Simulation-Based Methods for Studying Reliability and Preventive Maintenance of Public Infrastructure
Abstract
In recent times, simulation has made significant progress as a tool for improving the performance of complex stochastic systems that arise in various domains in the industrial and service sectors. In particular, what is remarkable is that simulation is being increasingly used in diverse domains, e.g., devising strategies needed for emergency response to terrorist threats in homeland security systems and civil engineering of bridge structures for motor vehicle transport. In this chapter, we will focus on (1) describing some of the key decision-making problems underlying (a) response to emergency bomb-threat scenarios in a public building, and (b) prevention of catastrophic failures of bridges used for motor-vehicle transport; (2) providing an overview of simulation-based technologies that can be adopted for solving the associated problems. Our discussion will highlight some performance measures applicable to emergency response and prevention that can be estimated and improved upon via discrete-event simulation. We will describe two problem domains in which measurement of these metrics is critical for optimal decision-making. We believe that there is a great deal of interest currently, within both the academic world and the government sector, in enhancing our homeland security systems. Simulation already plays a vital role in this endeavor. The nature of the problems in this chapter is unconventional and quite unlike that seen commonly in classical simulation-based domains of manufacturing and service industries.
Recommended Citation
A. Gosavi and S. L. Murray, "Simulation-Based Methods for Studying Reliability and Preventive Maintenance of Public Infrastructure," Simulation Methods for Reliability and Availability of Complex Systems, vol. 36, pp. 107 - 121, Springer Verlag, Jan 2010.
The definitive version is available at https://doi.org/10.1007/978-1-84882-213-9_5
Department(s)
Engineering Management and Systems Engineering
Second Department
Psychological Science
International Standard Serial Number (ISSN)
1614-7839
Document Type
Book - Chapter
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2010 Springer Verlag, All rights reserved.
Publication Date
01 Jan 2010