4 results about "Maritime safety" patented technology

The present application belongs to the technical field of flow field intelligent prediction based on numerical simulation, and particularly relates to a ship surface fluid pressure field intelligent prediction method, program, device and storage medium based on a combination of a reduced-order model and a neural network. The present application maps the unstructured grid data obtained by numerical simulation into structured grid data by using a surrogate model, ensuring the uniformity of the subsequent data processing format. On this basis, the main modal of the surface pressure field and the corresponding grid node normal vector is extracted by the reduced-order model. Then, the full-link neural network is used to realize the rapid prediction of the new ship type basis coefficient, so that for the new ship type, only the design parameters need to be input without inputting the ship grid, the rapid prediction of the ship surface load distribution, the external normal vector distribution and the pressure resistance can be realized, and reliable technical support can be provided for the ship structure strength design and safe navigation at sea.

This invention relates to the interdisciplinary field of maritime safety supervision in transportation and artificial intelligence, and discloses an intelligent auxiliary method and system for Port State Control (PSC) inspections of liquefied natural gas (LNG) vessels. The method includes structured processing and relational mapping of multi-source basic data, semantic storage of maritime regulatory texts in parent-child segmentation, and generation of a specialized knowledge base data with a five-dimensional relational mapping network. Responding to the identification information of the vessel to be inspected, the method calls upon the specialized knowledge base data and performs calculations using a risk analysis model combining a rule engine and machine learning classification to generate personalized inspection checklist data labeled with risk level, high-risk inspection areas, and inspection priorities. Through the synergy of the method and system, the method addresses pain points such as inefficient regulatory retrieval for LNG vessel PSC inspections, reliance on experience for defect determination, and cumbersome report generation, significantly improving inspection efficiency and accuracy, standardizing the inspection process, and enabling personalized training for professionals and continuous system optimization.