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MULTIFIDELITY MODELING OF IRRADIATED PARTICLE-LADEN TURBULENCE SUBJECT TO UNCERTAINTY
International Journal for Uncertainty Quantification ( IF 1.5 ) Pub Date : 2020-01-01 , DOI: 10.1615/int.j.uncertaintyquantification.2020032236
Lluis Jofre , M. Papadakis , P. T. Roy , A. Aiken , G. Iaccarino

The study of thermal radiation interacting with particle-laden turbulence is of great importance in a wide range of scientific and engineering applications. The computational study of such systems is challenging as a result of the large number of thermo-fluid mechanisms governing the underlying physics. To build confidence and improve the prediction accuracy of such simulations, the impact of uncertainties on the quantities of interest must be measured. This, however, requires a computational budget that is typically a large multiple of the cost of a single calculation, and thus may become infeasible for expensive simulation models featuring a large number of uncertain inputs and highly nonlinear behavior. In this regard, multifidelity methods have become increasingly popular in recent years as acceleration strategies to reduce the computational cost. These methods are based on a hierarchy of generalized numerical resolutions, or model fidelities, and attempt to leverage the correlation between high- and low-fidelity models to obtain a more accurate statistical estimator with a relatively small number of high-fidelity calculations. In this work, the performance of a collection of different multifidelity strategies and modeling approaches is assessed to propagate the uncertainties encountered in the simulation of irradiated particle-laden turbulence relevant to volumetric solar energy receivers. The results obtained indicate that multifidelity methods provide speedups on the order of 101−103 × with respect to straightforward Monte Carlo approaches, resulting in remarkable reductions in computational cost.

中文翻译:

不确定性对辐照颗粒物湍流的多分辨率建模

热辐射与颗粒湍流相互作用的研究在广泛的科学和工程应用中非常重要。由于控制基本物理的大量热流体机制,这种系统的计算研究具有挑战性。为了建立信心并提高此类仿真的预测准确性,必须测量不确定性对目标数量的影响。然而,这需要计算预算,该计算预算通常是单次计算成本的大倍,因此对于具有大量不确定性输入和高度非线性行为的昂贵仿真模型可能变得不可行。在这方面,近年来,作为降低计算成本的加速策略,多保真方法已变得越来越流行。这些方法基于广义数值分辨率或模型保真度的层次结构,并尝试利用高保真度模型和低保真度模型之间的相关性,以相对少量的高保真度计算获得更准确的统计估计量。在这项工作中,评估了各种不同的保真度策略和建模方法的性能,以传播与体积太阳能接收器相关的充满粒子的湍流模拟过程中遇到的不确定性。获得的结果表明,多保真方法可将速度提高10倍左右 或模型保真度,并尝试利用高保真度模型和低保真度模型之间的相关性,以较少数量的高保真度计算获得更准确的统计估计量。在这项工作中,评估了多种不同保真度策略和建模方法的性能,以传播与体积太阳能接收器相关的充满粒子的湍流模拟中遇到的不确定性。获得的结果表明,多保真方法可将速度提高10倍左右 或模型保真度,并尝试利用高保真度模型和低保真度模型之间的相关性,以较少数量的高保真度计算获得更准确的统计估计量。在这项工作中,评估了多种不同保真度策略和建模方法的性能,以传播与体积太阳能接收器相关的充满粒子的湍流模拟中遇到的不确定性。获得的结果表明,多保真方法可将速度提高10倍左右 评估了各种不同的保真度策略和建模方法的性能,以传播与体积太阳能接收器相关的充满粒子的湍流模拟中遇到的不确定性。获得的结果表明,多保真方法可将速度提高10倍左右 评估了各种不同的保真度策略和建模方法的性能,以传播与体积太阳能接收器相关的充满粒子的湍流模拟中遇到的不确定性。获得的结果表明,多保真方法可将速度提高10倍左右相对于简单的蒙特卡洛方法,为1 -10 3 ×,从而显着降低了计算成本。
更新日期:2020-01-01
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