相关期刊:《Communications in Computational Physics》《Numerical Mathematics(Theory,Methods and Applications)》《港口装卸》《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》更多>>
相关基金:国家自然科学基金Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry国家重点基础研究发展计划更多>>
Project supported in part by the National Natural Science Foundation of China(Grant No.11771259);Shaanxi Provincial Joint Laboratory of Artificial Intelligence(GrantNo.2022JCSYS05);Innovative Team Project of Shaanxi Provincial Department of Education(Grant No.21JP013);Shaanxi Provincial Social Science Fund Annual Project(Grant No.2022D332)。
We propose the meshfree-based physics-informed neural networks for solving the unsteady Oseen equations.Firstly,based on the ideas of meshfree and small sample learning,we only randomly select a small number of spatio...
Radial Basis Function(RBF)kernels are key functional forms for advanced solutions of higher-order partial differential equations(PDEs).In the present study,a hybrid kernel was developed for meshless solutions of PDEs ...
The authors would like to express their gratitude to Prof.De-cheng Wan at Shanghai Jiao Tong University for invitation for this vision paper.The first author,A.Khayyer,would like to express his sincere appreciation to Prof.Antonio J.Gil at Swansea University and Dr Chun Hean Lee at the University of Glasgow for discussions regarding viscoelastic and elastoplastic modelling.The authors appreciate the research grants by Japan Society for the Promotion of Science(JSPS)(Grant No.JP18K04368,JP21H01433 and JP21K14250).
This paper presents a review on state-of-the-art of developments corresponding to fluid-structure interaction(FSI)solvers developed within the context of particle methods.The paper reviews and highlights the potential...
supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2017MA028);supported by the Natural Science Foundation of Shandong Province(Grant No.ZR2020MA059).
By introducing the radial basis functions(RBFs)into the reproducing kernel particle method(RKPM),the calculating accuracy and stability of the RKPM can be improved,and a novel meshfree method of the radial basis RKPM(...
Supported by Project of National Natural Science Foundation of China(No.42074120).
In this paper,the authors propose a method of three-dimensional(3D)magnetotelluric(MT)forward modeling algorithm based on the meshfree and finite element coupling method.The model is discretized by regular nodes in th...
In this work,we study the gradient projection method for solving a class of stochastic control problems by using a mesh free approximation ap-proach to implement spatial dimension approximation.Our main contribu-tion ...
the VLIR-UOS TEAM Project,VN2017TEA454A103,‘An innovative solution to protect Vietnamese coastal riverbanks from floods and erosion’,funded by the Flemish Government.https://www.vliruos.be/en/projects/project/22?pid=3251.
This study adapts the flexible characteristic of meshfree method in analyzing three-dimensional(3D)complex geometry structures,which are the interlocking concrete blocks of step seawall.The elastostatic behavior of th...
supported by the National Natural Science Foundation of China(Nos.11701253,11971259,11801216);Natural Science Foundation of Shandong Province(No.ZR2017BA010)。
In this paper,we investigate a stochastic meshfree finite volume element method for an optimal control problem governed by the convection diffusion equations with random coefficients.There are two contributions of thi...