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Marine structures such as ships and offshore platforms often suffer structural deformation during service due to factors including collision and corrosion. After deformation occurs, the rapid evaluation of the hydrodynamic performance of structures is a prerequisite for ensuring safety and formulating maintenance strategies. To this end, this paper establishes a rapid evaluation framework for the hydrodynamic performance of deformed marine structures, which integrates image acquisition, Artificial Intelligence (AI)-based Three-Dimensional (3D) reconstruction, numerical simulation, and emergency decision-making. The specific procedure of the framework consists of four steps: First, a multi-view image acquisition scheme for structures considering deformed regions is designed to collect two-dimensional images and complete preprocessing. Second, the 3D model of the structure is reconstructed based on the HunYuan3D model, followed by preprocessing operations such as hole filling and topological repair. Third, the processed model is imported into hydrodynamic software to complete the numerical simulation and performance evaluation of the structure. Finally, a follow-up disposal plan is formulated and decision-making suggestions are provided based on the evaluation results.The framework is validated on a deformed ship: the errors of the governing geometric parameters of the reconstructed model are within 3%, and the simulated deterioration of the stability reserve and motion responses is consistent with the mechanisms reported for damaged hulls. Positioning the framework as a rapid preliminary screening and decision-support tool for emergency scenarios, the results demonstrate an efficient evaluation of the hydrodynamic performance of deformed structures with a balance among low cost, high efficiency, and verifiable reliability, providing data support for the emergency decision-making of deformed ships and offshore platforms.
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Zhou et al. (2026) studied this question.
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