Shape optimization of clinching tools using the response surface methodology with Moving Least-Square approximation

2009 ◽  
Vol 209 (1) ◽  
pp. 289-296 ◽  
Author(s):  
M. Oudjene ◽  
L. Ben-Ayed ◽  
A. Delamézière ◽  
J.-L. Batoz
Author(s):  
B. Nandulal ◽  
B. N. Rao ◽  
C. Lakshmana Rao

This paper presents an enriched meshless method based on an improved moving least-square approximation (IMLS) method for fracture analysis of cracks in homogeneous, isotropic, linear-elastic, two-dimensional bimaterial solids, subject to mixed-mode loading conditions. The method involves an element-free Galerkin formulation in conjunction with IMLS and a new enriched basis functions to capture the singularity field in linear-elastic bi-material fracture mechanics. In the IMLS method, the orthogonal function system with a weight function is used as the basis function. The IMLS has higher computational efficiency and precision than the MLS, and will not lead to an ill-conditioned system of equations. The proposed enriched basis function can be viewed as a generalized enriched basis function, which degenerates to a linear-elastic basis function when the bimaterial constant is zero. Numerical examples are presented to illustrate the computational efficiency and accuracy of the proposed method.


Author(s):  
R. J. Yang ◽  
N. Wang ◽  
C. H. Tho ◽  
J. P. Bobineau ◽  
B. P. Wang

Abstract Response surface methods or metamodels are commonly used to approximate large engineering systems. This paper presents a new metric for evaluating a response surface method or a metamodeling technique. Five response surface methods are studied: Stepwise Regression, Moving Least Square, Kriging, Multiquadratic, and Adaptive and Interactive Modeling System. A real world frontal impact design problem is used as an example, which is a complex, highly nonlinear, transient, dynamic, large deformation finite element model. The optimal Latin Hypercube Sampling method is used to distribute the sampling points uniformly over the entire design space. The Root Mean Square Error is used as the error indicator to study the accuracy and convergence rate of the metamodels for this vehicle impact analysis. A hybrid approach/strategy for selecting the best metamodels of impact responses is proposed.


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