Optimization and material characterization of sandwich foam structures for floor of high-speed train

Sandwich structures play a critical role in improving the efficiency and performance of various industrial applications, including those in the automotive, marine, railway, and aerospace sectors. However, optimizing their design is challenging due to the need to balance key crashworthiness indicators such as Specific Energy Absorption (SEA) and Crash Force Efficiency (CFE). This study employed a multi-objective optimization approach that integrates the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with the Radial Basis Function (RBF) metamodel. To support the structural design of a high-speed train floor, material characterization of aluminum foam sandwich structures was conducted. The sandwich panels, composed of aluminum alloy face sheets and aluminum foam cores, were analyzed under both three-point and four-point bending conditions. Finite Element Method (FEM) simulations were developed and validated through experimental tests, demonstrating strong correlation between numerical and experimental results. It was observed that increasing the core thickness significantly enhanced the crashworthiness performance, whereas variations in face sheet thickness had only a minor impact under both loading conditions. Notably, specimens with a core thickness of 30 mm (30-TPB and 30-FPB) exhibited superior crashworthiness characteristics, making them well-suited for use in high-speed train floor structures.