Title of article :
Robust design optimisation of advance hybrid (fiber–metal) composite structures
Author/Authors :
DongSeop Lee، نويسنده , , Carlos Morillo، نويسنده , , Sergio Oller، نويسنده , , Gabriel Bugeda، نويسنده , , Eugenio Onate، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Pages :
12
From page :
181
To page :
192
Abstract :
Hybrid Composite Structures (HCSs) are consisting of alternating layers of Fiber-Reinforced Polymer and metal sheets. Mechanical properties and responses for off-design conditions of HCSs can be improved using an innovative methodology coupling Multi-Objective Genetic Algorithm and robust design method. The concept of robust design approach ensures that a structure will be tolerant to unexpected loading and operating conditions. In this paper, two applications are considered; the first is to maximise the stiffness of the HCS while minimising its total weight through a Multi-Objective Design Optimisation. The second application considers a Robust Multi-Objective Design Optimisation (RMDO) to minimise total weight of HCS and to minimise both, the normalised mean displacement and the standard deviations of displacement, considering critical load cases. For the optimisation process, a distributed/parallel Multi-Objective Genetic Algorithm in robust multi-objective optimisation platform is used and it is coupled to a Finite Element Analysis based composite structure analysis tool to find the optimal combination of laminates sequences for HCSs. Numerical results show the advantages in mechanical properties of HCS over the metal structures, and also the use of RMDO methodology to obtain higher characteristics of HCS in terms of mechanical properties and its stability at the variability of load cases.
Keywords :
robust design optimisation , Multi-objective optimisation , Stacking sequence , Finite element analysis , Hybrid (fiber–metal) composite structures
Journal title :
COMPOSITE STRUCTURES
Serial Year :
2013
Journal title :
COMPOSITE STRUCTURES
Record number :
1345478
Link To Document :
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