scholarly journals Extreme Inundation Statistics on a Composite Beach

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1573
Author(s):  
Ahmed Abdalazeez ◽  
Ira Didenkulova ◽  
Denys Dutykh ◽  
Céline Labart
Keyword(s):  
Time Series ◽  
Wave Breaking ◽  
Statistical Characteristics ◽  
Wave Runup ◽  
Incoming Wave ◽  
Wave Statistics ◽  
Nonlinear Shallow Water Equations ◽  
Wave Heights ◽  
Wave Nonlinearity ◽  
Constant Slope

The runup of initial Gaussian narrow-banded and wide-banded wave fields and its statistical characteristics are investigated using direct numerical simulations, based on the nonlinear shallow water equations. The bathymetry consists of the section of a constant depth, which is matched with the beach of constant slope. To address different levels of nonlinearity, time series with five different significant wave heights are considered. The selected wave parameters allow for also seeing the effects of wave breaking on wave statistics. The total physical time of each simulated time-series is 1000 h (~360,000 wave periods). The statistics of calculated wave runup heights are discussed with respect to the wave nonlinearity, wave breaking and the bandwidth of the incoming wave field. The conditional Weibull distribution is suggested as a model for the description of extreme runup heights and the assessment of extreme inundations.

Run-up of narrow and wide-banded irregular waves on a beach

2020 ◽  
Author(s):  
Ahmed Abdalazeez ◽  
Denys Dutykh ◽  
Ira Didenkulova ◽  
Céline Labart
Keyword(s):  
Time Series ◽  
Gaussian Distribution ◽  
Irregular Waves ◽  
Statistical Characteristics ◽  
Higher Moments ◽  
Random Waves ◽  
Wave Runup ◽  
Mean Values ◽  
Wave Nonlinearity ◽  
The Right

<p>The runup of initial Gaussian narrow-banded and wide-banded wave fields and its statistical characteristics are investigated using direct numerical simulations, based on the nonlinear shallow water equations. The bathymetry consists of the section of a constant depth, which is matched with the beach of constant slope. To address different levels of nonlinearity, the time series with five different significant wave heights are considered. The total time of each such calculated time-series is 1000 hours.</p><p>It is shown for narrow-banded wave signal that runup oscillations are no more distributed by the Gaussian distribution. The distribution is shifted to the right towards larger positive values of wave runup. Its mean value increases with an increase in nonlinearity, which reflects the known phenomenon of wave set-up. The higher moments of runup oscillations, skewness and kurtosis are negative. The skewness is decreasing with an increase in wave nonlinearity, while kurtosis is negative and varies non-monotonically with an increase in wave nonlinearity. For Gaussian wide-banded signal, the runup oscillations also deviate from Gaussian distribution. The distribution is also shifted to the right towards larger positive values of wave runup. Its mean values increase with an increase in nonlinearity, while all other higher moments change non-monotonically.     </p><p>For the extreme wave runup heights, we conclude that the tail of the probability density function behaves like a conditional Weibull distribution if the incident random waves are represented by Gaussian narrow-banded or wide-banded spectrum. This distribution can be used for evaluation of wave inundation during extreme floods (rogue runups). </p>

scholarly journals ON THE TRANSFORMATION OF WAVE STATISTICS DUE TO SHOALING

1988 ◽  
Vol 1 (21) ◽  
pp. 7
Author(s):  
E.P.D. Mansard ◽  
E.R. Funke ◽  
J.S. Readshaw ◽  
R.K. Girard
Keyword(s):  
Physical Model ◽  
Wave Energy ◽  
Low Frequency ◽  
Nearshore Zone ◽  
Frequency Wave ◽  
Wave Statistics ◽  
Wave Measurements ◽  
Wave Heights ◽  
Significant Wave Heights ◽  
Constant Slope

The results of a 1:40 scale physical model investigation into the shoaling process are described. The model simulated a nearly constant slope of 1:40 with wave measurements made at a depth of approximately 25 and 9 m. Two hundred individual tests were undertaken, with four offshore significant wave heights as the only test variant. The results indicate that the most severe nearshore wave conditions do not occur with the worst offshore conditions. There is evidence of a significant increase in low frequency wave energy in the nearshore zone.

scholarly journals Comprehensive Wind and Wave Statistics and Extreme Values for Design and Analysis of Marine Structures in the Adriatic Sea

2021 ◽  
Vol 9 (5) ◽  
pp. 522
Author(s):  
Marko Katalinić ◽  
Joško Parunov
Keyword(s):  
Adriatic Sea ◽  
Extreme Values ◽  
Wave Climate ◽  
Offshore Structures ◽  
Model Parameters ◽  
Peak Period ◽  
Significant Wave ◽  
Wave Statistics ◽  
Wave Heights ◽  
Almost All

Wind and waves present the main causes of environmental loading on seagoing ships and offshore structures. Thus, its detailed understanding can improve the design and maintenance of these structures. Wind and wave statistical models are developed based on the WorldWaves database for the Adriatic Sea: for the entire Adriatic Sea as a whole, divided into three regions and for 39 uniformly spaced locations across the offshore Adriatic. Model parameters are fitted and presented for each case, following the conditional modelling approach, i.e., the marginal distribution of significant wave height and conditional distribution of peak period and wind speed. Extreme significant wave heights were evaluated for 20-, 50- and 100-year return periods. The presented data provide a consistent and comprehensive description of metocean (wind and wave) climate in the Adriatic Sea that can serve as input for almost all kind of analyses of ships and offshore structures.

scholarly journals SARIMA Approach to Generating Synthetic Monthly Rainfall in the Sinú River Watershed in Colombia

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 602
Author(s):  
Luisa Martínez-Acosta ◽  
Juan Pablo Medrano-Barboza ◽  
Álvaro López-Ramos ◽  
John Freddy Remolina López ◽  
Álvaro Alberto López-Lambraño
Keyword(s):  
Time Series ◽  
Water Resources ◽  
Autocorrelation Function ◽  
Information Criterion ◽  
Monthly Rainfall ◽  
Statistical Characteristics ◽  
Rainfall Time Series ◽  
River Watershed ◽  
Statistical Measures ◽  
Sarima Models

Seasonal Auto Regressive Integrative Moving Average models (SARIMA) were developed for monthly rainfall time series. Normality of the rainfall time series was achieved by using the Box Cox transformation. The best SARIMA models were selected based on their autocorrelation function (ACF), partial autocorrelation function (PACF), and the minimum values of the Akaike Information Criterion (AIC). The result of the Ljung–Box statistical test shows the randomness and homogeneity of each model residuals. The performance and validation of the SARIMA models were evaluated based on various statistical measures, among these, the Student’s t-test. It is possible to obtain synthetic records that preserve the statistical characteristics of the historical record through the SARIMA models. Finally, the results obtained can be applied to various hydrological and water resources management studies. This will certainly assist policy and decision-makers to establish strategies, priorities, and the proper use of water resources in the Sinú river watershed.

scholarly journals On the Connection between the GEP Performances and the Time Series Properties

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1853
Author(s):  
Alina Bărbulescu ◽  
Cristian Ștefan Dumitriu
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Functional Form ◽  
Financial Time Series ◽  
Gene Expression Programming ◽  
Parametric Models ◽  
Statistical Characteristics ◽  
Data Series ◽  
Financial Time ◽  
Data Generating Process

Artificial intelligence (AI) methods are interesting alternatives to classical approaches for modeling financial time series since they relax the assumptions imposed on the data generating process by the parametric models and do not impose any constraint on the model’s functional form. Even if many studies employed these techniques for modeling financial time series, the connection of the models’ performances with the statistical characteristics of the data series has not yet been investigated. Therefore, this research aims to study the performances of Gene Expression Programming (GEP) for modeling monthly and weekly financial series that present trend and/or seasonality and after the removal of each component. It is shown that series normality and homoskedasticity do not influence the models’ quality. The trend removal increases the models’ performance, whereas the seasonality elimination results in diminishing the goodness of fit. Comparisons with ARIMA models built are also provided.

Numerical Research on FPSOs With Green Water Occurrence

2009 ◽  
Vol 53 (01) ◽  
pp. 7-18
Author(s):  
Renchuan Zhu ◽  
Guoping Miao ◽  
Zhaowei Lin
Keyword(s):  
Three Dimensional ◽  
Green Water ◽  
Floating Body ◽  
Incoming Wave ◽  
Model Case ◽  
Floating Structures ◽  
Design And Optimization ◽  
Head Waves ◽  
Wave Heights ◽  
The Impact

Green water loads on sailing ships or floating structures occur when an incoming wave significantly exceeds freeboard and water runs onto the deck. In this paper, numerical programs developed based on the platform of the commercial software Fluent were used to numerically model green water occurrence on floating structures exposed to waves. The phenomena of the fixed floating production, storage, and offloading unit (FPSO) model and oscillating vessels in head waves have been simulated and analyzed. For the oscillating floating body case, a combination idea is presented in which the motions of the FPSO are calculated by the potential theory in advance and computional fluid dynamics (CFD) tools are used to investigate the details of green water. A technique of dynamic mesh is introduced in a numerical wave tank to simulate the green water occurrence on the oscillating vessels in waves. Numerical results agree well with the corresponding experimental results regarding the wave heights on deck and green water impact loads; the two-dimensional fixed FPSO model case conducted by Greco (2001), and the three-dimensional oscillating vessel cases by Buchner (2002), respectively. The research presented here indicates that the present numerical scheme and method can be used to actually simulate the phenomenon of green water on deck, and to predict and analyze the impact forces on floating structures due to green water. This can be of great significance in further guiding ship design and optimization, especially in the strength design of ship bows.

An Experimental Study of Shallow Water Wave Statistics on Mild Bed Slopes

2011 ◽  
Author(s):  
Vasiliki Katsardi ◽  
Chris Swan
Keyword(s):  
Water Depth ◽  
Measured Data ◽  
Intermediate Water ◽  
Statistical Distributions ◽  
Spectral Bandwidth ◽  
Peak Period ◽  
Wave Statistics ◽  
Wave Heights ◽  
Bed Slope ◽  
Water Depths

This paper describes a new series of laboratory observations, undertaken in a purpose built wave flume, in which a number of scaled simulations of realistic ocean spectra were allowed to evolve over a range of mild bed slopes. The purpose of the study was to examine the distribution of wave heights and its dependence on the local water depth, d, the local bed slope, m, and the nature of the input spectrum; the latter considering variations in the spectral peak period, Tp, the spectral bandwidth and the wave steepness. The results of the study show that for mild bed slopes the statistical distributions of wave heights are effectively independent of both the bed slope and the spectral bandwidth. However, the peak period plays a very significant role in the sense that it alters the effective water depth. Following detailed comparisons with the measured data, the statistical distributions for wave heights in relatively deep water are found to be in reasonable agreement with the Forristall [1] and Glukhovskii [2] distributions. For intermediate water depths, the Battjes & Groenendijk [3] distribution works very well. However, for the shallowest water depths none of the existing distributions provides good agreement with the measured data; all leading to an over-estimate of the largest wave heights.

scholarly journals Experimental Research of Statistical Characteristics of Wind Wave Breaking

2019 ◽  
Vol 25 (6) ◽  
Author(s):  
A. E. Korinenko ◽  
V. V. Malinovsky ◽  
V. N. Kudryavtsev ◽  
◽  
◽  
...  
Keyword(s):  
Experimental Research ◽  
Wave Breaking ◽  
Wind Wave ◽  
Statistical Characteristics

scholarly journals Modeling the Covid-19 Epidemic Using Time Series Econometrics

2020 ◽  
Author(s):  
Adam Goliński ◽  
Peter Spencer
Keyword(s):  
Time Series ◽  
Logistic Model ◽  
Classical Model ◽  
Realistic Model ◽  
Statistical Characteristics ◽  
Asian Countries ◽  
Time Series Econometrics ◽  
Case Count ◽  
The Uk ◽  
Empirical Stance

AbstractThe classic ‘logistic’ model has provided a realistic model of the behavior of Covid-19 in China and many East Asian countries. Once these countries passed the peak, the daily case count fell back, mirroring its initial climb in a symmetric way, just as the classic model predicts. However, in Italy and Spain, and now the UK and many other Western countries, the experience has been very different. The daily count has fallen back gradually from the peak but remained stubbornly high. The reason for the divergence from the classical model remain unclear. We take an empirical stance on this issue and develop a model that is based upon the statistical characteristics of the time series. With the possible exception of China, the workhorse logistic model is decisively rejected against more flexible alternatives.

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