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首页> 外文期刊>Journal of Computational Physics >High-order solution-adaptive central essentially non-oscillatory (CENO) method for viscous flows
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High-order solution-adaptive central essentially non-oscillatory (CENO) method for viscous flows

机译:粘性流的高阶溶液自适应中央基本非振荡(CENO)方法

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摘要

A high-order, central, essentially non-oscillatory (CENO), finite-volume scheme in combi- nation with a block-based adaptive mesh refinement (AMR) algorithm is proposed for solution of the Navier-Stokes equations on body-fitted multi-block mesh. In contrast to other ENO schemes which require reconstruction on multiple stencils, the proposed CENO method uses a hybrid reconstruction approach based on a fixed central stencil. This feature is crucial to avoiding the complexities associated with multiple stencils of ENO schemes, providing high-order accuracy at relatively lower computational cost as well as being very well suited for extension to unstructured meshes. The spatial discretization of the inviscid (hyperbolic) fluxes combines an unlimited high-order k-exact least-squares reconstruction technique following from the optimal central stencil with a monotonicity- preserving, limited, linear, reconstruction algorithm. This hybrid reconstruction procedure retains the unlimited high-order /c-exact reconstruction for cells in which the solution is fully resolved and reverts to the limited lower-order counterpart for cells with under- resolved/discontinuous solution content. Switching in the hybrid procedure is determined by a smoothness indicator. The high-order viscous (elliptic) fluxes are computed to the same order of accuracy as the hyperbolic fluxes based on a k-order accurate cell interface gradient derived from the unlimited, cell-centred, reconstruction. A somewhat novel h-refinement criterion based on the solution smoothness indicator is used to direct the steady and unsteady mesh adaptation. The proposed numerical procedure is thoroughly analyzed for advection-diffusion problems characterized by the full range of Péclet numbers, and its predictive capabilities are also demonstrated for several inviscid and laminar flows. The ability of the scheme to accurately represent solutions with smooth extrema and yet robustly handle under-resolved and/or non-smooth solution content (i.e., shocks and other discontinuities) is shown. Moreover, the ability to perform mesh refinement in regions of under-resolved and/or non-smooth solution content is also demonstrated.
机译:提出了一种高阶,中央,基本非振荡(CENO)有限体积方案与基于块的自适应网格细化(AMR)算法相结合的方法,以解决人体拟合多点运动中的Navier-Stokes方程块状网格。与其他ENO方案需要在多个模板上进行重建相比,所提出的CENO方法使用基于固定中心模板的混合重建方法。该功能对于避免与ENO方案的多个模板相关联的复杂性,以相对较低的计算成本提供高阶精度以及非常适合扩展到非结构化网格至关重要。无粘性(双曲线)通量的空间离散化结合了无限的高阶k精确最小二乘重建技术,该技术源自最优的中心模版,并具有单调性,有限,线性的重建算法。对于其中溶液完全溶解的细胞,此混合重建过程保留了无限制的高阶/ c-精确重构,而对于溶液含量不足/不连续的细胞,则还原为有限的低阶对应物。混合过程中的切换由平滑度指示器确定。高阶粘性(椭圆形)通量的计算精度与双曲线通量相同,基于基于无级,以单元为中心的重构的k级精确单元界面梯度。基于解决方案平滑度指示器的某种新颖的h细化准则用于指导稳态和非稳态网格自适应。拟议的数值程序被彻底分析了对流扩散问题,其特征是全范围的佩克利特数,并且还证明了其对几种无粘性和层流的预测能力。示出了该方案准确地表示具有平滑极值的解决方案的能力,而该解决方案却能够稳健地处理未解决和/或不平滑的解决方案内容(即,冲击和其他不连续性)。此外,还展示了在溶解度低和/或溶液溶液含量不光滑的区域进行网格细化的能力。

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