Fire Resilience Assessment and Application in Urban Rail Transit Systems
Abstract
1. Introduction
2. Fire Resilience Assessment Analysis for Urban Underground Rail Transit
2.1. Fire Analysis of Urban Underground Rail Transit
2.1.1. Hazard-Inducing Factors in Underground Rail Systems
2.1.2. Fire Characteristic Analysis
2.2. Fire Resilience
3. Fire Resilience Assessment System
3.1. Selection of Evaluation Methods
3.1.1. WSR Methodology
3.1.2. Cross-Influence Analysis
3.1.3. Analytic Hierarchy Process
3.1.4. Analytic Network Process
3.1.5. The Systematic Integration of WSR, 4M, CIA, and ANP
3.2. Establishment of Fire Resilience Assessment Process for Urban Underground Rail Transit
3.2.1. Framework Development for Fire Resilience Assessment System
3.2.2. Principles of Fire Resilience Assessment System
3.2.3. Fire Resilience Assessment Indicators
3.3. Fire Factor Identification in Urban Underground Rail Transit
3.3.1. Identification of Fire Factor from Method WSR
- (1)
- The physical dimension examines material mechanisms during operation, covering facility equipment and built environments.
- (2)
- The operational dimension addresses organizational management and operational processes, focusing on coordinated firefighting technologies and equipment deployment.
- (3)
- The human dimension analyzes behavioral, psychological, and interactive aspects of personnel that directly influence fire progression, assessed through competency and behavioral factors.
3.3.2. 4M Theoretical Classification and Recognition
- (1)
- The personnel aspect encompasses personnel competency and behavior, where competency affects response speed and handling capability while behavior determines fire prevention and evacuation efficiency.
- (2)
- The equipment and facilities dimension covers equipment, tools, and technical conditions, including firefighting facilities, ventilation systems, escape devices, electromechanical equipment and fire compartmentation. These hardware directly determine the fire prevention and control capabilities and escape conditions.
- (3)
- The environment involves station architectural structures, decoration materials, spatial characteristics, and surrounding fire facilities, which collectively influence smoke diffusion, fire load, and external rescue conditions.
- (4)
- The management element comprises organizational administration and technical measures that enhance overall fire response capability through institutional frameworks and technological applications.
4M | Indicators | Specific Details |
---|---|---|
Personnel | Emergency awareness | Staff/passenger safety awareness affects reaction speed |
Emergency skills | Skills such as using fire extinguishers and guiding people | |
Psychological quality | Affects decision-making ability | |
Evacuation behavior | Whether passengers follow instructions and maintain order | |
Emergency decision | Staff assessment of fire conditions and response measures | |
Collaborative | Internal collaboration and external rescue | |
Fire assessment | Computer simulation | |
Firefighting techniques | Advanced firefighting equipment | |
Equipment and Facilities | Firefighting equipment | The completeness and reliability of fire extinguishers, fire hydrants, and automatic sprinkler systems |
Ventilation systems | Effectively reduce smoke concentration, improve visibility | |
Escape facilities | The width, number, and accessibility of passageways, the rationality of exit settings, and the integrity | |
Electromechanical equipment | Equipment aging or improper maintenance | |
Fire compartmentation facilities | Fire doors/walls and other facilities | |
Monitoring and alarm systems | Timely fire warning to gain time for response. | |
Environment | Building structure | Platform/station hall layout and space height |
Material characteristics | The combustion performance and smoke | |
Ventilation conditions | The design and operating status of the ventilation system | |
Fire load | The amount and distribution of combustible materials | |
Surrounding fire protection | Other civil firefighting facilities/fire stations | |
Management | Emergency plan | Clarify the responsibilities and action processes |
Emergency drill | Test the feasibility of the contingency plan | |
Staff training | Improve staff fire emergency response capabilities. | |
Information transmission | Ensure that fire information is communicated |
3.3.3. Establish of Assessment Index System
4. Calculation and Analysis of Fire Resilience Assessment Model
4.1. Construction of ANP Network Structure
4.2. Construction of Judgment Matrices
4.3. Solving Judgment Matrices
4.4. Construction of ANP Supermatrix and Final Weight Calculation
4.5. Determination of Model Weights for Assessment Indicators
5. Application of Resilience Safety Assessment Model for Urban Underground Rail Transit Fire
5.1. Introduction to Example Scenarios
5.2. Construct a Judgment Matrix by Applying the Fire Resilience Assessment Indicators of Urban Underground Rail Transit
5.2.1. Establish an Influence Relationship Matrix
5.2.2. Construction of Judgment Matrix and Calculation
5.3. Weight Calculation of Fire Resilience Safety Assessment Indicators
5.4. Analysis of Assessment Results
- (1)
- Fire safety teams should analyze fire cases from various locations, strengthen safety management in alignment with local conditions, and conduct regular risk assessments with corrective reports. Key equipment such as ventilation, smoke detection, and surveillance systems must be maintained to ensure operational reliability during fires.
- (2)
- Station managers should institutionalize fire emergency training for staff, passengers, and responders, promoting scientific self-rescue and mutual aid knowledge to achieve widespread awareness.
- (3)
- Fire-resistant design must be integrated throughout the rail transit planning and construction phases, with strict quality control to enhance building fire resistance and overall disaster resilience.
6. Conclusions
- (1)
- An urban underground rail transit fire resilience safety assessment indicator system was established through systematic research. The WSR methodology was integrated with the 4M theory to initially identify fire risk factors from three broad dimensions: human, organizational, and material aspects. The identified factors were further refined and categorized using the 4M theory to derive more specific indicators. Through resilience characteristics analysis, corresponding resilience capacities were determined. The identified fire risk indicators were then matched with these resilience capacities, resulting in the development of a comprehensive framework. The final system comprises 14 secondary indicators organized under four primary indicators: resistance capacity, adaptation capacity, absorption capacity, and resilience capacity. This study first proposed the integration of WSR methodology and 4M theory for urban rail transit fire resilience. This dual-lens approach resolves indicator redundancy in traditional models.
- (2)
- Developed a novel CIA-ANP computational architecture that quantifies nonlinear interdependencies among 14 resilience indicators. This model overcomes static evaluation limitations, establishing the first network-based weighting system validated through Xi’an Metro Line 1’s operational data.The model initially employed the CIA approach to evaluate systematic relation-ships among core indicators. Through rigorous expert surveys using the 1–9 scale, CR < 0.1 and matrix operations, mutual influence relationships between indicators were precisely quantified, forming a logically structured assessment framework. Subsequently, the ANP method was introduced to construct a dual-layer network structure consisting of control and network layers. This enabled in-depth analysis of interdependencies among the 14 secondary indicators. A total of 52 judgment matrices were developed, and the weights of each indicator were determined through limit supermatrix calculations. The approach ensured the objectivity of the assessment process, with the resulting weight distribution providing scientific basis for formulating targeted resilience enhancement strategies.
- (3)
- The assessment system and model were validated through a case study of Xi’an Metro Line 1. Expert scoring was conducted to apply the established ANP network analysis model for urban underground rail transit fire resilience assessment in practical scenarios. The results demonstrated that resistance capacity (A) obtained the highest weight of 0.41855 among the four primary indicators. At the secondary indicator level, ‘fire cause investigation and assessment (D2)’ and ‘reflection on the accident and summary of lessons learned (D3)’ ranked first and second with global weights of 0.17763 and 0.16779 respectively, confirming their decisive role in enhancing the metro system’s overall resilience. Based on the weight distribution results, corresponding disaster-adaptive countermeasures were proposed. This practical application effectively verified the significant practical value of both the evaluation system and the analytical model.
- (4)
- The empirical validation was only carried out on Xi’an Metro Line 1, which leads to inherent limitations in the general applicability of the research conclusions. Specifically, the quantitative weight distribution of the model is affected by subway environmental factors, personnel management factors, and equipment operation factors in different scenarios. Therefore, such quantitative weight distribution should be regarded as a product of specific scenarios rather than a fixed rule with universal guiding significance. However, the adopted methodological framework (WSR-4M indicator integration and CIA-ANP quantification) still has general applicability, as it can customize resilience assessments according to the specific conditions of the local subway, such as environment, personnel management, and equipment operation. To advance this research, future work will focus on: ① Algorithmic optimization of the ANP model through machine learning integration to enable real-time resilience monitoring; ② Multi-system validation extending the framework to above-ground rail networks, airport terminals, and bus hubs to identify universal resilience principles; ③ Dynamic resilience management via IoT-enabled data fusion for predictive interventions. Methodologically, we will hybridize ANP with entropy weighting to reduce expert dependency and establish open-access incident datasets for benchmarking.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A. Regarding the Spray Equipment, Building Fire Prevention, Emergency Command for Staff, and the Judgment Matrix for the Cause of the Fire
Indicators | A1 | A2 | A4 |
---|---|---|---|
Temperature and smoke detection equipment A1 | 1 | 8 | 5 |
Ventilation and smoke extraction equipment A2 | 0.125 | 1 | 0.333333333 |
Surveillance equipment A4 | 0.2 | 3 | 1 |
Indicators | B1 | B3 | B4 |
---|---|---|---|
Internal material fire resistance rating B1 | 1 | 7 | 3 |
Off-site firefighting facilities B3 | 0.14286 | 1 | 0.2 |
The setting of fire partitions B4 | 0.33333 | 5 | 1 |
Indicators | D1 | D2 | D3 |
---|---|---|---|
Emergency repair and restoration D1 | 1 | 2 | 0.125 |
Fire cause investigation and assessment D2 | 0.5 | 1 | 0.142857143 |
Reflection on the accident and summary D3 | 8 | 7 | 1 |
Indicators | B1 | B2 | B3 | B4 |
---|---|---|---|---|
Internal material fire resistance rating B1 | 1 | 0.5 | 3 | 8 |
Fire protection in buildings B2 | 2 | 1 | 7 | 6 |
Off-site firefighting facilities B3 | 0.333333333 | 0.142857143 | 1 | 3 |
The setting of fire partitions B4 | 0.125 | 0.166666667 | 0.333333333 | 1 |
Appendix B. The Matrix Calculation Results Regarding the Sprinkler System, Building Fire Prevention, Emergency Command for Staff, and the Cause of the Fire
Indicators | A1 | A2 | A4 | Weighting | Sorting |
---|---|---|---|---|---|
Temperature and smoke detection equipment A1 | 1 | 8 | 5 | 0.741840 | 1 |
Ventilation and smoke extraction equipment A2 | 0.125 | 1 | 0.33333 | 0.075200 | 3 |
Surveillance equipment A4 | 0.2 | 3 | 1 | 0.182950 | 2 |
CI = 0.022.3 CR < 0.1 Consistency test passed |
Indicators | B1 | B3 | B4 | Weighting | Sorting |
---|---|---|---|---|---|
Internal material fire resistance rating B1 | 1 | 7 | 3 | 0.649120 | 1 |
Off-site firefighting facilities B3 | 0.14286 | 1 | 0.2 | 0.071930 | 3 |
The setting of fire partitions B4 | 0.33333 | 5 | 1 | 0.278950 | 2 |
CI = 0.03244 CR < 0.1 Consistency test passed |
Indicators | D1 | D2 | D3 | Weighting | Sorting |
---|---|---|---|---|---|
Emergency repair and restoration D1 | 1 | 2 | 0.125 | 0.129340 | 2 |
Fire cause investigation and assessment D2 | 0.5 | 1 | 0.14286 | 0.085180 | 3 |
Reflection on the accident and summary D3 | 8 | 7 | 1 | 0.785480 | 1 |
CI = 0.03821 CR < 0.1 Consistency test passed |
Indicators | B1 | B2 | B3 | B4 | Weighting | Sorting |
---|---|---|---|---|---|---|
Internal material fire resistance rating B1 | 1 | 0.5 | 3 | 8 | 0.321340 | 2 |
Fire protection in buildings B2 | 2 | 1 | 7 | 6 | 0.522680 | 1 |
Off-site firefighting facilities B3 | 0.33333 | 0.14286 | 1 | 3 | 0.106140 | 3 |
The setting of fire partitions B4 | 0.125 | 0.16667 | 0.33333 | 1 | 0.049840 | 4 |
CI = 0.05444 CR < 0.1 Consistency test passed |
Appendix C. Regarding Temperature and Smoke Sensing Equipment, Monitoring Equipment, External Fire-Fighting Facilities, Fire Safety Training, and the Judgment Matrix for Fire Causes
Temperature and Smoke Detection Equipment A1 | A2 | A4 |
---|---|---|
Ventilation and smoke extraction equipment A2 | 1 | 4 |
Surveillance equipment A4 | 0.25 | 1 |
Surveillance Equipment A4 | C2 | C3 |
---|---|---|
Staff emergency command capabilities C2 | 1 | 6 |
Emergency response plan C3 | 0.166667 | 1 |
Off-Site Firefighting Facilities B3 | D1 | D3 |
---|---|---|
Emergency repair and restoration D1 | 1 | 0.333333 |
Reflection on the accident and summary D3 | 3 | 1 |
Fire Safety Training and Awareness C1 | D1 | D2 | D3 |
---|---|---|---|
Emergency repair and restoration of professional capabilities D1 | 1 | 5 | 0.333333 |
Fire cause investigation and assessment D2 | 0.2 | 1 | 0.125 |
Reflection on the accident and summary of lessons learned D3 | 3 | 8 | 1 |
Fire Cause Investigation and Assessment D2 | B1 | B2 | B3 | B4 |
---|---|---|---|---|
Internal material fire resistance rating B1 | 1 | 0.5 | 3 | 8 |
Fire protection in buildings B2 | 2 | 1 | 7 | 6 |
Off-site firefighting facilities B3 | 0.333333 | 0.142857 | 1 | 3 |
The setting of fire partitions B4 | 0.125 | 0.166667 | 0.333333 | 1 |
Appendix D. Regarding Temperature and Smoke Sensing Equipment, Monitoring Equipment, External Fire-Fighting Facilities, Fire Safety Training, and the Matrix Calculation Results of Fire Causes
Indicators | A2 | A4 | Weighting | Sorting |
---|---|---|---|---|
Ventilation and smoke extraction equipment A2 | 1 | 4 | 0.800000 | 1 |
Surveillance equipment A4 | 0.25 | 1 | 0.200000 | 2 |
CR = 0 < 0.1 Consistency test passed |
Indicators | C2 | C4 | Weighting | Sorting |
---|---|---|---|---|
Staff emergency command capabilities C2 | 1 | 6 | 0.857140 | 1 |
Emergency response plan C3 | 0.16667 | 1 | 0.142860 | 2 |
CR = 0 < 0.1 Consistency test passed |
Indicators | D1 | D2 | Weighting | Sorting |
---|---|---|---|---|
Emergency repair and restoration D1 | 1 | 0.33333 | 0.250000 | 2 |
Reflection on the accident and Summary D3 | 3 | 1 | 0.750000 | 1 |
CR = 0 < 0.1 Consistency test passed |
Indicators | D1 | D2 | D3 | Weighting | Sorting |
---|---|---|---|---|---|
Emergency repair and restoration D1 | 1 | 0.5 | 0.25 | 0.12654 | 3 |
Fire cause investigation and assessment D2 | 2 | 1 | 0.2 | 0.18648 | 2 |
Reflection on the accident and summary D3 | 4 | 5 | 1 | 0.68698 | 1 |
CR < 0.1 Consistency test passed |
Indicators | D1 | D3 | Weighting | Sorting |
---|---|---|---|---|
Emergency repair and restoration D1 | 1 | 0.25 | 0.2 | 2 |
Reflection on the accident and summary D3 | 4 | 1 | 0.8 | 1 |
CR = 0 < 0.1 Consistency test passed |
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Characteristic Indicators | Definition | Key Role |
---|---|---|
Robustness | The basic resilience of the system in the event of a fire. | Improve the fire resistance of buildings. |
Redundancy | Enhance system reliability through backup facilities or resources. | Reducing the impact of accidents. |
Rapidity | Respond quickly after a disaster, allocate resources, and restore functionality. | Reduce functional downtime, minimize secondary disasters. |
Resourcefulness | Enhance fire response strategies. | Improve fire prevention efficiency and reduce the risk of human error. |
Adaptability | After a fire through design and management adjustments. | Enhance system flexibility. |
Recoverability | The comprehensive ability to maintain basic functions and quickly repair after a disaster. | Accelerate operational recovery and reduce long-term downtime losses. |
Primary Indicators | Fire Resilience | Secondary Indicators Analysis |
---|---|---|
Resistance capacity | Robustness | Temperature and smoke detection equipment |
Ventilation and smoke extraction equipment | ||
Automatic sprinkler systems | ||
Surveillance equipment | ||
Adaptability capacity | Redundancy Resourcefulness Adaptability | Internal material fire resistance rating |
Fire protection in buildings | ||
Off-site firefighting facilities | ||
The setting of fire partitions | ||
Absorptive capacity | Redundancy Resourcefulness | Fire safety training and awareness |
Staff emergency command capabilities | ||
Emergency response plan development | ||
Resilience capacity | Rapidity Recoverability | Emergency repair and restoration |
Fire cause investigation and assessment | ||
Reflection on the accident and summary |
Goal Level | Primary Indicators | Explanation of Primary Indicators | Secondary Indicators |
---|---|---|---|
Fire resilience Safety assessment system for urban underground rail transit | Resistance Capacity A | Ability to prevent the spread of fire and reduce damage to system functionality. | Temperature and smoke detection equipment A1 |
Ventilation and smoke extraction equipment A2 | |||
Automatic sprinkler systems A3 | |||
Surveillance equipment A4 | |||
Adaptability capacity B | The ability to mitigate the impact of a fire on system functionality through backup facilities | Internal material fire resistance rating B1 | |
Fire protection in Buildings B2 | |||
Off-site firefighting facilities B3 | |||
Setting of fire partitions B4 | |||
Absorptive capacity C | Ability to flexibly adjust operational strategies, based on the characteristics and progression of a fire. | Fire safety training and awareness C1 | |
Staff emergency command capabilities C2 | |||
Emergency response plan development, drills, and refinement C3 | |||
Resilience capacity D | Ability to quickly resume operations, repair damaged facilities and equipment. | Emergency repair and restoration of professional capabilities D1 | |
Fire cause investigation and assessment D2 | |||
Reflection on the accident and summary of lessons learned D3 |
Scale | Meaning |
---|---|
1 | The two elements are equally affected by the secondary criterion. |
3 | When comparing the two elements, the former is slightly larger than the latter due to the influence of the secondary criterion. |
5 | When comparing the two elements, the former is greater than the latter due to the influence of the secondary criterion. |
7 | When comparing the two elements, the former is significantly larger than the latter due to the influence of the secondary criterion. |
9 | When comparing the two elements, the former is greatly affected by the secondary criterion compared to the latter. |
2, 4, 6, 8 | The median value of the above adjacency judgment |
The reciprocal of the above value | If the ratio of the degree to which elements i and j are affected by the sub-criterion is a, then the ratio of the degree to which element j and element i are affected by the sub-criterion is 1/a. |
m | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
---|---|---|---|---|---|---|---|---|---|
RI | 0 | 0 | 0.52 | 0.89 | 1.12 | 1.26 | 1.36 | 1.41 | 1.46 |
Indicators | A1 | A2 | A3 | A4 | B1 | B2 | B3 | B4 | C1 | C2 | C3 | D1 | D2 | D3 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Temperature and smoke detection equipment A1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
Ventilation and smoke extraction equipment A2 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
Automatic sprinkler systems A3 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |
Surveillance equipment A4 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
Internal material fire resistance rating B1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 |
Fire protection in buildings B2 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 |
Off-site firefighting facilities B3 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 |
The setting of fire partitions B4 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 |
Fire safety training and awareness C1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
Staff emergency command capabilities C2 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
Emergency response plan C3 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 1 |
Emergency repair and restoration D1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 |
Fire cause investigation and assessment D2 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 1 |
Reflection on the accident and summary D3 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 |
Indicators | A1 | A2 | A3 | A4 | B1 | B2 | B3 | B4 | C1 | C2 | C3 | D1 | D2 | D3 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Temperature and smoke detection equipment A1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
Ventilation and smoke extraction equipment A2 | 1 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
Automatic sprinkler systems A3 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
Surveillance equipment A4 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 |
Internal material fire resistance rating B1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 |
Fire protection in buildings B2 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 | 1 |
Off-site firefighting facilities B3 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 |
The setting of fire partitions B4 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 |
Fire safety training and awareness C1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 |
Staff emergency command capabilities C2 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 |
Emergency response plan C3 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 |
Emergency repair and restoration D1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 |
Fire cause investigation and assessment D2 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 1 |
Reflection on the accident and summary D3 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 0 |
Primary Indicators | Weighting | Secondary Indicators | Local Weighting | Global Weighting | Sorting |
---|---|---|---|---|---|
Resistance capacity A | 0.41855 | Temperature and smoke detection equipment A1 | 0.36978 | 0.15477 | 4 |
Ventilation and smoke extraction equipment A2 | 0.37931 | 0.15876 | 3 | ||
Automatic sprinkler systems A3 | 0.08289 | 0.03469 | 8 | ||
Surveillance equipment A4 | 0.16803 | 0.07033 | 5 | ||
Adaptability capacity B | 0.1133 | Internal material fire resistance rating B1 | 0.13839 | 0.01568 | 13 |
Fire protection in buildings B2 | 0.61942 | 0.07018 | 6 | ||
Off-site firefighting facilities B3 | 0.04095 | 0.00464 | 14 | ||
The setting of fire partitions B4 | 0.20124 | 0.0228 | 10 | ||
Absorptive capacity C | 0.10115 | Fire safety training and awareness C1 | 0.18269 | 0.01848 | 12 |
Staff emergency command capabilities C2 | 0.28908 | 0.02924 | 9 | ||
Emergency response plan C3 | 0.52823 | 0.05343 | 7 | ||
Resilience capacity D | 0.367 | Emergency repair and restoration D1 | 0.05880 | 0.02158 | 11 |
Fire cause investigation and assessment D2 | 0.48401 | 0.17763 | 1 | ||
Reflection on the accident and summary D3 | 0.45719 | 0.16779 | 2 |
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Bai, Z.; Zhang, P.; Sun, L.; Li, B.; Zhang, J. Fire Resilience Assessment and Application in Urban Rail Transit Systems. Systems 2025, 13, 761. https://doi.org/10.3390/systems13090761
Bai Z, Zhang P, Sun L, Li B, Zhang J. Fire Resilience Assessment and Application in Urban Rail Transit Systems. Systems. 2025; 13(9):761. https://doi.org/10.3390/systems13090761
Chicago/Turabian StyleBai, Zujin, Pei Zhang, Linhui Sun, Boying Li, and Jing Zhang. 2025. "Fire Resilience Assessment and Application in Urban Rail Transit Systems" Systems 13, no. 9: 761. https://doi.org/10.3390/systems13090761
APA StyleBai, Z., Zhang, P., Sun, L., Li, B., & Zhang, J. (2025). Fire Resilience Assessment and Application in Urban Rail Transit Systems. Systems, 13(9), 761. https://doi.org/10.3390/systems13090761