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O ptimiz ing thermal elastic properties of m ulti phase and m ulti layer c omposites by using i terative MapReduce guided genetic algorithm

TAO YOU1,* , YINGJIE XU2, CHENGLIE DU1

Affiliation

  1. Institute of Computer Testing, Control and Simulation , School of Computer Science , Northwestern Polytechnic al University, Xi’an, 710072 China
  2. Engineering Simulation a nd Aerospace Computing Key Laboratory of Contemporary Design & Integrated Manufacturing Technology , Northwestern Polytechnic al University, Xi’an, 710072 China

Abstract

The objective of this work is to optimize the thermal elastic properties of multi phase and multi layer (MPML) composites by controlling the interfaces and matrix layers thicknesses. Aiming at the traditional genetic algorithm (GA) including parallel genetic al gorithm (PGA) faces efficiency, scalability, and programming difficulty to solve this kind of optimization problems, we propose an iterative MapReduce guided genetic algorithm (IMGA). This method brings bond into MapReduce, and reasonably allocates various stages of GA to the map and reduce operator, then completes target optimization through multi step iteration of map and reduce. The IMGA is interfaced with finite element code to find an optimal design for minimizing the coefficient of thermal expansion (CTE) of the MPML unidirectional fiber reinforced composite with constraints of elastic modulus and fiber volume fraction. Satisfactory results are obtained by comparing IMGA and GA..

Keywords

Multi-phase and multi-layer, Thermal-elastic properties, Genetic Algorithm, Bond, Iterative MapReduce.

Citation

TAO YOU, YINGJIE XU, CHENGLIE DU, O ptimiz ing thermal elastic properties of m ulti phase and m ulti layer c omposites by using i terative MapReduce guided genetic algorithm, Optoelectronics and Advanced Materials - Rapid Communications, 9, 1-2, January-February 2015, pp.193-200 (2015).

Submitted at: Oct. 11, 2014

Accepted at: Jan. 21, 2015