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
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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
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发表时间:
2021
期刊:
影响因子:
2.8
通讯作者:
Iyer A
Iyer A
中科院分区:
工程技术3区
文献类型:
--
作者:
Iyer A

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雷诺平均纳维尔-斯托克斯(RANS)模拟和风洞测试已成为低压涡轮机(LPT)叶片工业设计的首选工具。然而,也有一个新兴的兴趣,在使用尺度分辨模拟,包括直接数值模拟(DNS)。这些可以产生洞察力和数据,以支持为LPT设计开发改进的RANS模型。此外,它们可以支持虚拟LPT风洞能力,这比实验更便宜,更快,数据更丰富。目前的研究应用PyFR,基于Python的计算流体动力学(CFD)求解器,在雷诺数为200,000的非结构化网格上,每个方程具有超过110亿个自由度,在具有发散端壁的三维MTU-T161 LPT叶片上进行可压缩流的五阶精确千万亿次DNS。各种流量指标,包括等熵马赫数分布在跨中,表面剪切,和尾流压力损失与现有的实验数据进行了比较,发现是一致的。随后,更详细地分析了各种流动特征。这些包括叶片吸力侧和压力侧的分离/过渡过程、端壁涡流以及各个展向位置的尾流演变。这些结果构成了有史以来规模最大、保真度最高的CFD模拟之一,证明了高阶精确GPU加速CFD作为LPT叶片工业DNS工具的潜力。
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.
湍流尺度对低压涡轮空气动力学的影响:A 部分 - 优化的湍流边界条件
DOI: --
发表时间: 2018
期刊: Turbomachinery
影响因子: --
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发表时间: 2001-06
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发表时间: 2009-09-10
影响因子: 2.9
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影响因子: 1.7
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