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Estimation of grid-induced errors in computational fluid dynamics solutions using a discrete error transport equation

机译:使用离散误差传输方程估算计算流体力学解决方案中网格引起的误差

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摘要

Computational fluid dynamics (CFD) has become a widely used tool in research and engineering for the study of a wide variety of problems. However, confidence in CFD solutions is still dependent on comparisons with experimental data. In order for CFD to become a trusted resource, a quantitative measure of error must be provided for each generated solution. Although there are several sources of error, the effects of the resolution and quality of the computational grid are difficult to predict y priori. This grid-induced error is most often attenuated by performing a grid refinement study or using solution adaptive grid refinement. While these methods are effective, they can also be computationally expensive and even impractical for large, complex problems.This work presents a method for estimating the grid-induced error in CFD solutions of the Navier-Stokes and Euler equations using a single grid and solution or a series of increasingly finer grids and solutions. The method is based on the discrete error transport equation (DETE), which is derived directly from the discretized PDE and provides a value of the error at every cell in the computational grid. The DETE is developed for two-dimensional, laminar Navier-Stokes and Euler equations within a generalized unstructured finite volume scheme, such that an extension to three dimensions and turbulent flow would follow the same approach.The usefulness of the DETE depends on the accuracy with which the source term, the grid-induced residual, can be modeled. Three different models for the grid-induced residual were developed: the AME model, the PDE model, and the extrapolation model. The AME model consists of the leading terms of the remainder of a simplified modified equation. The PDE model creates a polynomial fit of the CFD solution and then uses the original PDE in differential form to calculate the residual. Both the AME and PDE are used with a single grid and solution. The extrapolation model uses a fine grid solution to calculate the grid-induced residual on the coarse grid and then extrapolates that residual back to the fine grid.The DETE and residual models were then evaluated for four flow problems: (1) steady flow past a circular cylinder; (2) steady, transonic flow past an airfoil; (3) unsteady flow of an isentropic vortex; (4) unsteady flow past a circular cylinder with vortex shedding. Results demonstrate the fidelity of the DETE with each residual model as well as usefulness of the DETE as a tool for predicting the grid-induced error in CFD solutions.
机译:计算流体力学(CFD)已成为研究和工程学中广泛用于研究各种问题的工具。但是,对CFD解决方案的信心仍然取决于与实验数据的比较。为了使CFD成为受信任的资源,必须为每个生成的解决方案提供定量的错误度量。尽管存在多种错误源,但是很难先验地预测分辨率和计算网格质量的影响。通过执行网格细化研究或使用解决方案自适应网格细化,通常会减轻这种由网格引起的误差。尽管这些方法是有效的,但它们在计算上也很昂贵,甚至对于大型,复杂的问题也不可行。或一系列日益完善的网格和解决方案。该方法基于离散误差传输方程(DETE),该方程直接从离散化PDE导出,并提供计算网格中每个单元的误差值。 DETE是为广义的非结构化有限体积方案中的二维,层状Navier-Stokes和Euler方程开发的,因此扩展到三维和湍流将遵循相同的方法.DETE的有效性取决于精度可以对源项(网格引起的残差)进行建模。针对网格引起的残差开发了三种不同的模型:AME模型,PDE模型和外推模型。 AME模型由简化的修改方程的其余部分的前导项组成。 PDE模型创建CFD解决方案的多项式拟合,然后使用微分形式的原始PDE计算残差。 AME和PDE都可用于单个网格和解决方案。外推模型使用精细网格解决方案计算粗网格上的网格诱发残差,然后将该残差外推回精细网格。然后评估DETE和残差模型的四个流动问题:(1)超过圆柱体(2)稳定的跨音速流过机翼; (3)等熵涡流的非定常流动; (4)非恒定流经过具有涡旋脱落的圆柱体。结果证明了DETE在每个残差模型中的保真度,以及DETE作为预测CFD解决方案中网格引起的误差的工具的有用性。

著录项

  • 作者

    Williams, Brandon;

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  • 年度 2009
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  • 原文格式 PDF
  • 正文语种 en
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