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.

Investigating the loss of integrity (E) in cabin walls and decks, as well as the role of insulation capabilities, holds significant implications for preventing serious human, economic and environmental damage caused by the ignition of cabins in ships and ocean platforms due to fires and explosions. In this study, the fire resistance of A-60 class ship bulkheads and decks was evaluated through two groups of standard fire resistance tests. In the first test, the steel structure side of the bulkhead was exposed to the fire, while in the second test, the mineral wool and L-shaped stiffeners side of the deck was exposed to the fire. Numerical material models for steel and mineral wool were established based on standards, and the temperature distribution and structural deformation were simulated using Abaqus. The results showed a good correlation with the experimental data. The maximum and average temperature increases on the unheated surface of the bulkhead during the standard fire resistance test were 158 °C and 136 °C, respectively. The corresponding values for the deck were 176 °C and 138 °C. Upon the conclusion of the experiment, the maximum displacement deformation in the direction towards the furnace from the center of the cabin wall was 54 mm, and from the center of the deck, the maximum displacement deformation towards the furnace was 28 mm. This research can provide guidance for the design of fire-resistant ship compartment structures.

In this research, two distinct designs of protective structures were developed to address structural damage caused by ships impacting the internal structures of floating docks during maintenance operations. The designed protective structures consist of support sections and load-bearing sections, with the load-bearing section comprising three frame sections. For ease of description, the front frame section, middle frame section, and rear frame section are referred to as Frame A, Frame B, and Frame C, respectively. A drop-weight test was conducted with a stern-shaped indenter impacting the structures at 3.89 m/s. This study also assessed varying impact speeds and positions. The results showed that Specimen 2 had localized indentations on Frame B, while Specimen 1 exhibited overall deformation of Frame B and additional deformations in Frame A. The simulations agreed with the experimental results, confirming the model’s accuracy. At speeds from 2.34 m/s to 5.45 m/s, Specimen 2 consistently showed localized deformations, while Specimen 1 showed comprehensive deformation of Frame B at 3.89 m/s due to lower rigidity. When the indenter impacted the specimens at different locations with a speed of 5.45 m/s, the two specimens exhibited varying degrees of damage. As the impact location shifted from the central area to the end, the maximum indentation depth of Specimen 1 decreased from 52.26 mm to 41.71 mm, while that of Specimen 2 decreased from 43.26 mm to 38.50 mm. The reduction in indentation depth and extent as the impact location approached the support frame can be attributed to the increasing involvement of the web plate beneath the frame in resisting the impact. Additionally, compared to Specimen 1, Specimen 2 exhibited a relatively smaller overall indentation depth, and the impact of location variation on indentation depth was also relatively minor.

Ship-to-ship impacts can lead to serious outcomes such as environmental contamination, cargo and economic losses, and risks to crew safety. The steady growth of maritime traffic has amplified the likelihood of such incidents, emphasizing the necessity of more reliable mitigation technologies. Conventional protective systems are often inadequate for present-day demands, underscoring the need for improved energy-absorbing solutions. In this study, a double-chamber airbag is developed to strengthen the lateral crash resistance of vessels, particularly under deliberate collision conditions. The model is analyzed using finite element simulations, which are further verified through experimental comparison to ensure computational accuracy. The proposed configuration is benchmarked against a single-chamber airbag, and the findings reveal its superior capability in attenuating impact forces. Parametric analyses under varying velocities and impact angles confirm that the new design offers stable crashworthiness and effectively redistributes collision energy. At low speeds, it reduces local deformation, while under high-energy or oblique impacts, it cushions the structure and prevents severe hull damage. The observed trends demonstrate the potential of the double-chamber concept for future ship protection applications in complex operational environments.

Assembly sequence planning for prefabricated modular cabin units must satisfy geometric, precedence, stability, direction, and tool constraints while remaining responsive to workshop disturbances. This study formulates the task as a constrained, scalarized multi-criteria optimization problem, and combines constraint-aware greedy screening, blockwise split-and-recombination operators, and a feasibility-guided population injection in an improved genetic algorithm (IGA). The fair computational study used identical population sizes, evaluation budgets, stopping rules, crossover probabilities, and mutation probabilities for GA and IGA, with 30 independent runs on a reconstructed, anonymized 15-component benchmark derived from the component attributes and sequences reported in the submitted manuscript. IGA reached the best-known fitness of 0.115741 in 30/30 runs and required a mean of 10.6 generations to reach that value, whereas GA reached it in 26/30 runs and required 124.8 generations among successful runs. Simulated annealing and ant colony optimization reached the same best-known value, so global optimality is not claimed for the 15-component benchmark; exhaustive enumeration only verifies the optimum of a reduced nine-component instance. Ablation, diversity, parameter sensitivity, and synthetic 30–60-component tests clarify the contributions and limits of each mechanism. The event-triggered dynamic planning layer was additionally evaluated for six disturbance types and completed replanning in 0.52–0.62 s, reducing normalized waiting times by 33.3–100% in the release-delay scenarios. The results support feasibility and rapid replanning for this computational benchmark, while validation on complete shipyard matrices and measured task-time data remains necessary.