Abstract
This paper introduces a pipeline that assembles a dataset of metocean conditions consisting of wind, wave, and surface currents, and then clusters these data to find the characteristic environmental conditions of each region on the Brazilian coast and the associated Exclusive Economic Zone. Clustering uses the Partitioning Around Medoids algorithm with the silhouette coefficient. As examples, we first present an analysis of the whole Exclusive Economic Zone and then a focused analysis around the Santos port in Southeastern Brazil.
Issue Section:
Ocean Engineering
References
1.
Vogel
, M.
, Hanson
, J.
, Fan
, S.
, Forristall
, G. Z.
, Li
, Y.
, Fratantonio
, R.
, and Jonathan
, P.
, 2016
, “Efficient Environmental and Structural Response Analysis by Clustering of Directional Wave Spectra
,” Proceedings of the Vol. Day 3, May 4, 2016 of OTC Offshore Technology Conference
, Houston, TX
, May 2–5
.2.
Camus
, P.
, Mendez
, F. J.
, Medina
, R.
, and Cofino
, AS˜
, 2011
, “Analysis of Clustering and Selection Algorithms for the Study of Multivariate Wave Climate
,” Coast. Eng.
, 58
(6
), pp. 453
–462
. 3.
Romeu
, M. A. R.
, Fontoura
, J. A. S.
, and Melo
, E.
, 2015
, “Typical Scenarios of Wave Regimes off Rio Grande do Sul, Southern Brazil
,” J. Coast. Res.
, 31
(1
), pp. 61
–68
. 4.
Prevosto
, M.
, Forristall
, G. Z.
, Jeans
, G.
, Herry
, C.
, Harte
, G.
, Harrington-Missin
, L.
, and Dooley
, P.
, 2012
, “Worldwide Approximations of Current Profiles for Steel Riser Design: The WACUP Project
,” Proceedings of the Pipeline and Riser Technology of International Conference on Offshore Mechanics and Arctic Engineering, Vol. 3
, Rio de Janeiro, Brazil
, July 1–6
, pp. 261
–268
.5.
Liu
, Y.
, and Weisberg
, R. H.
, 2005
, “Patterns of Ocean Current Variability on the West Florida Shelf Using the Self-Organizing map
,” J. Geophys. Res. Oceans
, 110
(C6
), pp. 1
–12
. 6.
Jeans
, G.
, Gibson
, R.
, and Jones
, O.
, 2015
, “A New Quantitative Assessment of Current Profile Clustering Methods for Riser Engineering
,” Proceedings of the Offshore Technology; Offshore Geotechnics of International Conference on Offshore Mechanics and Arctic Engineering
, St. John’s, Newfoundland, Canada
, May 31–June 5
.7.
Kanner
, S.
, Aubault
, A.
, Peiffer
, A.
, and Yu
, B.
, 2017
, “Efficient Algorithm for Discretization of Metocean Data Into Clusters of Arbitrary Size and Dimension
,” Vol. 10—Ocean Renewable Energy of International Conference on Offshore Mechanics and Arctic Engineering
, Trondheim, Norway
, June 25–30
.8.
Kanner
, S.
, Aubault
, A.
, Peiffer
, A.
, and Yu
, B.
, 2018
, “Maximum Dissimilarity-Based Algorithm for Discretization of Metocean Data Into Clusters of Arbitrary Size and Dimension
,” Ocean Renewable Energy of International Conference on Offshore Mechanics and Arctic Engineering, Vol. 10
, Madrid, Spain
, June 17–22
.9.
Gibson
, R.
, and Christou
, M.
, 2019
, “Metocean Criteria for the Fatigue Analysis of Subsea Pipelines
,” Ocean Engineering of International Conference on Offshore Mechanics and Arctic EngineeringVol. 7B
, Glasgow, Scotland, UK
, June 9–14
.10.
Moreno
, F. M.
, and Tannuri
, E. A.
, 2021
, “Clustering Applied to Large Sets of Environmental Conditions for Selecting Typical Scenarios for Ship Maneuvering Real-Time Simulations
,” Vol. Volume 6: Ocean Engineering of International Conference on Offshore Mechanics and Arctic Engineering. Online Conference.
, Virtual Conference
, June 21–30
.11.
Center for Artificial Intelligence
, 2020
. KELM Knowledge-Enhanced Machine Learning for Reasoning about Ocean Data
, https://c4ai.inova.usp.br/keml-en/, Accessed June 15, 2021.12.
HYbrid Coordinate Ocean Model
, 2019
. HYCOM THREDDS Server
. https://tds.hycom.org/ thredds/catalogs/GLBv0.08/expt\53.X.html, Accessed June 20, 2021.13.
Chassignet
, E. P.
, Hurlburt
, H. E.
, Smedstad
, O. M.
, Halliwell
, G. R.
, Hogan
, P. J.
, Wallcraft
, A. J.
, Baraille
, R.
, and Bleck
, R.
, 2007
, “The HYCOM (HYbrid Coordinate Ocean Model) Data Assimilative System
,” J. Mar. Syst.
, 65
(1–4
), pp. 60
–83
. 14.
Cummings
, J. A.
, 2005
, “Operational Multivariate Ocean Data Assimilation. Quarterly Journal of the Royal Meteorological Society
”. Vol. 131
, pp. 3583
–3604
.15.
Cummings
, J. A.
, and Smedstad
, O. M.
, 2013
, Variational Data Assimilation for the Global Ocean
, Springer Berlin Heidelberg
, Berlin/Heidelberg
, 303
–343
.16.
National Centers for Environmental Information
, 2017
. NCEI—Coasts & Oceans THREDDS Server
. https://www.ncei.noaa.gov/threddsocean/catalog/ncep/nww3/catalog.html, Accessed June 20, 2021.17.
Tolman
, H. L.
, 2009
, User Manual and System Documentation of WAVEWATCH III TM Version 3.14 †
. Technical Report, MMAB Contribution No. 276.18.
19.
Ankerst
, M.
, Breunig
, M. M.
, Kriegel
, H. P.
, and Sander
, J.
, 1999
, “OPTICS: Ordering Points to Identify the Clustering Structure
,” ACM SIGMOD Record
, 28
(2
), pp. 49
–60
. 20.
Attias
, M.
, 1999
, “A Variational Bayesian Framework for Graphical Models
,” Proceedings of the 12th International Conference on Neural Information Processing Systems
, Denver, CO
, Nov. 29–Dec. 4
, MIT Press, pp. 209
–215
.21.
Vendramin
, L.
, Campello
, R. J.
, and Hruschka
, E. R.
, 2010
, “Relative Clustering Validity Criteria: A Comparative Overview
,” Stat. Anal. Data Min.
, 3
(4
), pp. 209
–235
. 22.
Kaufman
, L.
, and Rousseeuw
, P. J.
, 1987
, “Clustering by Means of Medoids
,” Proceedings of Statistical Data Analysis Based on L1 Norm Conference
, Neuchatel, Switzerland
, Aug. 31–Sept. 4
, pp. 405
–416
.23.
Rousseeuw
, P. J.
, 1987
, “Silhouettes: A Graphical Aid to the Interpretation and Validation of Cluster Analysis
,” J. Comput. Appl. Math.
, 20
(1
), pp. 53
–65
. 24.
Ma
, M.
, 2020
. Wind Rose
, https://www.mathworks.com/ matlabcentral/fileexchange/17748-windrose, Accessed June 20, 2021.Copyright © 2023 by ASME
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