Data underlying chapter 5 of the PhD dissertation: Multi-fidelity probabilistic design framework for early-stage design of novel vessels

This repository contains the code and data supporting the results presented in Chapter 5 of the dissertation "Multi-Fidelity Probabilistic Design Framework for Early-Stage Design of Novel Vessels". To facilitate early-stage design exploration, this research explores the development of MF models by using available data from past design variations. The case studies include both a simplified problem of a cantilever beam, and the ship design problem of the AXE frigates. <br>The data include: (1) the parametric models for the conventional and the AXE frigate developed in Rhino and Grasshopper used to generate the hull mesh, (2)the ansys models for the cantilever beam (3) the simulation data, (4) the data associated with the analyzed cases, and (5)the Python scripts for the development of the MF models can be found in this gitlab repository. The analysis solvers used to calculate the vertical bending moments for calculating the vertical bending moments are not included in this repository.

本仓库包含支撑学位论文《新型船舶早期设计用多保真度概率设计框架（Multi-Fidelity Probabilistic Design Framework for Early-Stage Design of Novel Vessels）》第5章所呈现研究结果的代码与数据。为助力早期设计探索工作，本研究依托既往设计变体的可用数据，开展多保真度（Multi-Fidelity, MF）模型的开发研究。本次案例研究涵盖两类问题：一是悬臂梁简化问题，二是AXE护卫舰（AXE frigates）船舶设计问题。本GitLab仓库所收录的数据与脚本具体包括：(1) 基于Rhino与Grasshopper搭建的常规船体及AXE护卫舰参数化模型，用于生成船体网格；(2) 悬臂梁的Ansys模型；(3) 仿真数据集；(4) 与分析案例相关的配套数据；(5) 用于开发多保真度模型的Python脚本。需注意，本仓库未收录用于垂向弯矩计算的分析求解器。