Authors: David B. Segala; Thomas A. Wettergren
Addresses: Naval Undersea Warfare Center, 1176 Howell Street, Newport, RI 02841, USA ' Naval Undersea Warfare Center, 1176 Howell Street, Newport, RI 02841, USA
Abstract: In multidimensional design optimisation, competing objectives lead to performance trade-offs that can only be made judiciously once the trade-off surface is understood in the context of the problem constraints. Examining the Pareto front of the multi-objective problem provides the designer with an understanding of which design parameter combinations lead to various desirable trade-offs between competing objectives. We consider a bi-objective design problem in composite materials, where we wish to maximise the energy dissipation due to the cohesive failure between fibres and matrix material and minimise fibre and matrix material failure of a dynamically loaded unidirectional composite. We develop and utilise the genetic algorithm normal boundary intersection (GANBI) method to iteratively determine the Pareto front for this composite design framework. The utility of the approach is demonstrated with numerical examples.
Keywords: genetic algorithms; Pareto optimisation; optimal design; composites; finite element analysis; FEA; fibres; fracture; failure criteria; composite design; design optimisation; multi-objective optimisation; energy dissipation; composite materials.
International Journal of Design Engineering, 2016 Vol.6 No.3, pp.196 - 217
Received: 16 Sep 2015
Accepted: 13 Jan 2016
Published online: 09 Sep 2016 *