Risk-Based Maintenance Optimization of Deteriorating Bridges
Publication: Journal of Structural Engineering
Volume 141, Issue 4
Abstract
Risk-based performance measures integrate probability of component or system failure with the consequences of this event. In this paper, a novel risk-based maintenance optimization methodology for deteriorating bridges to find the optimum maintenance options and their timing is proposed. Finding the optimum maintenance types and schedule for different components of bridges is formulated as a multicriteria optimization in which the lifetime maximum value of expected losses associated with failure and the lifetime total expected maintenance cost are considered as the conflicting objectives. The risk-based maintenance approach accounts for different deterioration levels of bridge components and consequences of both component failure and system failure. The methodology is illustrated on a bridge superstructure. The effects of considered life span of the structure and availability of maintenance options on optimum solutions are also investigated.
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Acknowledgments
The support from (a) the National Science Foundation through Grant CMS-0639428, (b) the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA), (c) the U.S. Federal Highway Administration Cooperative Agreement Award DTFH61-07-H-00040, and (d) the U.S. Office of Naval Research through Contracts N 00014-08-1-0188 and N 00014-12-1-0023 is gratefully acknowledged. The computational help received from Ph.D. candidate You Dong is also gratefully acknowledged. The opinions and conclusions presented in this paper are those of the authors and do not necessarily reflect the views of the sponsoring organizations.
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Published In
Journal of Structural Engineering
Volume 141 • Issue 4 • April 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Mar 7, 2013
Accepted: Jan 27, 2014
Published online: Jul 11, 2014
Discussion open until: Dec 11, 2014
Published in print: Apr 1, 2015
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