Resilience Evaluation of High-Speed Railway Subgrade Construction Systems in Goaf Sites
Abstract
:1. Introduction
2. Resilience of High-Speed Railway Subgrade Construction Systems in Goaf Sites
2.1. Composition of High-Speed Railway Subgrade Construction Systems in Goaf Sites
2.2. Characteristic Elements of Resilience
2.2.1. Risk Resistance
2.2.2. Recovery Capability
2.2.3. Resilience Evaluation Indexes of High-Speed Railway Subgrade Construction Systems in Goaf Sites
3. ANP-Entropy Weight-Fuzzy Comprehensive Resilience Evaluation Model
3.1. ANP-Entropy Weight-Fuzzy Comprehensive Evaluation Theory
3.2. Construction of Resilience Evaluation Model for High-Speed Railway Subgrade Construction Systems in Goaf Sites
3.2.1. Construct Factor Sets
3.2.2. Establishment of Evaluation Sets
3.2.3. Establishment of Evaluation Matrix R
3.2.4. Weight Calculation
3.2.5. Fuzzy Comprehensive Evaluation
4. Case Application
4.1. Background of the Project
- (1)
- Characteristics of mined-out areas
- (2)
- Project management and emergency disposal
- (3)
- Staffing and mechanical equipment
- (4)
- Hydrogeological and climatic conditions
4.2. Determination of Index Weight
4.3. Fuzzy Comprehensive Evaluation Based on Comprehensive Weights
4.4. Weight Analysis of Resilience Index
5. Discussion
6. Conclusions
- (1)
- The introduction of resilience theory provides new ideas and methods for safety management of high-speed railway construction sites above goaf. Combined with the system composition and characteristic elements, the evaluation index system of high-speed railway subgrade construction system resilience in goaf sites was established, which includes four first-level indexes and 25 second-level indexes, covering the four elements of labor, machinery, environment and management and different dimensions of system resilience in construction, meaning that the result has a high credibility.
- (2)
- We used the ANP-entropy weight-fuzzy evaluation model to evaluate resilience. This model not only considers the possible interrelationship among various resilience indexes, reduces the possibility that the weight calculation is greatly affected by the subjective and is thus inaccurate, but also takes into account the fuzziness and randomness of the index boundaries, therefore, the scientificity of the evaluation process and evaluation results are ensured.
- (3)
- The resilience grade of the Taijiao high-speed railway subgrade construction was evaluated, and the result is “high resilience”, indicating that under the influence of goaf, the system can return to a normal safety state from the impacts within a certain time. Through the determination of resilience grade, the indicators’ weight calculation and the introduction of optimization measures were carried out. Finally, the research results provide new safety management ideas for high-speed railway projects constructed in mined-out areas from the perspective of sustainability, and optimize the results-oriented safety risk management mode, which is beneficial for improving the safety resilience and risk resistance level of the construction site.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- TB 10012-2019; State Railway Administration Code for geological survey of Railway Engineering. China Railway Publishing House Co., Ltd.: Beijing, China, 2019.
- Yan, D. Safety Impact Assessment of Ancient City Coal Mine Goaf on Hequ Section of Lunan High Speed Railway; China Railway Siyuan Survey and Desig Group Co., Ltd.: Beijing, China, 2019. [Google Scholar]
- Yang, W.X. Investigation and Treatment of Mined-Out Area of Coal Mine under Expressway. Master’s Thesis, Chang’an University, Xi’an, China, April 2005. [Google Scholar]
- Holling, C.S. Resilience and Stability of Ecological Systems. Annu. Rev. Ecol. Evol. Syst. 1973, 4, 23. [Google Scholar] [CrossRef] [Green Version]
- Mo, J.W.; Teng, C.G.; Li, J.; Zhong, J.D. Resilience evaluation of high-speed railway construction engineering system based on entropy weight two-dimensional cloud model. Railw. Sci. Eng. 2022, 19, 26–33. [Google Scholar]
- Wears, R.L. Resilience Engineering: Concepts and Precepts. Qual. Saf. Health Care 2006, 15, 447. [Google Scholar] [CrossRef] [Green Version]
- Hughes, L. The effects of event occurrence and duration on resilience and adaptation in energy systems. Energy 2015, 84, 443–454. [Google Scholar] [CrossRef]
- Liu, J.Y.; Zeng, Z.P. Construction of evaluation index system of elastic city and its empirical research. E-government 2014, 11, 82–88. [Google Scholar]
- Zhao, Y.Y.; Ma, W.Z.; Wen, H.Y. Resilience evaluation of tunnel construction emergency system. J. Civ. Eng. Manag. 2021, 38, 167–172. [Google Scholar]
- Hao, Q.W. Study on Resilience Evaluation of Safety System in Subway Construction Site. Master’s Thesis, Xi’an Technological University, Xi’an, China, May 2019. [Google Scholar]
- Huang, L.; Wu, C.; Yang, M.; Wang, B. Application of resilience theory in safety science. China Saf. Sci. J. 2017, 27, 1–6. [Google Scholar]
- Bai, Y. Operation Safety Risk Analysis and Resilience Evaluation of Changji High Speed Railway. Master’s Thesis, Jilin University, Changchun, China, August 2020. [Google Scholar]
- Li, T.Y. New progress in research on resilient cities. Int. Urban Plann. 2017, 32, 15–25. [Google Scholar] [CrossRef]
- Jiang, X.; Sun, Z.X.; Xu, P.; Liu, L. Vulnerability assessment of emergency management system in hydropower project construction stage. J. Saf. Sci. Technol. 2016, 12, 142–147. [Google Scholar]
- Chen, L. Research on System Vulnerability of Green Building Project in Construction Stage Based on System Dynamics. Master’s Thesis, Jiangxi University of Finance and Economics, Nanchang, China, June 2021. [Google Scholar]
- Zhong, S.L. Study on Resilience Evaluation of Highway Tunnel Construction System. Master’s Thesis, Chongqing Jiaotong University, Chongqing, China, April 2021. [Google Scholar]
- Leire, L.; Josune, H.; Jose, M.S. Resilience framework for critical infrastructures: An empirical study in a nuclear plant. Reliab. Eng. Syst. Saf. 2015, 141, 92–105. [Google Scholar]
- Bruneau, M.; Stephanie, E.C.; Ronald, T.E.; George, C.L.; O’Rourke, T.D. A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities. Earthq. Spectra 2003, 19, 733–752. [Google Scholar] [CrossRef] [Green Version]
- Zobel, C.W. Representing perceived tradeoffs in defining disaster resilience. Decis. Support Syst. 2010, 50, 394–403. [Google Scholar] [CrossRef]
- Gibson, C.A.; Tarrant, M. A ‘conceptual models’ approach to organisational resilience. Aust. J. Emerg. Manag. 2010, 25, 6–12. [Google Scholar]
- Ahern, J. Novel Urban Ecosystems: Concepts, Definitions and a Strategy to Support Urban Sustainability and Resilience. Landsc. Archit. Front. 2016, 4, 10–21. [Google Scholar]
- Shu, C.Y. Quantitative Evaluation Method of Social Resilience in Urban Communities from the Perspective of Capital. Master’s Thesis, Southeast University, Nanjing, China, June 2019. [Google Scholar]
- Guo, Q.J.; Hao, Q.W.; Wang, Y.J.; Wang, J. Evaluation of subway system toughness based on ANP-extendable cloud model. J. Syst. Simul. 2021, 33, 943–950. [Google Scholar]
- Esfandi, S.; Rahmdel, L.; Nourian, F.; Sharifi, A. The role of urban spatial structure in energy resilience: An integrated assessment framework using a hybrid factor analysis and analytic network process model. Sustain. Cities Soc. 2022, 76, 103458. [Google Scholar] [CrossRef]
- Datola, G.; Bottero, M.; Angelis, E. Enhancing Urban Resilience Capacities: An Analytic Network Process-based Application. Environ. Clim. Technol. 2021, 25, 1270–1283. [Google Scholar] [CrossRef]
- Bi, W. Research on Fire Toughness Identification and Measurement of Biwei Urban Subway Station System. Master’s Thesis, Southeast University, Nanjing, China, May 2020. [Google Scholar]
- Wang, Q.L.; Ke, Y.H.; Gao, Y.M.; Cheng, C.; Wang, Y.H.; Lin, J.X. Toughness analysis of high-speed rail time series network under disaster space-time attribute. J. Xidian Univ. 2022, 68, 1–11. [Google Scholar]
- Liu, D.; Xu, L.; Zhu, W.F. Evaluation of regional agricultural water resources resilience based on optimal combination weighting and improved TOPSIS model. J. Northeast Agric. Univ. 2019, 50, 86–96. [Google Scholar]
- Liu, C.Y.; Shang, S.; Zhao, Q.; Xie, H. Assessment of resilience after flood disaster in Hunan Province based on GIS and TOPSIS-PSR. Water Power Energy Sci. 2018, 36, 70–73. [Google Scholar]
- Tang, Y.C.; Bi, W.; Varga, L.; Dolan, T.; Li, Q.M. An integrated framework for managing fire resilience of metro station system: Identification, assessment, and optimization. Int. J. Disaster Risk Reduct. 2022, 77, 103037. Available online: https://www.sciencedirect.com/science/article/pii/S2212420922002564?via%3Dihub (accessed on 12 May 2022). [CrossRef]
- Qiao, H.; Pei, J.J. Urban Stormwater Resilience Assessment Method Based on Cloud Model and TOPSIS. Int. J. Environ. Res. Public Health 2021, 19, 38. [Google Scholar] [CrossRef] [PubMed]
- Wang, S.L.; Na, R.; Guo, E.L.; Teliger, B.; Cheng, Z.Y.; Bai, J.W. Based on entropy weight TOPSIS model city of Inner Mongolia toughness evaluation study. J. Chifeng Inst. (Nat. Sci. Ed.) 2022, 38, 17–21. [Google Scholar]
- Luo, H.; Liu, J.; Xu, J.C.; Wang, L.; Tang, Z.Y.; Suo, G.Y. Method based on entropy weight of qinling area rural community climate resilience assessment. J. Nat. Disasters 2022, 31, 111–118. [Google Scholar]
- Mo, J.W.; Teng, C.G.; Li, J.; Zhong, J.D. Two dimensional cloud model based on entropy weight of high iron toughness evaluation. J. Constr. Eng. Syst. Railr. J. Sci. Eng. 2022, 12, 26–33. [Google Scholar]
- Hong, T.; Wang, B.; Li, L.L.; Gou, X.J. The Coupling Relationship between Urban Resilience Level and Urbanization Level in Hefei. Math. Probl. Eng. 2022, 2022, 7339005. [Google Scholar] [CrossRef]
- Jiao, L.D.; Deng, J.L.; Wu, Y.; Huo, X.S. Evaluation of urban resilience based on PSR + cloud model. Eco-Economy 2022, 38, 114–120. [Google Scholar]
- Yang, S.; Huo, Q.F. Toughness Evaluation of Subway Operation System Based on Extension Cloud Theory. J. Chongqing Jiaotong Univ. (Soc. Sci. Ed.) 2022, 22, 44–52. [Google Scholar]
- Guo, Y.Y.; Luo, F.Z.; Zhong, X.R. Evaluation of urban safety resilience based on entropy weight-normal cloud model. Disaster Sci. 2021, 36, 168–174. [Google Scholar]
- Li, Z.J.; Zhao, H.; Liu, J.N.; Zhang, J.Q.; Shao, Z.G. Evaluation and promotion strategy of resilience of urban water supply system under flood and drought disasters. Sci. Rep. 2022, 12, 7404. Available online: https://www.nature.com/articles/s41598-022-11436-w#citeas (accessed on 6 May 2022). [CrossRef]
- Chakravarthi, S.S.; Kannan, R.J.; Natarajan, V.A.; Gao, X.Z. Deep Learning Based Intrusion Detection in Cloud Services for Resilience Management. Comput. Mater. Contin. 2022, 71, 5117–5133. [Google Scholar]
- Li, S.Q.; Wu, X.Y.; Yuan, X.M.; Zhou, Y. BP-SD Simulation Study on Safety System Vulnerability of Construction Enterprises. Chin. J. Saf. Sci. 2014, 24, 26–32. [Google Scholar]
- Yan, X.X.; Wang, J.L.; Fan, L.; Li, W.C. Subway flood risk analysis from the perspective of resilient city based on Bow-Tie-Bayesian network model. Disaster 2022, 37, 36–43. [Google Scholar]
- Hu, Y.; Guo, J.; Pei, X.R. Analysis of resilience of railway system under disaster risk. J. Wuhan Light Ind. Univ. 2022, 41, 72–79. [Google Scholar]
- Sen, M.K.; Dutta, S. A Bayesian Network Modeling Approach for Time-Varying Flood Resilience Assessment of Housing Infrastructure System. Nat. Hazards Rev. 2022, 23, 04022006. [Google Scholar] [CrossRef]
- Luo, C.; Qi, C.M.; Bu, B. Vulnerability simulation analysis of building construction safety system based on system dynamics. Saf. Environ. Eng. 2021, 28, 1–7, 43. [Google Scholar]
- Weng, Y.N.; Lu, Y.; Wang, M.; Xu, T.K.; Zhang, X.; Zhang, L. Research on comprehensive evaluation system of safety management ability of Beijing Metro. Urban Rapid Rail. Tr. 2015, 28, 49–54. [Google Scholar]
- Zhang, H.M.; Yang, J.Y.; Li, L.S.; Shen, D.Y.; Wei, G.; Khan, H.R.; Dong, S.J. Measuring the resilience to floods: A comparative analysis of key flood control cities in China. Int. J. Disaster Risk Reduct. 2021; Unpublished work. [Google Scholar]
- Melissa, P.; Ian, R.; James, M.; Peter, H.; Graham, R.M.; Judith, M.; Richard, S.; Sonya, G. Disaster resilience in Australia: A geographic assessment using an index of coping and adaptive capacity. Int. J. Disast. Risk. Reduct. 2021; Unpublished work. [Google Scholar]
- Tong, L.Y.; Qiu, Y.; Du, G.Y.; Huang, W.; Liu, S.Y. Experimental study on treatment of multi-layer goaf by grouting and filling method under expressway. J. Highw. Transp. Res. Dev. 2002, 19, 19–22, 27. [Google Scholar]
- Jian, B. Organization and management of mining construction safety in goaf. Heilongjiang Sci. Technol. Inf. 2016, 20, 69. [Google Scholar]
- Wu, G.S. Research on Safety Risk Management of Yunzaobang Bridge Crossing Existing Railway Construction of Beijing-Shanghai High Speed Railway. Master’s Thesis, Southwest Jiaotong University, Chengdu, China, May 2013. [Google Scholar]
- Mu, W.G.; Han, G.L.; Gao, X.L.; Li, P.; Zhang, C.S. Impact analysis of adjacent deep coal mine goaf on Lunan high speed railway. Railw. Surv. 2022, 48, 29–33. [Google Scholar]
- Li, G.H.; Li, G.F. Study on railway engineering geological route selection in goaf. J. Railw. Eng. Soc. 2012, 29, 15–20, 100. [Google Scholar]
- Ren, L.W.; Ning, H.; Zou, Y.F.; Dun, Z.L.; Guo, W.B.; Tian, Z.F. Research status and Prospect of subgrade deformation control of high-speed railway in goaf. Chin. Coal. Soc. 2021, 46, 2534–2547. [Google Scholar]
- Huang, Q. Research on System Resilience Evaluation of Urban Rail Transit Construction Engineering. Master’s Thesis, Fujian University of Technology, Fuzhou, China, July 2019. [Google Scholar]
- Xun, X.L.; Yuan, Y.B. Research on the urban resilience evaluation with hybrid multiple attribute TOPSIS method: An example in China. Nat. Hazards. 2020, 103, 557–577. [Google Scholar] [CrossRef]
- Song, Y.; Huang, Z.L.; Xu, Y.X. Study on urban resilience evaluation and resilience construction path based on TOPSIS entropy weight method—A case study of Anhui Province. J. Anhui Agric. Univ. 2021, 30, 100–105. [Google Scholar]
- Liu, M.; Tiao, J.F. Determination of the Weight of Urban Resilience Evaluation Index from the Perspective of Disaster Prevention. Int. J. Social Sci. Educ. Res. 2022, 5, 17–32. [Google Scholar]
- Liu, L.; Zhou, J.Z.; An, X.L.; Zhang, Y.C.; Yang, L. Using fuzzy theory and information entropy for water quality assessment in Three Gorges region, China. Expert. Syst. Appl. 2009, 37, 2517–2521. [Google Scholar] [CrossRef]
- Guan, F.J. Multi dimensional spatiotemporal goaf route selection and survey evaluation of Taijiao railway. J. Railway. Eng. Soc. 2020, 37, 11–16. [Google Scholar]
- Bai, Z.X. Environmental Impact Report of the New Taiyuan Jiaozuo Intercity Railway; Daxi Railway Passenger Dedicated Line Co., Ltd.: Taiyuan, China, 2016. [Google Scholar]
- Zheng, G.; Cheng, X.S.; Zhou, H.Z.; Gang, Z.; Zhang, T.Q.; Diao, Y.; Wang, R.Z.; Yi, F.; Guo, W. Evaluation and Control of Structural Toughness of Geotechnical and Underground Engineering. Chin. Civi. Eng. J. 2022, 7, 1–39. [Google Scholar]
- Ren, W.X.; Jin, Q.W. Structure robustness, redundancy and vulnerability. J. Harbin. Inst. Technol. 2018, 50, 1–10. [Google Scholar]
- Peng, X.; Li, D.Q.; Cao, Z.J.; Gong, W.P.; Juang, C.H. Reliability- based robust geotechnical design using Monte Carlo simulation. Bull Eng. Geol. Environ. 2017, 76, 1217–1227. [Google Scholar] [CrossRef]
- Jiang, J.; Cao, Y.F.; Zhang, Q.J.; Lv, D.G.; Lu, X.Z.; Li, G.Q.; Ye, J.H. Research progress on quantitative determination method of building structure robustness. Prog. Steel. Build. Struct. 2022, 24, 1–21. [Google Scholar]
- Lin, J.X. Simulation Analysis and Optimization of Geotechnical Robustness in Foundation Pit Engineering. Master’s Thesis, Shijiazhuang Tiedao University, Shijiazhuang, China, June 2019. [Google Scholar]
Organization Member System | Material Technology System | Management System | Environment System | |
---|---|---|---|---|
Stability B1 | Safety cognition ability of personnel C1 [10,16] Professional skills of personnel C2 [10] Physical and mental state of personnel C3 [10] | Quality of material C4 [15,55] Supply and quality of Material C5 [15,55] Status and performance of mechanical equipment C6 [16] Construction specification C7 Construction technique C8 | Rules and regulations C9 [12] | Environmental risk assessment and countermeasures C10 [12] Surrounding environment and working environment C11 [56] |
Redundancy B2 | Redundancy of facilities equipment C12 Redundancy of emergency facilities and material reserves C13 Monitoring system of subgrade deformation C14 | Emergency and safeguarding of accidents C15 | ||
Efficiency B3 | Emergency rescue ability of personnel C16 | Ability to deal with environmental emergencies C17 [12] | Emergency management mechanism C18 [14] Emergency organization efficiency C19 [16] Emergency program C20 [15,55] | Emergency corridors and shelters C21 |
AdaptabilityB4 | Emergency response drill C22 [16] Safety education and training of personnel C23 [12] | Emergency apparatus C24 [15] | Characteristics of goaf C25 |
Target | First Grade Indexes | Weight | Second Grade Indexes | Weights | Subjective Weights | Sort |
---|---|---|---|---|---|---|
A Resilience of High-Speed Railway Subgrade Construction System in Mined-Out Area | Stability B1 | 0.4559 | Safety cognition ability of personnel C1 | 0.0227 | 0.0057 | 21 |
Professional skills of personnel C2 | 0.1077 | 0.0269 | 15 | |||
Physical and mental state of personnel C3 | 0.0118 | 0.0030 | 24 | |||
Quality of material C4 | 0.0121 | 0.0030 | 23 | |||
Supply of material C5 | 0.0221 | 0.0055 | 22 | |||
Status and performance of mechanical equipment C6 | 0.0438 | 0.0109 | 20 | |||
Construction specification C7 | 0.0498 | 0.0124 | 18 | |||
Construction technique C8 | 0.1176 | 0.0294 | 13 | |||
Rules and regulations C9 | 0.1197 | 0.0299 | 12 | |||
Environmental risk assessment and countermeasures C10 | 0.3929 | 0.0981 | 2 | |||
Surrounding environment and working environment C11 | 0.0998 | 0.0249 | 17 | |||
Redundancy B2 | 0.1301 | Redundancy of facility equipment C12 | 0.0084 | 0.0011 | 25 | |
Redundancy of emergency facilities and material reserves C13 | 0.2099 | 0.0273 | 14 | |||
Monitoring system of subgrade deformation C14 | 0.4603 | 0.0598 | 8 | |||
Emergency and safeguarding of accidents C15 | 0.3214 | 0.0418 | 11 | |||
Efficiency B3 | 0.1849 | Emergency rescue ability of personnel C16 | 0.0372 | 0.0113 | 19 | |
Ability to deal with environmental emergencies C17 | 0.3859 | 0.1170 | 1 | |||
Emergency management mechanism C18 | 0.1989 | 0.0603 | 7 | |||
Emergency organization efficiency C19 | 0.1449 | 0.0439 | 10 | |||
Emergency program C20 | 0.1471 | 0.0446 | 9 | |||
Emergency corridors and shelters C21 | 0.0861 | 0.0261 | 16 | |||
Adaptability B4 | 0.2291 | Emergency response drill C22 | 0.2601 | 0.0825 | 4 | |
Safety education and training of personnel C23 | 0.2854 | 0.0905 | 3 | |||
Emergency apparatus C24 | 0.1988 | 0.0630 | 6 | |||
Characteristics of goaf C25 | 0.2557 | 0.0811 | 5 |
First Grade Indexes | Weight | Second Grade Indexes | Objective Weights | Sort |
---|---|---|---|---|
Stability B1 | 0.4412 | Safety cognition ability of personnel C1 | 0.0383 | 15 |
Professional skills of personnel C2 | 0.0478 | 1 | ||
Physical and mental state of personnel C3 | 0.0376 | 20 | ||
Quality of material C4 | 0.0401 | 10 | ||
Supply of material C5 | 0.0459 | 3 | ||
Status and performance of mechanical equipment C6 | 0.0378 | 18 | ||
Construction specification C7 | 0.0368 | 21 | ||
Construction technique C8 | 0.0398 | 11 | ||
Rules and regulations C9 | 0.0408 | 8 | ||
Environmental risk assessment and countermeasures C10 | 0.0417 | 7 | ||
Surrounding environment and working environment C11 | 0.0346 | 24 | ||
Redundancy B2 | 0.1719 | Redundancy of facility equipment C12 | 0.0452 | 4 |
Redundancy of emergency facilities and material reserves C13 | 0.0467 | 2 | ||
The monitoring system of subgrade deformation C14 | 0.0417 | 6 | ||
Emergency and safeguarding of accidents C15 | 0.0383 | 16 | ||
Efficiency B3 | 0.2298 | Emergency rescue ability of personnel C16 | 0.0382 | 17 |
Ability to deal with environmental emergencies C17 | 0.0364 | 23 | ||
Emergency management mechanism C18 | 0.0387 | 14 | ||
Emergency organization efficiency C19 | 0.0402 | 9 | ||
Emergency program C20 | 0.0395 | 13 | ||
Emergency corridors and shelters C21 | 0.0368 | 22 | ||
Adaptability B4 | 0.1569 | Emergency response drill C22 | 0.0346 | 25 |
Safety education and training of personnel C23 | 0.0377 | 19 | ||
Emergency apparatus C24 | 0.0451 | 5 | ||
Characteristics of goaf C25 | 0.0395 | 12 |
First Grade Indexes | Weight | Second Grade Indexes | Comprehensive Weights | Sort |
---|---|---|---|---|
Stability B1 | 0.3456 | Safety cognition ability of personnel C1 | 0.0220 | 23 |
Professional skills of personnel C2 | 0.0373 | 12 | ||
Physical and mental state of personnel C3 | 0.0203 | 25 | ||
Quality of material C4 | 0.0216 | 24 | ||
Supply of material C5 | 0.0257 | 18 | ||
Status and performance of mechanical equipment C6 | 0.0244 | 21 | ||
Construction specification C7 | 0.0246 | 20 | ||
Construction technique C8 | 0.0346 | 15 | ||
Rules and regulations C9 | 0.0354 | 14 | ||
Environmental risk assessment and countermeasures C10 | 0.0699 | 2 | ||
Surrounding environment and working environment C11 | 0.0298 | 17 | ||
Redundancy B2 | 0.1509 | Redundancy of facility equipment C12 | 0.0231 | 22 |
Redundancy of emergency facilities and material reserves C13 | 0.0370 | 13 | ||
The monitoring system of subgrade deformation C14 | 0.0508 | 7 | ||
Emergency and safeguarding of accidents C15 | 0.0400 | 11 | ||
Efficiency B3 | 0.2665 | Emergency rescue ability of personnel C16 | 0.0247 | 19 |
Ability to deal with environmental emergencies C17 | 0.0767 | 1 | ||
Emergency management mechanism C18 | 0.0495 | 8 | ||
Emergency organization efficiency C19 | 0.0421 | 9 | ||
Emergency program C20 | 0.0420 | 10 | ||
Emergency corridors and shelters C21 | 0.0315 | 16 | ||
Adaptability B4 | 0.237 | Emergency response drill C22 | 0.0585 | 5 |
Safety education and training of personnel C23 | 0.0641 | 3 | ||
Emergency apparatus C24 | 0.0541 | 6 | ||
Characteristics of goaf C25 | 0.0603 | 4 |
Grade | Grade Description | |
---|---|---|
1 | Very Low Resilience | Under the influence of goaf, the system has poor resistance ability and absorption ability to the possible risks in the process of subgrade construction. After the risk impacts, the ability of recovery and adaptability of the system is insufficient. It will take a long time for the system to recover from the impacts. |
2 | Low Resilience | Under the influence of goaf, the system has poor resistance ability and absorption ability to the possible risks during subgrade construction, poor ability of recovery and adaptability after risk impacts, and it will take a certain time for the system to recover from the impacts. |
3 | Middle Resilience | Under the influence of goaf, the system has poor resistance ability and absorption ability to the possible risks in the process of subgrade construction. After the risk impacts, the system has a good ability of recovery and adaptability, and the system can recover from the impacts in a certain time. |
4 | High Resilience | Under the influence of goaf, the system has better resistance ability and absorption ability to the possible risks in the process of subgrade construction and has a better ability of recovery and adaptability after the risk impacts. The system can return to normal safety state from the impacts in a certain time. |
5 | Very High Resilience | Under the influence of goaf, the system has good resistance ability and absorption ability to the possible risks in the process of subgrade construction, and has a good ability of recovery and adaptability after the risk impacts. The system can recover from the impacts in a certain period of time. |
Second Grade indexes | Very High Resilience (100–90) | High Resilience (89–80) | Middle Resilience (79–70) | Low Resilience (69–60) | Very Low Resilience (59–0) |
---|---|---|---|---|---|
Safety cognition ability of personnel C1 | 12 | 2 | |||
Professional skills of personnel C2 | 2 | 10 | 2 | ||
Physical and mental state of personnel C3 | 9 | 4 | 2 | ||
Quality of material C4 | 10 | 4 | |||
Supply of material C5 | 9 | 5 | |||
Status and performance of mechanical equipment C6 | 8 | 5 | 1 | ||
Construction specification C7 | 1 | 10 | 3 | ||
Construction technique C8 | 9 | 5 | |||
Rules and regulations C9 | 1 | 9 | 4 | ||
Environmental risk assessment and countermeasures C10 | 2 | 11 | 1 | ||
Surrounding environment and working environment C11 | 8 | 6 | |||
Redundancy of facility equipment C12 | 11 | 3 | |||
Redundancy of emergency facilities and material reserves C13 | 2 | 10 | 2 | ||
The monitoring system of subgrade deformation C14 | 4 | 8 | 2 | ||
Emergency and safeguarding of accidents C15 | 3 | 8 | 3 | ||
Emergency rescue ability of personnel C16 | 10 | 3 | 1 | ||
Ability to deal with environmental emergencies C17 | 2 | 12 | |||
Emergency management mechanism C18 | 1 | 7 | 6 | ||
Emergency organization efficiency C19 | 3 | 8 | 3 | ||
Emergency program C20 | 3 | 6 | 5 | ||
Emergency corridors and shelters C21 | 5 | 9 | |||
Emergency response drill C22 | 2 | 8 | 4 | ||
Safety education and training of personnel C23 | 9 | 5 | |||
Emergency apparatus C24 | 3 | 10 | 1 | ||
Characteristics of goaf C25 | 10 | 4 |
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Wang, H.; Zhou, J.; Dun, Z.; Cheng, J.; Li, H.; Dun, Z. Resilience Evaluation of High-Speed Railway Subgrade Construction Systems in Goaf Sites. Sustainability 2022, 14, 7806. https://doi.org/10.3390/su14137806
Wang H, Zhou J, Dun Z, Cheng J, Li H, Dun Z. Resilience Evaluation of High-Speed Railway Subgrade Construction Systems in Goaf Sites. Sustainability. 2022; 14(13):7806. https://doi.org/10.3390/su14137806
Chicago/Turabian StyleWang, Hui, Jing Zhou, Zhiyuan Dun, Jianhua Cheng, Hujun Li, and Zhilin Dun. 2022. "Resilience Evaluation of High-Speed Railway Subgrade Construction Systems in Goaf Sites" Sustainability 14, no. 13: 7806. https://doi.org/10.3390/su14137806