High-Accuracy and Fast Calculation Framework for Berthing Collision Force of Docks Based on Surrogate Models

Author:

Zeng Haikun1,Zhu Ruihu12,Wang Qiming3,Zou Junjie1

Affiliation:

1. College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China

2. Key Laboratory of Coastal Disaster and Defence (Hohai University), Ministry of Education, Nanjing 210098, China

3. School of Mathematics, Hohai University, Nanjing 211100, China

Abstract

The accurate prediction of the collision force magnitude resulting from ship berthing on docks is crucial for the rationality and safety of dock structural design. This paper presents a novel framework for the calculation of berthing collision force for ships (CBCF), which integrates field data, finite element models, and surrogate models. Based on field data and finite element analysis, the framework constructs and compares four surrogate models with low sample requirements, ultimately selecting the optimal surrogate model for predicting collision force. Furthermore, a sensitivity analysis of the parameters is conducted based on the selected model, followed by a comparison with the various methods used for collision force prediction. The results illustrate the effectiveness of the proposed framework in replacing finite element models for the rapid and accurate prediction of collision force. Comparison with existing methods also underscores the advantages of the proposed framework, including low sample requirements, high calculation accuracy, and exceptional efficiency. In summary, this study not only introduces a novel and precise surrogate model framework for the swift prediction of berthing collision force, but it also offers valuable insights into the prevention of ship collision with wharf accidents and facilitates the rational and safe design of wharf structures.

Funder

National Natural Science Foundation of China

the National Key Research and Development Program of China

the Research Funds for the Central Universities

Huaneng Group Technology Project

Publisher

MDPI AG

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