# Risk Assessment of Drilling and Blasting Method Based on Nonlinear FAHP and Combination Weighting
## 1 Introduction  
Tunnel engineering, as a critical component of modern infrastructure construction, faces numerous challenges due to complex geological conditions and construction environments [1]. Particularly in drill-and-blast tunneling, the risks of collapse are prominent due to the dynamic effects of blasting, uncertainties in the surrounding rock conditions, and the complexity of the construction techniques [2, 3, 4]. These risks significantly impact the safety, progress, and cost of engineering projects. Therefore, effectively assessing and controlling the risks in drill-and-blast tunneling is of great importance to engineering construction. To address the risks associated with drill-and-blast tunneling, scholars have proposed various risk assessment methods. [PERSON] [5] constructed a tunnel collapse risk assessment model through case analysis, advanced geological prediction, and D-S evidence theory, effectively identifying collapse risks in drill-and-blast tunneling. [PERSON] [6] proposed an improved Dempster-Shafer evidence theory, enhancing the accuracy of collapserisk assessment in drill-and-blast tunneling through multi-source data fusion. [PERSON] [7] proposed a cloud model-based risk assessment method for tunnel construction environments, which provides a foundation for transforming qualitative concepts into quantitative expressions under uncertainty. Additionally, [PERSON] [8] and [PERSON] [9] utilized Bayesian networks and dynamic Bayesian networks (DBN) to dynamically assess collapse risks in drill-and-blast tunneling, revealing the causal relationships between the risk factors. [PERSON] [10] introduced a coupled risk analysis model for deep foundation pit construction based on the N-K model and dynamic Bayesian networks, providing a reference for studying the risk coupling mechanism in deep foundation pit construction near existing underpass tunnels. [PERSON] [11] introduced a game theory-based G2-EW-TOPSIS model for evaluating the efficiency of drill-and-blast tunneling, constructing an evaluation index system from three dimensions: drilling efficiency, construction duration, and collaborative influencing factors. [PERSON] [1] investigated the composition of tunnel construction risks under complex geological and construction conditions, analyzing the coupling mechanisms of single and dual risk factors using the N-K model and coupling degree model. These studies have provided significant theoretical and methodological support for the analysis and control of risks in drill-and-blast tunneling. However, risk assessment in drill-and-blast tunneling still faces several challenges [12; 13]. First, the complex coupling relationships between the risk factors make it difficult for single risk assessment methods to comprehensively reflect the dynamic evolution of risks. Second, the uncertainties and fuzziness in the construction environment of drill-and-blast tunneling render traditional quantitative analysis methods inadequate for accurate risk assessment. Therefore, there is an urgent need for a risk assessment method that can comprehensively consider subjective and objective factors and address fuzziness and nonlinearity. In the 1970s, operations researcher [PERSON] proposed the analytic hierarchy process (AHP) [14]. As a multi-criteria decision-making tool, AHP has been widely applied in engineering risk assessment due to its clear structure and ease of operation. [PERSON] [15] used AHP to determine the weights of dynamic risk evaluation indicators for ultra-shallow buried large-span multi-arch tunnel construction and combined it with fuzzy comprehensive evaluation for risk assessment. [PERSON] [16] utilized the analytic hierarchy process (AHP) to quantify risk factors related to clogging in clay-rich strata, providing a basis for controlling construction risks in such environments. [PERSON] [17] employed AHP and the Delphi method to quantify risk factors for tunnel collapse, establishing a risk classification system.