A Study on Stable Regularized Moving Least-Squares Interpolation and Coupled with SPH Method

Hua Jiang, Yunsai Chen, Xing Zheng, Shanqin Jin and Qingwei Ma

Mathematical Problems in Engineering, 2020, vol. 2020, 1-28

Abstract:

The smoothed particle hydrodynamics (SPH) method has been popularly applied in various fields, including astrodynamics, thermodynamics, aerodynamics, and hydrodynamics. Generally, a high-precision interpolation is required to calculate the particle physical attributes and their derivatives for the boundary treatment and postproceeding in the SPH simulation. However, as a result of the truncation of kernel function support domain and irregular particle distribution, the interpolation using conventional SPH interpolation experiences low accuracy for the particles near the boundary and free surface. To overcome this drawback, stable regularized moving least-squares (SRMLS) method was introduced for interpolation in SPH. The surface fitting studies were performed with a variety of polyline bases, spatial resolutions, particle distributions, kernel functions, and support domain sizes. Numerical solutions were compared with the results using moving least-squares (MLS) and three SPH methods, including CSPH, K2SPH, and KGFSPH, and it was found that SRMLS not only has nonsingular moment matrix, but also obtains high-accuracy result. Finally, the capability of the algorithm coupled with SRMLS and SPH was illustrated and assessed through several numerical tests.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9042615

DOI: 10.1155/2020/9042615

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