cfd不确定度量化方法研究综述

The quest to figure out how uncertain our predictions are inputational fluid dynamics (CFD) is all the rage in the world of fluid mechanics. It's like peering into a crystal ball to see if we can really trust the results we're getting. Lately, all the cool researchers have been busying up with ways to dig into the uncertainty lurking in CFD simulations. They're basically playing detective, trying to uncover where all the uncertainty ising from and how it's messing with our simulation results. It's like a thrilling mystery novel, but instead of a whodunit, it's a "where'd-ite-from"!
探究我们的预测如何不确定是输入流体动力学（CFD），这都是流体力学界的愤怒。

这就像对等进入一个水晶球看看我们能否真正相信我们得到的结果。

最近，所有酷的研究者都在忙于探索CFD模拟中隐藏的不确定性他们基本上在扮演侦探，试图发现所有不确定性的源头和它是如何搅乱我们的模拟结果。

这就像一部令人惊奇的神秘小说，但与其说是谁干的，不如说是"从哪里来的"！
One of the exciting and lively approaches for dealing with uncertainty in CFD is the use of probabilistic methods. These methods involve using probabilistic models and statistical analysis to figure out how uncertain our input parameters and model assumptions really are. It's like throwing a bunch of dice
and seeing whates up! Monte Carlo simulation, Latin hypercube sampling, and response surface methodology are some of the cool tools we use to shake things up and get a good feel for how uncertain our CFD simulations really are. These methods let us create multiple versions of the CFD model, so we can really get a handle on just how wild and crazy our simulation results might be. It's like taking a roller coaster ride through a world of uncertainty!
处理CFD不确定性的令人兴奋和生动的方法之一是使用概率法。

这些方法涉及使用概率模型和统计分析来判断我们的输入参数和模型假设
究竟有多不确定。

这就像扔一堆骰子和看到什么！ Monte Carlo模拟，拉丁语超立方体取样，和反应表面方法，是一些很酷的工具我们用
来摇晃事物，并有一个很好的感受我们的CFD模拟是多么的不确定。

这些方法让我们创建了多种版本的 CFD 模型，这样我们就能真正掌握到我们的模拟结果是多么疯狂。

这就像乘坐过山车穿越一个不确定
的世界！
When ites to uncertainty quantification in CFD, one big challenge is figuring out if our models are up to snuff. Model inadequacy is all about the limitations and simplifications in the mathematical orputational models we use for CFD simulations. And then there's model discrepancy, which is basically the gap
between what our models predict and what actually goes down in the physical world. But fear not, my friends, because we'vee up with some nifty methods to tackle these issues! We've got model calibration, where we fine-tune our models to make 'em more accurate. Then there's model validation, where we put our models to the test to see if they're really on the money. And
let's not forget about model discrepancy quantification, which helps us measure just how far off our models might be. With these tricks up our sleeve, we're making sure that CFD simulations are as reliable and accurate as can be. So, bring it on, uncertainty - we're ready for ya!
当CFD的不确定性量化时，一个巨大的挑战就是是否我们的模型被扼杀。

模型的不足完全涉及我们用于CFD模拟的数学矫形模型的局限性和简化。

然后是模型差异，基本上就是我们模型预测的和物理世界中实际下降的差距。

但是不要害怕，我的朋友，因为我们已经有一些微薄的方法来解决这些问题！我们有模型校准，在那里，我们微调我们的模型使其更准确。

然后是模型验证，在那里，我们把我们的模型测试看看它们是否真的在钱。

我们不要忘记模型差异量化，它帮助我们衡量我们的模型可能有多远。

有了这些把戏我们就能确保CFD模拟尽可能可靠准确来吧，不确定，我们准备好了！。