Quantitative Method For Post-Windstorm Function of Community Shelters Considering The Impact of Urban Road Network

Lu Zhang; Shuang Tan

doi:10.21625/essd.v9i4.1135

Lu Zhang , Shuang Tan

https://doi.org/10.21625/essd.v9i4.1135

Issue
Vol. 9 Issue 4 (2024)

Submitted
October 10, 2024

Accepted
December 5, 2024

Published
December 31, 2024

Keywords:

Windstorm, Community shelters, Refugee, Wind-induced fragility, Urban road network, Post-windstorm functionality

PDF XML

Abstract

During strong windstorms in coastal cities, community shelters play a crucial role in reducing injures and ensuring the basic living needs of citizens. However, previous studies mainly focus on the function assessment of healthcare systems during earthquakes, few studies discuss the post-windstorm functionality of community shelters. Thus, this study proposes a quantitative method for the post-windstorm function of community shelters considering the impact of urban road networks. In which, the refugee traveling time (RTT) and refugee admitted ratio (RAR) are introduced to quantify the post-windstorm functionality of community shelters. Both the networks of urban roads and community shelters are established using graph theory, and the wind-induced fragilities of urban road facilities are included to quantify the physical damages during windstorms, including tree/pole blow-down, damages on building envelops, etc. Then, the population distribution and refugee generation models are also introduced. To determine accurate RTT and RAR, an efficient traffic flow allocation algorithm based on stochastic non-equilibrium assignment model are proposed to calculate the post-windstorm flows on urban roads. The proposed method can accurately and effectively quantify the post-windstorm functionality of community shelters, which can be applied on different cities and help improving urban resilience under wind hazards.

Full text article

Generated from XML file

References

Roueche, D. B., Prevatt, D. O. (2013). Residential damage patterns following the 2011 Tuscaloosa, AL and Joplin, MO tornadoes. Journal of Disaster Research, 8(6), 1061–1067. https://doi.org/10.20965/jdr.2013.p1061.

Huang, X., Wang, N. (2024). An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclone. Reliability Engineering and System Safety, 242, 109731. https://doi.org/10.1016/j.ress.2023.109731.

Nofal, O., Rosenheim, N., Kameshwar, S., Patil, J., Zhou, X., van de Lindt, J. W., Duenas-Osorio, L., Cha, E. J., Endrami, A., Sutley, E., Cutler, H., Lu, T., Wang, C., Jeon, H. (2023). Community-level post-hazard functionality methodology for buildings exposed to floods. Computer-aided Civil and Infrastructure Engineering, 39, 1099-1122. https://doi.org/10.1111/mice.13135.

Dong, Y., Guo, Y., Ellingwood, B. R., Mahmoud, H. N. (2022). Deaggregation of wind speeds for hurricane scenarios used in risk-informed resilience assessment of coastal communities. Journal of Structural Engineering. 148(11), 04022175. https://doi.org/10.1061/(ASCE)ST.1943-541X.0003410.

Pei, S., Zhai, C., Hu, Jie., Liu, J., Song, Z. (2023). Seismic functionality of healthcare network considering traffic congestion and hospital malfunctioning: A medical accessibility approach. International Journal of Disaster Risk Reduction. 97, 104019. https://doi.org/10.1016/j.ijdrr.2023.104019.

Huang, X., Wang, N. (2024). Post-disaster restoration planning of interdependent infrastructure Systems: A framework to balance social and economic impacts. Structural Safety. 107, 102408. https://doi.org/10.1016/j.strusafe.2023.102408.

Anwar, G. A., Dong, Y., Ouyang, M. (2022). Systems thinking approach to community buildings resilience considering utility networks, interactions, and access to essential facilities. Bulletin of Earthquake Engineering. 21, 633-661. http://dx.doi.org/10.1007/s10518-022-01557-y.

Zhang, J., Li, Y., Yuan, H., Du, G., Zhang, M. (2024). A demand-based three-stage seismic resilience assessment and multi-objective optimization method of community water distribution networks. Reliability Engineering and System Safety, 250, 110279. https://doi.org/10.1016/j.ress.2024.110279.

Amin, K., Padgett, J. E. (2023). Probabilistic risk assessment of hurricane-induced debris impacts on coastal transportation infrastructure. Reliability Engineering and System Safety, 240, 109579. https://doi.org/10.1016/j.ress.2023.109579.

Nie, Y., Li, J., Liu, G., Zhou, P. (2023). Cascading failure-based reliability assessment for post-seismic performance of highway bridge network. Reliability Engineering and System Safety, 238, 109457. https://doi.org/10.1016/j.ress.2023.109457.

Liu, W., Song, Z., Ouyang, M., Li J. (2020). Recovery-based seismic resilience enhancement strategies of water distribution networks. Reliability Engineering and System Safety, 203, 107088. https://doi.org/10.1016/j.ress.2020.107088.

Yu, P., Wen, W., Ji. D., Zhai, C., Xie, L. (2019). A framework to assess the seismic resilience of urban hospitals. Advances in Civil Engineering, 7654683. https://doi.org/10.1155/2019/7654683.

Sharma, N., Gardoni, P. (2022). Mathematical modeling of interdependent infrastructure: an object-oriented approach for generalized network-system analysis. Reliability Engineering and System Safety, 217, 108042. https://doi.org/10.1016/j.ress.2021.108042. 10.1016/j.ress.2021.108042.

Bocchini, P., Frangopol, D. M. (2012). Restoration of bridge networks after an earthquake: multicriteria intervention optimization. Earthquake Spectra, 28, 427-455. http://dx.doi.org/10.1193/1.4000019. 10.1193/1.4000019.

Chen, B., Shang, L., Qin, M., Chen, X., Yang Q. (2018). Wind interference effects of high-rise building on low-rise building with flat roof. Journal of Wind Engineering and Industrial Aerodynamics, 183, 88-113. https://doi.org/10.1016/j.jweia.2018.10.019. 10.1016/j.jweia.2018.10.019.

Wang, J., Wang, N. (2024). Forecasting road network functionality states during extreme rainfall events to facilitate real-time emergency response planning. Reliability Engineering and System Safety, 252, 110452. http://dx.doi.org/10.1016/j.ress.2024.110452. 10.1016/j.ress.2024.110452.

Gu, D., Shuai, Q., Wang, Y. (2023). Cim-powered physics-based assessment of wind damages to building clusters considering trees. Developments in the Built Environment, 15, 100178. https://doi.org/10.1016/j.dibe.2023.100178. 10.1016/j.dibe.2023.100178.

Gu, D., Zhao, P., Chen, Wang., Huang, Y., Lu, X. (2021). Near real-time prediction of wind-induced tree damage at a city scale: simulation framework and case study for tsinghua university campus. International Journal of Disaster Risk Reduction, 53, 102003. https://doi.org/10.1016/j.ijdrr.2020.102003. 10.1016/j.ijdrr.2020.102003.

Wen, J., Xie, Qiang. (2020). Field investigation and structural analysis of wind-induced collapse of outdoor single-post billboards. Engineering Failure Analysis, 117, 104810. https://doi.org/10.1016/j.engfailanal.2020.104810. 10.1016/j.engfailanal.2020.104810.

Panteli, M., Pickering, C., Wilkinson, S., Dawson, R., Mancarella, P. (2017). Power system resilience to extreme weather: fragility modeling, probabilistic impact assessment, and adaptation measures. Ieee Transactions on Power Systems, 32(5), 3747-3757. http://dx.doi.org/10.1109/tpwrs.2016.2641463. 10.1109/TPWRS.2016.2641463.

Russo, F., Rindone C. (2024). Methods for risk reduction: training and exercises to pursue the planned evacuation. Sustainability 16(4):1474. https://doi.org/10.3390/su16041474

Authors

Lu Zhang

Ph.D. Candidate at School of Civil Engineering, Chongqing University, China

[email protected] (Primary Contact)

Shuang Tan

M.Eng. Postgraduate at School of Civil Engineering, Chongqing University, China

Zhang , L., & Tan, S. (2024). Quantitative Method For Post-Windstorm Function of Community Shelters Considering The Impact of Urban Road Network. Environmental Science & Sustainable Development, 9(4), 72–78. https://doi.org/10.21625/essd.v9i4.1135

Download Citation

This work is licensed under a Creative Commons Attribution 4.0 International License.

The Author shall grant to the Publisher and its agents the nonexclusive perpetual right and license to publish, archive, and make accessible the Work in whole or in part in all forms of media now or hereafter known under a Creative Commons Attribution 4.0 License or its equivalent, which, for the avoidance of doubt, allows others to copy, distribute, and transmit the Work under the following conditions:

Attribution: other users must attribute the Work in the manner specified by the author as indicated on the journal Web site;

With the understanding that the above condition can be waived with permission from the Author and that where the Work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.

The Author is able to enter into separate, additional contractual arrangements for the nonexclusive distribution of the journal's published version of the Work (e.g., post it to an institutional repository or publish it in a book), as long as there is provided in the document an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post online a pre-publication manuscript (but not the Publisher's final formatted PDF version of the Work) in institutional repositories or on their Websites prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (see The Effect of Open Access). Any such posting made before acceptance and publication of the Work shall be updated upon publication to include a reference to the Publisher-assigned DOI (Digital Object Identifier) and a link to the online abstract for the final published Work in the Journal.
Upon Publisher's request, the Author agrees to furnish promptly to Publisher, at the Author's own expense, written evidence of the permissions, licenses, and consents for use of third-party material included within the Work, except as determined by Publisher to be covered by the principles of Fair Use.
The Author represents and warrants that:

The Work is the Author's original work;
The Author has not transferred, and will not transfer, exclusive rights in the Work to any third party;
The Work is not pending review or under consideration by another publisher;
The Work has not previously been published;
The Work contains no misrepresentation or infringement of the Work or property of other authors or third parties; and
The Work contains no libel, invasion of privacy, or other unlawful matter.

The Author agrees to indemnify and hold Publisher harmless from Author's breach of the representations and warranties contained in Paragraph 7 above, as well as any claim or proceeding relating to Publisher's use and publication of any content contained in the Work, including third-party content.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Received 2024-10-10
Accepted 2024-12-05
Published 2024-12-31

1. Introduction.

In recent years, the economic losses and population injuries caused by strong windstorms have increased considerably and frequently in coastal cities. Such as the Hurricane Michael landing at the western Atlantic coast in 2018 and the Typhoon Lekima landing at the western Pacific coast in 2019, which caused transportation disruptions, water and power outages, and unsuitable living buildings in multiple regions of the United States and China, forcing tens of thousands of people to seek refuge in emergency shelters, ranging from a few days to several months ((Roueche & Prevatt, 2013); (Huang & Wang, 2024)). Due to the capacity of the city shelter systems (CSS) after strong wind disasters is closely related to the ability to evacuate and transport people to shelters after strong wind disasters. Thus, it is necessary to carry out the capacity assessment of CSS after strong storm disasters to help quickly organize personnel to shelters, and minimize wind disaster losses and casualties as much as possible for the government.

A large number of previous studies focused on the function assessment of urban systems after extreme disaster events, including earthquakes, typhoons, tornadoes, floods, etc. ((Nofal et al., 2023); (Dong et al., 2022); (Pei et al., 2023); (Huang & Wang, 2024); (Anwar et al., 2022); (Zhang et al., 2024)). Among them, most studies are related to the function assessment of urban systems after earthquake disasters, and several scholars have conducted functional evaluation on network systems such as water supply, power supply, hospitals, and transportations after earthquake disasters ((Amin & Padgett, 2023); (Nie et al., 2023); (Liu et al., 2020); (Yu et al., 2019)). Several studies focus on evacuation plans through transportation systems under risks, but their consideration of physical damages to transportation systems is limited (Russo & C, 2024). The studies on windstorm disasters mainly focus on power supply and transportation systems, and most of them investigated on independent systems((Pei et al., 2023); (Huang & Wang, 2024)). The CSS function under strong windstorms depends on urban road networks and shelters at the same time. After windstorms, refugees need to be transferred to shelters through the road network, and the space provided by shelters for refugees is generally limited. If a shelter is crowded with refugees, new refugees have to change their destination to another shelter and the overflow of refugees would be transferred once through the road network. The studies on function assessment of CSS considering the influences of coupled shelters and road networks after strong storm disasters are very limited.

The function assessment of CSS is similar to the post-disaster hospital capacity assessment, but compared to earthquake disasters, the main losses are living function loss of buildings during strong windstorms, and the function of CSS after strong windstorms will be affected by normal traffic flows. Given the lack of studies on the function assessment of CSS that considers the interdependence between urban shelters and road networks after strong windstorms. Thus, this study proposes a framework for the function assessment of CSS after strong windstorms. The proposed method can be applied to evaluate CSS function of any cities under strong windstorms, which can help the government make more reasonable decisions during post- and pre-windstorms to reduce wind-induced personnel and economic losses in coastal areas.

2. Quantitative Method For Post-Windstorm Function of Community Shelters

Given that previous studies usually neglect the interdependence between shelters and road networks, and there is no function assessment method for CSS after strong windstorms. Thus, this study establishes an assessment framework for CSS function considering the interdependence between shelters and road networks under strong windstorms by introducing graph theory and engineering fragilities, as shown in Figure 1. The key steps involved are as follows: (1) CSS topology model. Identify shelters and road networks through the GIS method, and simplify key facilities and road networks into nodes and links using graph theory. (2) Wind-induced engineering fragilities. Based on, conduct fragility analysis on the key infrastructures of the identified urban shelters and road networks. (3) CSS function indicators and assessment. Construct function indicators of CSS including the shelter efficiency and capacity under wind disasters, and conduct the function evaluation of CSS. The detailed contents are described from section 3 to section 5.

Figure 1.Framework of the post-windstorm function of community shelter system (CSS) (from authors)

3. Modeling The Interdependent Network Between Shelters and Urban Roads

To carry out the function assessment of CSS, the primary step is constructing a dual system network of shelters and road networks. Graph theory is often used to simplify the actual engineering systems into a topological structure model composed of nodes and links(Sharma & Gardoni, 2022) (Bocchini & Frangopol, 2012) as shown in Figure 2. The required information for establishing a topology model includes the types of key infrastructures, the distribution of road networks, and the relationships between each key facility, such as road networks, sports venues, medical facilities, schools, etc. These data can be can be extracted through open-resource satellite maps.

Figure 2.Topology network of CSS (from authors)

Based on the collected information from GIS, the topology model can be established by several matrixes using graph theory(Sharma & Gardoni, 2022), as shown in Figure 3. (1) Connection matrix, describing the matrix of key facility connection relationships; (2) Demand matrix, reflecting the evacuation needs of each node after a disaster; (3) Capacity matrix, reflecting the proportion of people that can be accommodated in shelters; (4) Traffic efficiency matrix, reflecting the traffic efficiency between different nodes. Normalized values are used for each matrix.

Figure 3.Topology matrixes (from authors)

4. Wind Hazards

To evaluate the emergency shelter function of cities after strong storms, it is necessary to determine the distribution of strong storm disaster fields in the city, and then determine the damage status of key facilities based on the vulnerability results of various key facilities in the network system, and then evaluate the network function status.

Wind Hazard Map

The distribution characteristics of wind speed fields at the urban community scale can be determined through wind tunnel tests(Chen et al., 2018) and computational fluid dynamics simulations(Wang & Wang, 2024). Considering the high cost of wind tunnel tests, this study uses CFD methods to determine the wind speed field distribution in the study area under different wind directions.

Wind-Induced Physical Damages

The variety of critical urban facilities means that conducting fragility analyses for each one can be time-consuming and computationally intensive. Therefore, this study categorizes common wind-induced fragilities into two main categories, as illustrated in Figure 4. (1) Wind-induced fragility of envelopes. Consider wind-induced damage to low rise building roof panels and damage to roof windows caused by wind-induced debris on the roof(Gu et al., 2023). (2) Wind induced fragility of ancillary facilities of road network{(Gu et al., 2021); (Wen & Xie, 2020); (Panteli et al., 2017)}. The ancillary facilities of the road network only consider wind-induced damage to poles, billboards, and roadside trees, and the damage mode only considers bottom bending failure. The state equations of wind-induced damage for each key facility are shown in Figure 4.

Figure 4.Wind-induced fragility models (from authors)

5. Functionality Loss of Community Shelter System

Evaluating the CSS function requires comprehensive consideration of various indicators. This study intends to use two types of indicators, namely shelter efficiency and venue capacity, to evaluate the emergency shelter function. By comparing the post disaster values of the two indicators with the initial state values, the final shelter system function indicator value Q is obtained, as shown in Figure 1.

5.1.Refugee Travelling Time (RTT)

Using the total travel time as the efficiency indicator for evacuees, as shown in equation (1). Where i represents the starting node of the ith group of refugees, j represents the jth shelter, represents the number of refugees from node i to node j, represents the shortest path length from node i to node j, and represents the travel speed from node i to node j. Actually, the majority of buildings are concrete and steel structures in China cities, and they are rarely damaged by windstorms. After a windstorm, only some nodes and routes may be interrupted due to physical damage of road ancillary facilitates, the transportation system usually continues to operate with the reduced function. Which means that the normal transportation needs, such as the flow to work or to study, are still exist with the flow of refugees at same time after the windstorm, and the shelter needs account for a small proportion of total transportation needs. Based on above, the stochastic non-equilibrium assignment is used to calculate the traffic flow and speed of each line, and the Logit probability function is used in this paper. To evaluate the CSS function, the and of the shortest path from node i to node j ( j is the shelter node) to define the Refugee travelling time indicator as shown in equation (1). In which, is determined by the stochastic non-equilibrium assignment.

\documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle P_{\text{initial/post}}^{RTT} = \sum_{i=1}^{N} \sum_{\substack{j=1 \\ j \neq i}}^{M} S_{ij} \frac{d_{ij}}{V_{ij}} \end{document} (1)

5.2. Refugee Admitted Ratio (RAR)

Using the ratio of the number of refugees to the capacity of the venue as another evaluation indicator, as shown in equation (2). Where j represents the jth shelter, represents the total number of refugees arriving at node j, and represents the capacity of the shelter at node j. To consider the impact of strong storm disasters, the capacity of emergency shelters and the number of refugees generated after the windstorms are continuously updated to update the capacity of refugees.

\documentclass{article} \usepackage{amsmath} \begin{document} \displaystyle P_{\text{initial/post}}^{RAR} = \sum_{j=1}^{M} \frac{S_j}{R_j} \end{document} (2)

6. Conclusion.

Considering the significant economic and human losses often experienced in coastal cities during severe storm events, it is necessary to evacuate large numbers of people to emergency shelters to minimize these losses. However, there is a paucity of research evaluating the effectiveness of urban emergency shelter functions specifically in the context of wind disasters. Thus, this study proposes a quantitative method for post-windstorm function of community shelters considering the impact of urban road network. In which, the refugee travelling time (RTT) and refugee admitted ratio (RAR) are introduced to quantify the post-windstorm functionality of community shelters. Both the networks of urban roads and community shelters are established using graph theory, and the wind-induced fragilities of urban road facilities are included to quantify the physical damages during windstorms, including tree/pole blow-down, damages on building envelops, etc. Then, the population distribution and refugee generation models are also introduced. To determine accurate RTT and RAR, an efficient traffic flow allocation algorithm based on stochastic non-equilibrium assignment model are proposed to calculate the post-windstorm flows on urban roads. The proposed method can accurately and effectively quantify the post-windstorm functionality of community shelters, which can be applied on different cities and help improving urban resilience under wind hazards.

Acknowledgment.

The abstract of this paper was presented at the Resilient and Responsible Architecture and Urbanism (RRAU) Conference—6th Edition, which was held on the 8^th – 10^th of December 2024.

Ethics approval.

Not applicable.

Conflict of interest.

The authors declare that there is no competing interest.

References

Roueche D.B., Prevatt D.O.. Residential damage patterns following the 2011 Tuscaloosa, AL and Joplin, MO tornadoes. Journal of Disaster Research. 2013; 8(6):1061-1067. DOI
Huang X., Wang N.. An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclone. Reliability Engineering and System Safety. 2024; 242DOI
Nofal O., Rosenheim N., Kameshwar S., Patil J., Zhou X., Lindt J.W., Duenas-Osorio L., Cha E.J., Endrami A., Sutley E., Cutler H., Lu T., Wang C., Jeon H.. Community-level post-hazard functionality methodology for buildings exposed to floods. Computer-aided Civil and Infrastructure Engineering. 2023; 39:1099-1122. DOI
Dong Y., Guo Y., Ellingwood B.R., Mahmoud H.N.. Deaggregation of wind speeds for hurricane scenarios used in risk-informed resilience assessment of coastal communities. Journal of Structural Engineering. 2022; 148(11)DOI
Pei S., Zhai C., Hu Jie, Liu J., Song Z.. Seismic functionality of healthcare network considering traffic congestion and hospital malfunctioning: A medical accessibility approach. International Journal of Disaster Risk Reduction. 2023; 97DOI
Huang X., Wang N.. Post-disaster restoration planning of interdependent infrastructure Systems: A framework to balance social and economic impacts. Structural Safety. 2024; 107DOI
Anwar G.A., Dong Y., Ouyang M.. Systems thinking approach to community buildings resilience considering utility networks, interactions, and access to essential facilities. Bulletin of Earthquake Engineering. 2022; 21:633-661. DOI
Zhang J., Li Y., Yuan H., Du G., Zhang M.. A demand-based three-stage seismic resilience assessment and multi-objective optimization method of community water distribution networks. Reliability Engineering and System Safety. 2024; 250DOI
Amin K., Padgett J.E.. Probabilistic risk assessment of hurricane-induced debris impacts on coastal transportation infrastructure. Reliability Engineering and System Safety. 2023; 240DOI
Nie Y., Li J., Liu G., Zhou P.. Cascading failure-based reliability assessment for post-seismic performance of highway bridge network. Reliability Engineering and System Safety. 2023; 238DOI
Liu W., Song Z., Ouyang M., J Li. Recovery-based seismic resilience enhancement strategies of water distribution networks. Reliability Engineering and System Safety. 2020; 203DOI
Yu P., Wen W., D. Ji, Zhai C., Xie L.. A framework to assess the seismic resilience of urban hospitals. Advances in Civil Engineering. 2019; 7654683DOI
Sharma N., Gardoni P.. Mathematical modeling of interdependent infrastructure: an object-oriented approach for generalized network-system analysis. Reliability Engineering and System Safety. 2022; 217DOI
Bocchini P., Frangopol D.M.. Restoration of bridge networks after an earthquake: multicriteria intervention optimization. Earthquake Spectra. 2012; 28:427-455. DOI
Chen B., Shang L., Qin M., Chen X., Q Yang. Wind interference effects of high-rise building on low-rise building with flat roof. Journal of Wind Engineering and Industrial Aerodynamics. 2018; 183:88-113. DOI
Wang J., Wang N.. Forecasting road network functionality states during extreme rainfall events to facilitate real-time emergency response planning. Reliability Engineering and System Safety. 2024; 252DOI
Gu D., Shuai Q., Wang Y.. Cim-powered physics-based assessment of wind damages to building clusters considering trees. Developments in the Built Environment. 2023; 15DOI
Gu D., Zhao P., Chen Wang, Huang Y., Lu X.. Near real-time prediction of wind-induced tree damage at a city scale: simulation framework and case study for tsinghua university campus. International Journal of Disaster Risk Reduction. 2021; 53DOI
Wen J., Xie Qiang. Field investigation and structural analysis of wind-induced collapse of outdoor single-post billboards. Engineering Failure Analysis. 2020; 117DOI
Panteli M., Pickering C., Wilkinson S., Dawson R., Mancarella P.. Power system resilience to extreme weather: fragility modeling, probabilistic impact assessment, and adaptation measures. Ieee Transactions on Power Systems. 2017; 32(5):3747-3757. DOI
Russo F., C Rindone. Methods for risk reduction: training and exercises to pursue the planned evacuation. Sustainability. 2024; 16(4)DOI

Plum Analytics

Read Counter : 560 Download : 512

Share Now

[BIBR-1] Roueche D.B., Prevatt D.O.. Residential damage patterns following the 2011 Tuscaloosa, AL and Joplin, MO tornadoes. Journal of Disaster Research. 2013; 8(6):1061-1067. DOI

[BIBR-2] Huang X., Wang N.. An adaptive nested dynamic downscaling strategy of wind-field for real-time risk forecast of power transmission systems during tropical cyclone. Reliability Engineering and System Safety. 2024; 242DOI

[BIBR-3] Nofal O., Rosenheim N., Kameshwar S., Patil J., Zhou X., Lindt J.W., Duenas-Osorio L., Cha E.J., Endrami A., Sutley E., Cutler H., Lu T., Wang C., Jeon H.. Community-level post-hazard functionality methodology for buildings exposed to floods. Computer-aided Civil and Infrastructure Engineering. 2023; 39:1099-1122. DOI

[BIBR-4] Dong Y., Guo Y., Ellingwood B.R., Mahmoud H.N.. Deaggregation of wind speeds for hurricane scenarios used in risk-informed resilience assessment of coastal communities. Journal of Structural Engineering. 2022; 148(11)DOI

[BIBR-5] Pei S., Zhai C., Hu Jie, Liu J., Song Z.. Seismic functionality of healthcare network considering traffic congestion and hospital malfunctioning: A medical accessibility approach. International Journal of Disaster Risk Reduction. 2023; 97DOI

[BIBR-6] Huang X., Wang N.. Post-disaster restoration planning of interdependent infrastructure Systems: A framework to balance social and economic impacts. Structural Safety. 2024; 107DOI

[BIBR-7] Anwar G.A., Dong Y., Ouyang M.. Systems thinking approach to community buildings resilience considering utility networks, interactions, and access to essential facilities. Bulletin of Earthquake Engineering. 2022; 21:633-661. DOI

[BIBR-8] Zhang J., Li Y., Yuan H., Du G., Zhang M.. A demand-based three-stage seismic resilience assessment and multi-objective optimization method of community water distribution networks. Reliability Engineering and System Safety. 2024; 250DOI

[BIBR-9] Amin K., Padgett J.E.. Probabilistic risk assessment of hurricane-induced debris impacts on coastal transportation infrastructure. Reliability Engineering and System Safety. 2023; 240DOI

[BIBR-10] Nie Y., Li J., Liu G., Zhou P.. Cascading failure-based reliability assessment for post-seismic performance of highway bridge network. Reliability Engineering and System Safety. 2023; 238DOI

[BIBR-11] Liu W., Song Z., Ouyang M., J Li. Recovery-based seismic resilience enhancement strategies of water distribution networks. Reliability Engineering and System Safety. 2020; 203DOI

[BIBR-12] Yu P., Wen W., D. Ji, Zhai C., Xie L.. A framework to assess the seismic resilience of urban hospitals. Advances in Civil Engineering. 2019; 7654683DOI

[BIBR-13] Sharma N., Gardoni P.. Mathematical modeling of interdependent infrastructure: an object-oriented approach for generalized network-system analysis. Reliability Engineering and System Safety. 2022; 217DOI

[BIBR-14] Bocchini P., Frangopol D.M.. Restoration of bridge networks after an earthquake: multicriteria intervention optimization. Earthquake Spectra. 2012; 28:427-455. DOI

[BIBR-15] Chen B., Shang L., Qin M., Chen X., Q Yang. Wind interference effects of high-rise building on low-rise building with flat roof. Journal of Wind Engineering and Industrial Aerodynamics. 2018; 183:88-113. DOI

[BIBR-16] Wang J., Wang N.. Forecasting road network functionality states during extreme rainfall events to facilitate real-time emergency response planning. Reliability Engineering and System Safety. 2024; 252DOI

[BIBR-17] Gu D., Shuai Q., Wang Y.. Cim-powered physics-based assessment of wind damages to building clusters considering trees. Developments in the Built Environment. 2023; 15DOI

[BIBR-18] Gu D., Zhao P., Chen Wang, Huang Y., Lu X.. Near real-time prediction of wind-induced tree damage at a city scale: simulation framework and case study for tsinghua university campus. International Journal of Disaster Risk Reduction. 2021; 53DOI

[BIBR-19] Wen J., Xie Qiang. Field investigation and structural analysis of wind-induced collapse of outdoor single-post billboards. Engineering Failure Analysis. 2020; 117DOI

[BIBR-20] Panteli M., Pickering C., Wilkinson S., Dawson R., Mancarella P.. Power system resilience to extreme weather: fragility modeling, probabilistic impact assessment, and adaptation measures. Ieee Transactions on Power Systems. 2017; 32(5):3747-3757. DOI

[BIBR-21] Russo F., C Rindone. Methods for risk reduction: training and exercises to pursue the planned evacuation. Sustainability. 2024; 16(4)DOI

Quantitative Method For Post-Windstorm Function of Community Shelters Considering The Impact of Urban Road Network

Abstract

Full text article

References

Authors

Most read articles by the same author(s)

Address

Social Media

Article Sidebar

Abstract

Full text article

References

Authors

Article Details

Most read articles by the same author(s)