Optimization of Maintenance for Coastal Inlets with Uncertainty
Jay R. Lund
Abstract
Jay R. Lund
Abstract
Maintenance dredging costs the nation roughly $400 million per year. Yet, relative to other areas of water resources engineering, little attempt has been made to apply operations research methods to reduce the cost or increase the reliability of maintenance dredging operations. This paper extends the results of a U.S. Army Corps of Engineers sponsored study to demonstrate a preliminary methodology for estimating the optimal dredging frequency for coastal inlets. The method incorporates both a stochastic model of sediment deposition from littoral drift and a dredging cost model to estimate both the long term annualized cost and navigation reliability of various maintenance strategies. The managers of the inlet can then choose a dredging or sand-bypass strategy representing the most appropriate trade-off of cost and reliability. The problem of employing the method with imperfect transport and sedimentation models is discussed.
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Maintenance dredging costs the nation roughly $400 million per year. Yet, relative to other areas of water resources engineering, little attempt has been made to apply operations research methods to reduce the cost or increase the reliability of maintenance dredging operations. This paper extends the results of a U.S. Army Corps of Engineers sponsored study to demonstrate a preliminary methodology for estimating the optimal dredging frequency for coastal inlets. The method incorporates both a stochastic model of sediment deposition from littoral drift and a dredging cost model to estimate both the long term annualized cost and navigation reliability of various maintenance strategies. The managers of the inlet can then choose a dredging or sand-bypass strategy representing the most appropriate trade-off of cost and reliability. The problem of employing the method with imperfect transport and sedimentation models is discussed.
Key concepts: Dredging, Reliability (semiconductor), Inlet, Sedimentation, Marine engineering, Environmental science, Engineering, Operations research