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CFD Best Practice Recommendations——流體分析最佳實踐建議

2016-10-06  by:CAE仿真在線  來源:互聯(lián)網(wǎng)

這是《CFD Best Practice Recommendations》的翻譯。英文看起來無感,翻譯過來看著更方便。這里面大部分都是CFD工程師都知道的常識,但還是有一些很有價值的建議。英文原文參考附錄。
對于網(wǎng)格的建議
關鍵是要確保網(wǎng)格smooth,避免網(wǎng)格size和形狀的突然變化,因為這會導致計算精度的顯著降低。因此要注意以下方面:
1. 定義計算域,減小遠場環(huán)境條件對流動的影響和交互作用。尤其:
-將inlet和outlet邊界設置在關切區(qū)域盡量遠的的地方,尤其當應用了均一的遠場條件時,應當確保這個邊界所在的區(qū)域的流動沒有顯著的變化。
-避免將inlet或outlet放置在幾何形狀劇烈變化的區(qū)域或者a region of recirculiaton.
2. 避免網(wǎng)格密度或size的跳躍式變化
3. 避免網(wǎng)格的高度失真和尖銳的網(wǎng)格夾角
4. 確保網(wǎng)格stretching是連續(xù)的
5. 避免邊界層區(qū)域有非結構的四面體網(wǎng)格
6. 將物理量(壓力,速度等)梯度較大的區(qū)域的網(wǎng)格細化,例如邊界層,機翼的leading eadge以及任何流動特性有大的改變的區(qū)域
7. 確保邊界層網(wǎng)格的層數(shù)足夠滿足你希望的計算精度,避免邊界層在厚度方向少于10個point。(就是邊界層盡量不要少于10層的意思唄?有必要這么多嗎?)
8. 檢查這些網(wǎng)格質(zhì)量參數(shù) aspect ratio, internal angle, concavity, skewness, negative volume

對solution assessment的建議

1. 仔細檢查邊界條件以保證正確性和與流動的兼容性?
2. 運行校核前所有的數(shù)值和參數(shù)設置
3. 校核初始條件是否合適
4. 監(jiān)視計算收斂情況。除了殘差外,還推薦監(jiān)視一些對你所仿真的問題有代表性的物理量,如指定區(qū)域的 drag force,速度,溫度或者壓力等
5. 觀察收斂曲線的變化情況。如果收斂曲線振蕩或者殘差減少量在某一范圍內(nèi)變化,就表示求解過程有一些不精確的方面
6. 采用一些內(nèi)部的一致性和精確性條件 by verifying: 
-一些物理量的守恒,如穩(wěn)態(tài)流動的總熱焓和質(zhì)量流量。
-非粘性流動的熵增率和阻力系數(shù)應該是0,他們能強烈地反映出數(shù)值發(fā)散的影響.(就是如果非0的話計算的準確性就有問題的意思吧)
7. 必要的時候比較不同網(wǎng)格size時的計算結果,確認計算對網(wǎng)格size的依賴性
8. 一些物理量對誤差源比其它物理量更為敏感,如壓力不如切應力敏感,切應力不如溫度梯度或者heat flux敏感
9. 如果你的計算看起來很難收斂,你可以:
-從殘差分布情況和與其相關的流域找線索,例如,殘差很大的區(qū)域或者某些流體特性物理量處于異常水平的區(qū)域
-減小控制收斂的參數(shù),例如 CFL number(?)或者一些松弛因子。
-考慮嘗試不同的初始化條件
-確認網(wǎng)格質(zhì)量對收斂性的影響
-先用更穩(wěn)健的算法計算出一個初始流場,如先用一階精度計算,然后再切換到更精確的算法   

對EVALUATION OF UNCERTAINTIES的建議
(這里的不確定性,我理解是指仿真與實際物理問題之間的差異)

這是個非常難的問題,因為不確定性通常并沒有一個清晰的定義,并且需要對流動的物理特性有很好的判斷。下面是一些建議
1. 嘗試列出最重要的那些不確定因素,例如
 -幾何模型的簡化和制造公差
 -operational condition條件 如 入口速度或者入口的流入角度
 -模型對實際物理問題的近似處理,如將低馬赫數(shù)的可壓縮流體近似成不可壓縮流體,這種類型的不確定性是可量化和可控的。
 -與湍流模型或其他物理模型相關的不確定性。
2. 進行一些敏感性分析,以確定某些不確定因素對仿真結果的影響程度



原文:



RECOMMENDATIONS ON GRIDS

The key recommendation is to ensure smooth grids, avoiding abrupt changes in grid size or shape, as this can lead to a significant loss of accuracy. Hence take good care to:

? Define the computational domain, in order to minimize the influence and interactions between the flow and the far-field conditions. In particular,

– Place inlet and outlet boundaries as far away as possible from the region of interest. In particular, if uniform far-field conditions are imposed, you should ensure that the boundary is not in a region where the flow may still vary significantly.

– Avoid inlet or outlet boundaries in regions of strong geometrical changes or in regions of recirculation.

? Avoid jumps in grid density or in grid size.

? Avoid highly distorted cells or small grid angles.

? Ensure that the grid stretching is continuous.

? Avoid unstructured tetrahedral meshes in boundary layer regions.

? Refine the grids in regions with high gradients, such as boundary layers, leading edges of airfoils and any region where large changes in flow properties might occur.

? Make sure that the number of points in the boundary layers is sufficient for the expected accuracy. Avoid less than 10 points over the inner part of the boundary layer thickness.

? Monitor the grid quality by adequate mesh parameters, available in most of the grid generators, such as aspect ratio, internal angle, concavity, skewness, negative volume.

RECOMMENDATIONS ON SOLUTION ASSESSMENT

Once you run your code, the following recommendations will be useful to enhance your confidence in the results obtained:

? Check very carefully the selected boundary conditions for correctness and compatibility with the physics of the flow you are modeling.

? Verify all the numerical settings and parameters, before launching the CFD run.

? Verify that your initial solution is acceptable for the problem to be solved.

? Monitor the convergence to ensure that you reach machine accuracy. It is recommended to monitor, in addition to the residuals, the convergence of representative quantities of your problem, such as a drag force or coefficient, a velocity, temperature or pressure at selected points in the flow domain.

? Look carefully at the behavior of the residual convergence curve in function of number of iterations. If the behavior is oscillatory, or if the residual does not converge to machine accuracy by showing a limit cycle at a certain level of residual reduction, it tells you that some inaccuracy affects your solution process.

? Apply internal consistency and accuracy criteria, by verifying:

– Conservation of global quantities such as total enthalpy and mass flow in steady flow calculations.

– The entropy production and drag coefficients with inviscid flows, which are strong indicators of the influence of numerical dissipation, as they should be zero.

? Check, whenever possible, the grid dependence of the solution by comparing the results obtained on different grid sizes.

? Some quantities are more sensitive than others to error sources. Pressure curves are less sensitive than shear stresses, which in turn are less sensitive than temperature gradients or heat fluxes, which require finer grids for a given accuracy level.

? If your calculation appears difficult to converge, you can

– Look at the residual distribution and associated flow field for possible hints, e.g. regions with large residuals or unrealistic levels of the relevant flow parameters.

– Reduce the values of parameters controlling convergence, such as the CFL number or some under-relaxation parameter, when available.

– Consider the effects of different initial flow conditions.

– Check the effect of the grid quality on the convergence rate.

– Use a more robust numerical scheme, such as a first order scheme, during the initial steps of the convergence and switch to more accurate numerical schemes as the convergence improves.

RECOMMENDATIONS ON EVALUATION OF UNCERTAINTIES

? This is a very difficult issue, as the application uncertainties are generally not well defined and require a sound judgment about the physics of the considered flow problem. Some recommendations can be offered:

? Attempt to list the most important uncertainties, such as

– Geometrical simplifications and manufacturing tolerances around the CAD definition.

– Operational conditions, such as inlet velocity or inlet flow angle.

– Physical approximations, such as handling an incompressible flow as a low Mach number compressible flow. This type of uncertainty is manageable, as it can more easily be quantified.

– Uncertainties related to turbulence or other physical models.

? Perform a sensitivity analysis of the relevant uncertainty to investigate its influence.




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