Optimization of laminated composite plates and shells using genetic algorithms, neural networks and finite elements

Abstract

Structural optimization using computational tools has become a major research field in recent years. Methods commonly used in structural analysis and optimization may demand considerable computational cost, depending on the problem complexity. Therefore, many techniques have been evaluated in order to diminish such impact. Among these various techniques, Artificial Neural Networks (ANN) may be considered as one of the main alternatives, when combined with classic analysis and optimization methods, to reduce the computational effort without affecting the final solution quality. Use of laminated composite structures has been continuously growing in the last decades due to the excellent mechanical properties and low weight characterizing these materials. Taken into account the increasing scientific effort in the different topics of this area, the aim of the present work is the formulation and implementation of a computational code to optimize manufactured complex laminated structures with a relatively low computational cost by combining the Finite Element Method (FEM) for structural analysis, Genetic Algorithms (GA) for structural optimization and ANN to approximate the finite element solutions. The modules for linear and geometrically non-linear static finite element analysis and for optimize laminated composite plates and shells, using GA, were previously implemented. Here, the finite element module is extended to analyze dynamic responses to solve optimization problems based in frequencies and modal criteria, and a perceptron ANN module is added to approximate finite element analyses. Several examples are presented to show the effectiveness of ANN to approximate solutions obtained using the FEM and to reduce significatively the computational cost.

Review of modern optimization methods for bearing systems of buildings аnd structures

“…Эти методы содержат элемент случайности и позволяют решать широкий класс современных задач оптимизации строительных конструкций. Известен ряд подходов к оптимизации, таких как методы роя частиц [17][18][19], отжига [20,21], светлячков [22,23], муравьиной колонии [24,25], теплопередачи [26], взрыва [27], поиска гармонии [28], генетические алгоритмы [29][30][31], нейронные сети [32][33][34] и т.п. Ряд из них имеет существенные ограничения для применения к задачам оптимизации строительных конструкций, поэтому в опубликованных научных работах рассматриваются лишь элементарные примеры.…”

“…Первоначально рассмотрим работы по оптимизации конструкций различных типов. Оптимизируются композитные сталебетонные [33] и деревянно-бетонные конструкции [15], тонкостенные взрывозащитные панели [35], многослойные пластинчатые системы из двух материалов [ [40].…”

Shear Stress Prediction Using FEA-ANN Hybrid Modeling Of Eicher 11.10 Chassis Frame

“…Benardos et al (2007) have been adopted the multitude of different approaches in order to deal with this problem which has investigated all aspects of the ANN modelling procedure, from training data collection and pre/post-processing to elaborate training schemes and algorithms. Cardozo et al (2011) presented the formulation and implementation of a computational code to optimize manufactured complex laminated structures with a relatively low computational cost by combining the Finite Element Method (FEM) for structural analysis, Genetic Algorithms (GA) for structural optimization and ANN to approximate the finite element solutions.…”

Risk-Based Optimization of RC-Beams Under Different Local Damage Scenarios

“…These methods contain an element of randomness and allow solving a wide class of modern problems for the optimization of load-bearing structures. A number of optimization approaches are known, such as particle swarm methods [1][2][3], annealing [4,5], fireflies [6,7], ant colony [8,9], heat transfer [10], explosion [11], harmony search [12], genetic algorithms [13][14][15], neural networks [16][17][18], etc. A number of them have significant limitations for application to the problems of optimization of load-bearing structures, taking into account the level of their safety; in many published scientific works, only elementary examples are considered.…”