The optimized calibration method for the local shape factors of radial point interpolation method

In the radial point interpolation method (RPIM), the shape factors such as the parameters of basis function, the support domain size and the average node distance directly affect the interpolation precision and computational efficiency, and the small shape parameter may lead to interpolation instability. In order to optimize parameter selection in RPIM, the algorithm based on the local shape factor calibration method (LSFCM)is proposed in the electromagnetic field problem. The global root mean square (RMS) interpolation error curve with different support domain size, node distance and different parameters can simplify the process of the shape parameter selection and node interpolation. The numerical results show the algorithm has improved the interpolation precision and computational efficiency.