在船舶工程领域，三维小样模型是表示实际物体的基本几何形状和大体结构的简化版三维数字模型，常被用于验证和优化船舶的结构和性能。传统的三维小样模型被表示为一系列计算机辅助设计（CAD）操作，操作过程复杂且依赖专业建模知识。虽然大语言模型（LLM）在各领域表现出色，但在三维建模中的应用可能因“幻觉”现象导致建模的准确性和鲁棒性较差。为此，提出了一种大模型驱动的船舶三维小样增强式建模方法，采用参数化建模指令集表示三维小样模型。首先，基于检索增强生成方法，查找并调用已有的三维小样模型代码指令，使用大模型工具调用来驱动模型中定义的参数，减少生成三维小样模型的幻觉。其次，引入外部船舶专业知识库，对生成的三维模型进行信息补充，添加模型的特征、工艺要求等，使得三维小样模型在下游应用中发挥更大作用。研究结果表明，大模型驱动的船舶三维小样增强式建模能有效处理不同的建模需求，快速生成包含15个特征以内的船舶三维小样模型，显著提升建模效率。

In the field of ship engineering, a 3D sample model is a simplified 3D digital model representing the basic geometric shape and general structure of an actual object. It is often used to verify and optimize the structure and performance of ships. Traditional 3D sample models are represented as a series of computer-aided design (CAD) operations, which are complex and rely on specialized modeling knowledge. Although large language models (LLM) perform well in various fields, their application in 3D modeling may lead to inaccuracies and robustness issues due to the phenomenon of 'hallucinations.' Therefore, a large model-driven enhanced 3D sample modeling method for ships is proposed, using a parametric modeling instruction set to represent the 3D sample model. First, based on a retrieval-enhanced generation method, existing 3D sample model code instructions are searched and invoked, using large model tools to drive the parameters defined in the model, reducing hallucinations in generating 3D sample models. Second, an external ship professional knowledge base is introduced to supplement the generated 3D model with information, adding features, process requirements, etc., making the 3D sample model more useful in downstream applications. The research results show that the large model-driven enhanced 3D sample modeling can effectively handle different modeling requirements, quickly generating 3D sample models with up to 15 features that meet the requirements, significantly improving modeling efficiency.