Numerical integration poses greater challenges in Galerkin meshless methods than finite element methods owing to the non-polynomial feature of meshless shape functions.The reproducing kernel gradient smoothing integra...Numerical integration poses greater challenges in Galerkin meshless methods than finite element methods owing to the non-polynomial feature of meshless shape functions.The reproducing kernel gradient smoothing integration(RKGSI)is one of the optimal numerical integration techniques in Galerkin meshless methods with minimum integration points.In this paper,properties,quadrature rules and the effect of the RKGSI on meshless methods are analyzed.The existence,uniqueness and error estimates of the solution of Galerkin meshless methods under numerical integration with the RKGSI are established.A procedure on how to choose quadrature rules to recover the optimal convergence rate is presented.展开更多
基金National Natural Science Foundation of China(Grant No.11971085)Natural Science Foundation of Chongqing(Grant No.cstc2021jcyj-jqX0011)。
文摘Numerical integration poses greater challenges in Galerkin meshless methods than finite element methods owing to the non-polynomial feature of meshless shape functions.The reproducing kernel gradient smoothing integration(RKGSI)is one of the optimal numerical integration techniques in Galerkin meshless methods with minimum integration points.In this paper,properties,quadrature rules and the effect of the RKGSI on meshless methods are analyzed.The existence,uniqueness and error estimates of the solution of Galerkin meshless methods under numerical integration with the RKGSI are established.A procedure on how to choose quadrature rules to recover the optimal convergence rate is presented.
