Investigation of the Accuracy of RANS Models to Predict the Flow Through a Low-Pressure Turbine

Investigation of the Accuracy of RANS Models to Predict the Flow Through a Low-Pressure Turbine
复制标题

研究 RANS 模型预测低压涡轮流量的准确性

DOI：
--
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Rathakrishnan Bhaskaran
Rathakrishnan Bhaskaran
中科院分区：
--
文献类型：
--
作者：
R. Pichler;R. Sandberg;V. Michelassi;Rathakrishnan Bhaskaran

文献摘要

被引文献

相似文献

©ASME版权所有2015年。本文采用湍流模型对某低压透平的直接数值模拟数据进行了研究。许多可压缩湍流模型使用守恒量和湍动能的Favre平均输运方程以及其他模拟方程。首先对输运方程所规定的湍流模型误差传播进行了一般性的讨论，引出了对湍流模型改进有意义的项。为了给湍流模型提供验证其模型的手段，Favre平均动量方程中出现的项在三个轴向位置沿节距分布给出。这三个位置的选择使得它们代表具有不同流动特性的区域。总体趋势表明，与热力学涨落和Favre涨落有关的项都很小，在大多数流场中可以忽略不计。最大误差出现在尾缘区附近，那里发生了旋涡脱落。最后讨论了线性模型及其改进的空间。使用局部优化的湍流粘度，显示了最新模型的改进潜力。另一方面，本研究也凸显了纯局部优化的危险性。
© Copyright 2015 by ASME. In the present paper direct numerical simulation data of a low pressure turbine is investigated in light of turbulence modelling. Many compressible turbulence models use Favre average transport equations of the conservative variables and turbulent kinetic energy along with other modelling equation. First a general discussion on the turbulence modelling error propagation prescribed by transport equations is presented, leading to the terms that are considered to be of interest for turbulence model improvement. In order to give turbulence modellers means of validating their models the terms appearing in the Favre averaged momentum equations are presented along pitchwise profiles at three axial position. These three positions have been chosen such that they represent regions with different flow characteristics. General trends indicate that terms related with thermodynamic fluctuations and Favre fluctuations are small and can be neglected for most of the flow field. The largest errors arise close to the trailing edge region where vortex shedding occurs. Finally, linear models and the scope for their improvement are discussed. Using locally optimized turbulence viscosities, the improvement potential of state of the art models is shown. On the other hand this study also highlights the danger of pure local optimization.