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Predicting Transition in Turbomachinery, Part II - Model Validation and Benchmarking

机译:预测涡轮机械,第二部分 - 模型验证和基准测试中的过渡

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The ability to predict boundary layer transition locations accurately on turbomachinery airfoils is critical both to evaluate aerodynamic performance and to predict local heat-transfer coefficients with accuracy. In state-of-the-art Reynolds Averaged Navier-Stokes (RANS) simulations used to predict flowfields on turbomachinery airfoils, boundary layers are often assumed to be turbulent over the entire airfoil surface. Consequently, losses are not accurately predicted, particularly in the case of stalled airfoils. Here we report on an effort to include empirical transition models developed in Part I of this report in a RANS solver. To validate the new models, a two-dimensional design optimization was performed to obtain a pair of Low-Pressure Turbine (LPT) airfoils with the objective of increasing airfoil loading by 25%. Subsequent experimental testing of the resulting two new airfoils confirmed pre-test predictions of both high and low Reynolds number loss levels. In addition, the accuracy of the new transition modeling capability was benchmarked with a number of legacy cascade and LPT rig data sets. Good agreement between measured and predicted profile losses was found in both cascade and rig environments. However, use of the transition modeling capability has elucidated deficiencies in typical RANS simulations that are conducted to predict component performance. Efficiency-versus-span comparisons between rig data and multi-stage steady and time-accurate LPT simulation results indicate that loss levels in the endwall regions are significantly under-predicted. Possible causes for the under-predicted endwall losses are discussed as well as suggestions for future improvements that would make RANS-based transitional simulations more accurate.
机译:在涡轮机翼型上准确地预测边界层过渡位置的能力对于评估空气动力学性能并以精度来预测局部传热系数的关键。在最先进的Reynolds中,Vier-Stokes(RANS)模拟用于预测涡轮机翼型上的流场,通常假设边界层在整个翼型表面上湍流。因此,不准确地预测损失,特别是在停滞翼型的情况下。在这里,我们报告努力包括在Rans解决者的本报告第I节中开发的经验转换模型。为了验证新模型,执行二维设计优化以获得一对低压涡轮机(LPT)翼型,其目的是将翼型载荷增加25%。随后的试验测试两种新翼型的试验证实了高低雷诺数损失水平的预测预测。此外,新的过渡建模能力的准确性与许多遗留级联和LPT钻机数据集进行了基准测试。在级联和钻机环境中发现了测量和预测的概况损失之间的良好一致性。然而,使用过渡建模能力在典型的RAN模拟中阐明了缺陷,以预测成分性能。钻机数据和多级稳态和时间准确的LPT仿真结果的效率 - 跨度比较表明,端壁区域中的损耗程度显着预测。讨论了预测的终止损失的可能原因以及对未来改进的建议,以使基于RAN的过渡模拟更准确。

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