Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements
International audience We investigate a nonlinear phase-resolved reconstruction algorithm and models for the deterministic prediction of ocean waves based on a large number of spatio-temporal optical measurements of surface elevations. We consider a single sensor (e.g., LIDAR, stereo-video, etc.) mo...
Published in: | Volume 7B: Ocean Engineering |
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ftccsdartic:oai:HAL:hal-01855465v1 2023-05-15T14:23:27+02:00 Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements Desmars, Nicolas Perignon, Yves Ducrozet, Guillaume Guérin, Charles-Antoine Grilli, Stephan T. FERRANT, Pierre Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA) École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS) Department of Ocean Engineering (DOE/URI) University of Rhode Island (URI) Madrid, Spain 2018-06 https://hal.archives-ouvertes.fr/hal-01855465 https://hal.archives-ouvertes.fr/hal-01855465/document https://hal.archives-ouvertes.fr/hal-01855465/file/Desmars2018.pdf https://doi.org/10.1115/OMAE2018-78367 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.1115/OMAE2018-78367 hal-01855465 https://hal.archives-ouvertes.fr/hal-01855465 https://hal.archives-ouvertes.fr/hal-01855465/document https://hal.archives-ouvertes.fr/hal-01855465/file/Desmars2018.pdf doi:10.1115/OMAE2018-78367 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering https://hal.archives-ouvertes.fr/hal-01855465 ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering, Jun 2018, Madrid, Spain. ⟨10.1115/OMAE2018-78367⟩ [SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] info:eu-repo/semantics/conferenceObject Conference papers 2018 ftccsdartic https://doi.org/10.1115/OMAE2018-78367 2021-11-07T00:47:05Z International audience We investigate a nonlinear phase-resolved reconstruction algorithm and models for the deterministic prediction of ocean waves based on a large number of spatio-temporal optical measurements of surface elevations. We consider a single sensor (e.g., LIDAR, stereo-video, etc.) mounted on a fixed offshore structure and remotely measuring fields of free surface elevations. Assuming a uniform distribution of measurement points over the sensor aperture angles, the density of free surface observation points geometrically decreases with the distance from the sensor. Additionally, wave shadowing effects occur, which become more important at small viewing angles (i.e., grazing incidence on the surface). These effects result in observations of surface elevation that are sparsely distributed. Here, based on earlier work by [1], we present and discuss the characteristics of an algorithm, aimed at assimilating such sparse data and able to deterministically reconstruct and propagate ocean surface elevations for their prediction in time and space. This algorithm could assist in the automatic steering and control of a variety of surface vehicles. Specifically, we compare prediction results using linear wave theory and the weakly nonlinear Choppy Wave Model [2, 3], extended here to an “improved” second order formulation. The latter model is based on an efficient Lagrangian formulation of the free surface and was shown to be able to model wave properties that are important to the proper representation of nonlinear free surfaces, namely wave shape and celerity. Synthetic datasets from highly nonlinear High Order Spectral simulations are used as reference oceanic surfaces. Predicted results are analyzed over an area that evolves in time, using the theoretical amount of information assimilated during the reconstruction of the wave field. For typical horizons of prediction, we discuss the capabilities of our assimilation process for each wave model considered. Conference Object Arctic Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Volume 7B: Ocean Engineering |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
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ftccsdartic |
language |
English |
topic |
[SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] |
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[SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] Desmars, Nicolas Perignon, Yves Ducrozet, Guillaume Guérin, Charles-Antoine Grilli, Stephan T. FERRANT, Pierre Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements |
topic_facet |
[SPI.MECA.MEFL]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Fluids mechanics [physics.class-ph] |
description |
International audience We investigate a nonlinear phase-resolved reconstruction algorithm and models for the deterministic prediction of ocean waves based on a large number of spatio-temporal optical measurements of surface elevations. We consider a single sensor (e.g., LIDAR, stereo-video, etc.) mounted on a fixed offshore structure and remotely measuring fields of free surface elevations. Assuming a uniform distribution of measurement points over the sensor aperture angles, the density of free surface observation points geometrically decreases with the distance from the sensor. Additionally, wave shadowing effects occur, which become more important at small viewing angles (i.e., grazing incidence on the surface). These effects result in observations of surface elevation that are sparsely distributed. Here, based on earlier work by [1], we present and discuss the characteristics of an algorithm, aimed at assimilating such sparse data and able to deterministically reconstruct and propagate ocean surface elevations for their prediction in time and space. This algorithm could assist in the automatic steering and control of a variety of surface vehicles. Specifically, we compare prediction results using linear wave theory and the weakly nonlinear Choppy Wave Model [2, 3], extended here to an “improved” second order formulation. The latter model is based on an efficient Lagrangian formulation of the free surface and was shown to be able to model wave properties that are important to the proper representation of nonlinear free surfaces, namely wave shape and celerity. Synthetic datasets from highly nonlinear High Order Spectral simulations are used as reference oceanic surfaces. Predicted results are analyzed over an area that evolves in time, using the theoretical amount of information assimilated during the reconstruction of the wave field. For typical horizons of prediction, we discuss the capabilities of our assimilation process for each wave model considered. |
author2 |
Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA) École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS) Department of Ocean Engineering (DOE/URI) University of Rhode Island (URI) |
format |
Conference Object |
author |
Desmars, Nicolas Perignon, Yves Ducrozet, Guillaume Guérin, Charles-Antoine Grilli, Stephan T. FERRANT, Pierre |
author_facet |
Desmars, Nicolas Perignon, Yves Ducrozet, Guillaume Guérin, Charles-Antoine Grilli, Stephan T. FERRANT, Pierre |
author_sort |
Desmars, Nicolas |
title |
Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements |
title_short |
Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements |
title_full |
Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements |
title_fullStr |
Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements |
title_full_unstemmed |
Phase-Resolved Reconstruction Algorithm and Deterministic Prediction of Nonlinear Ocean Waves From Spatio-Temporal Optical Measurements |
title_sort |
phase-resolved reconstruction algorithm and deterministic prediction of nonlinear ocean waves from spatio-temporal optical measurements |
publisher |
HAL CCSD |
publishDate |
2018 |
url |
https://hal.archives-ouvertes.fr/hal-01855465 https://hal.archives-ouvertes.fr/hal-01855465/document https://hal.archives-ouvertes.fr/hal-01855465/file/Desmars2018.pdf https://doi.org/10.1115/OMAE2018-78367 |
op_coverage |
Madrid, Spain |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering https://hal.archives-ouvertes.fr/hal-01855465 ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering, Jun 2018, Madrid, Spain. ⟨10.1115/OMAE2018-78367⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1115/OMAE2018-78367 hal-01855465 https://hal.archives-ouvertes.fr/hal-01855465 https://hal.archives-ouvertes.fr/hal-01855465/document https://hal.archives-ouvertes.fr/hal-01855465/file/Desmars2018.pdf doi:10.1115/OMAE2018-78367 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1115/OMAE2018-78367 |
container_title |
Volume 7B: Ocean Engineering |
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1766296002313060352 |