# Risk Assessment of Drilling and Blasting Method Based on Nonlinear FAHP and Combination Weighting
## 1 Introduction
Some scholars have further enhanced the applicability of AHP by combining it with other methods [18; 19; 20; 21]. [PERSON] [22] discussed the risks of adverse events in tunnel boring machine (TBM) construction, using fault tree analysis (FTA) and AHP with Nitidetch Koonathongsumrit [23] for risk assessment. The study demonstrated that AHP performs well in quantifying risk probability and impact. [PERSON] [24] proposed a dynamic safety evaluation method based on fuzzy set theory (FST) and Bayesian networks (BN), incorporating AHP to determine the weights of risk indicators. The study showed that AHP is effective in risk assessment under complex construction environments. [PERSON] [25] introduced a fuzzy comprehensive evaluation method based on CRITIC and D-AHP-combined weighting, improving risk assessment accuracy by compensating for the shortcomings of single weighting methods. [PERSON] [26] employed AHP and the fuzzy comprehensive evaluation method (FCEM) to assess risks in the construction of a super-large quasi-rectangular pipe-jacking tunnel under a high-speed railway. [PERSON] [27] introduced the FAHP-I-TOPSIS method for water innyh risk assessment in tunnels, demonstrating the advantages of fuzzy AHP in handling uncertainties and ambiguities. [PERSON] [28] applied fuzzy AHP to assess construction risks at tunnel portals, further validating the applicability of AHP in complex construction environments. [PERSON] [29] constructed a deep foundation pit construction risk evaluation model based on combined weighting and nonlinear fuzzy AHP (FAHP), effectively addressing fuzziness and nonlinearity in risk assessment by introducing nonlinear operators. Additionally, [PERSON] [30] proposed an improved FAHP method for the structural safety assessment of water diversion tunnels, enhancing the consistency of expert judgments and the reliability of risk assessment by incorporating Dempster-Shafer evidence theory. [PERSON] [31] introduced a tunnel blasting scheme evaluation model and blasting parameter optimization method, using FAHP to evaluate the rationality of blasting schemes and optimize key parameters. Despite the significant achievements of AHP in construction risk assessment, its application in drill-and-blast tunneling still has limitations. While risk assessment methods such as AHP have been applied to engineering risk evaluation, drill-and-blast tunneling involves uncertainties and fuzziness. Relying solely on personnel experience for risk identification may lead to oversight, and the weighting methods in existing evaluation approaches are often singular and heavily dependent on subjective expert judgment, resulting in certain limitations. This study addresses these limitations by introducing a \"Work Breakdown Structure-Risk Breakdown Structure\" to construct a risk evaluation index system for drill-and-blast tunneling, avoiding risk omissions and overlaps. A game theory-based combined weighting method is employed to coordinate the weights obtained from subjective and objective weighting methods, reducing the influence of subjective factors and avoiding biases caused by single weighting methods, thereby improving the reliability of weight calculations. By introducing nonlinear operators into the fuzzy analytic hierarchy process (FAHP) for drill-and-blast tunneling risk evaluation, a new risk evaluation model based on combined weighting and nonlinear FAHP is established. This model is applied to the drill-and-blast tunneling section of the No. 1 Tunnel at the Pingdao entrance of the Daliangshan Tunnel, a control project on the Leshan-Xichang Expressway, to verify the rationality and feasibility of the new model. Construction of Risk Assessment Indicators for Drilling and Blasting Method Based on the WBS--RBS Method  
The work breakdown structure (WBS) decomposes a project into the smallest operational tasks, while the risk breakdown structure (RBS) [32; 33] decomposes risk factors in the construction process into the smallest risk units.