Enriched Reproducing Kernel Approximation: Reproducing Functions with Discontinuous Derivatives

Pierre Joyot (1) , Jean Trunzler (1) , Francisco Chinesta (2)

1 ESTIA INSTITUTE OF TECHNOLOGY
2 LMSP - Laboratoire de Mécanique des Systèmes et des Procédés

In this paper we propose a new approximation technique within the context of meshless methods able to reproduce functions with discontinuous derivatives. This approach involves some concepts of the reproducing kernel particle method (RKPM), which have been extended in order to reproduce functions with discon-tinuous derivatives. This strategy will be referred as Enriched Reproducing Kernel Particle Approximation (E-RKPA). The accuracy of the proposed technique will be compared with standard RKP approximations (which only reproduces polynomials).

Domaines: Mécanique des structures [physics.class-ph]

Pierre Joyot, Jean Trunzler, Francisco Chinesta. Enriched Reproducing Kernel Approximation: Reproducing Functions with Discontinuous Derivatives. M. Griebel; M. Schweitzer. Meshfree Methods for Partial Differential Equations II. Lecture Notes in Computational Science and Engineering, 43, 2005, ⟨10.1007/3-540-27099-X_6⟩. ⟨hal-01633391⟩