Simulation-Based Assessment of Postearthquake Functionality of Buildings with Disruptions to Cross-Dependent Utility Networks

Masoomi, Hassan; Burton, Henry; Tomar, Agam; Mosleh, Ali

doi:10.1061/(asce)st.1943-541x.0002555

Cited by 24 publications

(16 citation statements)

References 43 publications

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“…While structural damages from earthquakes have been investigated in various capacities, there has been a limited examination of the impact on traffic networks and the resilience of bridges after earthquakes [14][15][16][17][18][19][20][21][22][23][24][25][26][27]. Additionally, most impact analyses of traffic networks have been based on the simplified application of traffic capacity.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes

Cho

Lee

et al. 2021

Applied Sciences

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Highway systems play a key role in providing mobility to society, especially during emergency situations, including earthquakes. Bridges in highway systems are susceptible to damage from earthquakes, causing traffic capacity loss leading to a serious impact on surrounding areas. To better prepare for such scenarios, it is important to estimate capacity loss and traffic disruptions from earthquakes. For this purpose, a traffic-capacity-analysisbased methodology was developed to model the performance of a transportation network immediately following an earthquake using a macroscopic multi-level urban traffic planning simulation model EMME4. This method employs the second order linear approximation (SOLA) traffic assignment and calculates total system travel time for various capacity loss scenarios due to bridge damage from earthquakes. It has been applied to Pohang City in Korea to evaluate the performance of traffic networks in various situations. The results indicate a significant increase in travel time and a decrease in travel speed as the intensity of an earthquake increases. However, the impact on traffic volume varies depending on the bridges. It is assumed that the location of the bridges and traffic routing patterns might be the main reason. The results are expected to help estimate the impact on transportation networks when earthquakes cause traffic capacity loss on bridges.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes

Cho

Lee

et al. 2021

Applied Sciences

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“…The Cabinet Office, Government of Japan [6] released details of the 1995 Kobe (Japan) earthquake, which had a magnitude of 7.2 (on Richter scale) with 6437 fatalities and missing persons and seriously damaged major lifelines such as bridges, roads, and subways, Sichuan (China) earthquake in 2008 which had a magnitude of 7.9 (on Richter scale), claimed 80,000 lives and damage to infrastructures due to landslides and soil liquefaction [7], Ludian (China) in 2014 which had a 6.1-magnitude (on Richter scale) claimed 600 lives and damage to lifelines and property, Kathmandu (Nepal) in 2015 with 7.8-magnitude (on Richter scale) earthquake killed 9,000 people and severely damaging lifeline system [8] Chiapas (Mexico) 8.2-magnitude (on Richter scale) earthquake in 2017 with 61 persons killed and large scale destruction due to landslides [9]. Recently, many studies have been performed based on post earthquake scenario like performance assessment of Salyankot water supply project in nepal [10], risk-based assessment of infrastructure system [11,12], firefighting capacity evaluation of water distribution system [13], collective action in post-earthquake Nepal [14], estimation of restoration time of power and telecommunication lifelines [15], assessment of functionality of buildings [16], restoration of water system using discrete-event simulation [17].…”

Section: Study Areamentioning

confidence: 99%

“…The relationship of pipeline risk for ground shaking (transient ground deformation) in several different 16.79 million. The projection was nearly correct and with the average growth rate since the census of 1881, the population would touch 20.347 million by 2021.…”

Section: Study Areamentioning

confidence: 99%

Performance of Water Supply Lines in a Post-Earthquake Scenario

Hasan¹

2021

Pol. J. Environ. Stud.

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An earthquake can affect a vast category of buried lifelines performance such as water distribution system, sewage disposal system, petroleum enterprises, etc. In the present study, damage in terms of performance and working of water distribution system after severe earthquakes in a metropolitan city is assessed to develop serviceability priorities. A system simulation based on Kameda's model is also developed for obtaining useful information on the behavior of the water supply system in the pre-and post-earthquake scenario. The event modeled is the earthquake that is believed to produce extensive losses to life and property. The priorities strategy for rehabilitation of buried water distribution system is framed considering important factors such as damage in terms of leakage, reliable water demand after earthquake damage, and water distribution path length. In this study, repair management is applied systematically to restore the reliable water supply in a water distribution path. The recommendations are framed and priority of repair of the water distribution system of various paths of city zone is established such as pre-assuming a post-earthquake scenario, from the case study of one of the most important metropolitan cities of Asian country i.e., Delhi.

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“…Though queuing models are used extensively in manufacturing, material-handling systems, construction systems, and infrastructure recovery, only recently have they been used in the context of post-earthquake building portfolio recovery (Costa, 2019; Masoomi and Van De Lindt, 2019; Masoomi et al, 2020). Queuing models can capture real-world components of very complex processes and take into account uncertainties through probability distributions.…”

Section: Stochastic Queuing Modelmentioning

confidence: 99%

“…Though their model had capabilities to include restoration priority for each neighborhood and resource constraints, their case study assumed that all resources were available, and all neighborhoods had the same priority. In another study, Masoomi et al (2020) included the residential sector in their model to study post-earthquake building functionality that accounts for other interdependent networks such as electric power and water networks. Though resource constraints were included in this study, the recovery prioritization was only applied to the infrastructure network.…”

Section: Introductionmentioning

confidence: 99%

Modeling housing recovery after the 2018 Lombok earthquakes using a stochastic queuing model

Alisjahbana

Kiremidjian

2020

Earthquake Spectra

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Post-earthquake housing recovery monitoring is necessary, especially since the housing sector usually represents 50 percent of the total monetary disaster loss. However, very scarce recovery data, in addition to the complexities of the recovery process, make modeling housing recovery very difficult. Time-based stochastic models, which are commonly used in well-known frameworks such as the U.S. Federal Emergency Management Agency’s HAZARD-US (HAZUS), do not explicitly capture how the recovery process occurs in real life. In this article, we introduce a stochastic queuing model that considers the total number of damaged buildings, the damage distribution, resource constraints, and government-led reconstruction prioritization strategies. We applied our model to seven regions affected by the 2018 Lombok earthquakes, which destroyed over 226,000 residential buildings. In this study, we use publicly available daily data of the reconstruction progress obtained by local authorities for all damaged buildings. Using that dataset, we present recovery parameters for the Lombok region, including delay and reconstruction times. These parameters are an improvement over parameters currently available, which only apply to the U.S. region. Furthermore, we show that our model captures the observed recovery trajectory disaggregated by damage states, which provides insights into how the different building damage states recover individually. Results show that our queuing model reduces the root mean squared error (RMSE) of the recovery trajectory by 31.58% and is better able to represent the observed overall recovery trajectory compared to a time-based stochastic model.

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Simulation-Based Assessment of Postearthquake Functionality of Buildings with Disruptions to Cross-Dependent Utility Networks

Cited by 24 publications

References 43 publications

Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes

Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes

Performance of Water Supply Lines in a Post-Earthquake Scenario

Modeling housing recovery after the 2018 Lombok earthquakes using a stochastic queuing model

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