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

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 structu...

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Published inComposite structures Vol. 158; pp. 72 - 82
Main Authors Karen, Idris, Yazici, Murat, Shukla, Arun
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 15.12.2016
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ISSN0263-8223
1879-1085
1879-1085
DOI10.1016/j.compstruct.2016.07.081

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Abstract 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.
AbstractList 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.
Author Karen, Idris
Yazici, Murat
Shukla, Arun
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Keywords Corrugated steel core
Sandwich panel
Shock tube
Blast loading
Hybrid evolutionary algorithm
Polymer foam infill
Language English
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Snippet Developing sandwich structures with high energy absorption capability is important for shock loading applications. In the present study, a hybrid evolutionary...
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StartPage 72
SubjectTerms Absorption
Algorithms
Blast loading
Corrugated steel core
Design analysis
Design optimization
Foams
Hybrid evolutionary algorithm
Optimization
Polymer foam infill
Sandwich construction
Sandwich panel
Sandwich structures
Shock tube
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Title Designing foam filled sandwich panels for blast mitigation using a hybrid evolutionary optimization algorithm
URI https://dx.doi.org/10.1016/j.compstruct.2016.07.081
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