Predicting self-healing strength recovery using a multi-objective genetic algorithm

C. Knipprath, G. P. McCombe, R. S. Trask, I. P. Bond

Research output: Contribution to journalArticlepeer-review

17 Citations (SciVal)


This study aims to identify the optimum location and distribution of a healing agent within the delamination of a fibre reinforced plastic to ensure effective self-healing by utilising a multi-objective Genetic Algorithm (GA). Two optimisation problems were formulated and addressed with a different set of objectives. A simple finite element (FE) model is used to evaluate the mechanical performance of the healing component. The FE model consists of an idealised delamination region, which allows the direct discretisation of the problem used for the optimisation algorithm. Effective healing locations are found for a specific load case with a healing efficiency of up to 95% for the best performing solution.

Original languageEnglish
Pages (from-to)752-759
Number of pages8
JournalComposites Science and Technology
Issue number6
Publication statusPublished - 27 Mar 2012


  • A. Smart materials
  • C. Damage tolerance
  • C. Finite element analysis (FEA)
  • C. Probabilistic methods
  • Self-healing

ASJC Scopus subject areas

  • Engineering(all)
  • Ceramics and Composites


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