Structural Shape Optimization By Coupled FE–MM and Swarm Intelligence-Based Algorithm

Abstract

This paper sets propelling a more current strategy for mechanical shape optimization by joining a coupled finite element (FE) method–meshfree method (MM) with swarm intelligence (SI)-based stochastic ‘zero-order’ search procedure. The arranged gathering massively fits as a structural shape optimization since MM is utilized here for structural examination shape analysis and to avoid a remeshing in view of fundamental mesh modification if there should be an occurrence of tremendous shape varieties, discontinuous secondary field variables across element boundaries, etc. while using FE. This is same as FE strategy that helps in beating the weaknesses of MM like high computational exertion and simplicity of forcing essential boundary conditions (EBCs). Populace-based stochastic optimization strategy, e.g., PSO abrogates computational burden, multifaceted nature and blunders aligned with structure affectability assessment Right now, plan limit portrayal Akima spline introduction has been considered on account of its improved persistence and smoothness over cubic spline. The convenience of present strategy, results got with current technique is contrasted and different strategies for past writing. The adequacy, legitimacy and execution of the present procedure are built up through mathematical instances of cantilever beam and fixed–fixed bar geometry for shape optimization with conduct limitations on displacement. For both these issues, h-refinement for opening issue geometry has been examined and furthermore impact of various design variables fit as a shape optimization has likewise been researched.