Optimal Sampling of Infrastructure Condition: Motivation, Formulation, and Evaluation
Publication: Journal of Infrastructure Systems
Volume 15, Issue 4
Abstract
Infrastructure management is the process through which inspection, maintenance, and rehabilitation decisions are made to minimize total life-cycle cost. Condition measurement, spatial sampling, and forecasting introduce uncertainty into the process. The first and third uncertainties are captured in the infrastructure management literature. However, the second has not been recognized and quantified. This study focuses on motivating the incorporation of the spatial sampling uncertainty in decision-making, quantifying this uncertainty, and investigating its effect on the expected minimum life-cycle cost. Evaluation measures are defined to assess the contributions of the developed framework, namely incorporating uncertainty due to spatial sampling in the decision-making process and selecting the sample size optimally. A numerical analysis indicates that in general both contributions are important under a wide range of realistic scenarios and the implications of the combined effects on minimizing life-cycle cost and long-term budget planning are marked.
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Acknowledgments
This study was funded by US National Science Foundation Grant No. UNSPECIFIED0093452.
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Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 15 • Issue 4 • December 2009
Pages: 313 - 320
Copyright
© 2009 ASCE.
History
Received: Jan 11, 2008
Accepted: May 11, 2009
Published online: Nov 13, 2009
Published in print: Dec 2009
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