Nature inspired optimization techniques for the design optimization of laminated composite structures using failure criteria

The design optimization of laminated composites using naturally inspired optimization techniques such as vector evaluated particle swarm optimization (VEPSO) and genetic algorithms (GA) are used in this paper. The design optimization of minimum weight of the laminated composite is evaluated using different failure criteria. The failure criteria considered are maximum stress (MS), Tsai-Wu (TW) and failure mechanism based (FMB) failure criteria. Minimum weight of the laminates are obtained for different failure criteria using VEPSO and GA for different combinations of loading. From the study it is evident that VEPSO and GA predict almost the same minimum weight of the laminate for the given loading. Comparison of minimum weight of the laminates by different failure criteria differ for some loading combinations. The comparison shows that FMBFC provide better results for all combinations of loading.

[1]  Andries Petrus Engelbrecht,et al.  Fundamentals of Computational Swarm Intelligence , 2005 .

[2]  Raphael T. Haftka,et al.  Design and optimization of laminated composite materials , 1999 .

[3]  Carlos A. Coello Coello,et al.  A Study of the Parallelization of a Coevolutionary Multi-objective Evolutionary Algorithm , 2004, MICAI.

[4]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[5]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[6]  Marco Laumanns,et al.  A Tutorial on Evolutionary Multiobjective Optimization , 2004, Metaheuristics for Multiobjective Optimisation.

[7]  Ranjan Ganguli,et al.  Target vector optimization of composite box beam using real-coded genetic algorithm: a decomposition approach , 2006 .

[8]  Ranjan Ganguli,et al.  Strength design of composite beam using gradient and particle swarm optimization , 2007 .

[9]  R. Christensen,et al.  Mechanics of composite materials , 1979 .

[10]  S. Gopalakrishnan,et al.  Towards a Rational Failure Criterion for Unidirectional Composite Laminae , 2005 .

[11]  A. V. Krishna Murty,et al.  A failure mechanism-based approach for design of composite laminates , 1999 .

[12]  Ranjan Ganguli,et al.  On the effect of progressive damage on composite helicopter rotor system behavior , 2007 .

[13]  S. Vel,et al.  MULTI-OBJECTIVE OPTIMIZATION OF FIBER REINFORCED COMPOSITE LAMINATES FOR STRENGTH, STIFFNESS AND MINIMAL MASS , 2006 .

[14]  G. Narayana Naik.  Development and Design Optimization of Laminated Composite Structures: Using Failure Mechanism Based Failure Criterion , 2012 .

[15]  David E. Goldberg,et al.  ENGINEERING OPTIMIZATION VIA GENETIC ALGORITHM, IN WILL , 1986 .

[16]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[17]  A. V. Krishna Murty,et al.  A failure mechanism based failure theory for laminated composites including the effect of shear stress , 2005 .

[18]  Xiaohua Liu,et al.  Solving multi objective optimization problems using particle swarm optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[19]  Stephen W. Tsai,et al.  A General Theory of Strength for Anisotropic Materials , 1971 .

[20]  Konstantinos E. Parsopoulos,et al.  MULTIOBJECTIVE OPTIMIZATION USING PARALLEL VECTOR EVALUATED PARTICLE SWARM OPTIMIZATION , 2003 .

[21]  Ranjan Ganguli,et al.  An automated hybrid genetic-conjugate gradient algorithm for multimodal optimization problems , 2005, Appl. Math. Comput..

[22]  H. Kunzi,et al.  Lectu re Notes in Economics and Mathematical Systems , 1975 .

[23]  Károly Jármai,et al.  Analysis and optimum design of fibre-reinforced composite structures , 2004 .

[24]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[25]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[26]  Raphael T. Haftka,et al.  Optimization with non-homogeneous failure criteria like Tsai–Wu for composite laminates , 2006 .