|Table of Contents|

[1] Lu Zheng, Yan Deyu, Jiang Huanjun, et al. Earthquake disaster chain model based on complex networks for urban engineering systems [J]. Journal of Southeast University (English Edition), 2024, 40 (3): 230-237. [doi:10.3969/j.issn.1003-7985.2024.03.002]
Copy

Earthquake disaster chain model based on complex networks for urban engineering systems()
Share:

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
40
Issue:
2024 3
Page:
230-237
Research Field:
Civil Engineering
Publishing date:
2024-09-20

Info

Title:
Earthquake disaster chain model based on complex networks for urban engineering systems
Author(s):
Lu Zheng1 2 Yan Deyu1 Jiang Huanjun1 2
1Department of Disaster Mitigation for Structures, Tongji University, Shanghai 200092, China
2State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China
Keywords:
earthquake disaster chain seismic resilience secondary disaster complex network vulnerability risk level
PACS:
TU312
DOI:
10.3969/j.issn.1003-7985.2024.03.002
Abstract:
According to news reports on severe earthquakes since 2008, a total of 51 cases with magnitudes of 6.0 or above were analyzed, and 14 frequently occurring secondary disasters were identified. A disaster chain model was developed using principles from complex network theory. The vulnerability and risk level of each edge in this model were calculated, and high-risk edges and disaster chains were identified. The analysis reveals that the edge “floods→building collapses” has the highest vulnerability. Implementing measures to mitigate this edge is crucial for delaying the spread of secondary disasters. The highest risk is associated with the edge “building collapses→casualties, ” and increased risks are also identified for chains such as “earthquake→building collapses→casualties, ” “earthquake→landslides and debris flows→dammed lakes, ” and “dammed lakes→floods→building collapses.” Following an earthquake, the prompt implementation of measures is crucial to effectively disrupt these chains and minimize the damage from secondary disasters.

References:

[1] Ding Y, Dong Y Q, Shi Y D, et al. State-of-the-art on seismic isolation of long-span spatial structures[J]. Journal of Southeast University(Natural Science Edition), 2023, 53(5): 857-868. DOI:10.3969/j.issn.1001-0505.2023.05.013. (in Chinese)
[2] Lu Z, Yan D Y, Zhou M Y, et al. Vulnerability analysis of a complex super high-rise connected structure under the combined action of earthquake and wind[J]. Journal of Southeast University(English Edition), 2024, 40(1): 13-23. DOI: 10.3969/j.issn.1003-7985.2024.01.002.
[3] Yi C X, Shi P J. Entropy generation and natural disasters[J].Journal of Beijing Normal University(Natural Science), 1994, 30(2): 276-280.(in Chinese)
[4] Wang D. Network model of emergency events based on correlation[D]. Dalian: Dalian University of Technology, 2013.(in Chinese)
[5] Zhang Y L, Zhang J P, Ren A Z, et al. Multiple disaster coupled prediction modeling using multi-agent models[J]. Journal of Tsinghua University(Science and Technology), 2011, 51(2): 198-203. DOI:10.16511/j.cnki.qhdxxb.2011.02.008. (in Chinese)
[6] Li Y J, Wang X Q, Qiao X J. Modeling evolution of seismic secondary disasters with stochastic petri nets[J]. Operations Research and Management Science, 2014, 23(4): 264-273. DOI:10.3969/j.issn.1007-3221.2014.04.034. (in Chinese)
[7] Xie Z L. Evolution mechanism and cooperated emergency management mechanism for urban post-earthquake disasters[D]. Chengdu: Southwest Jiaotong University, 2011.(in Chinese)
[8] Ma Z J, Xie Z L. Evolution mechanism of earthquake-induced urban disasters based on Bayesian networks[J]. Journal of Catastrophology, 2012, 27(4): 1-5, 24. DOI:10.3969/j.issn.1000-811X.2012.04.001. (in Chinese)
[9] Wang J X, Gu X Y, Huang T R. Using Bayesian networks in analyzing powerful earthquake disaster chains[J].Natural Hazards, 2013, 68(2): 509-527. DOI: 10.1007/s11069-013-0631-0.
[10] Han L N, Zhang J Q, Zhang Y C, et al. Hazard assessment of earthquake disaster chains based on a Bayesian network model and ArcGIS[J].ISPRS International Journal of Geo-Information, 2019, 8(5): 210. DOI: 10.3390/ijgi8050210.
[11] Kabir G, Suda H, Cruz A M, et al. Earthquake-related Natech risk assessment using a Bayesian belief network model[J]. Structure and Infrastructure Engineering, 2019, 15(6): 725-739. DOI: 10.1080/15732479.2019.1569070.
[12] Liang Y. Multi-hazard risk assessment and emergency decision of urban underground infrastructure based on Bayesian network and knowledge graph[D]. Harbin: Harbin Institute of Technology, 2021.(in Chinese)
[13] Fang D H, Yu K, Wan D Y, et al. Scenario evolution analysis of earthquake secondary disasters based on Bayesian network[J].Journal of Wuhan University of Technology(Information & Management Engineering), 2021, 43(6): 493-499. DOI:10.3963/j.issn.2095-3852.2021.06.001. (in Chinese)
[14] Liu A H. Research on the dynamics evolution model of urban disaster chain and the risk assessment method of disaster chain[D]. Changsha: Central South University, 2013.(in Chinese)
[15] Liu L, Xu H, Li S M. Review on the scenario and scenario-response theory for unconventional emergency management[J]. Journal of UESTC(Social Sciences Edition), 2013, 15(6): 20-24. DOI:10.14071/j.1008-81052013.06.008. (in Chinese)
[16] Tang P, Xia Q, Wang Y Y. Addressing cascading effects of earthquakes in urban areas from network perspective to improve disaster mitigation[J]. International Journal of Disaster Risk Reduction, 2019, 35: 101065. DOI: 10.1016/j.ijdrr.2019.101065.
[17] Chen J, Zhang Y, Liu L. Vulnerability analysis of multimodal transport networks based on complex network theory[J]. Journal of Southeast University(English Edition), 2021, 37(2): 209-215. DOI: 10.3969/j.issn.1003-7985.2021.02.011.
[18] Yin Y, Wang S X. Dependency-based importance measures of components in mechatronic systems with complex network theory[J]. Journal of Southeast University(English Edition), 2022, 38(2): 137-144. DOI: 10.3969/j.issn.1003-7985.2022.02.005.
[19] Xiong W, Zhang D N, Ma X L, et al. Review of resilience assessment in urban floods on transportation road network infrastructures[J]. Journal of Southeast University(Natural Science Edition), 2024, 54(2): 329-345. DOI:10.3969/j.issn.1001-0505.2024.02.010. (in Chinese)
[20] Zhang L, Lu J, Lei D. Vulnerability analysis of bus-metro composite network based on complex network and spatial information embedding[J].Journal of Southeast University(Natural Science Edition), 2019, 49(4): 773-780. DOI:10.3969/j.issn.1001-0505.2019.04.022. (in Chinese)
[21] Liu X. Research on prediction and analysis of cascading disasters based on text mining[D]. Wuhan: China University of Geosciences, 2021.(in Chinese)
[22] Ren X L, Lu L Y. Review of ranking nodes in complex networks[J]. Chinese Science Bulletin, 2014, 59(13): 1175-1197. DOI:10.1360/972013-1280. (in Chinese)
[23] Cui P, Han Y S, Chen X Q. Distribution and risk analysis of dammed lakes reduced by Wenchuan earthquake[J]. Journal of Sichuan University(Engineering Science Edition), 2009, 41(3): 35-42. DOI:10.15961/j.jsuese.2009.03.024. (in Chinese)
[24] Li H N, Xiao S Y, Huo L S. Damage investigation and analysis of engineering structures in the Wenchuan earthquake[J]. Journal of Building Structures, 2008(4): 10-19. DOI:10.14006/j.jzjgxb.2008.04.002. (in Chinese)
[25] Zhou H W, Yang X G, Li H T, et al. Risk elimination techniques and management of earthquake lakes[J]. Journal of Sichuan University(Engineering Science Edition), 2009, 41(3): 96-101. DOI:10.15961/j.jsuese.2009.03.028. (in Chinese)

Memo

Memo:
Biography: Lu Zheng(1982—), male, doctor, professor, luzheng111@tongji.edu.cn.
Foundation item: National Key Research and Development Program of China(No. 2022YFC3803000).
Citation: Lu Zheng, Yan Deyu, Jiang Huanjun. Earthquake disaster chain model based on complex networks for urban engineering systems[J].Journal of Southeast University(English Edition), 2024, 40(3):230-237.DOI:10.3969/j.issn.1003-7985.2024.03.002.
Last Update: 2024-09-20