dc.creatorRueda-Bayona, Juan Gabriel
dc.creatorGuzmán, Andrés
dc.creatorCabello Eras, Juan José
dc.date2020-10-15T16:23:22Z
dc.date2020-10-15T16:23:22Z
dc.date2020
dc.date.accessioned2023-10-03T20:06:58Z
dc.date.available2023-10-03T20:06:58Z
dc.identifierhttps://hdl.handle.net/11323/7142
dc.identifier0733950X
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9174318
dc.descriptionThe design of marine structures requires the simulation of wave parameters that consider sea-state and water-depth transitions. Proper selection of the model coefficients (e.g., alpha and gamma of the JONSWAP spectra) is then required, because of the wave-hydrodynamic nonlinearities during these ocean processes. Therefore, the model coefficient selection should be tested using a nonlinear analysis to assess the effect of the selected spectra coefficients over the modeled wave parameters. The present study performed a design of experiment (DOE)-analysis of variance (ANOVA) and probability analysis to assess the effect of alpha and gamma parameters over the significant wave height (Hs) and peak period (Tp) during sea-state and water-depth transitions. The DOE-ANOVA demonstrated for the mean and extreme wave states of the study area that alpha and gamma parameters positively affect the Hs behavior in deep and intermediate waters. Furthermore, the standardized effects of alpha and gamma over the Tp during extreme wave states suggest quadruplets of wave-wave interactions. The joint and normal probability distributions of alpha and gamma for extreme and normal waves showed a Gaussian distribution, allowing identification of specific alpha and gamma values for the JONSWAP spectra model. The selected alpha and gamma parameters were then validated through the comparison of the modeled Hs (JONSWAP) against other local studies. Considering its relevance in design strategies for offshore structures, this research contributed to the understanding of the nonlinear effects of alpha and gamma parameters over the Hs and Tp during variations of water depth and wave states, easing the selection of the model coefficients.
dc.formatapplication/pdf
dc.languageeng
dc.publisherCorporación Universidad de la Costa
dc.relationASCE. 2017. Minimum design loads and associated criteria for buildings and other structures. ASCE/SEI 7-16. Reston, VA: ASCE.
dc.relationBooij, N., R. C. Ris, and L. H. Holthuijsen. 1999. “A third-generation wave model for coastal regions: 1. Model description and validation.” J. Geophys. Res.: Oceans 104 (C4): 7649–7666. https://doi.org/10 .1029/98JC02622
dc.relationBoukhanovsky, A. V., and C. Guedes Soares. 2009. “Modelling of multipeaked directional wave spectra.” Appl. Ocean Res. 31 (2): 132–141. https://doi.org/10.1016/j.apor.2009.06.001.
dc.relationBoukhanovsky, A. V., L. J. Lopatoukhin, and C. Guedes Soares. 2007. “Spectral wave climate of the North Sea.” Appl. Ocean Res. 29 (3): 146–154. https://doi.org/10.1016/j.apor.2007.08.004.
dc.relationCalini, A., and C. M. Schober. 2017. “Characterizing JONSWAP rogue waves and their statistics via inverse spectral data.” Wave Motion 71: 5–17. https://doi.org/10.1016/j.wavemoti.2016.06.007.
dc.relationChakrabarti, S. 2005. Handbook of offshore engineering. Amsterdam, Netherlands: Elsevier.
dc.relationCifuentes, C., and M. H. Kim. 2017. “Hydrodynamic response of a cage system under waves and currents using a morison-force model.” Ocean Eng. 141: 283–294. https://doi.org/10.1016/j.oceaneng.2017.06 .055.
dc.relationDeltares. 2014a. Delft3D-WAVE. Simulation of short-crested waves with SWAN—User manual. Delft, Netherlands: Deltares.
dc.relationDeltares. 2014b. Delft3D-FLOW. Simulation of multi-dimensional hydrodynamic flows and transport phenomena, including sediments—User manual. Delft, Netherlands: Deltares.
dc.relationDerschum, C., I. Nistor, J. Stolle, and N. Goseberg. 2018. “Debris impact under extreme hydrodynamic conditions part 1: Hydrodynamics and impact geometry.” Coastal Eng. 141: 24–35. https://doi.org/10.1016/j .coastaleng.2018.08.016
dc.relationDevis-Morales, A., R. A. Montoya-Sánchez, G. Bernal, and A. F. Osorio. 2017. “Assessment of extreme wind and waves in the Colombian Caribbean Sea for offshore applications.” Appl. Ocean Res. 69: 10– 26. https://doi.org/10.1016/j.apor.2017.09.012.
dc.relationDong, G., H. Chen, and Y. Ma. 2014. “Parameterization of nonlinear shallow water waves over sloping bottoms.” Coastal Eng. 94: 23–32. https://doi.org/10.1016/j.coastaleng.2014.08.012
dc.relationElhakeem, A., W. Elshorbagy, and T. Bleninger. 2015. “Long-term hydrodynamic modeling of the Arabian Gulf.” Mar. Pollut. Bull. 94 (1–2): 19–36. https://doi.org/10.1016/j.marpolbul.2015.03.020.
dc.relationEscobar, C. A. 2011. “Relevancia de procesos costeros en la hidrodinámica del Golfo de Urabá (Caribe colombiano).” Bull. Mar. Coastal Res. 40 (2): 327–346.
dc.relationFEMA and NOAA (Federal Emergency Management Agency and National Oceanic and Atmospheric Administration). 2012. FEMA P-646: Guidelines for design of structures for vertical evacuation from tsunamis. Redwood City, CA: Applied Technology Council.
dc.relationFragasso, J., L. Moro, L. M. Lye, and B. W. T. Quinton. 2019. “Characterization of resilient mounts for marine diesel engines: Prediction of static response via nonlinear analysis and response surface methodology.” Ocean Eng. 171: 14–24. https://doi.org/10.1016/j .oceaneng.2018.10.051
dc.relationGarcia, M., I. Ramirez, M. Verlaan, and J. Castillo. 2015. “Application of a three-dimensional hydrodynamic model for San Quintin Bay, B.C., Mexico. Validation and calibration using OpenDA.” J. Comput. Appl. Math. 273: 428–437. https://doi.org/10.1016/j.cam.2014.05.003.
dc.relationHanley, M. E., et al. 2014. “Shifting sands? Coastal protection by sand banks, beaches and dunes.” Coastal Eng. 87: 136–146. https://doi.org /10.1016/j.coastaleng.2013.10.020.
dc.relationHasselmann, K. 1962. “On the non-linear energy transfer in a gravity-wave spectrum Part 1. General theory.” J. Fluid Mech. 12 (4): 481–500. https://doi.org/10.1017/S0022112062000373.
dc.relationHasselmann, K. 1963a. “On the non-linear energy transfer in a gravity wave spectrum Part 2. Conservation theorems; wave-particle analogy; irreversibility.” J. Fluid Mech. 15 (2): 273–281. https://doi.org/10 .1017/S0022112063000239.
dc.relationHasselmann, K. 1963b. “On the non-linear energy transfer in a gravitywave spectrum. Part 3. Evaluation of the energy flux and swell-sea interaction for a Neumann spectrum.” J. Fluid Mech. 15 (3): 385–398. https://doi.org/10.1017/S002211206300032X.
dc.relationHasselmann, K., et al. 1973. “Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP).” Ergänzungsheft zur Deutschen Hydrographischen Zeitschrift 8 (12): 93.
dc.relationHolthuijsen, L. H. 2010. Waves in oceanic and coastal waters. Cambridge, UK: Cambridge University Press.
dc.relationJi, C., Q. Zhang, and Y. Wu. 2018. “An empirical formula for maximum wave setup based on a coupled wave-current model.” Ocean Eng. 147: 215–226. https://doi.org/10.1016/j.oceaneng.2017.10.021
dc.relationLe Provost, C., M. L. Genco, F. Lyard, P. Vincent, and P. Canceil. 1994. “Spectroscopy of the world ocean tides from a finite element hydrodynamic model.” J. Geophys. Res. 99 (C12): 24777–24797. https://doi.org /10.1029/94JC01381.
dc.relationLiu, S., Y. Li, and G. Li. 2007. “Wave current forces on the pile group of base foundation for the East Sea Bridge, China.” J. Hydrodyn. 19 (6): 661–670. https://doi.org/10.1016/S1001-6058(08)60001-3.
dc.relationLocarnini, R. A., et al. 2013. World ocean atlas 2013, Volume 1: Temperature. NOAA Atlas NESDIS 73. Silver Spring, MD: U.S. Department of Commerce
dc.relationLucas, C., and C. Guedes Soares. 2015. “Bivariate distributions of significant wave height and mean wave period of combined sea states.” Ocean Eng. 106: 341–353. https://doi.org/10.1016/j.oceaneng.2015.07.010.
dc.relationMackay, E. B. L. 2011. “Modelling and description of omnidirectional wave spectra.” In Proc., European Wave and Tidal Energy. Southampton, UK: University of Southampton
dc.relationMackay, E. B. L. 2016. “A unified model for unimodal and bimodal ocean wave spectra.” Int. J. Mar. Energy 15: 17–40. https://doi.org/10.1016/j .ijome.2016.04.015
dc.relationMcCombs, M. P., R. P. Mulligan, and L. Boegman. 2014. “Offshore wind farm impacts on surface waves and circulation in Eastern Lake Ontario.” Coastal Eng. 93: 32–39. https://doi.org/10.1016/j.coastaleng .2014.08.001.
dc.relationMesa García, J. C. 2010. “Metodología para el reanálisis de series de oleaje para el Caribe Colombiano.” M.Sc. thesis, Facultad de Minas, Universidad Nacional de Colombia.
dc.relationMontazeri, N., U. D. Nielsen, and J. Juncher Jensen. 2016. “Estimation of wind sea and swell using shipboard measurements—A refined parametric modelling approach.” Appl. Ocean Res. 54: 73–86. https://doi.org/10 .1016/j.apor.2015.11.004.
dc.relationMontgomery, D. C. 2017. Design and analysis of experiments. Hoboken, NJ: John Wiley & Sons
dc.relationMyrhaug, D. 2018. “Some probabilistic properties of deep water wave steepness.” Oceanologia 60 (2): 187–192. https://doi.org/10.1016/j .oceano.2017.10.003.
dc.relationNOAA (National Oceanic and Atmospheric Administration). 2016. “NCEP North American Regional Reanalysis: NARR.” Accessed July 4, 2020. https://www.esrl.noaa.gov/psd/data/gridded/data.narr.html.
dc.relationNOAA (National Oceanic and Atmospheric Administration). 2018a. “ETOPO1 Global Relief Model.” ETOPO1 Global Relief Model. Accessed July 20, 2018. https://www.ngdc.noaa.gov/mgg/global/.
dc.relationNOAA (National Oceanic and Atmospheric Administration). 2018b. “NOAA WAVEWATCH III® CFSR Reanalysis Hindcasts.” NOAA WAVEWATCH III. Accessed July 20, 2018. https://polar.ncep.noaa .gov/waves/CFSR_hindcast.shtml.
dc.relationOchi, M. K., and E. N. Hubble. 1976. “Six-parameter wave spectra.” In Proc., 15th Int. Conf. on Coastal Engineering, 301–328. Reston, VA: ASCE.
dc.relationOrtega, S., A. F. Osorio, P. Agudelo-Restrepo, and J. I. Velez. 2011. “Methodology for estimating wave power potential in places with scarce instrumentation in the Caribbean Sea.” In OCEANS 2011 IEEE, 1–5. Santander, Spain: IEEE.
dc.relationPascoal, R., L. P. Perera, and C. Guedes Soares. 2017. “Estimation of directional sea spectra from ship motions in sea trials.” Ocean Eng. 132: 126–137. https://doi.org/10.1016/j.oceaneng.2017.01.020.
dc.relationPhillips, O. M. 1960. “On the dynamics of unsteady gravity waves of finite amplitude Part 1. The elementary interactions.” J. Fluid Mech. 9 (2): 193–217. https://doi.org/10.1017/S0022112060001043.
dc.relationPower, H. E., B. Gharabaghi, H. Bonakdari, B. Robertson, A. L. Atkinson, and T. E. Baldock. 2019. “Prediction of wave runup on beaches using gene-expression programming and empirical relationships.” Coastal Eng. 144: 47–61. https://doi.org/10.1016/j.coastaleng.2018.10.006.
dc.relationRestrepo, J. C., K. Schrottke, C. Traini, J. C. Ortíz, A. Orejarena, L. Otero, A. Higgins, and L. Marriaga. 2016. “Sediment transport and geomorphological change in a high-discharge tropical delta (Magdalena River, Colombia): Insights from a period of intense change and human intervention (1990–2010).” J. Coastal Res. 32 (3): 575–589. https://doi.org/10.2112/JCOASTRES-D-14-00263.1.
dc.relationRueda Bayona, J. G. 2015. “Caracterización hidromecánica de plataformas marinas en aguas intermedias sometidas a cargas de oleaje y corriente mediante modelación numérica.” Master thesis, Facultad de Minas, Universidad Nacional de Colombia.
dc.relationRueda Bayona, J. G. 2017. “Identificación de la influencia de las variaciones convectivas en la generación de cargas transitorias y su efecto hidromecánico en las estructuras Offshore.” Ph.D. thesis, Civil and Environmental Engineering Dept., Universidad del Norte.
dc.relationRueda-Bayona, J. G., A. Guzmán, and R. Silva. 2020. “Genetic algorithms to determine JONSWAP spectra parameters.” Ocean Dyn. 70: 561–571. https://doi.org/10.1007/s10236-019-01341-8.
dc.relationRueda-Bayona, J. G., A. F. Osorio-Arias, A. Guzmán, and G. Rivillas-Ospina. 2019. “Alternative method to determine extreme hydrodynamic forces with data limitations for offshore engineering.” J. Waterw. Port Coastal Ocean Eng. 145 (2): 05018010. https://doi .org/10.1061/(ASCE)WW.1943-5460.0000499.
dc.relationSakhare, S., and M. C. Deo. 2009. “Derivation of wave spectrum using data driven methods.” Mar. Struct. 22: 594–609. https://doi.org/10.1016/j .marstruc.2008.12.004.
dc.relationSanil Kumar, V., and K. Ashok Kumar. 2008. “Spectral characteristics of high shallow water waves.” Ocean Eng. 35 (8): 900–911. https://doi .org/10.1016/j.oceaneng.2008.01.016.
dc.relationSun, Y., and X. Zhang. 2017. “A second order analytical solution of focused wave group interacting with a vertical wall.” Int. J. Nav. Archit. Ocean Eng. 9 (2): 160–176. https://doi.org/10.1016/j.ijnaoe .2016.09.002.
dc.relationUittenbogaard, R. E., J. A. T. M. van Kester, and G. S. Stelling. 1992. Implementation of three turbulence models in 3D-TRISULA for rectangular grids. Delft, Netherlands: Delft Hydraulics.
dc.relationWang, Y. 2014. “Calculating crest statistics of shallow water nonlinear waves based on standard spectra and measured data at the Poseidon platform.” Ocean Eng. 87: 16–24. https://doi.org/10.1016/j.oceaneng .2014.05.012.
dc.relationWijaya, A. P., and E. Van Groesen. 2016. “Determination of the significant wave height from shadowing in synthetic radar images.” Ocean Eng. 114: 204–2015. https://doi.org/10.1016/j.oceaneng.2016.01.011.
dc.relationYoung, D. L., and B. M. Scully. 2018. “Assessing structure sheltering via statistical analysis of AIS data.” J. Waterw. Port Coastal Ocean Eng. 144 (3): 04018002. https://doi.org/10.1061/(ASCE)WW.1943-5460 .0000445.
dc.relationZanaganeh, M., S. J. Mousavi, and A. F. Etemad Shahidi. 2009. “A hybrid genetic algorithm–adaptive network-based fuzzy inference system in prediction of wave parameters.” Eng. Appl. Artif. Intell. 22 (8): 1194– 1202. https://doi.org/10.1016/j.engappai.2009.04.009.
dc.relationZweng, M. M., et al. 2013. World ocean atlas 2013, Volume 2: Salinity. NOAA Atlas NESDIS 74. Silver Spring, MD: U.S. Department of Commerce.
dc.rightsCC0 1.0 Universal
dc.rightshttp://creativecommons.org/publicdomain/zero/1.0/
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rightshttp://purl.org/coar/access_right/c_14cb
dc.sourceJournal of Waterway, Port, Coastal and Ocean Engineering
dc.sourcehttps://ascelibrary.org/doi/10.1061/%28ASCE%29WW.1943-5460.0000601
dc.subjectDOE-ANOVA
dc.subjectJONSWAP spectra
dc.subjectNumerical modeling
dc.subjectProbability
dc.subjectWaves
dc.titleSelection of jonswap spectra parameters during water-depth and sea-state transitions
dc.typePre-Publicación
dc.typehttp://purl.org/coar/resource_type/c_816b
dc.typeText
dc.typeinfo:eu-repo/semantics/preprint
dc.typeinfo:eu-repo/semantics/draft
dc.typehttp://purl.org/redcol/resource_type/ARTOTR
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


Este ítem pertenece a la siguiente institución