Resumen
Dynamic risk assessment is a pivotal tool for enhancing construction safety and minimizing the potential for partial failure during deep and extensive excavation projects. To enhance the efficacy of dynamic risk assessment in deep excavation, this study introduces a novel risk assessment model designed to evaluate instability risk in extensive excavations. It comprises a risk factor selection model for identifying the most pertinent factors and an instability risk assessment model for gauging the extent of instability risk throughout the construction process. Then, the model was deployed in the construction of Anshan Road Station of the Qingdao Metro. To pinpoint the factors with the most pronounced impact on excavation instability, a risk factor selection model was employed, yielding a comprehensive risk evaluation index system. For real-time assessment of risk, the monitoring data were used as the primary source of evidence. A comprehensive comparative analysis involving actual data and predictions from conventional RBF and back propagation neural networks was performed. The outcome of this analysis underscored the superior accuracy and predictive capabilities of the assessment model. The instability risk assessment model offers the ability to dynamically evaluate the instability risk associated with extensive excavations featuring a combination of soil and rock. It can serve as a valuable methodological tool, furnishing essential support for the systematic prevention and mitigation of excavation instability disasters.