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This work aims at developing a genetic algorithm (GA) to pursue the optimization of hybrid laminated composite structures. Fiber orientation (predefined ply angles), material (glass-epoxy or carbon-epoxy layer) and total number of plies are considered as design variables. The GA is chosen as an optimization tool because of its ability to deal with...
Citations
... A detailed review of the optimization of various composite structures has been reported in reference [3]. Several studies have looked into the optimization of the plates modeled with composites for different objectives by means of a genetic algorithm (GA) and numerical study [4][5][6][7][8][9][10][11][12]. A considerable amount of research has been performed to obtain the optimum designs of the pressure hulls constructed with composites by means of optimization tools combined with numerical analysis subjected to instability constraint or both instability and material failure constraints. ...
This paper describes a design optimization study of the egg-shaped composite submersible pressure hull employing optimization and finite element analysis (FEA) tools as a first attempt to provide an optimized design of the composite egg-shaped pressure hull for manufacturing or further investigations. A total of 15 optimal designs for the composite egg-shaped pressure hull under hydrostatic pressure are obtained in terms of fibers’ angles and the number of layers for 5 lay-up arrangements and 3 unidirectional (UD) composite materials. The optimization process is performed utilizing a genetic algorithm and FEA in ANSYS. The minimization of the buoyancy factor (B.F) is selected as the objective for the optimization under constraints on both material failure and buckling strength. Nonlinear buckling analysis is conducted for one optimal design considering both geometric nonlinearity and imperfections. A sensitivity study is also conducted to further investigate the influence of the design variables on the optimal design of the egg-shaped pressure hull.
... According to [10], a composite laminate is generally designed depending on the following criteria: the thickness, number and orientations of the layers. For optimal results, optimization techniques including the genetic algorithm (GA) have been implemented. ...
... The buckling and failure load factors values for 48 ply laminate and 64 ply laminate are presented in Table 2. The obtained results were compared with the results gained from [6][7][8][9][10][11][12][13][14][15][16][17]. ...
An isotropic mechanical structure cannot withstand shocks, accidents, and mechanical loading. In this perspective, composite structures have been introduced to improve the performance of mechanical structures. We are interested in the study of laminates with the aim to find an optimal structure resistant to vibrations and buckling. To remedy the problem of vibrations and buckling, we use artificial intelligence methods to optimize the design of composite
structures. As it is a typical method of artificial intelligence adapted to this studied problem, we use genetic algorithms based on a new genetic operator. In the present article, an optimization procedure based on the new genetic operator called genetic immigration operator is developed to determine the maximum buckling load and fundamental frequency of the laminated plate with plies oriented at -
45◦/45◦ ,0◦, and 90◦. The aim of this paper is the use of two different methods for their effectiveness. These optimization works consist of first maximizing the buckling load factor with UGA (Uniform Genetic Algorithm) and a new evolutionary search strategies called Immigration Genetic: SIG (Standard Immigration Genetic Algorithm) and AIG (Improved Genetic Immigration Algorithm) and second of
solving a multi-objective problem with minimizing the cost and weight of the hybrid laminate made of the fibers of two composite materials. The resolution of this problem by the proposed genetic immigration approach is reinforced by the optimization of the CPU computation time which is due to the exploitation of the parallel architecture based on the multi-processor parallel computation.
... A detailed review of the optimization of different composite structures has been published in Ref [3]. Several studies have focused on the optimization of composite plates utilizing a GA and other optimization methods linked to numerical techniques [4][5][6][7][8][9][10][11][12][13]. A lot of research has also been done on the optimization of composite submersible pressure hulls employing a GA and other optimization methods, finite element analysis (FEA) and analytical analysis. ...
This paper presents the design optimization of composite submersible cylindrical pressure hull subjected to 3 MPa hydrostatic pressure. The design optimization study is conducted for cross-ply layups [0s/90t/0u], [0s/90t/0u]s, [0s/90t]s and [90s/0t]s considering three uni-directional composites, i.e. Carbon/Epoxy, Glass/Epoxy, and Boron/Epoxy. The optimization study is performed by coupling a Multi-Objective Genetic Algorithm (MOGA) and Analytical Analysis. Minimizing the buoyancy factor and maximizing the buckling load factor are considered as the objectives of the optimization study. The objectives of the optimization are achieved under constraints on the Tsai-Wu, Tsai-Hill and Maximum stress composite failure criteria and on buckling load factor. To verify the optimization approach, optimization of one particular layup configuration is also conducted in ANSYS with the same objectives and constraints.
... According to [10], a composite laminate is generally designed depending on the following criteria: the thickness, number and orientations of the layers. For optimal results, optimization techniques including the genetic algorithm (GA) have been implemented. ...
... The buckling and failure load factors values for 48 ply laminate and 64 ply laminate are presented in Table 2. The obtained results were compared with the results gained from [6][7][8][9][10][11][12][13][14][15][16][17]. ...
An isotropic mechanical structure cannot withstand shocks,
accidents, and mechanical loading. In this perspective,
composite structures have been introduced to improve the
performance of mechanical structures. We are interested in
the study of laminates with the aim to find an optimal
structure resistant to vibrations and buckling. To remedy the
problem of vibrations and buckling, we use artificial
intelligence methods to optimize the design of composite
structures. As it is a typical method of artificial intelligence
adapted to this studied problem, we use genetic algorithms
based on a new genetic operator. In the present article, an
optimization procedure based on the new genetic operator
called genetic immigration operator is developed to
determine the maximum buckling load and fundamental
frequency of the laminated plate with plies oriented at -
45◦/45◦ ,0◦, and 90◦. The aim of this paper is the use of two
different methods for their effectiveness. These optimization
works consist of first maximizing the buckling load factor
with UGA (Uniform Genetic Algorithm) and a new
evolutionary search strategies called Immigration Genetic:
SIG (Standard Immigration Genetic Algorithm) and AIG
(Improved Genetic Immigration Algorithm) and second of
solving a multi-objective problem with minimizing the cost
and weight of the hybrid laminate made of the fibers of two
composite materials. The resolution of this problem by the
proposed genetic immigration approach is reinforced by the
optimization of the CPU computation time which is due to
the exploitation of the parallel architecture based on the
multi-processor parallel computation.
... The investigation of this paper involves the concurrent multi-scale optimization of laminate hybrid composite plates and shells, which is promising to contribute to developing optimization methods for general hybrid composite structures. Some researchers [6,[12][13][14][15][16][17] have studied the optimization of hybrid composite structures. Grosset et al. [6] investigated the multi-material multi-objective composite optimization using the genetic algorithm, and draw a conclusion that it makes sense to put the stiffer graphite in the external layer and the softer glass in the inner layer for interply hybrid composites. ...
... Some researchers [7,[43][44][45] have studied the optimization of hybrid composite materials. For example, Grosset et al. [7] investigated multimaterial composite optimization with a multiobjective using a genetic algorithm, and they found the significant conclusion that it can be advantageous to put the stiff graphite in the outer layer and the softer glass in the inner layer. ...
... Akmar et al. [45] used ant colony optimization to optimize the stacking sequence of hybrid composite laminates: the aim being to minimize the cost and weight under the constraints of the fundamental frequency and buckling load. Lopez et al. [44] used a genetic algorithm to optimize hybrid composite laminated structures by regarding the fiber orientation, the material, and the number of plies as the design variables. Kalantari et al. [43] introduced a hybrid multiobjective evolutionary algorithm for optimizing hybrid composites under the constraint of flexural strength. ...
Hybrid composite materials, which contain more than one type of reinforcing fiber, have been gaining ever-increasing popularity. They can keep superior mechanical properties while greatly reducing the material cost. To fully explore the load-carrying potential, it is crucial to develop a series of corresponding optimization methods for hybrid composites design. In this paper, the concurrent patch optimization of hybrid composite plates is investigated, where fiber orientation, the stacking sequence, and material topology are optimized simultaneously. Discrete material optimization (DMO) is performed to optimize the hybrid composite plates, with the buckling load as the objective and the material cost as the constraint. Because the effectiveness of DMO has been demonstrated to perform the discrete variable optimization of composite structures. Furthermore, an innovative DMO framework based on proper orthogonal decomposition is established to reduce the computational cost, with the aim being to improve the optimization efficiency by reducing the order of the corresponding finite element model, and thus the time needed for the finite element analysis. The effectiveness of the proposed method is demonstrated by means of an illustrative example wherein both the material cost and the time needed for the buckling analysis are reduced dramatically.
... Mathematically, the layer orientations should minimize the strain energy developed in the composite material under the application of loads. [19][20][21][22] This property can be used in the set-up of the problem by defining an objective function that minimizes the total elastic strain energy U as ...
A computational procedure for the calculation of the material parameters involved in the structural design of multi-material components is presented. The developed scheme can be used in the design process for the full or partial replacement of a metallic part with a metal/fiber–reinforced composite bi-material, aiming at weight savings. Finite element simulations are incorporated into an algorithm that rapidly reduces the design space until a good set of design variables has been reached. The process is controlled by two objective functions (mass and strain energy minimization) and is subjected to several constraints according to the component’s design requirements. Three examples have been adopted to demonstrate the effectiveness of the approach. The results show that the upper limit for weight reduction is constrained by the yield strength of the metal component and therefore its corresponding thickness. Based on the design configuration, weight savings up to 25% could be reached.
... Em engenharia, cada vez mais busca-se por soluções ótimas para os problemas enfrentados. Estes podem ser das mais variadas naturezas, por exemplo: minimização da massa de uma estrutura [60][61][62]; maximização do aproveitamento espacial em fazendas eólicas [63,64]; maximização da autonomia de um veículo qualquer [65,66] etc. Desta forma, almeja-se um produto final que não tão somente atenda às restrições de um problema/projeto mas que o faça de maneira ótima, aliando as melhores características possíveis a sí. ...
... Metaheuristics (MHs), which do not rely on the function derivative and are suitable for discrete optimisation problems, have increasingly been used in recent years for the optimisation of laminated composite structures. Some well-established MH algorithms have been efficiently applied, including the genetic algorithm (GA) [5,7,9,13,14,17,18,[22][23][24][25][26][27][28][29][30], differential evolution [11,[31][32][33], particle swarm optimisation (PSO) [34][35][36][37][38][39][40], and the artificial bee colony algorithm [10,41]. In the present study, a novel MH algorithm, termed social group optimisation (SGO) [42], is employed for the first time for optimisation of laminated composite stiffened shell panels. ...
A review of the literature reveals a dearth of research on the maximisation of natural frequencies of laminated composite stiffened panels. The present study combines an analytical solution based on the smeared stiffener method with a novel social group optimisation (SGO) algorithm to develop a procedure for the solution of such an optimisation problem. For this purpose, cross-ply laminated circular-cylindrical panels with a simply supported condition, stiffened by stringers and rings, are considered. The quantities and sizes of the stiffener are optimised to maximise the fundamental frequency of the panels under practical constraints. Example optimisations of various panel geometries are performed. The optimisation results show that the fundamental frequency can be increased significantly by using tailored rings and that for the considered numerical examples, stringers do not make any beneficial contribution to the maximisation of the fundamental frequency. It is also demonstrated that the SGO algorithm is an efficient tool for this kind of mixed-integer constrained optimisation problem.
... The selection of the BSA was mainly based on two aspects: (a) it was shown to outperform several algorithms in unconstrained optimization (Civicioglu, 2013) and presented promising results for the optimization of transmission line towers structures, studied by Souza et al. (2016); (b) it has only one parameter to be set, different from other metaheuristic algorithms. Indeed, one of the main drawbacks of metaheuristic algorithms is that their efficiency depends on the tuning of many parameters usually by trial and error (Lopez et al. 2009a, Lopez et al. 2009b). ...
This paper presents a Backtracking Search Optimization algorithm (BSA) to simultaneously optimize the size, shape and topology of truss structures. It focuses on the optimization of these three aspects since it is well known that the most effective scheme of truss optimization is achieved when they are simultaneously considered. The minimization of structural weight is the objective function, imposing displacement, stress, local buckling and/or kinematic stability constraints. The effectiveness of the BSA at solving this type of optimization problem is demonstrated by solving a series of benchmark problems comparing not only the best designs found, but also the statistics of 100 independent runs of the algorithm. The numerical analysis showed that the BSA provided promising results for the analyzed problems. Moreover, in several cases, it was also able to improve the statistics of the independent runs such as the mean and coefficient of variation values. © 2016 Brazilian Association of Computational Mechanics. All rights reserved.
