scholarly journals Estimation of Irregular Wave Runup on Intermediate and Reflective Beaches Using a Phase-Resolving Numerical Model

2020 ◽  
Vol 8 (12) ◽  
pp. 993
Author(s):  
Jonas Pinault ◽  
Denis Morichon ◽  
Volker Roeber
Keyword(s):  
Time Series ◽  
Best Practices ◽  
Numerical Models ◽  
Laboratory Data ◽  
Irregular Waves ◽  
Wave Transformation ◽  
Model Parameters ◽  
Wave Runup ◽  
Data Set ◽  
Promising Alternative

Accurate wave runup estimations are of great interest for coastal risk assessment and engineering design. Phase-resolving depth-integrated numerical models offer a promising alternative to commonly used empirical formulae at relatively low computational cost. Several operational models are currently freely available and have been extensively used in recent years for the computation of nearshore wave transformations and runup. However, recommendations for best practices on how to correctly utilize these models in computations of runup processes are still sparse. In this work, the Boussinesq-type model BOSZ is applied to calculate runup from irregular waves on intermediate and reflective beaches. The results are compared to an extensive laboratory data set of LiDAR measurements from wave transformation and shoreline elevation oscillations. The physical processes within the surf and swash zones such as the transfer from gravity to infragravity energy and dissipation are accurately accounted for. In addition, time series of the shoreline oscillations are well captured by the model. Comparisons of statistical values such as R2% show relative errors of less than 6%. The sensitivity of the results to various model parameters is investigated to allow for recommendations of best practices for modeling runup with phase-resolving depth-integrated models. While the breaking index is not found to be a key parameter for the examined cases, the grid size and the threshold depth, at which the runup is computed, are found to have significant influence on the results. The use of a time series, which includes both amplitude and phase information, is required for an accurate modeling of swash processes, as shown by computations with different sets of random waves, displaying a high variability and decreasing the agreement between the experiment and the model results substantially. The infragravity swash SIG is found to be sensitive to the initial phase distribution, likely because it is related to the short wave envelope.

scholarly journals ASSESSING UNCERTAINTY IN THE MODELING OF RUNUP AND SWASH MORPHODYNAMICS USING XBEACH

2020 ◽  
pp. 21
Author(s):  
Jantien Rutten ◽  
Alec Torres Freyermuth ◽  
Jack Puleo
Keyword(s):  
Time Series ◽  
Wave Energy ◽  
Numerical Models ◽  
Wave Transformation ◽  
Swash Zone ◽  
Wave Runup ◽  
Frequency Spectra ◽  
Single Wave ◽  
Wave Energy Spectrum ◽  
Computational Resources

Phase-resolving numerical models are frequently used tools to investigate short and long wave transformation, nonlinear wave interactions, and wave runup. Moreover, nearshore morphodynamics can be explored with the recent advancement of the models and computational resources. Sea surface elevation time series that force phase-resolving models at the offshore boundary are often unavailable. Therefore, time series are usually recreated from wave energy-frequency spectra through the superposition of harmonics. The wave phases of the harmonics are unknown and therefore assumed to be randomly distributed. This implies that an infinite number of time series with different sequencing of waves can be recreated from a single wave-energy spectrum and, for that reason, recreated time series are a source of uncertainty in model predictions. This intrinsic uncertainty has been found to cause variability in wave overtopping of structures (e.g., Pearson et al, 2002; Williams et al., 2014; Romano et al., 2015) and in setup and runup at beaches (McCabe et al., 2011; Torres-Freyermuth et al., 2019). Torres-Freyermuth et al. (2019) investigated the effect of intrinsic uncertainty on runup at planar beaches for different wave conditions and beach slopes and suggested that uncertainty is especially important under dissipative conditions. Yet unknown is the effect of intrinsic uncertainty on bed evolution. Here we assess the effect of intrinsic uncertainty on inner surf and swash zone evolution at three beaches with different beach morphology.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/w3zi3Yoo170

A Physical Model of Wind Waves in the Coastal Zone

2008 ◽  
Author(s):  
Yana Saprykina ◽  
Natalia Andreeva ◽  
Sergey Kuznetsov ◽  
Zhivelina Cherneva ◽  
C. Guedes Soares
Keyword(s):  
Time Series ◽  
Coastal Zone ◽  
Wind Waves ◽  
Irregular Waves ◽  
Wave Transformation ◽  
Free Surface Elevation ◽  
Space And Time ◽  
Initial Stage ◽  
Instantaneous Values ◽  
The Waves

The variability of the amplitude-frequency structure of wind waves in space and time during their transformation in the coastal zone are considered. Wave time series, measured synchronously in 15 points along the wave propagation, obtained at field and laboratory experiments, were used for the analysis. Free surface elevation time series were represented as a sum of first and second harmonics with amplitudes slowly varying in time (or envelopes of the waves of corresponding frequency bands). Relative changes of these amplitudes in space and time were studied also. It was revealed, that at the initial stage of the wave transformation, the changes of amplitudes of the first and the second harmonics are similar and amplitudes of the second harmonics are proportional to the squared amplitudes of the first harmonics. At this stage the variability of parameters of individual irregular waves can be explained by Stokes theory. Nearer to the coast the instantaneous values of the amplitudes of the first and the second harmonics varies in time chaotically and is not possible to construct a simple model of the variability of the parameters of individual irregular waves. The main reason for this effect is the backward energy transfer from the second to the first harmonics of the waves during nearly resonant non-linear triad interactions.

scholarly journals Single-Beam Acoustic Doppler Profiler and Co-Located Acoustic Doppler Velocimeter Flow Velocity Data

Data ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 61
Author(s):  
Marilou Jourdain de Thieulloy ◽  
Mairi Dorward ◽  
Chris Old ◽  
Roman Gabl ◽  
Thomas Davey ◽  
...  
Keyword(s):  
Time Series ◽  
Flow Velocity ◽  
Numerical Models ◽  
Quality Data ◽  
Velocity Measurements ◽  
Ocean Energy ◽  
Data Set ◽  
Single Beam ◽  
Correlation Statistics ◽  
Acoustic Doppler Profiler

Acoustic Doppler Profilers (ADPs) are routinely used to measure flow velocity in the ocean, enabling multi-points measurement along a profile while Acoustic Doppler Velocimeters (ADVs) are laboratory instruments that provide very precise point velocity measurement. The experimental set-up allows laboratory comparison of measurement from these two instruments. Simultaneous multi-point measurements of velocity along the horizontal tank profile from Single-Beam Acoustic Doppler Profiler (SB-ADP) were compared against multiple co-located point measurements from an ADV. Measurements were performed in the FloWave Ocean Energy Research Facility at the University of Edinburgh at flow velocities between 0.6 ms − 1 and 1.2 ms − 1 . This paper describes the data; the analysis of the inter-instrument comparison is presented in an associated Sensors paper by the same authors. This data-set contains (a) time series of raw SB-ADP uni-directional velocity measurements along a 10 m tank profile binned into 54 measurements cells and (b) ADV point measurements of three-directional velocity time series recorded in beam coordinates at selected locations along the profile. Associated with the data are instrument generated quality data, metadata and user-derived quality flags. An analysis of the quality of SB-ADP data along the profile is presented. This data-set provides multiple contemporaneous velocity measurements along the tank profile, relevant for correlation statistics, length-scale calculations and validation of numerical models simulating flow hydrodynamics in circular test facilities.

scholarly journals The KM-Algorithm Identifies Regulated Genes in Time Series Expression Data

2009 ◽  
Vol 2009 ◽  
pp. 1-10
Author(s):  
Martina Bremer ◽  
R. W. Doerge
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Statistical Power ◽  
Regulatory Networks ◽  
Real Data ◽  
Model Parameters ◽  
Expression Data ◽  
Data Set ◽  
Gene Expression Time Series ◽  
Expression Time

We present a statistical method to rank observed genes in gene expression time series experiments according to their degree of regulation in a biological process. The ranking may be used to focus on specific genes or to select meaningful subsets of genes from which gene regulatory networks can be built. Our approach is based on a state space model that incorporates hidden regulators of gene expression. Kalman (K) smoothing and maximum (M) likelihood estimation techniques are used to derive optimal estimates of the model parameters upon which a proposed regulation criterion is based. The statistical power of the proposed algorithm is investigated, and a real data set is analyzed for the purpose of identifying regulated genes in time dependent gene expression data. This statistical approach supports the concept that meaningful biological conclusions can be drawn from gene expression time series experiments by focusing on strong regulation rather than large expression values.

scholarly journals Linear trends in seasonal vegetation time series and the modifiable temporal unit problem

2012 ◽  
Vol 9 (1) ◽  
pp. 71-77 ◽  
Author(s):  
R. de Jong ◽  
S. de Bruin
Keyword(s):  
Time Series ◽  
Vegetation Indices ◽  
Synthetic Data ◽  
Time Frame ◽  
Model Parameters ◽  
Temporal Aggregation ◽  
Data Set ◽  
Regression Methods ◽  
Influence Model ◽  
Area Unit

Abstract. Time series of vegetation indices (VI) derived from satellite imagery provide a consistent monitoring system for terrestrial plant productivity. They enable detection and quantification of gradual changes within the time frame covered, which are of crucial importance in global change studies, for example. However, VI time series typically contain a strong seasonal signal which complicates change detection. Commonly, trends are quantified using linear regression methods, while the effect of serial autocorrelation is remediated by temporal aggregation over bins having a fixed width. Aggregating the data in this way produces temporal units which are modifiable. Analogous to the well-known Modifiable Area Unit Problem (MAUP), the way in which these temporal units are defined may influence the fitted model parameters and therefore the amount of change detected. This paper illustrates the effect of this Modifiable Temporal Unit Problem (MTUP) on a synthetic data set and a real VI data set. Large variation in detected changes was found for aggregation over bins that mismatched full lengths of vegetative cycles, which demonstrates that aperiodicity in the data may influence model results. Using 26 yr of VI data and aggregation over full-length periods, deviations in VI gains of less than 1% were found for annual periods (with respect to seasonally adjusted data), while deviations increased up to 24% for aggregation windows of 5 yr. This demonstrates that temporal aggregation needs to be carried out with care in order to avoid spurious model results.

scholarly journals Financial Time Series Forecasting Using Directed-Weighted Chunking SVMs

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Yongming Cai ◽  
Lei Song ◽  
Tingwei Wang ◽  
Qing Chang
Keyword(s):  
Time Series ◽  
Financial Time Series ◽  
Training Data ◽  
Series Data ◽  
Support Vector ◽  
Data Set ◽  
Promising Alternative ◽  
Financial Time ◽  
Operation Speed ◽  
Support Vectors

Support vector machines (SVMs) are a promising alternative to traditional regression estimation approaches. But, when dealing with massive-scale data set, there exist many problems, such as the long training time and excessive demand of memory space. So, the SVMs algorithm is not suitable to deal with financial time series data. In order to solve these problems, directed-weighted chunking SVMs algorithm is proposed. In this algorithm, the whole training data set is split into several chunks, and then the support vectors are obtained on each subset. Furthermore, the weighted support vector regressions are calculated to obtain the forecast model on the new working data set. Our directed-weighted chunking algorithm provides a new method of support vectors decomposing and combining according to the importance of chunks, which can improve the operation speed without reducing prediction accuracy. Finally, IBM stock daily close prices data are used to verify the validity of the proposed algorithm.

scholarly journals IRREGULAR WAVE TRANSFORMATION IN A BOUSSINESO WAVE MODEL

1986 ◽  
Vol 1 (20) ◽  
pp. 205
Author(s):  
H.H. Pruser ◽  
H. Schaper ◽  
W. Zielke
Keyword(s):  
Water Waves ◽  
Wave Equations ◽  
Numerical Models ◽  
Wave Model ◽  
Wave Climate ◽  
Irregular Waves ◽  
Wave Transformation ◽  
Diffraction Reflection ◽  
Irregular Wave ◽  
Wave Models

Numerical wave models for shallow water waves are of particular importance for the calculation of the wave climate in harbours and coastal areas. Especially nonlinear time domain models, which are based on the Boussinesq-Wave- Equations, may be helpful in the future for simulating the interaction of currents with refraction, diffraction, reflection and for simulating shoaling..-of irregular waves in natural areas; a potential which has not yet been fully developed. During the last ten years numerical models, based on these equations, have been published; such as ABBOTT et. al. , HAUGUEL and SCHAPER / ZIELKE . Research on this topic is currently being carried on. Some efforts have been made to verify the capability of the models to describe the various physical phenomena. However, up to now, verification has been limited to regular waves. The aim of this paper therefore is, to consider questions concerning irregular, nonlinear waves.

scholarly journals Experimental investigation of the wave-induced motion of and force distribution along a flexible stem

2019 ◽  
Vol 880 ◽  
pp. 1036-1069 ◽  
Author(s):  
Niels G. Jacobsen ◽  
Wout Bakker ◽  
Wim S. J. Uijttewaal ◽  
Rob Uittenbogaard
Keyword(s):  
Experimental Investigation ◽  
Numerical Models ◽  
Laboratory Data ◽  
Hydrodynamic Forces ◽  
Stiffness Ratio ◽  
Shear Forces ◽  
Average Force ◽  
Direct Evaluation ◽  
Data Set ◽  
Flexible Stem

The work presents an experimental investigation into the motion of and hydrodynamic forces along a single flexible stem in regular waves. The experiment covers a large range in relevant non-dimensional parameters: the drag-to-stiffness ratio $CaL\in [0.003,3.8]$, the inertia-to-stiffness ratio $CaL/KC\in [4\times 10^{-5},14.8]$, the Keulegan–Carpenter number $KC\in [3.8,145]$ and the Reynolds number $Re\in [230,2900]$. The two first parameters relate to the response of the stem in waves and thus account for material properties, while the two last parameters are relevant for hydrodynamic forces on the stem. The displacement of the stem was captured with a digital video camera and the displacement along the stem was captured for every 2.5 mm at 25 Hz. This unique laboratory data set allowed for the following analyses: (i) Determination of the relevant non-dimensional parameter to predict the stem motion and shape. (ii) A direct comparison between the measured force for mimics of two lengths (0.15 m and 0.30 m) illustrating the force reduction potential for flexible mimics. (iii) Direct evaluation of the average force coefficients $C_{D}$ (drag) and $C_{M}$ (inertia) for the flexible stems. (iv) The distributed external hydrodynamic loading and the internal shear forces were estimated from the laboratory experiments. The distribution of the shear force helped to understand the breakage mechanisms of flexible stems. (v) A linkage between phase lags and internal shear forces was suggested. The data set is considered valuable as validation material for numerical models of stem motion in waves.

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 Time series of vegetation indices and the modifiable temporal unit problem

2011 ◽  
Vol 8 (4) ◽  
pp. 8545-8561
Author(s):  
R. de Jong ◽  
S. de Bruin
Keyword(s):  
Time Series ◽  
Vegetation Indices ◽  
Synthetic Data ◽  
Time Frame ◽  
Model Parameters ◽  
Temporal Aggregation ◽  
Data Set ◽  
Regression Methods ◽  
Influence Model ◽  
Area Unit

Abstract. Time series of vegetation indices (VI) derived from satellite imagery provide a consistent monitoring system for terrestrial plant systems. They enable detection and quantification of gradual changes within the time frame covered, which are of crucial importance in global change studies, for example. However, VI time series typically contain a strong seasonal signal which complicates change detection. Commonly, trends are quantified using linear regression methods, while the effect of serial autocorrelation is remediated by temporal aggregation over bins having a fixed width. Aggregating the data in this way produces temporal units which are modifiable. Analogous to the well-known Modifiable Area Unit Problem (MAUP), the way in which these temporal units are defined may influence the fitted model parameters and therefore the amount of change detected. This paper illustrates the effect of this Modifiable Temporal Unit Problem (MTUP) on a synthetic data set and a real VI data set. Large variation in detected changes was found for aggregation over bins that mismatched full lengths of vegetative cycles, which demonstrates that aperiodicity in the data may influence model results. Using 26 yr of VI data and aggregation over full-length periods, deviations in VI gains of less than 1 % were found for annual periods, while deviations (with respect to seasonally adjusted data) increased up to 24 % for aggregation windows of 5 yr. This demonstrates that temporal aggregation needs to be carried out with care in order to avoid spurious model results.

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