Meshless Local Petrov Galerkin (MLPG) methods are pure meshless techniques for solving Partial Differential Equations. They have been successfully used for solving many real-life problems. Their efficiency is downgraded by the requirement of performing numerical multi-dimensional integration of tricky, non-polynomial factors. Recently, Direct MLPG (DMLPG) methods have been proposed. DMLPG techniques require lower computational costs with respect to their MLPG counterparts. The DMLPG accuracy has been initially ana- lyzed in few papers, but its performance is quite unexplored. In this paper, we perform numerical comparisons between MLPG and DMLPG accuracy and efficiency in solving anisotropic diffusion problems. In particular, we set different boundary conditions, in order to check if and when MLPG and/or DMLPG suffer locking effects.

MESHLESS TECHNIQUES FOR ANISOTROPIC DIFFUSION

SARTORETTO, Flavio
2014-01-01

Abstract

Meshless Local Petrov Galerkin (MLPG) methods are pure meshless techniques for solving Partial Differential Equations. They have been successfully used for solving many real-life problems. Their efficiency is downgraded by the requirement of performing numerical multi-dimensional integration of tricky, non-polynomial factors. Recently, Direct MLPG (DMLPG) methods have been proposed. DMLPG techniques require lower computational costs with respect to their MLPG counterparts. The DMLPG accuracy has been initially ana- lyzed in few papers, but its performance is quite unexplored. In this paper, we perform numerical comparisons between MLPG and DMLPG accuracy and efficiency in solving anisotropic diffusion problems. In particular, we set different boundary conditions, in order to check if and when MLPG and/or DMLPG suffer locking effects.
File in questo prodotto:
File Dimensione Formato  
MazPinSar14.pdf

non disponibili

Tipologia: Documento in Post-print
Licenza: Accesso chiuso-personale
Dimensione 2.53 MB
Formato Adobe PDF
2.53 MB Adobe PDF   Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/40039
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 7
social impact