Eddy resolving simulations in aerospace - Invited paper (Numerical Fluid 2014)
Eddy resolving simulations in aerospace - Invited paper (Numerical Fluid 2014)
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DOI：
10.1016/j.amc.2015.02.018
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
P. Tucker;J. Tyacke
中科院分区：
文献类型：
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作者：
P. Tucker;J. Tyacke
探讨了大涡模拟(LES)、直接数值模拟(DNS)等涡旋分辨模拟(ERS)及其相关方法在航空航天领域的应用前景。对比了航空发动机和飞机对湍流建模的要求。对于后者，更普遍的是较高的雷诺数，这特别需要将ERS方法与雷诺平均纳维斯托克斯(RANS)方法相结合。概述了未来可能使用纯ERS方法的地区，以及需要与RAN杂交的地区。主要的关注点是航空发动机，其部件规模要小得多。这通常会产生更良性的雷诺数。讨论了涡旋分解方法在航空发动机的广泛区域中的应用，指出了这种方法的潜在好处和成本缺点。探讨了在部件甚至机身和发动机的耦合变得越来越重要的领域中使用这种计算密集型计算时的紧张情况。此外，还考虑了数值方法和网格划分的要求，以及ERS方法对未来数值算法的启示。据推测，这样的模拟现在已经准备好在工业中进行适当的使用。然而，要实现工业所需的模拟规模，满足紧迫的环境需求，挑战依然存在。例如，需要开发既能满足ERS的精度要求，又能适应未来计算机体系结构的最佳数值方法。
The future use of eddy resolving simulations (ERS) such as Large Eddy Simulation (LES), Direct Numerical Simulation (DNS) and related approaches in aerospace is explored. The turbulence modeling requirements with respect to aeroengines and aircraft is contrasted. For the latter, higher Reynolds numbers are more prevalent and this especially gives rise to the need for the hybridization of ERS methods with Reynolds Averaged Navier–Stokes (RANS) approaches. Zones where future use of pure ERS methods is now possible and those where hybridizations with RANS will be needed is outlined. The major focus is the aeroengine for which the component scales are much smaller. This gives rise to generally more benign Reynolds numbers. The use of eddy resolving methods in a wide range of zones in an aeroengine is discussed and the potential benefits and also cost drawbacks with such approaches noted. The tension when using such computationally intensive calculations in an area where the coupling of components and even the airframe and engine is becoming increasingly important is explored. Also, the numerical methods and meshing requirements are considered and the implications of ERS methods for future numerical algorithms. It is postulated that such simulations are ready now for niche uses in industry. However, to perform the scale of simulations that industry requires, to meet pressing environmental needs, challenges remain. For example, there is the need to develop optimal numerical methods that both map to the accuracy requirements for ERS and also future computer architectures.