摘 要
随着城市化进程的加速，地铁建设已成为缓解交通拥堵、优化城市空间布局的重要手段，而盾构法施工因其高效性和适应性被广泛应用于地铁隧道工程中。然而，盾构施工过程中可能对周边环境造成显著影响，并伴随一系列潜在风险，如地表沉降、地下水位变化及噪声污染等，这些问题亟需系统研究与科学应对。本研究以城市地铁盾构法施工为对象，旨在全面评估其环境影响并提出针对性的风险控制策略。通过结合现场监测数据与数值模拟分析，研究建立了多因素耦合的环境影响评价模型，并引入基于机器学习的预测方法以提高风险预警精度。结果表明，盾构施工引起的地层扰动与环境响应具有时空异质性特征，且不同地质条件下的影响程度差异显著。此外，研究提出了涵盖施工参数优化、支护结构改进及实时监测反馈的综合风险管理体系，有效降低了施工过程中的环境负面影响。本研究的创新点在于将大数据分析技术与传统工程经验相结合，构建了动态化、智能化的风险评估框架，为盾构法施工的环境友好型发展提供了理论支持和技术参考，同时为类似工程实践提供了可借鉴的经验模式。
关键词：盾构法施工；环境影响评估；风险控制策略；机器学习预测；地质条件差异
ABSTRACT
With the acceleration of urbanization, subway construction has become an essential approach to alleviating traffic congestion and optimizing urban spatial layouts, and the shield tunneling method has been widely adopted in subway tunnel projects due to its efficiency and adaptability. However, the shield construction process may significantly impact the surrounding environment, accompanied by potential risks such as ground settlement, groundwater level changes, and noise pollution, which necessitate systematic research and scientific countermeasures. This study focuses on the shield tunneling method in urban subway construction, aiming to comprehensively evaluate its environmental impacts and propose targeted risk control strategies. By integrating field monitoring data with numerical simulation analysis, a multi-factor coupled environmental impact assessment model was established, and a machine-learning-based prediction method was introduced to enhance the accuracy of risk warnings. The results indicate that the ground disturbance and environmental responses induced by shield tunneling exhibit spatiotemporal heterogeneity characteristics, with significant differences in impact levels under varying geological conditions. Furthermore, a comprehensive risk management system was proposed, encompassing optimization of construction parameters, improvement of support structures, and real-time monitoring feedback, effectively reducing the negative environmental effects during construction. The innovation of this study lies in combining big data analytics with traditional engineering experience to construct a dynamic and intelligent risk evaluation fr amework, providing theoretical support and technical references for the environmentally friendly development of shield tunneling methods, while offering replicable experience models for similar engineering practices.
Keywords: Shielding Method Construction; Environmental Impact Assessment; Risk Control Strategy; Machine Learning Prediction; Geological Condition Difference
目 录
第1章 绪论 1
1.1 城市地铁建设与盾构法施工背景 1
1.2 环境影响与风险控制的研究意义 1
1.3 国内外研究现状综述 2
1.4 本文研究方法与技术路线 2
第2章 盾构法施工的环境影响分析 3
2.1 地下水环境的影响机制 3
2.2 地表沉降与建筑物安全评估 3
2.3 噪声与振动对周边居民的影响 4
2.4 施工废弃物的环境影响评估 4
2.5 环境影响综合评价方法 5
第3章 盾构法施工的风险识别与评估 6
3.1 施工地质条件的风险分析 6
3.2 设备故障与操作失误的风险评估 6
3.3 地下管线破坏的风险预测 7
3.4 不可预见因素的风险管理策略 7
3.5 风险评估模型构建与应用 8
第4章 盾构法施工的环境影响与风险控制对策 9
4.1 绿色施工技术的应用与优化 9
4.2 地质灾害防控措施设计 9
4.3 施工过程中的环境监测体系 10
4.4 社会公众参与的风险沟通机制 10
4.5 综合风险管理框架的建立 11
结论 12
参考文献 13
致 谢 14
