Numerous elements influence the steadiness of the cutting slope for building houses. Many techniques and frameworks for assessing slope stability have been proposed in current research, yet there remains a deficiency in the findings related to cutting slope stability for construction. Consequently, a selection of general survey and investigative indicators for various cutting slope is made as the evaluation index, grounded in the examination of current slope stability evaluation techniques. To assess the stability of cutting slope, a hierarchical structure model is created through hierarchical analysis, followed by computing the weights of the target layer, quasi-test layer, and sub-category indices. Concurrently, alterations are made to the comprehensive index model, and the evaluation index weight derived from hierarchical analysis is integrated into the updated composite index model. Subsequently, a semi-quantitative assessment framework for the stability of cutting slope is constructed. For confirming the model's precision and accuracy, the suggested semi-quantitative assessment model was utilized on the stability analysis of 43 disaster locations in Jiangxi Province in 2023, yielding results that closely match the real-world scenario.

With the continuous expansion of urban rail transit networks, construction safety of connecting passages—as critical weak links in underground structural systems—has become pivotal for project success. Although artificial ground freezing technology effectively addresses adverse geological conditions (e.g., high permeability and weak self-stability), it is influenced by multi-field coupling effects (temperature, stress, and seepage fields), which may trigger chain risks such as freezing pipe fractures and frozen curtain leakage during construction. This study deconstructed the freezing method workflow (‘drilling pipe-laying → active freezing → channel excavation → structural support’) and established a hierarchical evaluation index system incorporating geological characteristics, technological parameters, and environmental impacts by considering sandy soil phase-change features and hydro-thermal coupling effects. For weight calculation, the Analytic Hierarchy Process (AHP) was innovatively applied to balance subjective-objective assignment deviations, revealing that the excavation support stage (weight: 52.94%) and thawing-grouting stage (31.48%) most significantly influenced overall risk. Subsequently, a Bayesian network-based risk assessment model was constructed, with prior probabilities updated in real-time using construction monitoring data. Results indicated an overall construction risk probability of 46.3%, with the excavation stage exhibiting the highest sensitivity index (3.97%), identifying it as the core risk control link. These findings provide a quantitative basis for dynamically identifying construction risks and optimizing mitigation measures, offering substantial practical value for enhancing safety in subway connecting passage construction within water-rich sandy strata.