Design optimization of composite laminated structures using genetic algorithms and finite element analysis

Almeida, Felipe Schaedler de; Awruch, Armando Miguel

doi:10.1016/j.compstruct.2008.05.004

Cited by 155 publications

(75 citation statements)

References 5 publications

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“…Moreover, in commercial designs, fiber orientation angles and the amount and thickness of layers are discrete variables, a fact which confirms the suitability of GAs for these kinds of problems. Many studies [32,33] are subsequently carried out by using the method of design optimization for composite structures.…”

Section: Genetic Algorithm For Composite Shellsmentioning

confidence: 99%

A Response Surface Modelling Approach for Resonance Driven Reliability Based Optimization of Composite Shells

Dey

Mukhopadhyay²,

Khodaparast³

et al. 2016

Period. Polytech. Civil Eng.

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IntroductionThe development of reliable composite structures in production process is always subjected to large variability due to manufacturing imperfection and uncertain operational factors. In practice, an additional factor of safety is assumed by designers due to difficulty in assessing reliability to avoid resonance in conjunction to uncertainties of stochastic natural frequencies. This existing practice of designer results in either an ultraconservative (overestimation of material cost) or an unsafe design. Hence, it is needed to overcome this current limitation wherein the design of composites are restricted to a deterministic regime despite of rapidly increasing demands of technological, economical and safety needs. Many literatures are available dealing with uncertainty quantification of composite structures [1][2][3]. Moreover, the reliability in conjunction to cost component involved in weight optimization of such composite structures are always a challenge for the designers. The common cause of employing composite structures in many applications (such as aircraft, civil structures) is weight sensitiveness wherein the objective of design optimization [4] is to lower the weight for achieving the better performance. For example, in structural design problem, the need of computation of the natural frequency is required to avoid the resonance which can vary with the uncertain geometric and material properties of the structure. In such engineering applications with complex systems, the consequences of uncertain system behaviour become severe in terms of cost and effort. The assessment of probability of failure and the need to improve the reliability of the systems have become essentially important for structural safety. Such necessities in turn raise the need for reliability based design optimization (RBDO) analysis [5]. The uncertain variation of system parameters can be mathematically coupled with optimization tools such as genetic algorithm (GA) to achieve safety as well as cost-effectiveness.Many studies are carried out by applying RBDO methods for optimal design of shallow composite structures. The random loading and material properties including manufacturing uncertainties are considered for example in [6][7][8][9][10][11]. Miki [12] and Fukunaga and Chou [13] proposed a graphical optimization method using lamination parameters for stiffened compos-

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Section: Genetic Algorithm For Composite Shellsmentioning

confidence: 99%

A Response Surface Modelling Approach for Resonance Driven Reliability Based Optimization of Composite Shells

Dey

Mukhopadhyay²,

Khodaparast³

et al. 2016

Period. Polytech. Civil Eng.

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“…When laminated composites are designed, design variables for a specific kind of material are fibers directions, number of layers, and thickness of each layer. Because of restrictions on the manufacture and use of these composite plates, choosing of fibers direction is usually limited to a set of definite discrete values and also layers' thickness is specific [4]. Moreover, among the various factors, stacking sequence of layers is one of the most important parameters that can increase structures' resistance to the damage caused by different loads.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity Analysis of a CPAM Inverse Algorithm for Composite Laminates Characterization

Masoumi

Ghasemi-Ghalebahman

2017

Shock and Vibration

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Using experimental data and numerical simulations, a new combined technique is presented for characterization of thin and thick orthotropic composite laminates. Four or five elastic constants, as well as ply orientation angles, are considered as the unknown parameters. The material characterization is first examined for isotropic plates under different boundary conditions to evaluate the method's accuracy. The proposed algorithm, so-called CPAM (Combined Programs of ABAQUS and MATLAB), utilizes an optimization procedure and makes simultaneous use of vibration test data together with their corresponding numerical solutions. The numerical solutions are based on a commercial finite element package for efficiently identifying the material properties. An inverse method based on particle swarm optimization algorithm is further provided using MATLAB software. The error function to be minimized is the sum of squared differences between experimental and simulated data of eigenfrequencies. To evaluate the robustness of the model's results in the presence of uncertainty and unwanted noises, a sensitivity analysis that employs Gaussian disorder model is directly applied to the measured frequencies. The results with high accuracy confirm the validity and capability of the present method in simultaneous determination of mechanical constants and fiber orientation angles of composite laminates as compared to prior methods.

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“…We postulate that we can use nature's design tools to tune and optimize for specific mechanical properties such as toughness and strength. Past efforts have sought to optimize composite materials through ply tailoring, number of plies, and laminate sequence, specifically using genetic algorithms to apply to the design optimization of composite laminate designs [13][14][15][16]. In addition, researchers have studied how to optimize composite topology with three materials for thermal conductivity properties [17].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Composite Fracture Properties: Method, Validation, and Applications

Dimas

Qin

et al. 2016

Journal of Applied Mechanics

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A paradigm in nature is to architect composites with excellent material properties compared to its constituents, which themselves often have contrasting mechanical behavior. Most engineering materials sacrifice strength for toughness, whereas natural materials do not face this tradeoff. However, biology's designs, adapted for organism survival, may have features not needed for some engineering applications. Here, we postulate that mimicking nature's elegant use of multimaterial phases can lead to better optimization of engineered materials. We employ an optimization algorithm to explore and design composites using soft and stiff building blocks to study the underlying mechanisms of nature's tough materials. For different applications, optimization parameters may vary. Validation of the algorithm is carried out using a test suite of cases without cracks to optimize for stiffness and compliance individually. A test case with a crack is also performed to optimize for toughness. The validation shows excellent agreement between geometries obtained from the optimization algorithm and the brute force method. This study uses different objective functions to optimize toughness, stiffness and toughness, and compliance and toughness. The algorithm presented here can provide researchers a way to tune material properties for a vast number of engineering problems by adjusting the distribution of soft and stiff materials.

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Design optimization of composite laminated structures using genetic algorithms and finite element analysis

Cited by 155 publications

References 5 publications

A Response Surface Modelling Approach for Resonance Driven Reliability Based Optimization of Composite Shells

A Response Surface Modelling Approach for Resonance Driven Reliability Based Optimization of Composite Shells

Sensitivity Analysis of a CPAM Inverse Algorithm for Composite Laminates Characterization

Optimization of Composite Fracture Properties: Method, Validation, and Applications

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