Dynamic evaluation method for daily coupling resilience of urban tunnel based on physical failure mechanism

Abstract

The present application relates to a kind of urban tunnel routine coupling resilience dynamic evaluation method based on physical failure mechanism, steps are as follows: S1. establishing routine coupling resilience index system, S2. build comprehensive influence relation matrix, and introduce influence path identification threshold, determine key coupling path by screening;S3. based on the action object and physical meaning, key coupling path is mapped to physical failure mechanism;S4. build system dynamics model;S5. based on system dynamics model, routine coupling resilience dynamic simulation calculation is carried out;S6. based on the dynamic simulation result obtained in S5, analysis and obtain the resilience variation law, identify active failure factor and key failure path identification.This method can reflect the coupling degradation process between civil structure and electromechanical system in the long-term operation process of urban tunnel system, provide basis for urban tunnel system risk early warning, inspection maintenance and operation management.

Description

Technical Field

[0001] This invention relates to the field of tunnel and underground engineering operation and maintenance, and in particular to a dynamic assessment method for the daily coupled toughness of urban tunnels based on physical failure mechanisms. Background Technology

[0002] After urban tunnels enter the long-term operation phase, their system performance gradually declines due to factors such as increased service life, continuous traffic load, changes in environmental conditions, and aging facilities and equipment, leading to various daily operational risks. These risks are typically characterized by high frequency of occurrence, relatively low individual impact, and significant long-term cumulative effects. They mainly manifest as structural defects in civil engineering, such as water leakage, cracks, steel corrosion, concrete carbonation, pavement damage, and water accumulation, as well as malfunctions in electromechanical systems such as power supply and distribution systems, ventilation systems, lighting systems, monitoring and communication systems, and fire protection and water supply and drainage systems.

[0003] In the operation and management of urban tunnels, structural defects and electromechanical system failures rarely occur in isolation. Power supply and distribution system failures can affect the normal operation of various electromechanical subsystems such as ventilation, lighting, monitoring and communication, fire protection, and water supply and drainage; ventilation system failures can alter the internal environmental conditions of the tunnel, thus affecting structural deterioration processes such as concrete carbonation; fire protection and water supply and drainage system failures can affect water drainage and further impact the service life of the tunnel structure. Therefore, the daily operational risks of urban tunnels exhibit significant cross-system coupling characteristics, with risk factors interacting and cascading. Assessing risks solely from the perspective of a single structural defect or a single electromechanical equipment failure is insufficient to fully reveal the transmission paths and evolution processes of risks within the tunnel system.

[0004] Existing methods for assessing the operational status of urban tunnels often focus on analyzing local components, single equipment, or specific risk factors. While these methods can reflect the local operational status of the tunnel to some extent, they fail to adequately consider the coupling relationship between the civil engineering structure and the electromechanical system. During long-term tunnel operation, external factors such as traffic flow, the proportion of new energy vehicles, temperature, relative humidity, carbon dioxide volume fraction, and power supply reliability change over time, further influencing the development of structural defects and the failure process of the electromechanical system. Traditional static assessment methods struggle to reflect the impact of these factors on the daily resilience of the tunnel system over time, and also find it difficult to dynamically simulate the evolution of daily coupled resilience throughout the entire service life.

[0005] To address the aforementioned issues, the field of urban tunnel operation and maintenance requires a dynamic assessment method for daily coupled toughness that can comprehensively consider structural defects, electromechanical system failures, and external driving factors. Summary of the Invention

[0006] In view of the shortcomings of the prior art, the technical problem to be solved by the present invention is to provide a dynamic assessment method for the daily coupled toughness of urban tunnels based on physical failure mechanisms. This method describes the interaction between structural toughness and electromechanical toughness from the perspective of physical failure mechanisms, simulates the toughness changes of urban tunnel systems during long-term operation, and identifies the dominant failure factors and critical failure paths at different operational stages, thereby providing a basis for risk warning, inspection and maintenance, and operation and maintenance management of urban tunnel systems.

[0007] This invention is achieved through the following technical solution: a dynamic assessment method for the daily coupling toughness of urban tunnels based on physical failure mechanisms, comprising the following steps: S1. Based on the daily operational characteristics of urban tunnel systems, establish a daily coupling resilience index system. S2. Based on the daily coupling resilience index system established in S1, a comprehensive influence relationship matrix is ​​constructed, and an influence path identification threshold is introduced to screen and determine key coupling paths; S3. Based on the target and physical meaning, map the critical coupling path determined in S2 to a physical failure mechanism; S4. Transform the physical failure mechanism in S3 into a causal feedback loop, and establish the variable relationships between state variables, flow rate variables, auxiliary variables and time variables in the form of a system flow graph to construct a system dynamics model; S5. Input the structural defects parameters, electromechanical system failure parameters, traffic parameters, environmental parameters, and weight parameters into the system dynamics model based on S4 to perform daily coupled toughness dynamic simulation calculations and obtain dynamic simulation results; S6. Based on the dynamic simulation results obtained in S5, analyze and obtain the toughness variation law, and identify the active failure factors and key failure paths in different operation stages according to the dynamic simulation results. The toughness variation law includes the daily coupling toughness variation law, structural toughness variation law, and electromechanical toughness variation law of the urban tunnel system.

[0008] Beneficial effects of this invention: (1) This invention incorporates civil engineering structural defects, electromechanical system failures and external driving factors into the same daily coupling resilience assessment framework, which can reflect the cross-system coupling characteristics of daily operation risks of urban tunnel systems.

[0009] (2) The present invention constructs a system dynamics model based on physical failure mechanism, which can simulate the dynamic changes of structural toughness, electromechanical toughness and daily coupling toughness during the long-term operation of urban tunnel system.

[0010] (3) The present invention can identify the dominant failure factors and key failure paths in different operation stages, which helps to understand the transmission process and evolution law of daily operation risks of urban tunnel systems.

[0011] (4) This invention can provide a basis for risk warning, inspection and maintenance and operation and maintenance management of urban tunnel systems, and help improve the safety and stability of urban tunnel systems during long-term operation. Attached Figure Description

[0012] Figure 1 This is a flowchart illustrating a dynamic assessment method for the daily coupling toughness of urban tunnels based on physical failure mechanisms. Figure 2 A key impact path diagram for the daily coupling resilience index of urban tunnel systems; Figure 3 A schematic diagram of the main causal feedback loop for the daily coupling resilience of an urban tunnel system; Figure 4 A schematic diagram of a system dynamic simulation model for the daily coupling resilience of an urban tunnel system; Figure 5 This is a schematic diagram of the dynamic simulation results of the daily coupling resilience of an urban tunnel system. Detailed Implementation

[0013] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0014] Reference Figures 1-5 As shown, this invention provides a dynamic assessment method for the daily coupling toughness of urban tunnels based on physical failure mechanisms, the steps of which are as follows: S1. Construct a daily coupling resilience index system.

[0015] Based on the daily operational characteristics of urban tunnel systems, a daily coupled resilience index system is established corresponding to structural defects, electromechanical system failures, and external driving factors. This system provides a foundation for subsequent analysis of index coupling relationships, determination of physical failure mechanisms, and construction of system dynamics models. The daily coupled resilience index system includes a target layer, a first criterion layer, a second criterion layer, and an index layer.

[0016] Specifically, the target layer is the daily coupling toughness of the urban tunnel system. The first criterion layer is daily coupling toughness failure. The second criterion layer includes structural toughness failure and electromechanical toughness failure. The index layer includes civil structure defect indices and electromechanical system failure indices, and determines external driving parameters. The specific index system is shown in Table 1.

[0017] (a) Failure of daily coupling toughness.

[0018] Routine coupled toughness failure is used to comprehensively characterize the degree of decline in the daily operational capacity of urban tunnel systems under the combined effects of structural toughness failure and electromechanical toughness failure.

[0019] (ii) Structural toughness failure.

[0020] The structural toughness failure is used to characterize the impact of civil engineering structural defects on the daily operation of urban tunnel systems. The civil engineering structural defect indices in the index layer serve as indicators of structural toughness failure. These indices include water leakage, uneven settlement, cracks, convergence deformation, steel reinforcement corrosion, concrete carbonization, aging of sealing strips, spalling, pavement cracking, and water accumulation.

[0021] Among them, water leakage, uneven settlement, cracks, convergence deformation, steel corrosion, concrete carbonization, aging of sealing waterstop strips, spalling and falling off, road surface cracks and water accumulation are used to characterize the development status of civil engineering structural defects and their impact on structural toughness during the long-term operation of urban tunnel systems.

[0022] (iii) Electromechanical toughness failure.

[0023] The electromechanical toughness failure is used to characterize the impact of electromechanical facility and equipment failures in urban tunnel systems on daily operation. The electromechanical system failure indicators in the indicator layer serve as indicators of electromechanical toughness failure. These electromechanical system failure indicators include power supply and distribution system failure, ventilation system failure, lighting system failure, monitoring and communication system failure, fire protection and water supply and drainage system failure, and mains power outage.

[0024] Among them, failures of power supply and distribution systems, ventilation systems, lighting systems, monitoring and communication systems, fire protection and water supply and drainage systems, and mains power outages are used to characterize the operating status of electromechanical facilities and equipment in urban tunnel systems and their impact on electromechanical resilience.

[0025] (iv) External driving parameters.

[0026] The external driving parameters include electromechanical system failure parameters, traffic parameters, and environmental parameters. Electromechanical system failure parameters include power supply reliability; traffic parameters include traffic flow and the proportion of new energy vehicles; and environmental parameters include temperature, relative humidity, and CO2 volume fraction. Traffic flow, the proportion of new energy vehicles, temperature, relative humidity, CO2 volume fraction, and power supply reliability are used as external driving parameters for daily coupled resilience dynamic simulation.

[0027] Among them, traffic flow and the proportion of new energy vehicles are used to characterize the impact of changes in vehicle operating conditions on urban tunnel systems; temperature, relative humidity, and carbon dioxide volume fraction are used to characterize changes in the tunnel operating environment; and power supply reliability is used to characterize the impact of external power supply conditions on the operating status of electromechanical systems.

[0028] Table 1 Daily Coupling Resilience Index of Urban Tunnel System

[0029] S2. Analyze the coupling relationship of indicators.

[0030] Based on the daily coupling resilience index system established by S1, the mutual influence relationship between the various indicators is analyzed, a comprehensive influence relationship matrix and a final influence matrix are constructed, and an influence path identification threshold is introduced to screen and determine key coupling paths.

[0031] The steps for determining the critical coupling path include: S21. Based on the daily coupling resilience index system, data on the influence relationships between various indicators are obtained through a questionnaire survey on the interrelationships of the indicators. Specifically, this includes: 1) Questionnaire.

[0032] A questionnaire was designed to investigate the interrelationships of daily coupling toughness evaluation indicators for urban tunnel systems. For the structural toughness failure indicators S1-S10 and the electromechanical toughness failure indicators E1-E6, a pairwise influence relationship evaluation table was constructed. The questionnaire uses a five-level scale to measure the interrelationships between indicators, with five levels representing extremely high influence, significant influence, moderate influence, minor influence, and no influence, corresponding to the five fuzzy language levels VH, H, M, L, and VL.

[0033] 2) Obtain data on the interrelationships between indicators.

[0034] A questionnaire survey was conducted, inviting experts and scholars from municipal infrastructure management departments, tunnel operation and maintenance units, and the field of tunnel risk assessment. A total of 10 experts were invited to participate, and 8 valid questionnaires were obtained, resulting in an effective response rate of 80%. Based on the valid questionnaire data, the interrelationships among the daily coupling resilience indicators of urban tunnel systems were determined.

[0035] S22. The Fuzzy-DEMATEL method was used to analyze the coupling relationship between the indicators.

[0036] The Fuzzy-DEMATEL method was used to analyze the interrelationships among the daily coupled resilience indicators of the urban tunnel system obtained from S21, resulting in a comprehensive influence matrix and a final influence matrix. The influence degree, affected degree, importance, and causation degree of each indicator were calculated. The key influence paths of each indicator were obtained through their influence degree, affected degree, importance, and causation degree (see reference). Figure 2 As shown in Table 2, this framework is used to build the model. Table 2. Indicator Impact, Influence, Importance, and Causality

[0037] The four indicators—influence, affectedness, importance, and causation—are used to quantify the role and importance of each failure indicator in the coupled network from different dimensions, providing a quantitative basis for subsequent identification of active failure factors. Specifically, influence characterizes the degree to which a particular indicator affects other indicators; affectedness characterizes the degree to which a particular indicator is affected by other indicators; importance measures the significance of an indicator within the system; and causation determines whether an indicator is a causal factor or a consequence factor within the system. A positive causation value indicates that the indicator has a strong tendency to influence the system or other indicators, classifying it as a causal factor; a negative causation value indicates that the indicator has a strong tendency to be affected by other indicators, classifying it as a consequence factor.

[0038] S23. Identify the critical coupling paths.

[0039] The percentile method was used to determine the threshold for identifying the impact path. Based on the S22 comprehensive impact relationship matrix and the final impact matrix, the threshold for identifying the impact path was introduced to identify and screen the key coupling paths that yielded the daily coupling resilience index of the urban tunnel system.

[0040] Specifically, the comprehensive influence coefficients between indicators in the comprehensive influence relationship matrix are used as the threshold calculation object. The top 95th percentile of all comprehensive influence coefficients is taken as the influence path identification threshold, which is 0.2501. When the comprehensive influence coefficient of one indicator on another indicator is greater than or equal to 0.2501, the corresponding action path of that indicator is identified as a key influence path. Based on the identification results, the key influence paths of the daily coupling resilience index of the urban tunnel system are obtained, as shown in Figure 2 and Table 3.

[0041] Table 3 Key Influence Paths of Indicators

[0042] As shown in Table 3, the key influencing paths of the daily coupled toughness index of the urban tunnel system include the internal coupling path of structural toughness, the internal coupling path of electromechanical toughness, and the cross-system coupling path of electromechanical-structural systems. These key influencing paths are used for subsequent determination of physical failure mechanisms and construction of system dynamics models.

[0043] S3. Physical failure mechanism determined.

[0044] Based on the affected objects and physical meanings, and combining the development patterns of structural defects in urban tunnel systems, the fault propagation patterns of electromechanical systems, and cross-system coupling relationships, the critical coupling paths identified in S2 are mapped to physical failure mechanisms. The affected objects include civil structures and electromechanical facilities; the physical meanings include defect development patterns, fault propagation patterns, and coupling relationships; and the physical failure mechanisms include internal failure mechanisms of structural toughness, internal failure mechanisms of electromechanical toughness, and cross-system coupling failure mechanisms between electromechanical and structural systems. Specifically, these include: S31 determines the internal failure mechanism of structural toughness.

[0045] The internal failure mechanism of structural toughness is defined as the interaction process among defects in civil engineering structures. This internal failure mechanism includes concrete carbonation-reinforcement corrosion-cracks, cracks-water leakage, water leakage-uneven settlement, and water leakage-water accumulation chains. Specifically, it includes water leakage leading to uneven settlement, water leakage leading to water accumulation, uneven settlement leading to pavement cracking, cracks leading to water leakage, cracks leading to spalling, convergence deformation leading to water leakage, convergence deformation leading to cracks, reinforcement corrosion leading to cracks, concrete carbonation leading to reinforcement corrosion, and aging of sealing strips leading to water leakage.

[0046] S32 identifies the internal failure mechanism of electromechanical toughness.

[0047] The internal failure mechanism of electromechanical resilience is defined as the transmission process of electromechanical system faults between various electromechanical subsystems. This internal failure mechanism includes a chain of failures in the mains power supply system leading to failure of the power distribution system, and then to failure of the various electromechanical subsystems. Specifically, this includes failures in the power distribution system leading to failures in the ventilation system, lighting system, monitoring and communication systems, fire protection and water supply systems, and the mains power supply system leading to failure of the power distribution system.

[0048] S33 identifies the electromechanical-structural cross-system coupling failure mechanism.

[0049] The electromechanical-structural cross-system coupling failure mechanism is defined as the impact of electromechanical system failures on the development process of civil engineering structural defects.

[0050] The electromechanical-structural cross-system coupled failure mechanisms include a ventilation system failure-carbon dioxide volume fraction change-concrete carbonation chain, and a fire protection and water supply system failure-water accumulation chain. Specifically, this includes the impact of ventilation system failure on the concrete carbonation process, and the impact of fire protection and water supply system failure on the water accumulation process.

[0051] S4. Construct a system dynamics model.

[0052] Based on the physical failure mechanism of the daily coupling resilience of the urban tunnel system determined by S3, it is transformed into a causal feedback loop. A system flow graph is used to establish the variable relationships between state variables, flow rate variables, auxiliary variables, and time variables, thus constructing a system dynamics model of the daily coupling resilience of the urban tunnel system. Specific steps include: S41. Based on the physical failure mechanism, establish the main causal feedback loop for daily coupling resilience.

[0053] Based on the aforementioned internal failure mechanisms of structural toughness, electromechanical toughness, and electromechanical-structural cross-system coupling failure mechanisms, a main causal feedback loop for the daily coupled toughness of urban tunnel systems is established (see reference). Figure 3 (As shown). Figure 3 The causal arrows in the table correspond to the key coupling paths mentioned above, and are used to characterize the interaction between structural defects, electromechanical system failures, and cross-system coupling failures. The physical processes involved in the routine coupling resilience model are shown in Table 4.

[0054] Table 4 Physical Processes in the Routine Coupling Resilience Model

[0055] Through the aforementioned physical failure mechanism, the critical coupling path obtained in S2 is transformed into a causal feedback relationship that can be used for system dynamics modeling.

[0056] S42. Determine the modeling object of the system dynamics model.

[0057] Taking the daily coupling resilience of urban tunnel systems as the modeling object, and the civil engineering structural defects, electromechanical system failures and their cross-system coupling relationships as the modeling basis, the S3 physical failure mechanism is taken as the main causal source of the system dynamics model.

[0058] S43. Determine the variable types for the system dynamics model.

[0059] The variable types include state variables, flow rate variables, auxiliary variables, and time variables. State variables characterize the daily coupling resilience level of the urban tunnel system. Flow rate variables characterize the development of structural defects, failure of electromechanical equipment, and changes in external driving factors. Auxiliary variables characterize environmental parameters, traffic parameters, equipment reliability parameters, and defect development parameters. Time variables characterize the operational lifespan of the urban tunnel system.

[0060] S44. System dynamics dynamic simulation model.

[0061] refer to Figure 4As shown, based on the S41 main causal feedback loop, the causal relationship between various indicators is transformed into the variable relationship in the system dynamics model. The connection between state variables, flow rate variables, auxiliary variables and time variables is established in the form of system flow graph, and a system dynamics dynamic simulation model of the daily coupling resilience of urban tunnel system is constructed.

[0062] The constructed system dynamics simulation model covers 17 key physical relationships in the civil engineering structure and electromechanical system, including a total of 58 variables. Among these 58 variables are 1 CDOR-routine coupling toughness level variable, 1 time variable, 38 flow rate variables, and 18 auxiliary variables.

[0063] Through the above steps, the physical failure mechanism of the daily coupling toughness of the urban tunnel system is transformed into a dynamic simulation model of the system dynamics, providing a model foundation for the subsequent input of civil engineering structural failure parameters, electromechanical system failure parameters, traffic parameters, environmental parameters and weight parameters, as well as the dynamic simulation calculation of daily coupling toughness.

[0064] S5. Calculate dynamic simulation.

[0065] The structural failure parameters, external driving parameters, and weighting parameters are input into an S4-based system dynamics model for daily coupled toughness dynamic simulation calculations to obtain the daily coupled toughness dynamic simulation results of the urban tunnel system. The external driving parameters include electromechanical system failure parameters, traffic parameters, and environmental parameters. The dynamic simulation results include the structural toughness failure probability, electromechanical toughness failure probability, daily coupled toughness failure probability, and daily coupled toughness value of the urban tunnel system under different operating times. Specifically, the structural toughness failure probability is obtained by weighting the failure probabilities of each structural toughness failure index; the electromechanical toughness failure probability is obtained by weighting the failure probabilities of each electromechanical toughness failure index; the daily coupled toughness failure probability is obtained by weighting the structural toughness failure probability and the electromechanical toughness failure probability; and the daily coupled toughness value is obtained by taking the complement of the daily coupled toughness failure probability.

[0066] Specifically, it includes: S51. Determine the parameters of civil engineering structural defects.

[0067] The parameters for structural defects in civil engineering structures are determined based on the evolution patterns of structural defects and the physical relationships between defects. These parameters include leakage level, uneven settlement development parameters, crack development parameters, convergence deformation parameters, steel reinforcement corrosion parameters, concrete carbonation parameters, aging parameters of sealing strips, spalling parameters, pavement cracking parameters, and water accumulation parameters.

[0068] The leakage parameters are determined based on the leakage level; the concrete carbonation and steel corrosion parameters are determined based on the physical process of concrete carbonation-steel corrosion. The leakage levels are shown in Table 5.

[0069] Table 5 Leakage Levels

[0070] S52. Determine the failure parameters of the electromechanical system.

[0071] The failure parameters of the electromechanical system are determined based on the reliability of the electromechanical facilities and equipment and the system connection relationships. The electromechanical system includes the power supply and distribution system, ventilation system, lighting system, monitoring and communication system, fire protection and water supply and drainage system, and mains power outage. For each electromechanical subsystem, representative main facilities and equipment are selected, and the failure process of the facilities and equipment is calculated based on their Weibull distribution parameters.

[0072] Since each electromechanical subsystem consists of multiple devices with independent functions, the Weibull distribution parameters of characteristic devices in each system are used to characterize the failure characteristics of the corresponding system. The Weibull distribution parameters of the electromechanical system are shown in Table 6.

[0073] Table 6. Weibull Distribution Parameters of Electromechanical Systems

[0074] S53. Determine traffic parameters and environmental parameters.

[0075] The traffic and environmental parameters are determined based on traffic flow, vehicle composition, and environmental changes data during the operation of the urban tunnel. Traffic parameters include traffic flow and the proportion of new energy vehicles; environmental parameters include temperature, relative humidity, and carbon dioxide volume fraction.

[0076] The vehicle composition is determined based on vehicle type classification, as shown in Table 7. Temperature and relative humidity are determined based on the historical average temperature and relative humidity distributions. Traffic flow and the proportion of new energy vehicles are determined based on the development trends of motor vehicles and new energy vehicles. Power supply reliability is used to characterize the impact of external power supply conditions on the operating status of the electromechanical system; the power supply reliability of a certain city from 2019 to 2024 is shown in Table 8.

[0077] Table 7 Different vehicle models and classifications

[0078] Table 8. Power Supply Reliability Rate of a Certain City, 2019-2024

[0079] S54. Determine the weight parameters.

[0080] The weighting parameters were determined through expert surveys and fuzzy comprehensive evaluation. These parameters include the weights of structural toughness failure indicators, electromechanical toughness failure indicators, and the weights of structural toughness failure and electromechanical toughness failure on routine coupled toughness failure, with the sum of all weights at the same level being 1. Specifically, this includes the influence of civil engineering factors on structural toughness failure, the influence of electromechanical system factors on electromechanical toughness failure, and the weights of structural toughness failure and electromechanical toughness failure on routine coupled toughness failure. The importance evaluation results of each indicator were obtained through expert surveys, and the fuzzy comprehensive evaluation method was used to quantify and normalize the expert evaluation results, ensuring that the sum of all weights at the same level is 1.

[0081] In this embodiment, 10 experts and scholars from municipal infrastructure management departments, tunnel operation and maintenance units, and the field of tunnel risk assessment were invited to participate in a questionnaire survey. Eight valid questionnaires were obtained, resulting in an effective response rate of 80%. Based on the questionnaire data, the fuzzy comprehensive evaluation method was used to quantitatively analyze the expert evaluation results and obtain the weights of the daily coupled resilience model. The weights of the daily coupled resilience model are shown in Table 9. The structural resilience failure probability is obtained by weighting the failure probabilities of each structural resilience failure index according to the corresponding sub-node weights, and the electromechanical resilience failure probability is obtained by weighting the failure probabilities of each electromechanical resilience failure index according to the corresponding sub-node weights. The daily coupled resilience failure probability is obtained by weighting the structural resilience failure probability and the electromechanical resilience failure probability according to the corresponding weights of the daily coupled resilience layer. In this embodiment, the weight corresponding to structural resilience failure is 0.5811, and the weight corresponding to electromechanical resilience failure is 0.4189.

[0082] Table 9 Weights of the Daily Coupling Resilience Model

[0083] S55. Perform daily coupling resilience dynamic simulation.

[0084] Substitute the structural distress parameters, electromechanical system failure parameters, traffic parameters, environmental parameters, and weight parameters from S51-S54 into the system dynamics model constructed in step four, and set the simulation period and time step to conduct dynamic simulation of the daily coupling toughness of the urban tunnel system. The model output indicators include the probability of structural toughness failure, the probability of electromechanical toughness failure, the probability of daily coupling toughness failure, the structural toughness value, the electromechanical toughness value, and the daily coupling toughness value, which are used for subsequent daily coupling toughness assessment.

[0085] S6. Assess daily coupling resilience.

[0086] Based on the dynamic simulation results obtained in S5, the toughness variation law is analyzed and obtained. Active failure factors and critical failure paths at different operational stages are identified according to the dynamic simulation results. The toughness variation law includes the daily coupling toughness variation law, structural toughness variation law, and electromechanical toughness variation law of the urban tunnel system. The specific steps are as follows: In S61.S5, obtain the dynamic simulation results of daily coupling resilience and plot the simulation results.

[0087] refer to Figure 5 As shown, based on a system dynamics model considering physical failure mechanisms, a dynamic simulation of the daily coupling toughness of an urban tunnel system was conducted using Vensim software. The simulation period was 100 years, and the simulation step size was 0.1 years. The daily coupling toughness level of the urban tunnel system and the failure probability of its related indicators were obtained through S5 dynamic simulation, and the simulation results were plotted.

[0088] S62. Analyze the changing patterns of daily coupling resilience.

[0089] refer to Figure 5 The dynamic simulation results show that the daily coupling toughness level of the urban tunnel system continuously declines with the increase of operating time. After 6.4 years of operation, the daily coupling toughness index decays to 0.7965, which is a relatively high toughness level; after 13.0 years of operation, it decreases to 0.5965, which is a medium toughness level; after 22.4 years of operation, it decreases to 0.3989, which is a relatively low toughness level; after 48.2 years of operation, it decreases to 0.1998, which is a very low toughness level; and after 100 years of operation, the daily coupling toughness index drops to 0.1209, which is a very low toughness level.

[0090] S63. Analyze the variation law of structural toughness.

[0091] According to the dynamic simulation results of structural toughness failure, except for uneven settlement, the probability of occurrence of other civil engineering structural risks generally shows an increasing trend year by year. During the 100-year operation period, concrete carbonization, pavement cracking, water accumulation, water leakage, cracks, and spalling will sequentially reach the failure state; the probabilities of steel reinforcement corrosion, convergence deformation, and aging of sealing strips increase with the increase in operation time. The probability of uneven settlement shows a trend of first increasing and then decreasing, and its change is related to the continuous increase in the probability of water leakage and the changes in the impact of water leakage on settlement.

[0092] S64. Analyze the variation law of electromechanical toughness.

[0093] According to the dynamic simulation results of electromechanical toughness failure, the failure probability of each electromechanical subsystem increases year by year with the increase of operating time. Among them, the failure processes of ventilation system, monitoring and communication system, lighting system, power supply and distribution system, and fire protection and water supply and drainage system show significant differences in their order of occurrence. Electromechanical system failure plays an important role in the evolution of daily coupling toughness, and the rapid decline in daily coupling toughness in the early stage of operation is mainly affected by electromechanical system failure.

[0094] S65. Identify the dominant failure factors and critical failure paths.

[0095] By combining the dynamic changes in daily coupling toughness, structural toughness, and electromechanical toughness, the dominant failure factors and critical failure paths at different operational stages are identified. In the initial operational phase, electromechanical system degradation has a significant impact on the overall decline in daily coupling toughness. As operational time increases, structural defects gradually develop and interact with electromechanical system failures, creating a superimposed effect on the failure probabilities of both structural and electromechanical toughness. Through this analysis, the dynamic evolution of daily coupling toughness in urban tunnel systems during long-term operation can be obtained, providing a basis for risk warning, inspection and maintenance, and operation and maintenance management.

[0096] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A dynamic assessment method for the daily coupling toughness of urban tunnels based on physical failure mechanisms, characterized by the following steps: as follows: S1. Based on the daily operation characteristics of urban tunnel systems, establish a daily coupling resilience index system; S2. Based on the daily coupling resilience index system established in S1, construct a comprehensive influence relationship matrix and a final influence matrix, and introduce an influence path identification threshold to screen and determine key coupling paths; S3. Based on the target and physical meaning, map the critical coupling path determined in S2 to a physical failure mechanism; S4. Transform the physical failure mechanism in S3 into a causal feedback loop, and establish the variable relationships between state variables, flow rate variables, auxiliary variables and time variables in the form of a system flow graph to construct a system dynamics model; S5. Input the structural defects parameters, external driving parameters, and weight parameters into the system dynamics model based on S4 to perform daily coupled toughness dynamic simulation calculations and obtain dynamic simulation results; S6. Based on the dynamic simulation results obtained in S5, analyze and obtain the toughness variation law, and identify the active failure factors and key failure paths in different operation stages according to the dynamic simulation results. The toughness variation law includes the daily coupling toughness variation law, structural toughness variation law and electromechanical toughness variation law of urban tunnel system.

2. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 1, characterized in that: The daily coupling resilience index system includes a target layer, a first criterion layer, a second criterion layer, and an index layer. The target layer is the daily coupling resilience of the urban tunnel system, the first criterion layer is the daily coupling resilience failure, the second criterion layer includes structural resilience failure and electromechanical resilience failure, and the index layer includes civil structure disease index and electromechanical system failure index, and determines external driving parameters, including electromechanical system failure parameters, traffic parameters, and environmental parameters.

3. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 1, characterized in that: The steps for determining the critical coupling path in S2 are as follows: S21. Based on the daily coupling resilience index system, data on the influence relationships between various indicators are obtained through a questionnaire on the interrelationships of the indicators; S22. The mutual influence relationship between the indicators obtained in S21 is analyzed by using the fuzzy decision experiment and evaluation laboratory method to obtain the comprehensive influence relationship matrix and the final influence matrix, and the influence degree, the degree of being influenced, the importance degree and the degree of cause of each indicator are calculated. S23. The percentile method is used to determine the threshold for identifying the influence path. Based on the comprehensive influence relationship matrix and the final influence matrix in S22, the threshold for identifying the influence path is introduced to identify the key coupling path of the daily coupling resilience index of the urban tunnel system.

4. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 1, characterized in that: The physical failure mechanisms include internal failure mechanisms of structural toughness, internal failure mechanisms of electromechanical toughness, and cross-system coupling failure mechanisms of electromechanical and structural systems. The internal failure mechanism of structural toughness is defined as the mutual influence process between civil structure defects, the internal failure mechanism of electromechanical toughness is defined as the transmission process of electromechanical system faults between various electromechanical systems, and the cross-system coupling failure mechanism of electromechanical and structural systems is defined as the impact of electromechanical system faults on the development process of civil structure defects.

5. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 4, characterized in that: The internal failure mechanisms of structural toughness include concrete carbonation-steel corrosion-cracks, cracks-water leakage, water leakage-uneven settlement, and water leakage-water accumulation chain; the internal failure mechanisms of electromechanical toughness include mains power outage-power supply and distribution system failure-failure chain of electromechanical subsystems; the cross-system coupling failure mechanisms of electromechanical and structural systems include ventilation system failure-carbon dioxide volume fraction change-concrete carbonation chain, and fire protection and water supply and drainage system failure-water accumulation chain.

6. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 1, 2, 3, 4, or 5, is characterized in that: The steps for constructing a system dynamics model using S4 are as follows: S41. Based on the physical failure mechanism, establish the main causal feedback loop of daily coupling resilience; S42. Taking the daily coupling toughness of urban tunnel systems as the modeling object, and taking civil engineering structural defects, electromechanical system failures and their cross-system coupling relationships as the modeling basis, the S3 physical failure mechanism is taken as the main causal relationship source of the system dynamics model; S43. Determine the variable types for the system dynamics model, including state variables, flow rate variables, auxiliary variables, and time variables; S44. Based on the main causal feedback loop of S41, the causal relationship between various indicators is transformed into the variable relationship in the system dynamics model. The connection between state variables, flow rate variables, auxiliary variables and time variables is established in the form of system flow graph, and a system dynamics dynamic simulation model of the daily coupling resilience of urban tunnel system is constructed.

7. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 2, characterized in that: The civil engineering structure defect index serves as an indicator of structural toughness failure. This index includes water leakage, uneven settlement, cracks, convergence deformation, steel reinforcement corrosion, concrete carbonization, aging of sealing strips, spalling, road surface cracking, and water accumulation. The electromechanical system failure index serves as an indicator of electromechanical toughness failure. This index includes power supply and distribution system failure, ventilation system failure, lighting system failure, monitoring and communication system failure, fire protection and water supply and drainage system failure, and mains power outage. The external driving parameters include traffic flow, the proportion of new energy vehicles, temperature, relative humidity, carbon dioxide volume fraction, and power supply reliability.

8. The dynamic assessment method for daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 1, 2, 3, 4, 5, or 7, characterized in that: The dynamic simulation results include the structural toughness failure probability, electromechanical toughness failure probability, daily coupling toughness failure probability, and daily coupling toughness value of the urban tunnel system under different operating times. The structural toughness failure probability is obtained by weighting the failure probabilities of each structural toughness failure index. The electromechanical toughness failure probability is obtained by weighting the failure probabilities of each electromechanical toughness failure index. The daily coupling toughness failure probability is obtained by weighting the structural toughness failure probability and the electromechanical toughness failure probability. The daily coupling toughness value is obtained by taking the complement of the daily coupling toughness failure probability.

9. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 8, characterized in that: The civil engineering structural defect parameters are determined based on the evolution law of structural defects and the physical influence relationship between defects. The electromechanical system failure parameters are determined based on the reliability of electromechanical facilities and equipment and the system connection relationship. The traffic parameters and environmental parameters are determined based on traffic flow, vehicle composition and environmental change data during the operation of urban tunnels. The weight parameters include the weight of structural toughness failure index, the weight of electromechanical toughness failure index, and the weight of structural toughness failure and electromechanical toughness failure on daily coupled toughness failure, and the sum of all weights at the same level is 1.

10. The method for dynamic assessment of the daily coupling toughness of urban tunnels based on physical failure mechanisms according to claim 6, characterized in that: The system dynamics simulation model in S4 includes 17 key physical relationships in the civil structure and electromechanical system, totaling 58 variables. These 58 variables include one CDOR-routine coupling toughness level variable, one time variable, 38 flow rate variables, and 18 auxiliary variables.

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