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Study On Quantitative Resilience Evaluation Of Urban Rail Transit Construction Engineering System

Posted on:2020-02-04Degree:MasterType:Thesis
Country:ChinaCandidate:Q HuangFull Text:PDF
GTID:2392330575499102Subject:Traffic and Transportation Engineering
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With the acceleration of urbanization and the rapid increase of urban population,the problem of ground traffic congestion has become more and more serious in large and medium-sized cities.Underground transportation has expanded urban space resources,effectively alleviated traffic congestion and provided basic conditions for the healthy and orderly development of the urban economy and society.With the increase of urban rail transit engineering projects,the total number of safety accidents occurring during the construction of urban rail transit is also increasing.As a high-risk construction project,urban rail transit projects are mostly complex underground projects with different unforeseen security risks and disasters.Therefore,the safety risk management of urban rail transit construction is essential to ensure the safety of urban rail transit construction,promote the healthy development of the city,and maintain social stability.At present,the current urban rail transit engineering risk assessment system is basically attributed to the simple passive,result-oriented engineering thinking method,which rarely emphasizes the adaptive ability of the system to adapt to the uncertain complex environment.In view of the current shortcomings of the method,the project introduces the concept of “elasticity” to describe the ability of the system to adapt to uncertain complex environments through self-adjustment.In other words,when faced with an interruption,the system can use appropriate methods to optimize or reorganize its structure to absorb or eliminate the adverse effects of interference,segment and suppress negative effects to ensure that the entire urban rail transit engineering system is in effect.Based on the definition of the academic field engineering system,the project defines the subsystems and their conceptual meanings that constitute the urban rail transit engineering system,and uses the relationship between elasticity and system to analyze the influencing factors affecting the elasticity of urban rail transit.The engineering system clarifies the relationship between various factors and quantifies the elasticity value.According to the definition of the existing engineering system,the project uses the inductive deduction principle to determine the six subsystems that constitute the urban rail transit engineering system,namely the object system,the technical system,the management system,the organization system,the process system and the support system and define their boundary conditions.Then,through the application of literature analysis,expert interviews and field data,the factors affecting the elasticity of urban rail transit engineering system are summarized and analyzed for six subsystems,and the research is carried out by appropriately increasing the intermediate variables.simplify.Third,the Bayesian network is used as a quantitative tool.First,establish a logical relationship between all variables and form a network structure.Then,according to the collected data,the probability of each node in the network structure is learned,and the elastic evaluation model of the urban rail transit engineering system on the Bayesian network is formed.Finally,this work uses the adjustability of the Bayesian network to set the expected value of a node,then observes the system changes of other related variables,and determines the strength of the protection measure according to the magnitude of the change.All of these contribute to the goal of urban rail transit construction projects,mention the quality of urban rail transit projects,contribute to the development of plans and measures from the perspective of optimal systems,and provide efficient decision support for the use of underground space in China.
Keywords/Search Tags:urban rail transit, construction engineering system, resilience, Bayen network
PDF Full Text Request
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