针对目前深基坑承压水风险分析中分析方法单一、事前风险评估理论不足、施工全过程动态风险预测缺乏等问题，提出基于贝叶斯网络（Bayesian network，简称BN）的深基坑承压水风险分析方法，实现承压水风险事故的事前分析和施工全过程的动态风险评价。该方法从环境、设计、施工、管理等方面建立深基坑承压水风险评价指标体系，构建静态BN风险分析模型，完成了风险概率预测、事故因素诊断、致灾因子识别等事前风险评估内容；在此基础上，通过设定风险转移节点和观测节点，引入Noisy-Max假设，实现基于监测数据的动态BN施工全过程承压水动态风险分析预测；以江阴靖江长江隧道江北深基坑工程为例，分析确定工程的承压水风险等级，进一步明确相关风险因素，准确预测出该工程的动态风险变化。结果表明，该风险分析方法具有较高的适用性和合理性，能为深基坑施工安全提供切实的指导和帮助。

In view of the existing problems of confined water risk analysis of deep foundation pit, such as single analysis method, insufficient risk prior assessment theory and lack of dynamic risk prediction during the construction process, this paper proposed a confined water risk analysis method of deep foundation pit based on Bayesian network (BN) to realize the pre-analysis of confined water risk accidents and the dynamic risk evaluation of the whole construction process. From aspects of environment, design, construction and management, the method established a risk evaluation index system of confined water of deep foundation pit, constructed static BN risk analysis model, and completed the risk probability prediction, accident factor diagnosis, disaster factor identification and other risk assessment contents in advance. On this basis, the dynamic risk analysis of confined water in the whole construction process based on monitoring data was realized by setting risk transfer nodes and observation nodes and introducing Noisy-Max hypothesis. Finally, taking the north deep foundation pit of Jingjiang Yangtze River tunnel project in Jiangyin as an example, the risk level of confined water in the project was analyzed, the related risk factors were further defined, and the dynamic risk change was accurately predicted. Results show that the proposed method has high applicability and can provide practical guidance for the safety of deep foundation pit construction.

TU46

国家自然科学基金（51878157、52178384）；江苏省交通工程建设局项目（2021QD05）