Improving approximation accuracy in Godunov-type smoothed particle hydrodynamics methods

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2025-03-01 Epub Date: 2024-10-16 DOI:10.1016/j.amc.2024.129128
G.D. Rublev , A.N. Parshikov , S.A. Dyachkov
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Abstract

The study examines the origin of errors resulting from the approximation of the right hand sides of the Euler equations using the Godunov type contact method of smoothed particle hydrodynamics (CSPH). The analytical expression for the numerical shear viscosity in CSPH method is obtained. In our recent study the numerical viscosity was determined by comparing the numerical solution of momentum diffusion in the shear flow with theoretical one. In this study we deduce the analytical expression for the numerical viscosity which is found to be similar to numerical one, confirming the obtained results. To reduce numerical diffusion, diffusion limiters are typically applied to expressions for contact values of velocity and pressure, as well as higher-order reconstruction schemes. Based on the performed theoretical analysis, we propose a new method for correcting quantities at interparticle contacts in CSPH method, which can be easily extended to the MUSCL-type (Monotonic Upstream-centered Scheme for Conservation Laws) method. Original CSPH and MUSCL-SPH approaches and ones with aforementioned correction are compared.
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提高戈杜诺夫型平滑粒子流体力学方法的近似精度
研究探讨了使用平滑粒子流体力学(CSPH)的戈杜诺夫接触法对欧拉方程右边进行近似所产生误差的根源。我们得到了 CSPH 方法中数值剪切粘度的解析表达式。在我们最近的研究中,通过比较剪切流中动量扩散的数值解与理论解,确定了数值粘度。在本研究中,我们推导出了数值粘度的分析表达式,发现其与数值粘度相似,从而证实了所获得的结果。为了减少数值扩散,通常会在速度和压力的接触值表达式以及高阶重构方案中应用扩散限制器。基于所做的理论分析,我们提出了一种在 CSPH 方法中修正粒子间接触量的新方法,该方法可以很容易地扩展到 MUSCL 类型(单调上游中心守恒定律方案)方法。比较了原始的 CSPH 和 MUSCL-SPH 方法以及采用上述修正的方法。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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