近年来伴随着我国交通产业的发展，大型桥梁不断兴建，沉井基础因其耐水性好，承载力强等诸多优点，成为大型桥梁最常见的基础形式。然而随着沉井体量不断增长，其施工的环境条件日益复杂，面临的风险越来越大。为了保证沉井的顺利下沉，减少各类事故的发生，本文基于建筑信息模型 (BIM) 技术、机器学习算法以及有限元数值模拟方法，构建的大型沉井参数化控制理论框架，结合典型实际案例对沉井下 沉施工全过程进行参数化分析和控制优化。具体工作如下：

(1) 通过对沉井下沉工艺及下沉控制参数的研究，提出了沉井施工参数化控制与优化理论的整体框架。针对沉井下沉过程中侧壁摩阻力难以通过经验公式准确预测的问题，建立了基于 PSO-SVM 算法的沉井侧壁摩阻力预测模型， 并基于工程实际 数据对侧摩阻力进行了预测；

(2)基于 Python和参数化软件 Grasshopper，建立了沉井下沉参数化分析平台。结合工程实际数据，对下沉全过程的下沉系数进行了分析，结合不同因素对下沉参数 的敏感性分析，最终得到基于参数化分析的沉井下沉初步优化方案；

(3) 在沉井下沉参数化理论和参数化分析平台的基础上，开发了参数化平台与 有限元软件 Abaqus 的接口。基于计算得到的应力分布和姿态控制参数对沉井下沉状 态重新进行了评估，并提出了进一步优化的方案，最终优化方案与初始方案相比更利于沉井施工下沉。

本文对大型沉井下沉施工参数化控制与优化平台的研究，丰富了沉井下沉施工可视化控制的理论实践，完善了大型沉井施工的参数化控制理论体系，具有一定的理论意义和实践参考价值。

关键词：大型沉井施工；施工控制；参数化分析；PSO-SVM 模型；有限元数值模拟；方案优化

In recent years, with the development of China's transportation industry, large bridges have been continuously built, and the caisson foundation has become the most common foundation form of large bridges because of its good performance in water resistance and bearing capacity. However, with the increasing volume of caisson and the complexity of construction conditions, the risks are growing rapidly. In order to ensure the construction of caisson and reduce the occurrence of various accidents, this thesis proposed a parametric control and optimization framework for caisson construction based on Building Information Modeling technique, machine learning algorithm and finite element numerical simulation method. Based on engineering practice,  the theoretical framework of large caisson parametric control proposed in this thesis is applied, and the specific work is as follows:

(1) Through the study of the caisson construction and sinking control parameters, the framework of parametric control and optimization for caisson construction was proposed. Aimed at the problem that accurate prediction of sidewall friction in sinking process were difficult to calculate through empirical formulas, a sidewall friction resistance prediction model based on PSO-SVM algorithm was established. The side friction was predicted based on actual engineering data;

(2) Based on Python and parametric software Grasshopper, a parameterization analysis platform for caisson construction was established. Combined with actual data from the project, the sinking coefficient of the whole process of sinking was analyzed. With the sensitivity  analysis of the sinking parameters by different factors,  the preliminary optimization scheme of sinking sinking based on parametric analysis was finally obtained;

(3) On the basis of parametric theory and parametric analysis platform, the interface between parametric platform and finite element software Abaqus was developed.  By calculating the stress distribution and attitude control parameters, the sinking condition of caisson  was recalculated,  and a further optimization scheme is proposed.  The final optimization scheme was better for the construction of the caisson construction than the initial scheme.