Nonlinear multi-variable optimization of layered composites with nontraditional interfaces

Abstract

This article deals with a nonlinear multi-variable optimization problem to minimize the critical thermal stress induced in a layered composite plate. The numerical model is solved by using the finite element analysis while the optimization is done by applying the particle swarm optimization technique. The plate contains nontraditional interfaces between the layers while their profiles follow a power law. Different parameters are optimized either individually or in combination by applying single and multi-variable optimizations so as to minimize the critical induced thermal stress in the structure. These optimized parameters include the interface profile parameter, the height of the nontraditional interface on the right surface relative to the mid-surface, and the thicknesses of the layers of the plate. It is found that the critical stress can be minimized greatly when tailoring the geometrical and interface parameters by using their optimum values.

Thermoelastic stress mitigation and weight reduction of functionally graded multilayer nonuniform thickness disc

“…It was considered by many researchers in various fields, such as vehicular applications, 34,35 civil engineering, 31 medical sector, 32 and course scheduling process. 33 In the area of mechanical structures, Shabana et al, [36][37][38] for instance, used it in order to enhance the performance of multilayer plates and cylinders. For discs, PSO was used to minimize their weights.…”

Prediction of influences of size and locations of delamination on dynamic characteristics of laminated composite plate using particle swarm optimization and artificial neural network

“…Shabana and Elsawaf [ 9 ] studied the thermal behavior of the composite structure through the non‐linear multi variable optimization approach and the results shows the effectiveness of particle swarm optimization (PSO) over other approaches, and the developed model provides a comprehensive knowledge of the subject. Esmaeeli et al [ 10 ] performed the artificial bee colony algorithm based multi‐objective optimization study in order to determine the feasible ply orientation as well as the material constants of the composite laminates.…”

Reliability-based design optimization of composite stiffened panels in post-buckling regime

“…GAs are based on the Darwin's "natural selection" principle (Goldberg (1989), Holland (1992)) and are translated to mathematical terminology through the creation of a population of individuals that evolve and improve thanks to the operators of crossover, mutation and selection. Some other population-based algorithms such as the particle swarm algorithm have shown effectiveness in the optimization of composite materials with high nonlinearities (Xu et al (2012), Xu and You (2013), Shabana and Elsawaf (2015)). …”