Reconstruction and Prediction of Short-Crested Seas Based on the Application of a 3D-FFT on Synthetic Waves: Part 1 — Reconstruction

2012 ◽  
Author(s):  
Peter Naaijen ◽  
Elise Blondel-Couprie
Keyword(s):  
Wave Field ◽  
Domain Size ◽  
Offshore Structures ◽  
Propagation Model ◽  
Wave Measurements ◽  
Measurement Domain ◽  
Frequency Components ◽  
Spatio Temporal ◽  
Domain Description ◽  
Temporal Measurement

This article explores the feasibility of using a 3-dimensional Fast Fourier Transform (3D FFT) to obtain a frequency domain description of a spatio temporal measured short crested wave field. As 3D FFT is also the basic technique behind wave measurements by navigational X-band radars, the frequency components obtained by these radars could be used as initialization of a wave propagation model, enabling deterministic prediction of wave elevation on board of ships / offshore structures. Different methods are presented to use the dispersion relation to filter wave components obtained by the 3D FFT. The effect on the accuracy of data windowing and temporal measurement domain size are explored by simulations with linear synthetic wave data: It is investigated how well a synthetic wave field reconstructs after inverse transforming the filtered frequency components obtained by 3D FFT. A second paper [1] will consider the prediction outside the measurement domain by using the filtered 3D FFT components.

scholarly journals Spatio-Temporal Deforestation Measurement Using Automatic Clustering

2016 ◽  
Vol 4 (1) ◽  
Author(s):  
Irene Erlyn Wina Rachmawan ◽  
Ali Ridho Barakbah ◽  
Tri Harsono
Keyword(s):  
Experimental Study ◽  
Satellite Images ◽  
New Approach ◽  
Deforestation Rate ◽  
Automatic Interpretation ◽  
Automatic Clustering ◽  
Landsat 7 ◽  
Spatio Temporal ◽  
Temporal Measurement ◽  
World Records

Deforestation is one of the crucial issues in Indonesia. In 2012, deforestation rate in Indonesia reached 0.84 million hectares, exceeding Brazil. According to the 2009 Guinness World Records, Indonesia's deforestation rate was 1.8 million hectares per year between 2000 and 2005. An interesting view is the fact that Indonesia government denied the deforestation rate in those years and said that the rate was only 1.08 million hectares per year in 2000 and 2005. The different problem is on the technique how to deal with the deforestation rate. In this paper, we proposed a new approach for automatically identifying the deforestation area and measuring the deforestation rate. This approach involves differential image processing for detecting Spatio-temporal nature changes of deforestation. It consists series of important features extracted from multiband satellite images which are considered as the dataset of the research. These data are proceeded through the following stages: (1) Automatic clustering for multiband satellite images, (2) Reinforcement Programming to optimize K-Means clustering, (3) Automatic interpretation for deforestation areas, and (4) Deforestation measurement adjusting with elevation of the satellite. For experimental study, we applied our proposed approach to analyze and measure the deforestation in Mendawai, South Borneo. We utilized Landsat 7 to obtain the multiband images for that area from the year 2001 to 2013. Our proposed approach is able to identify the deforestation area and measure the rate. The experiment with our proposed approach made a temporal measurement for the area and showed the increasing deforestation size of the area 1.80 hectares during those years.

Effect of Spatial Variation of a Wave Field on the Resulting Ripple Characteristics and Comparison to Present Ripple Predictors

2009 ◽  
Author(s):  
Blake J. Landry ◽  
Yovanni A. Catan˜o-Lopera ◽  
Matthew J. Hancock ◽  
Chiang C. Mei ◽  
Marcelo H. Garci´a
Keyword(s):  
Spatial Variation ◽  
Wave Field ◽  
Test Section ◽  
Laboratory Experiments ◽  
Laboratory Data ◽  
Standing Waves ◽  
Sand Ripple ◽  
Wave Measurements ◽  
Progressive Waves ◽  
Sediment Test

Laboratory experiments analyzed herein focus on the validity of ripple predictors under spatially variable wave envelopes. Present-day ripple predictors commonly derived from laboratory data (for smaller wave periods of about 1 to 4 s) within which only small regions of the facilities were used to observe and measure the sand ripple geometric characteristics of the nearly progressive waves measured overhead. When extended to large sediment test sections, our results show that the predictors are still valid along the tank under wave conditions which have significant wave envelope spatial variation (e.g., standing waves), provided that ripple predictors use the wave measurements directly above the respective locations within the computations. Results indicate that even under the case of mild reflection, noticeable variation in ripple characteristics can be seen along the sediment test section; thus, compels the necessity of measuring the wave field along the entire sediment section to achieve accurate results.

From Single Point Gauge to Spatio-Temporal Measurement of Ocean Waves: Prospects and Perspectives

2014 ◽  
Author(s):  
Paul C. Liu ◽  
J. C. Nieto Borge ◽  
German Rodriguez ◽  
Keith R. MacHutchon ◽  
Hsuan S. Chen
Keyword(s):  
Paradigm Shift ◽  
New World ◽  
Single Point ◽  
Ocean Waves ◽  
Data System ◽  
Preliminary Attempt ◽  
Recent Advancement ◽  
New Challenges ◽  
Spatio Temporal ◽  
Temporal Measurement

With the recent advancement of spatial measurements of ocean waves, we are clearly facing new challenges regarding how to handle an expanded new data system when it becomes widely available. In this paper we wish to present a preliminary attempt at confronting these prospects. Because the data is still very limited at present and also conceptually new, it’s a new, unfamiliar, and unrelenting world to pursue. We need a paradigm shift away from our familiar single-point conceptualization in order to effective approach the new world of truly spatial ocean waves.

scholarly journals Irregular Wave Validation of a Coupling Methodology for Numerical Modelling of Near and Far Field Effects of Wave Energy Converter Arrays

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 538 ◽  
Author(s):  
Gael Fernández ◽  
Vasiliki Stratigaki ◽  
Peter Troch
Keyword(s):  
Experimental Data ◽  
Wave Field ◽  
Wave Energy ◽  
Near Field ◽  
Coupled Model ◽  
Propagation Model ◽  
Irregular Waves ◽  
Far Field ◽  
Engineering Research ◽  
Field Effects

Between the Wave Energy Converters (WECs) of a farm, hydrodynamic interactions occur and have an impact on the surrounding wave field, both close to the WECs (“near field” effects) and at large distances from their location (“far field” effects). To simulate this “far field” impact in a fast and accurate way, a generic coupling methodology between hydrodynamic models has been developed by the Coastal Engineering Research Group of Ghent University in Belgium. This coupling methodology has been widely used for regular waves. However, it has not been developed yet for realistic irregular sea states. The objective of this paper is to present a validation of the novel coupling methodology for the test case of irregular waves, which is demonstrated here for coupling between the mild slope wave propagation model, MILDwave, and the ‘Boundary Element Method’-based wave–structure interaction solver, NEMOH. MILDwave is used to model WEC farm “far field” effects, while NEMOH is used to model “near field” effects. The results of the MILDwave-NEMOH coupled model are validated against numerical results from NEMOH, and against the WECwakes experimental data for a single WEC, and for WEC arrays of five and nine WECs. Root Mean Square Error (RMSE) between disturbance coefficient (Kd) values in the entire numerical domain ( R M S E K d , D ) are used for evaluating the performed validation. The R M S E K d , D between results from the MILDwave-NEMOH coupled model and NEMOH is lower than 2.0% for the performed test cases, and between the MILDwave-NEMOH coupled model and the WECwakes experimental data R M S E K d , D remains below 10%. Consequently, the efficiency is demonstrated of the coupling methodology validated here which is used to simulate WEC farm impact on the wave field under the action of irregular waves.

scholarly journals High-Fidelity Representation of Three-Hour Offshore Short-Crested Wave Field in the Fully Nonlinear Potential Flow Model REEF3D::FNPF

2020 ◽  
Author(s):  
Weizhi Wang ◽  
Csaba Pakozdi ◽  
Arun Kamath ◽  
Hans Bihs
Keyword(s):  
Wave Field ◽  
Potential Flow ◽  
Flow Model ◽  
Offshore Structures ◽  
High Fidelity ◽  
Fully Nonlinear ◽  
Space And Time ◽  
Nonlinear Potential ◽  
Potential Flow Model ◽  
Wave Properties

Abstract Stochastic wave properties are crucial for the design of offshore structures. Short-crested seas are commonly seen at the sites of offshore structures, especially during storm events. A long time duration is required in order to obtain the statistical properties, which is challenging for numerical simulations because of the high demand of computational resources. In this scenario, a potential flow solver is ideal due to its computational efficiency. A procedure of producing accurate representation of short-crested sea states using the open-source fully nonlinear potential flow model REEF3D::FNPF is presented in the paper. The procedure examines the sensitivity of the resolutions in space and time as well as the arrangements of wave gauge arrays. A narrow band power spectrum and a mildly spreading directional spreading function are simulated, and an equal energy method is used to generate input waves to avoid phase-locking. REEF3D::FNPF solves the Laplace equation together with the boundary conditions using a finite difference method. A sigma grid is used in the vertical direction and the vertical grid clustering follows the principle of constant truncation error. High-order discretisation methods are implemented in space and time. Message passing interface is used for high performance computation using multiple processors. Three-hour simulations are performed in full-scale at a hypothetic offshore site with constant water depth. The significant wave height, peak period, kurtosis, skewness and ergodicity are examined in the numerically generated wave field. The stochastic wave properties in the numerical wave tank (NWT) using REEF3D::FNPF match the input wave conditions with high fidelity.

Modeling Spatio-Temporal Characteristics of Metocean Conditions During Hurricanes Using Deep Neural Networks

2020 ◽  
Author(s):  
Chi Qiao ◽  
Andrew T. Myers
Keyword(s):  
Neural Networks ◽  
Principal Component Analysis ◽  
Dimension Reduction ◽  
Deep Neural Networks ◽  
Principal Component ◽  
Component Analysis ◽  
Offshore Structures ◽  
Complex Nature ◽  
Temporal Characteristics ◽  
Spatio Temporal

Abstract Surrogate modeling of the variability of metocean conditions in space and in time during hurricanes is a crucial task for risk analysis on offshore structures such as offshore wind turbines, which are deployed over a large area. This task is challenging because of the complex nature of the meteorology-metocean interaction in addition to the time-dependence and high-dimensionality of the output. In this paper, spatio-temporal characteristics of surrogate models, such as Deep Neural Networks, are analyzed based on an offshore multi-hazard database created by the authors. The focus of this paper is two-fold: first, the effectiveness of dimension reduction techniques for representing high-dimensional output distributed in space is investigated and, second, an overall approach to estimate spatio-temporal characteristics of hurricane hazards using Deep Neural Networks is presented. The popular dimension reduction technique, Principal Component Analysis, is shown to perform similarly compared to a simpler dimension reduction approach and to not perform as well as a surrogate model implemented without dimension reduction. Discussions are provided to explain why the performance of Principal Component Analysis is only mediocre in this implementation and why dimension reduction might not be necessary.

Nonlinear Fourier Analysis Algorithm and Models for Water Waves in Terms of Surface Elevation, Amplitude Modulations

2019 ◽  
Author(s):  
Alfred R. Osborne
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Waves ◽  
Shallow Water ◽  
Wave Field ◽  
Deep Water ◽  
Coherent Structures ◽  
Water Waves ◽  
Surface Elevation ◽  
Synthetic Aperture ◽  
Wave Measurements

Abstract This paper addresses two issues with regard to nonlinear ocean waves. (1) The first issue relates to the often-confused differences between the coordinates used for the measurement and characterization of ocean surface waves: The surface elevation and the complex modulation of a wave field. (2) The second issue relates to the very different kinds of physical wave behavior that occur in shallow and deep water. Both issues come from the known, very different behaviors of deep and shallow water waves. In shallow water one often uses the Korteweg-deVries that describes the wave surface elevation in terms of cnoidal waves and solitons. In deep water one uses the nonlinear Schrödinger equation whose solutions correspond to the complex envelope of a wave field that has Stokes wave and breather solutions. Here I make clear the relationships between the two ways of characterizing surface waves. Furthermore, and more importantly, I address the issues of matching the two types of wave behavior as the wave motion passes from deep to shallow water, or vice versa. For wave measurements we normally obtain the surface elevation with a wave staff, resistance gauge or pressure recorder for getting time series. Remote sensing applications relate to the use of lidar, radar or synthetic aperture radar for obtaining space series. The two types of wave behavior can therefore crucially depend on where the instrument is placed on the “ground track” or “field” over which the lidar or radar measurements are made. Thus the matching problem from deep to shallow water is not only important for wave measurements, but also for wave modeling. Modern wave models [Osborne, 2010, 2018, 2019a, 2019b] that maintain the coherent structures of wave dynamics (solitons, Stokes waves, breathers, superbreathers, vortices, etc.) must naturally pass from deep to shallow water where the nature of the nonlinear physics, and the form of the coherent structures, change. I address these issues and more herein. This paper is directed towards the development of methods for the real time measurement of waves by shipboard radar and for wave measurements by airplane and helicopter using lidar and synthetic aperture radar. Wave modeling efforts are also underway.

Domain-Spatial Correlation Function of Spherulitic Domain Evolution in Polymer Films

1997 ◽  
Vol 481 ◽  
Author(s):  
Tao Huang ◽  
Tomohiro Tsuji ◽  
M. R. Kamal ◽  
A. D. Rey
Keyword(s):  
Correlation Function ◽  
Spatial Correlation ◽  
Volume Fraction ◽  
Domain Size ◽  
Nucleation And Growth ◽  
Size Distribution Function ◽  
Domain Growth ◽  
Spatial Correlation Function ◽  
Time Dependent Domain ◽  
Spatio Temporal

ABSTRACTWe present a new theoretical model of nucleation and growth in term of a novel domainspatial correlation function. This model probes the patterns and spatio-temporal evolution of nucleation and growth process and agrees very well with experimental data. The dynamic domain-spatial correlation function directly and simultaneously explores the transformed volume fraction, the time-dependent domain size distribution function, and the spatial correlation function of domain core centers for the entire process, including the post-nucleation, domain growth and grain formation stages.

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