Optimization of steel web core sandwich panel with genetic algorithm. (15th February 2022) - Benzo, Pier Giovanni; Pereira, João M.; Sena-Cruz, José
Highlights: Weight, cost, and environmental footprint optimization study of sandwich floor panel. Structural verification formulas can be used for the penalty function coefficient. The original combination of genetic operators provides a reliable optimization tool. Thin steel sheet (≤1 mm) and a great number of webs (greater than5) yield efficient layout. Adhesive connections are important in the design of a cost-competitive floor panel. Abstract: In civil engineering there is a need for lightweight structural elements, specifically in applications such as the rehabilitation of degraded floors in existing buildings and modular construction. Metaheuristic search procedures are suitable to tackle optimization problems concerning material efficiency, but their use in real design applications is still limited. This paper presents the preliminary design in terms of structural, thermal, and acoustic performance of a floor system based on steel web core sandwich panels with polyurethane (PUR) foam core and a new genetic algorithm (GA) procedure developed to optimize its mass. The optimization study also addresses the minimization of cost and environmental impact and includes a wide range of practical engineering requirements. The constraints stemming from the building codes are incorporated in a new adaptive penalty function whose formulation and performance are thoroughly investigated. Examples of how to formulate the optimization problem in terms of Eurocode verifications are provided to foster the use of optimization procedures in current design practice. The results are presented in terms of design variables and constraints search histories as well as optimal feasible and unfeasible solutions. General conclusions and specific recommendations are drawn based on the case study presented for the design of sandwich floor panels and steel web core sandwich panels, respectively.