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Global error estimation in CFD mesh coarsening process for uncertainty quantification methods

机译:CFD网格粗化过程中的全局误差估计,用于不确定性量化方法

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摘要

Due to high performance of modern computers, Uncertainty Quantification is becoming an important part of engineering design. Every non intrusive Uncertainty Quantification method requires a considerable number of evaluations of the model, meaning that the design process is more expensive in terms of computational resources/time. In Computational Fluid Dynamics, the usual practice is to reduce the computational time by reducing the number of nodes of the used mesh. Each coarsening of the mesh leads to the increase of the error measured as the difference between the real solution and the solution provided by the computational model. In this work, an approach for quantification of the global error around the stochastic domain, in a mesh reduction process, is described and results obtained for a test case are detailed. The method is based on a comparison of the high accurate mesh against coarse mesh with lower accuracy, but less expensive in terms of computational time. The global error is defined as a volume difference between surrogate models created in the stochastic domain. The stochastic domain is given by pre-specified input variables with appropriate boundaries. Surrogate models are used and a non intrusive polynomial chaos model is created with response samples from high and low accuracy mesh. For the chosen test case, the input variables, related to the stochastic space, were the free stream pressure and free stream Mach number. A hypersonic flow solver developed at the von Karman Institute, Cosmic, was used to compute properties of a flow around the reentry spacecraft. A computational expensive mesh was used as a reference mesh. Due to computational resources, it was impossible to use expansive mesh for Monte Carlo simulation or high order Polynomial Chaos. Therefore, the global error estimation approach was applied to find an accurate and relatively inexpensive mesh for Uncertainty Quantification in hypersonic simulation. Multiple meshes with different coarsening were tested, based on expert knowledge of the problem. The global error estimation method allowed for finding a final mesh, with an error on the mean value 0.48% and on the standard deviation 5.89%, which was 4 times faster than the reference mesh.
机译:由于现代计算机的高性能,不确定性量化正在成为工程设计的重要组成部分。每种非侵入式不确定性量化方法都需要对模型进行大量评估,这意味着设计过程在计算资源/时间方面更加昂贵。在计算流体动力学中,通常的做法是通过减少所用网格的节点数来减少计算时间。网格的每次粗化都会导致测量的误差增加,该误差是实际解与计算模型提供的解之间的差。在这项工作中,描述了一种在网格减少过程中量化随机域周围全局误差的方法,并详细说明了针对测试用例获得的结果。该方法基于高精度的网格与精度较低的粗网格的比较,但是在计算时间方面较便宜。全局误差定义为在随机域中创建的替代模型之间的体积差异。随机域由带有适当边界的预先指定的输入变量给出。使用替代模型,并使用来自高精度和低精度网格的响应样本创建非侵入式多项式混沌模型。对于所选的测试用例,与随机空间相关的输入变量为自由流压力和自由流马赫数。由冯·卡曼研究所(Cosmic)开发的高超音速流动求解器用于计算再入航天器周围的流动特性。计算昂贵的网格被用作参考网格。由于计算资源的原因,不可能将膨胀网格用于蒙特卡洛模拟或高阶多项式混沌。因此,使用全局误差估计方法来为高超声速模拟中的不确定性量化找到准确且相对便宜的网格。基于对该问题的专业知识,测试了具有不同粗化度的多个网格。全局误差估计方法可以找到最终的网格,其平均值为0.48%,标准偏差为5.89%,这比参考网格快4倍。

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