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Probability-based multiple-criteria optimization of bridge maintenance using monitoring and expected error in the decision process

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Abstract

In the context of limited financial resources under uncertainty, an important challenge is to introduce monitoring concepts in the general assessment, maintenance and repair frameworks of highway bridges. Structural health monitoring (SHM) provides new information on structural performance. As the monitoring duration increases, additional information becomes available. The knowledge of the structure is more accurate, but the monitoring costs are greater. Based on the accuracy of monitoring, different decisions can be made. These decisions involve uncertainties, and, consequently, are expressed in terms of probabilities. A probability-based approach for multiple criteria optimization of bridge maintenance strategies based on SHM is proposed. A measure of the error in the decision process, based on monitoring occurrence and duration, is proposed. Optimal solutions are obtained considering multiple criteria such as expected failure cost, expected monitoring/maintenance cost, expected accuracy of monitoring results, and ensuring that all constraints are satisfied.

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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 Contract Number N-00014-08-0188 is gratefully acknowledged. The writers thank Victor Voiry for computational help. The opinions and conclusions presented in this paper are those of the writers and do not necessarily reflect the views of the sponsoring organizations.

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Orcesi, A.D., Frangopol, D.M. Probability-based multiple-criteria optimization of bridge maintenance using monitoring and expected error in the decision process. Struct Multidisc Optim 44, 137–148 (2011). https://doi.org/10.1007/s00158-010-0613-8

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  • DOI: https://doi.org/10.1007/s00158-010-0613-8

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