Artificial immune system for multi-objective design optimization of composite structures

We present a new, generic method/model for multi-objective design optimization of laminated composite components using a novel multi-objective optimization algorithm developed on the basis of the artificial immune system (AIS) paradigm. A co-variant of the popular clonal selection principle called as the Objective Switching Clonal Selection Algorithm (OSCSA) has been developed and implemented successfully for the multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are-the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; failure-mechanism-based failure criteria, maximum stress failure criteria and the Tsai-Wu failure criteria. The optimization method is validated for a number of different loading configurations-uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences as well as fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented.

[1]  S. N. Omkar,et al.  Vector evaluated particle swarm optimization (VEPSO) for multi-objective design optimization of composite structures , 2008 .

[2]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

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

[4]  Sundaram Suresh,et al.  Estimation of composite damage model parameters using spectral finite element and neural network , 2004 .

[5]  C. Janeway.  How the immune system recognizes invaders. , 1993, Scientific American.

[6]  Satchi Venkataraman,et al.  Optimization of Composite Panels - A Review , 1999 .

[7]  Lydia Woods Schindler.  Understanding the Immune System , 1991 .

[8]  T. R. Tauchert,et al.  Multiobjective Design of Symmetrically Laminated Plates , 1992 .

[9]  Marco Laumanns,et al.  SPEA2: Improving the strength pareto evolutionary algorithm , 2001 .

[10]  Layne T. Watson,et al.  COMPOSITE LAMINATE DESIGN OPTIMIZATION BY GENETIC ALGORITHM WITH GENERALIZED ELITIST SELECTION , 2001 .

[11]  Mark Walker,et al.  Multiobjective optimization of laminated plates for maximum prebuckling, buckling and postbuckling strength using continuous and discrete ply angles , 1996 .

[12]  Lino A. Costa,et al.  Multiple- and single-objective approaches to laminate optimization with genetic algorithms , 2004 .

[13]  Shapour Azarm,et al.  IMMUNE NETWORK SIMULATION WITH MULTIOBJECTIVE GENETIC ALGORITHMS FOR MULTIDISCIPLINARY DESIGN OPTIMIZATION , 2000 .

[14]  L.N. de Castro,et al.  An artificial immune network for multimodal function optimization , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[15]  D. Dasgupta.  Artificial Immune Systems and Their Applications , 1998, Springer Berlin Heidelberg.

[16]  R. Haftka,et al.  Optimization of laminate stacking sequence for buckling load maximization by genetic algorithm , 1993 .

[17]  S. Tonegawa.  Somatic generation of antibody diversity , 1983, Nature.

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

[19]  V. Deved,et al.  Proceedings of the 24th IASTED international conference on Artificial intelligence and applications , 2006 .

[20]  Russell C. Eberhart,et al.  Human tremor analysis using particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[21]  Raphael T. Haftka,et al.  Optimization of composite laminates , 1993 .

[22]  Martin J. Oates,et al.  The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation , 2000, PPSN.

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

[24]  Pablo Cortés,et al.  Viral System to Solve Optimization Problems: An Immune-Inspired Computational Intelligence Approach , 2008, ICARIS.

[25]  Manoj Kumar Tiwari,et al.  Fast clonal algorithm , 2008, Eng. Appl. Artif. Intell..

[26]  Leandro Nunes de Castro,et al.  The Clonal Selection Algorithm with Engineering Applications 1 , 2000 .

[27]  Kalyanmoy Deb,et al.  A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II , 2000, PPSN.

[28]  P. Marrack,et al.  How the immune system recognizes the body. , 1993, Scientific American.

[29]  Juhyun Park,et al.  Stacking sequence design of composite laminates for maximum strength using genetic algorithms , 2001 .

[30]  Carlos A. Coello Coello,et al.  Multiobjective Optimization Using Ideas from the Clonal Selection Principle , 2003, GECCO.

[31]  S. Vijayarangan,et al.  Optimal design of a composite leaf spring using genetic algorithms , 2001 .

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

[33]  J. McCall,et al.  Genetic algorithms for modelling and optimisation , 2005 .

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

[35]  H. Fawcett.  Manual of Political Economy , 1995 .

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

[37]  Khaled Rasheed,et al.  Constrained Multi-objective Optimization Using Steady State Genetic Algorithms , 2003, GECCO.

[38]  Michaël Bruyneel,et al.  A general and effective approach for the optimal design of fiber reinforced composite structures , 2006 .

[39]  Jagdish N. Bhagwati.  THE CASE FOR THREE TRADE , 1993 .

[40]  M. Walker,et al.  A technique for the multiobjective optimisation of laminated composite structures using genetic algorithms and finite element analysis , 2003 .

[41]  Henry Y. K. Lau,et al.  An immunity approach to strategic behavioral control , 2007, Eng. Appl. Artif. Intell..