为解决大规模新型地下空间的施工风险防控问题，提出城市地下大空间定义，分析城市地下大空间施工风险的特征，并从系统的角度分析城市地下大空间施工风险的理念，将城市地下大空间施工风险系统分为工程结构子系统、环境子系统和组织管理子系统3部分。首先，在分析各子系统特点及子系统间关系的基础上，整合贝叶斯网络、模糊综合评价法、马尔科夫链和系统动力学，构建城市地下大空间施工重大风险多因素耦合演变模型；
然后，在贝叶斯网络框架下提出风险因素耦合系数的概念，实现在定量描述风险因素耦合效应的同时简化贝叶斯网络的构建过程，并分别以马尔科夫链和系统动力学作为描述环境子系统和组织管理子系统演变行为的工具，实现对施工过程中风险演变趋势的预测；
最后，运用多因素耦合演变模型对北京地铁17号线东大桥站进行施工风险分析。结果表明： 1）城市地下大空间施工风险具有明显的阶段性特征，在开挖阶段达到最大； 2）风险因素耦合效应对风险事件发生概率有显著影响，忽略风险因素的耦合效应会使风险分析结果出现较大偏差。
Currently, construction risk prevention and regulation
are difficult in expansive newtype underground spaces. As a
result, the term of large urban underground space (ULUS) is defined, and the
characteristics of the ULUS construction risk are examined. Then, the idea of
investigating the construction risk of the ULUS from a systematic perspective
is advanced, splitting the risk system into three parts: structural,
environmental, and organization and management. Based on the Analysis of each
subsystem′s characteristics and the relationship
between the subsystems, a multifactor coupling and
evolution model of major risks in the ULUS construction is established by
combining the Bayesian network, fuzzy comprehensive evaluation method, Markov
chain, and system dynamics. Furthermore, the concept of the coupling
coefficient of risk factors is proposed in the model of a Bayesian network
framework, which can quantitatively express the coupling effect of risk factors
while streamlining the creation of the Bayesian network. Furthermore, the Markov chain and system
dynamics forecast the growth behavior of the environment and the organization
and management subsystems to predict the risk evolution trend during the
construction process. Finally, the model also evaluates the risk associated
with the building of the Dongdaqiao station on Beijing metro line 17. The
findings demonstrate that the construction risk of the ULUS has clear stage
characteristics, and the risk reaches the greatest in the excavation stage; the
coupling effect of the risk factors has a significant impact on the likelihood
of risk events, ignoring the coupling effects of risk factors will cause higher
deviations in the risk analysis results.
