scholarly journals STABILITY OF RUBBLE MOUND BREAKWATERS IN SHALLOW WATER AND SURF ZONE : AN EXPERIMENTAL STUDY

2012 ◽  
Vol 1 (33) ◽  
pp. 85
Author(s):  
Guirec Prevot ◽  
Olivier Boucher ◽  
Maryline Luck ◽  
Michel Benoit
Keyword(s):  
Shallow Water ◽  
Wave Height ◽  
Significant Wave Height ◽  
Characteristic Wave ◽  
Significant Wave ◽  
Wave Parameters ◽  
Rubble Mound ◽  
Wave Conditions ◽  
Wave Models ◽  
Rubble Mound Breakwaters

Rubble-mound breakwaters are often pre-designed with empirical formulae allowing the estimation of armour stone size or weight, taking into account the wave conditions (mainly a characteristic wave height and a characteristic period), the type and density of stone or block used, the slope of the mound, the acceptable level of damage, etc. In deep water conditions, the existing formulas are rather well established (e.g. Hudson and Van der Meer formulas among others). They use as input data wave parameters that are well defined (e.g. the significant wave height H1/3 or sometimes the height H1/10) and easily accessible, from in situ measurements or from numerical wave models. In shallow water however, and in particular in breaking wave conditions (where most of the small breakwaters are built), a number of physical processes (refraction, shoaling and breaking) significantly modify the incoming waves. They also lead to changes in the wave height distribution (which can no longer be regarded as being of Rayleightype) and in the shape of the wave spectrum. This, combined with the fact that most of the models used nowadays for nearshore wave propagation are spectral wave models (e.g. SWAN, TOMAWAC, etc.) and thus provide spectral parameters as output (typically the spectral significant wave height Hm0 and the peak period Tp or the mean energetic period Tm-1,0) has raised the question of which characteristic wave parameter should be used in stability formulas for rubble-mound breakwaters in shallow water. This has led to the consideration of more representative wave parameters such as H2% or Tm-1,0 which are sometimes less accessible from existing wave database or numerical modelling studies. The objective of the present study is to review and compare several available methods to calculate armour stone weight in shallow waters, and to provide some insight into the applicability and limitations of these methods based on a series of wave flume experiments.

Traffic on the Great Lakes and New Labrador Developments

1968 ◽  
Vol 5 (04) ◽  
pp. 347-373
Author(s):  
Robert B. Harris
Keyword(s):  
Great Lakes ◽  
Wave Height ◽  
Significant Wave Height ◽  
Design Criteria ◽  
Severe Storm ◽  
Significant Wave ◽  
Hood Canal ◽  
Floating Bridge ◽  
Wave Conditions

On 13 February 1979, the entire west span of the Hood Canal Floating Bridge sank under the action of a very severe storm. Although the significant wave height was estimated as high as 4.7 feet, wind and wave conditions during the storm were well within the design criteria of the bridge.

Gap-Filling and Predicting Wave Parameters Using Support Vector Regression Method

2011 ◽  
Author(s):  
Maziar Golestani ◽  
Mostafa Zeinoddini
Keyword(s):  
Support Vector Regression ◽  
Wave Height ◽  
Significant Wave Height ◽  
Rational Design ◽  
Wave Spectrum ◽  
Support Vector ◽  
Wave Spectra ◽  
Significant Wave ◽  
Wave Parameters ◽  
Data Gaps

Knowledge of relevant oceanographic parameters is of utmost importance in the rational design of coastal structures and ports. Therefore, an accurate prediction of wave parameters is especially important for safety and economic reasons. Recently, statistical learning methods, such as Support Vector Regression (SVR) have been successfully employed by researchers in problems such as lake water level predictions, and significant wave height prediction. The current study reports potential application of a SVR approach to predict the wave spectra and significant wave height. Also the capability of the model to fill data gaps was tested using different approaches. Concurrent wind and wave records (standard meteorological and spectral density data) from 4 stations in 2003, 2007, 2008 and 2009 were used both for the training the SVR system and its verification. The choice of these four locations facilitated the comparison of model performances in different geographical areas. The SVR model was then used to obtain predictions for the wave spectra and also time series of wave parameters (separately for each station) such as its Hs and Tp from spectra and wind records. New approach was used to predict wave spectra comparing to similar studies. Reasonably well correlation was found between the predicted and measured wave parameters. The SVR model was first trained and tested using various methods for selecting training data. Also different values for SVM parameters (e.g. tolerance of termination criterion, cost, and gamma in kernel function) were tested. The best possible results were obtained using a Unix shell script (in Linux) which automatically implements different values for different input parameters and finds the best regression by calculating statistical scores like correlation of coefficient, RMSE, bias and scatter index. Finally for a better understanding of the results, Quantile-Quantile plots were produced. The results show that SVR can be successfully used for prediction of Hs and wave spectrum out of a series of wind and spectral wave parameters inputs. Also it was noticed that SVR is an efficient tool to be used when data gaps are present in the data.

Beyond significant wave height: A new approach for validating spectral wave models

2015 ◽  
Vol 100 ◽  
pp. 11-25 ◽  
Author(s):  
Edgar Peter Dabbi ◽  
Ivan D. Haigh ◽  
David Lambkin ◽  
Jamie Hernon ◽  
Jon J. Williams ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
New Approach ◽  
Significant Wave ◽  
Wave Models

scholarly journals Wave directional measurement in Patos Lagoon, RS, Brazil

RBRH ◽  
2017 ◽  
Vol 22 (0) ◽  
Author(s):  
Natália Lemke ◽  
◽  
Lauro Julio Calliari ◽  
José Antônio Scotti Fontoura ◽  
Déborah Fonseca Aguiar
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Coastal Protection ◽  
Peak Period ◽  
Patos Lagoon ◽  
Significant Wave ◽  
Wave Parameters ◽  
Wave Heights ◽  
Significant Wave Heights

ABSTRACT The wave climate characterization in coastal environments is essentially important to oceanography and coastal engineering professionals regarding coastal protection works. Thus, this study aims to determine the most frequent wave parameters (significant wave height, peak period and peak direction) in Patos Lagoon during the period of operation of a directional waverider buoy (from 01/27/2015 to 06/30/2015). The equipment was moored at approximately 14 km from the São Lourenço do Sul coast at the geographic coordinates of 31º29’06” S and 51º55’07” W, with local depth of six meters, registering significant wave height, peak period and peak direction time series. During the analyzed period, the greatest wave frequencies corresponded to short periods (between 2 and 3.5 seconds) and small values of significant wave heights (up to 0.6 meters), with east peak wave directions. The largest wave occurrences corresponded to east peak wave directions (33.3%); peak wave periods between 2.5 and 3 seconds (25.6%) and between 3 and 3.5 seconds (22.1%); and to significant wave heights of up to 0.3 meters (41.2%) and from 0.3 to 0.6 meters (38%). This research yielded unprecedented findings to Patos Lagoon by describing in detail the most occurring wave parameters during the analyzed period, establishing a consistent basis for several other studies that might still be conducted by the scientific community.

scholarly journals SAMPLING BIAS IN THE ESTIMATION OF SIGNIFICANT WAVE HEIGHT EXTREME VALUES

2017 ◽  
pp. 33
Author(s):  
Fabio Dentale ◽  
Ferdinando Reale ◽  
Felice D'Alessandro ◽  
Leonardo Damiani ◽  
Angela Di Leo ◽  
...  
Keyword(s):  
Wave Height ◽  
Time Resolution ◽  
Significant Wave Height ◽  
Extreme Values ◽  
Sampling Bias ◽  
Threshold Value ◽  
Return Time ◽  
Sampling Interval ◽  
Significant Wave ◽  
Wave Models

It has been shown before, and it is intuitively evident, that in a Significant Wave Height (SWH) time series, the longer the sampling interval, the lower is the number of events which are above a given threshold value. As a consequence, the use of data with a low time resolution (such as a 3 h sampling, for instance) causes a considerable undervaluation of the extreme SWH values for a given return time RT. In this paper an example of such a bias is provided, and a method is suggested to estimate it on a regional basis. Results may help to improve the use of historical wave meters data which were often collected with a low time resolution, and may also provide a tool to improve the application of Numerical Meteo-Wave models to the evaluation of extremes.

Climatology, Variability and Extrema of Ocean Waves: The Web-Based KNMI/ERA-40 Wave Atlas

2006 ◽  
Author(s):  
Andreas Sterl ◽  
Sofia Caires
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Model ◽  
Ocean Waves ◽  
Wave Period ◽  
Web Based ◽  
Significant Wave ◽  
Wave Parameters ◽  
Wave Heights ◽  
The Web

The European Centre for Medium Range Weather Forecasts (ECMWF) has recently finished ERA-40, a reanalysis covering the period September 1957 to August 2002. One of the products of ERA-40 consists of 6-hourly global fields of wave parameters like significant wave height and wave period. These data have been generated with the Centre’s WAM wave model. From these results the authors have derived climatologies of important wave parameters, including significant wave height, mean wave period, and extreme significant wave heights. Particular emphasis is on the variability of these parameters, both in space and time. Besides for scientists studying climate change, these results are also important for engineers who have to design maritime constructions. This paper describes the ERA-40 data and gives an overview of the results derived. The results are available on a global 1.5° × 1.5° grid. They are accessible from the web-based KNMI/ERA-40 Wave Atlas at http://www.knmi.nl/waveatlas.

Correlation Enhanced Machine Learning Approach based Wave Height Prediction

2018 ◽  
Vol 4 (5) ◽  
pp. 10
Author(s):  
Ruchi Shrivastava ◽  
Dr. Krishna Teerth Chaturvedi
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Wave Height ◽  
Significant Wave Height ◽  
Work Performance ◽  
Feature Reduction ◽  
Learning Approaches ◽  
Significant Wave ◽  
Wave Parameters ◽  
Height Prediction

The prediction of wave height is one of the major problems of coastal engineering and coastal structures. In recent years, advances in the prediction of significant wave height have been considerably developed using flexible calculation techniques. In addition to the traditional prediction of significant wave height, soft computing has explored a new way of predicting significant wave heights. This research was conducted in the direction of forecasting a significant wave height using machine learning approaches. In this paper, a problem of significant wave height prediction problem has been tackled by using wave parameters such as wave spectral density. This prediction of significant wave height helps in wave energy converters as well as in ship navigation system. This research will optimize wave parameters for a fast and efficient wave height prediction. For this Pearson’s, Kendall’s and Spearman’s Correlation Coefficients and Particle Swarm Optimization feature reduction techniques are used. So reduced features are taken into consideration for prediction of wave height using neural network. In this work, performance evaluation metrics such as MSE and RMSE values are decreased and gives better performance of classification that is compared with existing research’s implemented methodology. From the experimental results, it is observed that proposed algorithm gives the better prediction as compared to PSO feature reduction technique. So, it is also concluded that Co-relation enhanced neural network is better as compared to PSO based neural network with increased number of features.

scholarly journals Round Robin Assessment of Radar Altimeter Low Resolution Mode and Delay-Doppler Retracking Algorithms for Significant Wave Height

2020 ◽  
Vol 12 (8) ◽  
pp. 1254 ◽  
Author(s):  
Florian Schlembach ◽  
Marcello Passaro ◽  
Graham D. Quartly ◽  
Andrey Kurekin ◽  
Francesco Nencioli ◽  
...  
Keyword(s):  
Climate Change ◽  
Wave Height ◽  
Significant Wave Height ◽  
Low Resolution ◽  
Spectral Variability ◽  
Sea State ◽  
Significant Wave ◽  
In Situ Data ◽  
Wave Models

Radar altimeters have been measuring ocean significant wave height for more than three decades, with their data used to record the severity of storms, the mixing of surface waters and the potential threats to offshore structures and low-lying land, and to improve operational wave forecasting. Understanding climate change and long-term planning for enhanced storm and flooding hazards are imposing more stringent requirements on the robustness, precision, and accuracy of the estimates than have hitherto been needed. Taking advantage of novel retracking algorithms, particularly developed for the coastal zone, the present work aims at establishing an objective baseline processing chain for wave height retrieval that can be adapted to all satellite missions. In order to determine the best performing retracking algorithm for both Low Resolution Mode and Delay-Doppler altimetry, an objective assessment is conducted in the framework of the European Space Agency Sea State Climate Change Initiative project. All algorithms process the same Level-1 input dataset covering a time-period of up to two years. As a reference for validation, an ERA5-based hindcast wave model as well as an in-situ buoy dataset from the Copernicus Marine Environment Monitoring Service In Situ Thematic Centre database are used. Five different metrics are evaluated: percentage and types of outliers, level of measurement noise, wave spectral variability, comparison against wave models, and comparison against in-situ data. The metrics are evaluated as a function of the distance to the nearest coast and the sea state. The results of the assessment show that all novel retracking algorithms perform better in the majority of the metrics than the baseline algorithms currently used for operational generation of the products. Nevertheless, the performance of the retrackers strongly differ depending on the coastal proximity and the sea state. Some retrackers show high correlations with the wave models and in-situ data but significantly under- or overestimate large-scale spectral variability. We propose a weighting scheme to select the most suitable retrackers for the Sea State Climate Change Initiative programme.

Wave Power Statistics for Sea States

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Dag Myrhaug ◽  
Bernt J. Leira ◽  
Håvard Holm
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Climate ◽  
Bivariate Distribution ◽  
Wave Power ◽  
Power Devices ◽  
Characteristic Wave ◽  
Significant Wave ◽  
Wave Power Potential

This paper provides a bivariate distribution of wave power and significant wave height, as well as a bivariate distribution of wave power and a characteristic wave period for sea states, and the statistical aspects of wave power for sea states are discussed. This is relevant for, e.g., making assessments of wave power devices and their potential for converting energy from waves. The results can be applied to compare systematically the wave power potential at different locations based on long term statistical description of the wave climate.

Extreme waves induced by cyclone Nargis at Myanmar coast: numerical modeling versus satellite observations

2021 ◽  
Author(s):  
Thit Oo Kyaw ◽  
Miguel Esteban ◽  
Martin Mäll ◽  
Tomoya Shibayama
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Measurement Data ◽  
India Meteorological Department ◽  
High Energy ◽  
Significant Wave ◽  
Simulation Results ◽  
Wave Conditions ◽  
Offshore Wave ◽  
Cyclone Nargis

AbstractThe deltaic coast of Myanmar was severely hit by tropical cyclone Nargis in May 2008. In the present study, a top-down numerical simulation approach using the Weather Research and Forecasting (WRF) and Simulating WAves Nearshore (SWAN) models was conducted to study the meteorological and offshore wave characteristics of cyclone Nargis near the coast of Myanmar. The WRF simulation results agree well with the observed data from the India Meteorological Department. SWAN simulation results were compared with the WaveWatch 3 model by National Oceanic and Atmospheric Administration and validated against available measurement data from satellites. The model results show relatively good agreement, and hindcast with satellites data (significant wave height only) shows a correlation coefficient value of 0.89. The SWAN and satellite comparisons also show better fit for high wave conditions. The resulted maximum significant wave height of 7.3 m by SWAN is considerably higher in energy than the seasonal waves normally prevalent at Myanmar’s deltaic coast. The possibility of high energy waves due to cyclones should be considered during the design and operation of coastal and offshore projects in the area, particularly given the risks that climate change can intensify cyclones in the future. Since Myanmar lacks a dense network of in-situ observational stations, the methodology used in the current study presents the potential application of various numerical techniques and satellite data to estimate extreme wave conditions near the Myanmar coast.

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