Crashworthiness Optimization Method of Ship Structure under Multi-Working Conditions

Numerous collision conditions can occur during ship operations, resulting in various consequences that require specific consideration for optimizing crashworthiness design. Existing studies have investigated design structures; however, they often focus on single working and do not comprehensively consider the diverse scenarios encountered operations. To overcome this drawback, paper proposes a novel method addresses multi-working combines orthogonal testing with backpropagation neural network (BPNN) to establish an efficient surrogate model optimization. The accuracy of BPNN was improved by introducing genetic algorithm Adam algorithm. technique order preference similarity ideal solution (TOPSIS) is introduced formulate condition optimization function. structure optimized using sparrow search (SSA) while considering constraint lightweight results demonstrate substantial reduction objective functions conditions. Moreover, predicted values are good agreement finite element simulation results, affirming effectiveness proposed improving providing valuable guidance engineering