文章基本信息

标题：The Performance of a Gradient-Based Method to Estimate the Discretization Error in Computational Fluid Dynamics
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作者：Adhika Satyadharma ; Harinaldi
期刊名称：Computation
电子版ISSN：2079-3197
出版年度：2021
卷号：9
期号：2
页码：10
DOI：10.3390/computation9020010
出版社：MDPI Publishing
摘要：Although the grid convergence index is a widely used for the estimation of discretization error in computational fluid dynamics, it still has some problems. These problems are mainly rooted in the usage of the order of a convergence variable within the model which is a fundamental variable that the model is built upon. To improve the model, a new perspective must be taken. By analyzing the behavior of the gradient within simulation data, a gradient-based model was created. The performance of this model is tested on its accuracy, precision, and how it will affect a computational time of a simulation. The testing is conducted on a dataset of 36 simulated variables, simulated using the method of manufactured solutions, with an average of 26.5 meshes/case. The result shows the new gradient based method is more accurate and more precise then the grid convergence index(GCI). This allows for the usage of a coarser mesh for its analysis, thus it has the potential to reduce the overall computational by at least by 25% and also makes the discretization error analysis more available for general usage.
关键词：computational fluid dynamics; verification and validation; discretization error; uncertainty quantification; grid convergence index computational fluid dynamics ; verification and validation ; discretization error ; uncertainty quantification ; grid convergence index