Fluid sloshing within containers subjected to external motion is a crucial yet intricate phenomenon with implications across various industries. This study investigates sloshing in a rectangular liquid tank through a series of experiments examining pitch excitations with diverse excitation frequencies and amplitudes across different liquid carrying rates. By analyzing pressure data and imagery of the free liquid surface, statistical trends in peak pressure at measurement points within the tank are identified, revealing the nonlinear behavior of the fluid. Spectral analysis generates power spectrum curves that delineate frequency components and energy distribution within the sloshing dynamics. Key findings include the identification of resonance-induced violent sloshing at a 20% liquid-carrying rate and a resonant frequency shift at a 70% liquid-carrying rate due to nonlinearity, displaying a “soft spring” characteristic in the frequency response. The free liquid surface exhibits four distinct waveforms depending on frequency. Notably, at a 70% liquid-carrying rate and resonant frequency excitation, three-dimensional vortex waves emerge, highlighting a complex three-dimensional effect within the tank. The power spectrum shows that the dominant response frequency aligns with the excitation frequency and its multiples. This investigation enhances our understanding of the intricate nature of sloshing in various liquid-carrying conditions, offering insights valuable for diverse industrial applications.

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