Discrete-Event-Based Simulation Model for Performance Evaluation of Post-Earthquake Restoration in a Smart City
Abstract
Emergency responders are typically notified immediately after a major earthquake strikes. However, a time delay, called the travel time, is usually experienced between the notification and the arrival of the responders on the scene. The reparative work necessary after the responders arrive takes an additional amount of time, called the response time, depending on the nature of the damage and the volume of resources available. In a smart city, the restoration time, which is the sum of the travel and response times, should be minimized. A new discrete-event-based simulation (DEBS) model is presented in this paper to estimate the restoration time needed to bring the situation under control after notifying the response center. The DEBS model not only relaxes restrictive assumptions on travel time made by the Markov chain models from the existing literature, but it can also quantify the impact of resource volumes on restoration times. Additionally, the DEBS model is very useful for training purposes. The DEBS model was employed on a case study from the state of Missouri (U.S.). The experiments demonstrate that numerical results with the model take a short amount of computational time and that it can be implemented on a real-time basis in a smart-city infrastructure.
Recommended Citation
A. Gosavi et al., "Discrete-Event-Based Simulation Model for Performance Evaluation of Post-Earthquake Restoration in a Smart City," IEEE Transactions on Engineering Management, vol. 67, no. 3, pp. 582 - 592, Institute of Electrical and Electronics Engineers (IEEE), Aug 2020.
The definitive version is available at https://doi.org/10.1109/TEM.2019.2927318
Department(s)
Civil, Architectural and Environmental Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Computational modeling; Earthquake; Earthquakes; emergency management; Markov processes; Mathematical model; Numerical models; Smart cities; smart city; Time factors; training
International Standard Serial Number (ISSN)
0018-9391
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Aug 2020