The application of artificial intelligence in the optimal design of mechanical systems

20th Innovative Manufacturing Engineering and Energy Conference

机械制造;能源学

Poteralski, A.^1 ; Szczepanik, M.^1

Institute of Computational and Mechanical Engineering, Faculty of Mechanical Engineering, Silesian University of Technology, Poland^1

关键词: Artificial Immune System;    Composites structures;    Computational technique;    Mechanical optimization;    Method of fundamental solutions;    Optimization problems;    Particle swarm optimizers;    Soft computing methods;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/161/1/012040/pdf
DOI  :  10.1088/1757-899X/161/1/012040

来源: IOP

【 摘 要 】

The paper is devoted to new computational techniques in mechanical optimization where one tries to study, model, analyze and optimize very complex phenomena, for which more precise scientific tools of the past were incapable of giving low cost and complete solution. Soft computing methods differ from conventional (hard) computing in that, unlike hard computing, they are tolerant of imprecision, uncertainty, partial truth and approximation. The paper deals with an application of the bio-inspired methods, like the evolutionary algorithms (EA), the artificial immune systems (AIS) and the particle swarm optimizers (PSO) to optimization problems. Structures considered in this work are analyzed by the finite element method (FEM), the boundary element method (BEM) and by the method of fundamental solutions (MFS). The bio-inspired methods are applied to optimize shape, topology and material properties of 2D, 3D and coupled 2D/3D structures, to optimize the termomechanical structures, to optimize parameters of composites structures modeled by the FEM, to optimize the elastic vibrating systems to identify the material constants for piezoelectric materials modeled by the BEM and to identify parameters in acoustics problem modeled by the MFS.