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Impact of geometric, operational, and model uncertainties on the non-ideal flow through a supersonic ORC turbine cascade

机译:几何,操作和模型不确定性对通过超音速ORC涡轮机级联的非理想流动的影响

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摘要

Typical energy sources for Organic Rankine Cycle (ORC) power systems feature variable heat load and turbine inlet/outlet thermodynamic conditions. The use of organic compounds with heavy molecular weight introduces uncertainties in the fluid thermodynamic modeling. In addition, the peculiarities of organic fluids typically lead to supersonic turbine configurations featuring supersonic flows and shocks, which grow in relevance in the aforementioned off-design conditions; these features also depend strongly on the local blade shape, which can be influenced by the geometric tolerances of the blade manufacturing. This study presents an Uncertainty Quantification (UQ) analysis on a typical supersonic nozzle cascade for ORC applications, by considering a two-dimensional high-fidelity turbulent Computational Fluid Dynamic (CFD) model. Kriging-based techniques are used in order to take into account at a low computational cost, the combined effect of uncertainties associated to operating conditions, fluid parameters, and geometric tolerances. The geometric variability is described by a finite Karhunen-Loeve expansion representing a non-stationary Gaussian random field, entirely defined by a null mean and its autocorrelation function. Several results are illustrated about the ANOVA decomposition of several quantities of interest for different operating conditions, showing the importance of geometric uncertainties on the turbine performances. (C) 2018 Elsevier Ltd. All rights reserved.
机译:有机朗肯循环(ORC)电力系统的典型能源具有可变的热负荷和涡轮进口/出口热力学条件。具有高分子量的有机化合物的使用在流体热力学模型中引入了不确定性。此外,有机流体的特殊性通常会导致以超音速流动和冲击为特征的超音速涡轮机配置,在上述非设计条件下相关性会增加;这些特征还强烈取决于叶片的局部形状,这可能会受到叶片制造的几何公差的影响。通过考虑二维高保真湍流计算流体动力学(CFD)模型,本研究针对ORC应用的典型超音速喷嘴级联提出了不确定性量化(UQ)分析。使用基于Kriging的技术以便以较低的计算成本考虑与操作条件,流体参数和几何公差相关的不确定性的综合影响。几何可变性由表示非平稳高斯随机场的有限Karhunen-Loeve展开描述,该场完全由零均值及其自相关函数定义。在不同的工况下,有关多个目标变量的ANOVA分解得到了一些结果,说明了几何不确定性对涡轮性能的重要性。 (C)2018 Elsevier Ltd.保留所有权利。

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