Optimization Of Composite Cylindrical Shells Research Articles

Optimal design of composite cylindrical shells subject to compression buckling strength

PurposeThe objective of the present work is to present the design optimization of composite cylindrical shell subjected to an axial compressive load and lateral pressure.Design/methodology/approachA novel optimization method is developed to predict the optimal fiber orientation in composite cylindrical shell. The optimization is carried out by coupling analytical and finite element (FE) results with a genetic algorithm (GA)-based optimization scheme developed in MATLAB. Linear eigenvalue were performed to evaluate the buckling behaviour of composite cylinders. In analytical part, besides the buckling analysis, Tsai-Wu failure criteria are employed to analyse the failure of the composite structure.FindingsThe optimal result obtained through this study is compared with traditionally used laminates with 0, 90, ±45 orientation. The results suggest that the application of this novel optimization algorithm leads to an increase of 94% in buckling strength.Originality/valueThe proposed optimal fiber orientation can provide a practical and efficient way for the designers to evaluate the buckling pressure of the composite shells in the design stage.

Robust optimization of composite cylindrical shell by a trigonometric mixed response surface method

AbstractThe response surface method (RSM) as a popular fitting method has been applied to numerous engineering issues. However, the existing RSM models cannot satisfy the analysis of complex nonconvex structure problems, especially in composite cylindrical shells. Thus a trigonometric mixed response surface method (TMRSM) is suggested to improve the accuracy and the fitting performance combing optimal Latin hypercube design (LHD), the moving least square method and the trigonometric functions. An improved robust design optimization (RDO) process is performed based on the weighted norm method and reliable constraints using the above TMRSM model to obtain more robust optimal design results. Three example functions and a composite cylindrical pressure shell are given to verify the effectiveness of the TMRSM model. This pressure shell design can check the robustness of the improved RDO process.

Multi-objective optimization of laminated composite shells for minimum mass/cost and maximum buckling pressure with failure criteria under external hydrostatic pressure

In the present study, Multi-objective optimization of composite cylindrical shell under external hydrostatic pressure was investigated. Parameters of mass, cost and buckling pressure as fitness functions and failure criteria as optimization criterion were considered. The objective function of buckling has been used by performing the analytical energy equations and Tsai-Wu and Hashin failure criteria have been considered. Multi-objective optimization was performed by improving the evolutionary algorithm of NSGA-II. Also the kind of material, quantity of layers and fiber orientations have been considered as design variables. After optimizing, Pareto front and corresponding points to Pareto front are presented. Trade of points which have optimized mass and cost were selected by determining the specified pressure as design criteria. Finally, an optimized model of composite cylindrical shell with the optimum pattern of fiber orientations having appropriate cost and mass is presented which can tolerate the maximum external hydrostatic pressure.

Multiobjective optimization of composite cylindrical shells for strength and frequency using genetic algorithm and neural networks

Abstract In this paper, the optimal fiber orientations relative to the principle axis of composite cylindrical shell composed of four and six layers were determined so that the natural frequency and strength of the shell are optimized. For this purpose, first, the free vibration analysis of the shell was carried out based on 3D elasticity. Then, for calculation of the strength objective function, the inverse form of Tsai-Hill yield criteria was used and the functions of strength and frequency were developed in terms of fiber orientation. Once the correctness of the above solutions was ensured, the objective functions were modeled with artificial neural network (ANN). The model made was then introduced into genetic algorithm (GA) and the maximum fitness function and optimal staking sequence of the layers with respect to the fibers angles were obtained. Optimal solutions obtained by combination of ANN and GA are compared to the solutions obtained by analytical solution and GA; eventually, the tables and diagrams are presented and different fiber orientations as optimization solutions are presented as the final results of the composite shell analysis.