Designing foam filled sandwich panels for blast mitigation using a hybrid evolutionary optimization algorithm

Karen I., YAZICI M., Shukla A.

COMPOSITE STRUCTURES, vol.158, pp.72-82, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 158
  • Publication Date: 2016
  • Doi Number: 10.1016/j.compstruct.2016.07.081
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.72-82
  • Keywords: Sandwich panel, Hybrid evolutionary algorithm, Blast loading, Corrugated steel core, Polymer foam infill, Shock tube, DYNAMIC-RESPONSE, GENETIC ALGORITHMS, CORE, PLATES, STRENGTH, SUBJECT, SYSTEM, BEAMS
  • Bursa Uludag University Affiliated: Yes


Developing sandwich structures with high energy absorption capability is important for shock loading applications. In the present study, a hybrid evolutionary optimization technique based on Multi-Island Genetic Algorithm and Hooke-Jeeves Algorithm is used in the design stage of the sandwich structures to obtain effective results. Optimum parameters of cell geometry were investigated using the hybrid optimization algorithm to design foam filled sandwich panels for three main boundary conditions. Shock tube experiments were conducted in order to simulate the shock load effects along with 3D and 2D finite element analysis. Using the experimental results, a simulation-based design optimization approach was prepared and used to develop the designs of new sandwich structures. Promising results were obtained for all three different boundary conditions. In the simply supported case, 21% improvement of shock absorption was achieved by using 57% less volume of foam with respect to the original fully foam filled sandwich panel. In the clamped-clamped case, 16% improvement of shock absorption with 52% less volume was obtained. In the rigid base case study, 6% improvement of shock absorption with 38% less volume usage was achieved. The structures developed in this study will be of use in the defense, automotive and other industries. (C) 2016 Published by Elsevier Ltd.