Gradient reproducing kernel particle method

Some Studies of the Reproducing Kernel Particle Method

Abstract. Interests in meshfree (or meshless) methods have grown rapidly in the recent years in solving boundary value problems arising in mechanics, especially in dealing with difficult problems involving large deformation, moving discontinuities, etc. Rigorous error estimates of a meshfree method, the reproducing kernel particle method (RKPM), have been theoretically derived and experimentall...

Method of Reproducing Kernel

Multiresolution Reproducing Kernel Particle Methods in Acoustics

In the analysis of complex phenomena of acoustic systems, the computational model-ing requires special attention for a realistic representation of the physics. As a powerful tool, the nite element method has been widely used in the study of complex systems. In order to capture the important physical phenomena, p-nite elements and/or hp-nite elements are employed. The reproducing kernel particle...

Reproducing Kernel Space Hilbert Method for Solving Generalized Burgers Equation

In this paper, we present a new method for solving Reproducing Kernel Space (RKS) theory, and iterative algorithm for solving Generalized Burgers Equation (GBE) is presented. The analytical solution is shown in a series in a RKS, and the approximate solution u(x,t) is constructed by truncating the series. The convergence of u(x,t) to the analytical solution is also proved.

Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces

We introduce a functional gradient descent trajectory optimization algorithm for robot motion planning in Reproducing Kernel Hilbert Spaces (RKHSs). Functional gradient algorithms are a popular choice for motion planning in complex many-degree-of-freedom robots, since they (in theory) work by directly optimizing within a space of continuous trajectories to avoid obstacles while maintaining geom...