High-order accurate direct numerical simulation of flow over a MTU-T161 low pressure turbine blade
High-order accurate direct numerical simulation of flow over a MTU-T161 low pressure turbine blade
复制标题
MTU-T161 低压涡轮叶片流动的高阶精确直接数值模拟
DOI:
10.1016/j.compfluid.2021.104989
复制
发表时间:
2021
影响因子:
2.8
通讯作者:
Iyer A
中科院分区:
文献类型:
--
作者:
Iyer A
Reynolds Averaged Navier-Stokes (RANS) simulations and wind tunnel testing have become the go-to tools for industrial design of Low-Pressure Turbine (LPT) blades. However, there is also an emerging interest in use of scale-resolving simulations, including Direct Numerical Simulations (DNS). These could generate insight and data to underpin development of improved RANS models for LPT design. Additionally, they could underpin a virtual LPT wind tunnel capability, that is cheaper, quicker, and more data-rich than experiments. The current study applies PyFR, a Python based Computational Fluid Dynamics (CFD) solver, to fifth-order accurate petascale DNS of compressible flow over a three-dimensional MTU-T161 LPT blade with diverging end walls at a Reynolds number of 200,000 on an unstructured mesh with over 11 billion degrees-of-freedom per equation. Various flow metrics, including isentropic Mach number distribution at mid-span, surface shear, and wake pressure losses are compared with available experimental data and found to be in agreement. Subsequently, a more detailed analysis of various flow features is presented. These include the separation/transition processes on both the suction and pressure sides of the blade, end-wall vortices, and wake evolution at various span-wise locations. The results, which constitute one of the largest and highest-fidelity CFD simulations ever conducted, demonstrate the potential of high-order accurate GPU-accelerated CFD as a tool for delivering industrial DNS of LPT blades.
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DOI:
--
发表时间:
2018
期刊:
Turbomachinery
影响因子:
--
作者:
Christoph Müller;Florian Herbst
通讯作者:
Florian Herbst
DOI:
10.1115/2001-gt-0311
发表时间:
2001-06
期刊:
--
影响因子:
--
作者:
P. Stadtmüller;L. Fottner
通讯作者:
P. Stadtmüller;L. Fottner
影响因子:
1.7
作者:
J. Gier;M. Franke;N. Hübner;T. Schröder
通讯作者:
J. Gier;M. Franke;N. Hübner;T. Schröder
DOI:
10.1002/nme.2579
发表时间:
2009-09-10
影响因子:
2.9
作者:
Geuzaine, Christophe;Remacle, Jean-Francois
通讯作者:
Remacle, Jean-Francois
影响因子:
1.7
作者:
Müller-Schindewolffs;Herbst F.
通讯作者:
Herbst F.