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Uncertainty in marine weather routing
Institution:1. Fluid Structure Interactions, Faculty of Engineering and Physical Sciences, Boldrewood Innovation Campus, University of Southampton, Southampton SO16 7QF, United Kingdom;2. Maritime Archaeology, Faculty of Arts and Humanities, University of Southampton, Avenue Campus, Highfield, Southampton, SO17 1BF, United Kingdom;3. Physical Geography, Faculty of Environmental and Life Sciences, Highfield Campus, University of Southampton, Southampton S017 1BJ, United Kingdom;1. National Engineering Laboratory for Pipeline Safety/ MOE Key Laboratory of Petroleum Engineering/ Beijing Key Laboratory of Urban Oil and Gas Distribution Technology, China University of Petroleum-Beijing, Fuxue Road No. 18, Changping District, Beijing, 102249, China;2. Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan;3. Department of Environment Systems, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8563, Japan;4. Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, 2-3-26 Aomi, Koto-ku, Tokyo, 135-0064, Japan;5. Big Data Institute, Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Clear Water Bay, New Territories, Hong Kong, China;1. Department of Maritime Transportation & Management Engineering, Istanbul Technical University, Istanbul, Turkey;2. Department of Marine Engineering, Istanbul Technical University, Istanbul, Turkey;1. Dept. of Systems & Naval Mechatronic Eng., National Cheng-Kung University, Tainan City 70101, Taiwan;2. International Wave Dynamics Research Center, National Cheng-Kung University, Tainan City 70101, Taiwan;1. National Maritime Research Institute, Japan, 6-38-1 Shinkawa, Mitaka, Tokyo, Japan;2. Mitsui O.S.K. Lines, Ltd., 2-1-1 Toranomon, Minato-ku, Tokyo, Japan;1. Department of Ocean Engineering and Naval Architecture, Indian Institute of Technology, Kharagpur, India;2. Department of Mechanical Engineering, Gitam Engineering College, Hyderabad, India
Abstract:Weather routing methods are essential for planning routes for commercial shipping and recreational craft. This paper provides a methodology for quantifying the significance of numerical error and performance model uncertainty on the predictions returned from a weather routing algorithm. The numerical error of the routing algorithm is estimated by solving the optimum path over different discretizations of the environment. The uncertainty associated with the performance model is linearly varied in order to quantify its significance. The methodology is applied to a sailing craft routing problem: the prediction of the voyaging time for an ethnographic voyaging canoe across long distance voyages in Polynesia. We find that the average numerical error is an order of magnitude smaller than the performance model uncertainty. These results illustrate the significance of considering the influence of numerical error and performance uncertainty when performing a weather routing study.
Keywords:Uncertainty analysis  Numerical error  Weather routing
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