Akifumi Okabe

Estimating Each element of Joint stiffness matrix using Neural network : Applied to a Y-shape Joint structure

A rigidity of a part connected by thin-walled box section beams is one of the key factors dominating the basic characteristics of an automobile body structure. In the beginning stage of the body design, it is important to quantitatively evaluate the rigidity of jointed part. Thus it is wished to develop the tool that can quickly and accurately obtain the joint stiffness value for using in the beginning stage of the design. In this paper, the new method that can quickly and accurately estimate the joint stiffness values from the design parameters was proposed. And the structural analysis tool using this method was made. Main flow of this method is as follows. The relation between the design parameters and the joint stiffness values is constructed by neural network. Once the relation was constructed, the joint stiffness values can be obtained by inputting the design parameters to the trained neural network.

Evaluation of Stress Intensity Factor of Spot Welded Joint Using Meshless Method

It has been required strongly to evaluate fatigue strength of spot welded joint accurately in the stage of designing automobile body structure. There is a evaluation method of fatigue strength based on stress intensity factors K in linear fracture mechanics. We applied Element Free Galerkin Method (EFGM) developed by T. Belytschko et al. to calculating stress intensity factors K of spot welded double cup specimen (is called DC for short) under multiaxial loads, and investigated the accuracy of the solutions. This paper shows that K obtained by using EFGM are appropriate results.