velocity in Ref.[1].The bestﬁt of the holeDOS was found withαp05eV1.Therefore,we better leave the nonparabolicity parameter untouched and adjust the energy relaxation timeτE p as above(blue and black curves).A reasonable agreement with the scattering experimental data is found usingτE p017ps or larger(up to0.20ps).It is impossible to reproduce the sharp saturation behavior found by Smith[4].As in the case of electrons,the terminal extraction method gives a perfectﬁt in the Ohmic regime.We conclude thatαp05eV1andτE p017ps are the best choice and henceFigure8:Hole drift velocity at room temperature.will be used in the high-temperature investigations.2.3Comparison with published data on ambient temperature de-pendenceThere exist a few published data for ambient temperatures different from room tem-perature.In Figs.9and10we show the drift velocities for245K and370K in com-parison to data by Canali et al[3].In the case of electrons the agreement is equally good using the same parameters as for room temperature.In the case of holes the 370K curveﬁts very well with the same parameters that have been found for300K, whereas for the lower temperature a larger misﬁt occurs.Increasing the energy re-laxation time would improve the situation,however it seems to be more likely that the misﬁt is related to the use of an effective hole mass which strongly depends on temperature in DESSIS ISE.We already argued in Ref.[2],(p.163)that the T L-dependence of the hole DOS mass should not be used for transport calculations.3DIODE24_BL from MOD_B_BOSCH3.12D default simulationA cross section of the planar diode DIODE24_BL(pPlus/nWell)together with a zoom into the critical region are shown in Fig.11.Avalanche breakdown occurs in small areas on both sides of the p n junction just below the Si-SiO2interface.Figure9:Electron drift velocity versus electricﬁeld for different lattice temperatures.Figure11:2D cross section of the smart-power diode DIODE24_BL.The insetshows the distribution of the impact ionization rate at breakdown.The maxima of the rate are located directly underneath the surface.The simulationof the breakdown voltage and the evaluation of the impact ionization model at hightemperatures hence will be obscured by the uncertainty from the lateral doping proﬁle and the possible existence of a surface channel for breakdown.In the following wehave to assume that DIODE24_BL is nevertheless a suitable test device.Dopingproﬁle and electricﬁeld across the critical region are shown in Fig.12.Theﬁeldvariation is about20%over a distance of100nm which is smooth enough to justify the application of a local-ﬁeld model.The default simulation of the forward and reverse IV-characteristics is deﬁned asfollows:SRH(minority carrier)lifetimes independent on doping and temperature,ﬁxed toτn14106s,τp42107s for the bestﬁt to the SRH-dominated branch of the298K forward IV-curve.Recombination processes are“Auger"(de-fault parameters including the T-dependence of the Auger coefﬁcients)and“SRH",BGN model is“slotboom",the statistics is“Boltzmann-Maxwell"(i.e.“Fermi"notswitched on).Electron-hole scattering(“carrier-carrier",Brooks-Herring)has to be included for a correct curvature in the bias range-0.8V–-1V where plasma ef-fects play an important role.Generation processes are“SRH"and impact ioniza-tion(“vanOverstraeten").The criticalﬁelds in the Chynoweth law were lowered by5%in order to match the measured breakdown voltage at323K:b n lowFigure12:Doping concentration and electricﬁeld proﬁle at zero bias across the p n junction near the surface.Figure13:Default simulation and measured forward IV-characteristics.The hori-zontal red line connects the built-in potentials for each temperature.11695106V/cm,b p low19342106V/cm,b n high11695106V/cm, b p high16083106V/cm.This can be considered as a concession to the above mentioned uncertainties induced by the lateral doping proﬁle and the proximity of the surface.We assume that those effects,if present,have at the most a weak temperature dependence that can be neglected.Figure14:Built-in potential and free carrier densities in the depletion zone at zero bias.In the right legend n pl denotes the extracted plasma density(n=p).The forward and reverse IV-characteristics in the temperature range298K–699K are presented in Figs.13and15,respectively.Since the intrinsic density of silicon at700K is about3361016cm3,a main feature is the transition from the extrinsic to the intrinsic regime at some elevated temperature(depending on the local doping concentration).In the forward-bias range we observe that SRH recombina-tion dominates up to a current of1105A for all temperatures.Then some Auger process starts to dominate(either band-to-band(b2b)Auger or trap-assisted Auger (TAA))which also deﬁnes the onset of a remarkable deviation of the simulated from the measured current.This deviation extends up to-1V and covers the entire bias range at the highest temperatures.SRH recombination is completely masked in the range550K–700K.Hence the forward-bias branch is not suitable to draw any con-clusions about a temperature dependence of the SRH lifetimes.The shrinkage of the built-in potential with increasing temperature is depicted in Fig.14.If the built-in potential is marked on each corresponding curve in Fig.13,one obtains an almost horizontal line.In Fig.14it is also shown how a plasma develops in the depletion zone with rising T(plasma density n pl n p equal to the intrinsic density n i).One can see that above600K the electron density in the neutral n-region exceeds the doping,which results in the above-mentioned intrinsic behavior.Aﬁrst inspection of the reverse-bias characteristics in Fig.15shows two fea-tures:the strong overestimation of the SRH-dominated current between323K and 450K,and far too large breakdown voltages for the higher temperatures.Below 11011A the experimental data turn into noise and are disregarded.A closer look on various quantities near breakdown at323K and648K,respectively,reveals someFigure15:Default simulation and measured reverse IV-characteristics. interesting aspects.In Fig.16electricﬁeld and ionization rate across the junctionare compared for the two temperatures.Since the maxima of theﬁeld are not muchdifferent from each other,the exponential function in the Chynoweth law produces a factor2difference at the most.However,the ionization rates differ by more thanfour orders of magnitude(37104)!This large difference is caused by theplasma density in the“depletion"region.(The impact ionization rate has the formG IIαn nv nαp pv p.)As indicated in the left part of Fig.17,the plasma has a density of about281012cm3at648K,a factor of62104larger than in thecase of323K.On the other hand,this plasma density is much smaller than the intrin-sic density at648K,which is about121016cm3.As the temperature increases,the SRH rate extends into the entire n-region because n iﬁrst approaches the electron density there,andﬁnally it determines the electron density.3.2Forward-bias analysisTo understand the physics behind the forward IV-characteristics it is useful to plot the dominant recombination processes.In Figs.18and19we present the proﬁles of the Auger and SRH rates along a vertical cut through the device that also covers the buried layer(BL).These proﬁles are shown for the two limiting temperatures and for three forward biases.In the right part of theﬁgures the integrated rates as a functionFigure16:Electricﬁeld and impact ionization rate across the junction for two tem-peratures.Figure17:Free carrier densities at breakdown(left)and SRH rate at+12V bias (right)across the junction for different temperatures.of distance from the surface yield information about the relative contribution from different regions.At298K the Auger rates are concentrated in the p-region and the integrated Auger rate collects only very small contributions from the BL.The SRHFigure18:Proﬁles of the Auger and SRH rates at298K for V bias=-0.2V,-0.6V,and -1.0V from bottom to top(left).Integrated rates as a function of distance from the p-contact(right).Figure19:Proﬁles of the Auger and SRH rates at699K for V bias=-0.2V,-0.6V,and -1.0V from bottom to top(left).Integrated rates as a function of distance from the p-contact(right).rate exhibits the usual peak in the depletion zone which disappears as the built-in voltage becomes zero.At high bias and high temperatures the SRH rate distribu-tion is broad.SRH recombination is outnumbered by Auger recombination between -0.6V and-1V(from the IV-curve weﬁnd-0.66V).At699K Auger recombination dominates in the whole forward bias range,but the BL region yields some contri-butions.This conﬁrms the remarks made in the previous section.The transition from SRH to Auger dominance is easily seen from a plot of the ideality factor for alltemperatures in Fig.20.Figure20:Ideality factor as function of ambient temperature.We can draw the following important conclusion.Currents larger than1105Aoriginate from an Auger-type recombination process.At lower temperatures its rate is concentrated in the p-contact region.Hence for b2b Auger R Auger C hhe p2n there,and since n isﬁxed by N A,a temperature effect can only be due to the minor-ity carrier density n or/and the Auger coefﬁcient C hhe.Besides b2b Auger,a secondrecombination process is possible in this regime:trap-assisted Auger(TAA)recom-bination.TAA is a SRH-type recombination process where the energy difference between band edge and trap level is transfered to excited electrons/holes.TAA starts to exceed the thermal SRH rate when c n p1τSRH,where c is the TAA coef-ﬁcient in DESSIS ISE.Then the TAA rate has a maximum in the p-contact region (like b2b Auger),but also a broad and large distribution in the entire n-region(like thermal SRH)giving the major contribution simply due to its large volume.In both regions the TAA rate turns into R TAA c pn!In order to understand the shape of the forward IV-curves and their temperature dependence,we have to care about the following issues:1.)The T-dependence of the band gap E g T as it inﬂuences n.2.)The effect of the carrier statistics,since it affects the T-dependence of the quasiFermi levels.3.)The BGN model,since it determines the minority carrier densities.4.)The size of C hhe,C eeh and the impact of their T-and n p-dependence.5.)The inﬂuence of surface recombination.6.)The role of TAA and a possible T-dependence of c.1.)A striking misﬁt between measured and simulated forward IV-curves is the wrongtemperature dependence highlighted in Fig.21.In order to check the inﬂuence of E g T the parameters in E g T were changed in such a way that the gap shrinkage was enhanced up to a reasonable limit guided by the experimental data in Fig.1.The resulting effect was far too weak to explain the discrepancy in Fig.21.2.)and3.)The carrier statistics and different BGN models have a strong impact on the minor-ity carrier ing any“traditional"BGN model in combination with Fermi statistics will give the same minority carrier density as without“Fermi"(a wanted feature in DESSIS ISE).To force Fermi statistics without neglecting BGN at all, the"schenk"BGN was used[5].Again,the distance between the298K and699K curves is not essentially changed.Figure21:The effect of carrier statistics and different BGN models on the tempera-ture dependence of the forward IV-characteristics.4.)The b2b Auger coefﬁcients C hhe and C eeh were systematically increased neglecting their temperature dependence.As shown in Fig.22one can match the data points in the Auger-dominated range with values of the order10291028cm6s1.How-ever,such values are2-3orders of magnitude larger than the usual and well-accepted value of1031cm6s1.5.)The minority carrier density at the surface never exceeds1016cm3.Assuming v sur f104cm/s for the surface recombination velocity,the resulting rate of sur-face recombination is always much less than the integrated rates shown in the right part of Figs.18and19(at small forward bias and for the lower temperatures the mi-nority carrier density is very small).Therefore,surface recombination can be safely ignored.Figure22:Variation of the b2b Auger coefﬁcients(frozen T-dependence)for298K, 398K,501K,and648K(from bottom to top).6.)The remaining thinkable process is TAA recombination[2],(p.80).Results for c11011and c51011cm3s1are presented in Fig.23.Termi-nation of simulated curves is caused by non-convergency of DESSIS ISE.With c51011cm3s1a goodﬁt for all temperatures could be obtained.c might have a similar temperature dependence as the b2b Auger coefﬁcients(thought to be due to phonon-assistance),although the spread of the deep-level wave functions in k-space would relax momentum conservation restrictions.Unfortunately,no assess-ment about the temperature dependence of c can be made.That TAA recombination could be identiﬁed as the dominant recombination pro-cess is not surprising.The implantation of the BL both creates a large volume of high electron density in favor of an Auger process and a large density of deep-lying trap states in favor of a SRH process.Hence the device behavior under forward bias is practically determined by induced features from the BL.3.3Reverse-bias analysis3.3.1LifetimesThe pre-breakdown branches of the reverse-bias curves exhibit a change from a rounded shape at“low"temperatures to an almost rectangular shape at higher tem-peratures.The temperature dependence itself seems to be irregular when compared with the default simulation.To gain more insight into the measured behavior we plot the SRH rate at+12.5V along a vertical cross section through the device includingFigure23:Variation of the TAA coefﬁcient c for298K,398K,and648K(from bottom to top).the BL region in Fig.24.Note that the volume of the outer region is huge com-Figure24:Proﬁles of the SRH rate at a bias of+12.5V along a vertical cut through the device from the p-contact to the pn-junction of the BL for various temperatures. Lifetime parameters were the same as in the previous section.pared to the volume of the p n depletion zone.At“low"temperatures the depleted p n-junction yields the major contributions,but at an intermediate temperature the outer region has a comparable share,whereas at the highest temperatures the BL part of the outer region dominates the SRH rate.This change in the relative contri-butions to the total SRH rate is essential to understand the reverse-bias IV-curves. The maximum doping in the BL is about81018cm3,far more than in the de-pleted p n-junction.Since the minority carrier lifetimes are strongly affected by the process conditions,in particular by implantations with a high dose,heavily doped re-gions have(much)smaller lifetimes which is expressed by the so-called Scharfetter relation(SRH(DopingDependence)in DESSIS ISE)[2],(p.73).The blue curves in Figs.26and27were obtained with the default parameter set including“DopingDe-pendence",i.e.the lifetime parameters“taumax"were set back to Dessis default.By chance,the agreement at323K is the same as before(compare Fig.15).Applying the Scharfetter relation we obtain pictures as in Fig.25where the SRH rate(left) and the hole lifetime(right)are shown for the“intermediate"temperature of348K.Figure25:Distributions of the SRH rate(left)and of the hole lifetime(right)through-out the device.One observes that the hole lifetime in the depletion zone of the p n-junction(blue region on the left side)is much larger(the color is orange!)than that in the BL region (green-blue area on the right side).Although the BL region is quasi-neutral,this leads to a total contribution to the SRH rate(yellow area on the left side)which is com-parable to the contribution from the highly depleted p n-junction.The qualitative difference in the curve shape is caused by the different speed at which the SRH rates reach their full size when the reverse bias is turned on.Since in the BL region n is always much larger than n1,the rate turns into R SRH N BL D p n2i e f fτBL p N BL D there.p decreases everywhere in the BL,but the denominator remains constant.In the p n-junction we have R SRH n p n2i e f fτpn p n n1τpn n p p1.n pin the numerator decreases,but also n and p in the denominator,i.e.it takes longerFigure26:Reverse-bias IV-curves with default lifetime parameters including“Dop-ingDependence"in SRH(blue solid lines)and with E trap015eV(red solid lines). to“switch on"the rate to its(large)maximum level in the p n-junction.Comparison of the398K default simulation with the measured data(the blue bold line in Fig.26)reveals that the transition to the BL-dominated generation hasalready occurred at this temperature in reality,but not in the simulation.One caneasily increase the relative contribution of the BL region e.g.by shifting the traplevel out of its mid gap position.In Fig.26we used E trap015eV which increases n1n i e f f exp E trap k B T and,therefore,decreases R SRH in the p n-junction but not much in the BL region.The resulting IV-curves are shown in red in Fig.26.At398K the shape of the curve is now more rectangular andﬁts better the measuredshape.On the other hand,one can play with the parameters of the Scharfetter relation to increase the importance of one particular region and,at the same time,to increase or decrease the total SRH rate.A perfectﬁt is not attainable because it would re-quire the knowledge of the different lifetime proﬁles in the p n-junction and the whole outer region,respectively.Fig.27shows the result if the power“al pha"in the Scharfetter relation is increased from1to1.5(red solid lines).Now all curves are shifted up giving a reasonable agreement between450K and700K.From these exercises we draw the conclusion that also the reverse-bias branch does not yield in-formation about the temperature dependence of the minority carrier lifetimes.Note, that the lifetime parameters“taumax"were not changed at all so far.For the fol-。

温度电压边际测试规范(中英文)

温度/电压边际测试规范Temperature/Voltage Margin Test Procedure1.0 PURPOSE(目的)：1.1The purpose of this document is to define a test methodology to temperature and voltage margin a product. This test shall be used on all products during the development phase in order to determined the product temperature/voltage margins vise the productspecifications. The essence of margin testing is to step stress the unit under test to see where it stop working.1.1 是用来定议温度与电压边际试验方法，这个试验是为了求得产品的温度、电压与规格之间的关系，是以逐步改变应力的方式，测试了解产品在什么温度时会没有输出。

2.0 SCOPE(范围)：2.1 All shall follow the following this test procedure.2.1对所有产品都须经过此测试。

3.0 SPECIFICATIONS (规格)：3.1E.U.T. engineering product Specification.3.1 参照待测物的产品规格。

4.0 TEST EQUIPMENT (测试设备)：4.1Environmental chamber should be capable of sustaining constanttemperatures of between -30 ℃. to 100 ℃. and of sustaining constant humidity of between 20% to 90% RH. The chamber must also have the capabilities to record both the temperature and the humidity vs. time.4.1 恒温恒湿机须有能力提供– 30℃到 100℃的温度，且湿度为 20% 到90%，还须有能力记录温度、湿度与时间的关系。

测控技术与仪器专业英语全书翻译

选择性和客观性的测量。We can distinguish two types of information :information on the state ,structure or nature of a certain characteristic ,so-called structural information ,and information on the magnitude, amplitude or intensity of a certain characteristic ,so-called metric information .The acquisition of structural information is called
a different state or phenomenon that cannot be misinterpreted by an observer .In other words, the instrument converts the initial observation into a representation that all observers can observe and will agree on . 这些仪器的任务是把国家或现象观察进入一种不同的国家或现象,不能被误解被
dipped in cold water, the water in the jug will feel relatively warm ,whereas if the hand is first dipped in warm water ,the water in the
jug will feel relatively cold. Besides the subjectivity of our observation ,we human observers are also handicapped by the fact that there are many states or phenomena in the real world around us which we

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J O U R N A L O F M A T E R I A L S S C I E N C E39(2004)3799–3800L E T T E R S Measurement ofﬁctive temperature of silica glass opticalﬁbersP.HELANDERAcreo FiberLab,Box1053,SE-82412HUDIKSVALL,SwedenE-mail:per.helander@acreo.seTheﬁctive temperature,Tf,gives information about the structural state of glass and correlates both to the op-tical and the mechanical properties[1].For instance, a lowﬁctive temperature gives low Rayleigh scatter-ing and thus lowﬁber attenuation[2].A spectroscopic method[3],where the position of a reﬂection peak in the infrared spectrum around1120cm−1is determined, has been improved and used.The reﬂection peak is due to the fundamental stretching vibration mode of Si O bonds.An improved method for determining the peak position is suggested and the radial variation of Tf for someﬁbers are presented.The Fourier transform infrared(FTIR)-spectrometer, Equinox55from Bruker,was equipped with an infrared microscope Hyperion2000having a special small area low noise detector,a motorized sample stage and an aperture for limiting the analyzed area.Theﬁbers were cut perpendicular to theﬁber axis using a standard ﬁber cleaver.The spectral resolution was varied from 0.25to4cm−1with the result that a low resolution (4cm−1)gives more than10times better repeatability in the peak position compared to the highest resolu-tion.This is probably caused by the fact that there is a smaller mechanical movement of the scanning mirror at a lower resolution giving better wavelength stability. Different aperture sizes were tried.For a10×10µm aperture and5min measurement time the repeatability in theﬁctive temperature was approx.1◦C.However, it should be noted that the measured spot on the sample surface is signiﬁcantly larger than the aperture due to diffraction.The repeatability of the peak position was proportional to the square root of the aperture size and also the square root of the measurement time.For most measurements a resolution of4cm−1,aperture size of 10×10µm and averaging over5min were used. The peak position was determined by making a least-squares polynomialﬁt and then calculating the point of zero derivative.First,it was found that the sensitivity to noise increases with increasing polynomial degree. Second,it was found that the choice of the discrete data points for theﬁt is very crucial.For instance,shifting the data points one step toward higher or lower wavelengths changed theﬁctive temperature as much as50◦C using a second-order polynomial.As Tf,and thus the peak, shifts in wavelengths it is also necessary to change data points for theﬁt.Keeping aﬁxed set of data points is not possible,as it will not,in general,give the true peak position.Increasing the polynomial degree reduces the problem but at the expense of the noise sensitivity.In-creasing the resolution gives more noise and results in a larger number of smaller steps.The reason for this problem is that the polynomial does not give a perfect ﬁt to the reﬂection curve especially for points far from the peak.But by raising the measured reﬂectivity val-ues to an exponent e,the curve gets a shape that makes a goodﬁt to a low-order polynomial.First,e in Equa-tion1is set to a value,then the coefﬁcients A,B and C in Equation1is determined by a least-squaresﬁt:R e=A+B·w+C·w2(1) where R is the measured reﬂectivity and w is the wave-length.The peak wavelength is the root of the derivative of theﬁtted curve.By changing the set of measurement points to higher and lower wavelengths and recalculat-ing the peak position,the stability of theﬁt is veriﬁed. With an e-value around−3.5the step was negligible for a wavelength range of±25nm.The step can be both positive and negative and thus also exactly zero.Ex-ponents between−3.5and−4all give small steps.By using Equation1the peak position can be determined accurately with a good repeatability.The peak position is allowed to vary over a wide range without any discon-tinuity in the calculated peak position and therefore in the calculated Tf.The repeatability of the peak position increases with the wavelength range,around the peak, up to about±rger ranges give only a very mi-nor increase in the repeatability and some interference from a shoulder around1200cm−1might occur.The radial variation of Tf has been studied before with some divergent results[4].One problem is that the reﬂection peak position varies not only with Tf but also with the material composition[5].This is a problem as opticalﬁber has a different composition in the core and in the cladding surrounding the core.Therefore,homo-geneousﬁbers(without any core)were drawn from a solid silica rod with the same drawing conditions as for the normalﬁbers drawn.The variation of the peak po-sition along the cross section of the125µm-diameter ﬁbers was studied by measuring at every5µm.As seen in Fig.1,there is almost no variation along the diameter of theﬁber without core but a strong variation for the normalﬁber with a Ge-doped core.The repeatability of the measurement was checked by performing several scans.Twenty-two points with a5-µm separation were measured.Aperture size was 10×10µm and the signal was averaged over5min. Thus,each diameter scan took about2hr and eight scans were made giving a total measurement time of 16hr.The relation between Tf and peak position is ob-tained by measurement of samples heat-treated at well-controlled temperatures[4].The error bars in Fig.20022–2461C 2004Kluwer Academic Publishers3799Radial position /µmP e a k p o s i t i o n /c m -1Figure 1Peak position versus radial position for a ﬁber with core and a homogeneous ﬁber without core.Figure 2Fictive temperature for a homogeneous ﬁber along one diame-ter with error bars calculated from eight measurements at each position.give one standard deviation calculated for each point.The signal amplitude is smaller and the standard de-viation is larger at the periphery of the ﬁber.There is no signiﬁcant radial variation but there is a variation from left to right indicating an asymmetry of the ﬁber.This may be due to an asymmetry during the drawing of the ﬁber such as an imperfect centering of the ﬁber in the heating zone.The repeatability was about 10◦C as compared to 1◦C for consecutive measurements of one single spot.Scanning along the diameter means that each point is measured eight times during a 14-hr period and this long duration is probably causing the poorer (but still rather good)repeatability.The conclu-sion is that there is no detectable radial variation of the ﬁctive temperature.Fibers were drawn at three different speeds 22,44and 82m/min with and without core,and the ﬁctive temperature was calculated using the results from the outer (undoped)part of the ﬁbers.The results are given in Table I and show an increase in the Tf at increasing drawing speed caused by more rapid cooling of the glass.The peak width was also calculated and is shown in Fig. 3.The width is almost constant for the homogeneous sample but varies for the normal ﬁber with variation in composition.This informa-tion could thus be used to distinguish between vari-T A B L E I Measured ﬁctive temperatures for different drawing speeds Drawing speed 22m/min 44m/min 82m/min Normal ﬁbers 1503◦C 1531◦C 1541◦C No core ﬁbers1514◦C1555◦C1562◦CFigure 3Peak width versus position for a ﬁber with core and a homo-geneous ﬁber.ations due to compositional variation and ﬁctive temperature.The present measurements show that the signal-to-noise ratio is sufﬁciently high allowing direct measure-ment on the cleaved ﬁber without any other sample preparation.The method of cleaving the ﬁber is sim-pler than the earlier published method [5]where the ﬁber was cut at a small angle.An aperture size as small as 10×10µm was used giving a repeatability of about 1◦C for consecutive measurements and 5min of aver-aging time.Over a 14-hr interval the repeatability was about 10◦C.An improved method for the calculation of the peak position was used.This circumvents the problem with a discontinuity in the peak position as the data points used for the calculation are changed.The radial variation of the peak position was found to be due to the chemical composition of the sample and no radial variation in Tf along the radius was found.The width of the reﬂection peak was calculated and seems to depend primarily on the material composition of the sample.AcknowledgmentThe author is grateful to Mr.H˚a kan Olsson for drawing the ﬁbers.References 1.A .A G A R W A Land M .T O M O Z A W A ,J.Non-Cryst.Sol.209(1997)166.2.K .T S U J I K A W A ,K .T A J I M A and M .O H A S H I ,J.Ligthwave Tech .18(11)(2000)1528.3.A .A G A R W A L ,K .M .D A V I S and M .T O M O Z A W A ,J.Non-Cryst.Sol .185(1995)191.4.D .-L .K I M and M .T O M O Z A W A ,ibid.286(2001)132.5.D .-L .K I M ,M .T O M O Z A W A ,S .D U B O I S and G .O R C E L ,J.Lightwave Tech .19(8)(2001)1155.Received 25Augustand accepted 29October 20033800。