Identification of key risk elements in quality management of mountainous railway tunnel projects:an integrated perspective of survey,design,and construction
Identifying the key risk factors that affect the quality of railway tunnel construction in mountainous areas can be challenging.However,it is crucial to identify and address these risks as early as possible to ensure successful project outcomes.To tackle this issue,the WBS-RBS method is used in accordance with relevant specifications.This method sorts out risk elements related to geological,natural,and technical aspects in the three stages of investigation,design,and construction.Based on this workflow,a multi-layer network structure framework of risk elements is established to effectively manage and mitigate risks throughout the project lifecycle.To determine the network parameters for the multilayer network relationship model of risk elements,Monte Carlo simulation is used in combination with experts'preferences for risk occurrence probability and consequence.This simulation helps to establish the node risk value,the connecting edge weights within the layer,and the connecting edge weights between the layers.Based on this model,complex network theory is introduced to further analyze and understand the relationships between the risk elements.Through complex network centrality indicators—degree centrality,eigenvector centrality,and closeness centrality—the importance of risk elements within the network is assessed.Gray correlation analysis synthesizes results from these indicators to derive the integrated importance of nodes.Subsequently,key elements posing quality risks in mountainous railroad tunnel projects are identified by sequentially removing nodes based on their comprehensive importance,using network cohesion as a guiding indicator.Finally,using a mountainous railroad tunnel project for validation,this study identifies key elements contributing to quality risks.These include issues such as improper tunnel design,ineffective team communication,and challenges posed by natural conditions like geology,weather,and climate complexity.These factors,ranking in the top 30％based on composite node importance,are identified as critical elements affecting the quality risk of mountainous railroad tunnel projects.This research aims to provide decision support for enhancing quality risk control in similar mountain railroad projects.
safety engineeringmountainous railway tunnelsengineering qualitysurvey,design and constructionmulti-layer complex networkrisk element identification
万方数据
维普
