SET-UP DUE TO RANDOM WAVES: INFLUENCE OF THE DIRECTIONAL SPECTRUM

The correct estimation of set-up is very important to evaluate coastal hazard and to design coastal structures. In this paper, we derived a mathematical expression for wave set-up in the context of random waves. The solution to this expression assumes straight, parallel depth contours and constant average flow parameters in the longshore direction. We then investigated the effect of different types of sea state taking account of different frequency spectrum and spreading function assumed in the expression on estimates of wave set-up. We found the set-up was highly influenced by the frequency spectrum used. Finally, we applied this expression to estimate set-up values at locations in Italy and in the United States using buoy data provided by ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale) and NDBC (National Data Buoy Centre).

Estimating nearshore waves by assimilating buoy directional spectrum data in SWAN

This paper describes a variational data assimilation algorithm based on the SWAN near shore wave-spectrum model. The approach allows single-point wave spectrum observations to be used to estimate the wave field for a nearshore region under stationary conditions, assuming a spatially uniform incident wave spectrum at the offshore boundary. The assimilated data are in the form of Fourier directional coefficients, the standard output from operational wave buoys, and are used directly by incorporating the relationship between directional spectrum and the Fourier coefficients into the formulation. The algorithm was tested on data from nearshore buoys deployed off the coast of North Carolina in May 2012, and the estimated wave field is compared to both the input data and to independent observation data. The results compare favorably to the independent data with overall RMS errors of 10–20 percent for significant wave height, about half a second for mean wave period, and as much as 3–4 SWAN spectral grid cells for mean direction. Overall, the results show that the algorithm can be effectively used to estimate the offshore boundary spectrum and accurately reproduce wave conditions in the domain.

The sagging shape of shoreline formed on downdrift side of the structures due to seasonal oblique wave incidence

Downdrift coastal erosion has occurred at natural or man-made groynes on Korea’s eastern coast, caused by oblique high waves in winter months. The resulting shoreline planform has a sagging shape with a maximum indentation point within the eroded shoreline. This study focused on solving the frequent and severe coastal erosion problem of this type at the Jeongdongjin review of wave data over 40 years from the National Oceanic and Atmospheric Administration (NOAA), as well as analyzing shoreline monitoring images for identifying the yielding line of maximum indentation points. An analytical method was developed to verify the eroding shoreline in a sagging shape and its maximum indentation by applying the conservation principle of sediment transport and the empirical model of equilibrium shoreline. To examine how well the empirical formula is suitable for the Jeongdongjin coast, the annual directional spectrum of the observed wave data was applied to the simple diffraction wave model for the gamma breakwater, and satisfactory agreement was obtained by comparing it with the shoreline results. Breaking wave height and angle, duration, longshore sediment transport coefficient, and protruding length of the groyne were the inputs. The theoretical results are in good agreement with those of the shoreline monitoring program. The factors mitigating downdrift coastal erosion of this type were identified by applying the obtained theoretical solution, and the engineering solutions were examined via factor analysis.

Theoretical Modeling and Analysis of Directional Spectrum Emissivity and Its Pattern for Random Rough Surfaces with a Matrix Method

The emissivity is an important surface property parameter in many fields, including infrared temperature measurement. In this research, a symmetry theoretical model of directional spectral emissivity prediction is proposed based on Gaussian random rough surface theory. A numerical solution based on a matrix method is determined based on its symmetrical characteristics. Influences of the index of refraction n and the root mean square (RMS) roughness σrms on the directional spectrum emissivity ε are analyzed and discussed. The results indicate that surfaces with higher n and lower σrms tend to have a peak in high viewing angles. On the contrary, surfaces with lower n and higher σrms tend to have a peak in low viewing angles. Experimental verifications based on infrared (IR) temperature measurement of Inconel 718 sandblasted surfaces were carried out. This model would contribute to understand random rough surfaces and their emitting properties in fields including machining, process controlling, remote sensing, etc.

In situ measurements of directional wave spectra from an unmanned aerial system

This Coastal and Hydraulics Engineering Technical Note (CHETN) describes the ability to measure the directional-frequency spectrum of sea surface waves based on the motion of a floating unmanned aerial system (UAS). The UAS used in this effort was custom built and designed to land on and take off from the sea surface. It was deployed in the vicinity of an operational wave sensor, the 8 m* array, at the US Army Engineer Research and Development Center (ERDC), Field Research Facility (FRF) in Duck, NC. While on the sea surface, an inertial navigation system (INS) recorded the response of the UAS to the incoming ocean waves. Two different INS signals were used to calculate one-dimensional (1D) frequency spectra and compared against the 8 m array. Two-dimensional (2D) directional-frequency spectra were calculated from INS data using traditional single-point-triplet analysis and a data adaptive method. The directional spectrum compared favorably against the 8 m array.

Numerical simulation of wave spectrum during a typhoon

The third-generation wave model WAVEWATCH-III was used to numerically simulate the wave under the influence of a typhoon in the coastal area of China. The wave spectrum at the buoy point was output, and the characteristics of the wave spectrum were analyzed. The change of the wave spectrum during the typhoon process reflected the growth process of typhoon formation, development and extinction. The relationship between the wave spectrum and the wind direction was intuitively shown by the directional spectrum, indicating the coexistence of wind waves and swells in the sea area during the typhoon process.

A Low-Cost Stereo Video System for Measuring Directional Wind Waves

Typical oceanographic instruments are expensive, complex to build, and hard to deploy and require constant and specialized maintenance. In this paper, we present a cheap and simple technique to estimate a three-dimensional surface elevation map, η(x,y,t), the directional spectrum, and the main sea state parameters using inexpensive smartphones. The proposed methodology uses Time Lagged Cross Correlation (TLCC) between the audio signals from two independent video records to perform the frame synchronization. This makes the system much easier to deploy, where the main requirement is a fixed or moving platform close to the sea. The time records are mostly limited by the equipment storage space and battery life, although it can be easily replaced or recharged. Here, we pose the basis for an inexpensive yet powerful stereo reconstruction device and discuss its capabilities and limitations. The smartphone system capabilities were illustrated here by near shore experiment, at Leme beach in the Southeast of Brazil, and the results were compared against a pressure sensor. For this particular setup, the root mean square error in terms of significant wave height is of the order of 11% with perfect estimation of the peak period. The results are promising and demonstrate the validity and applicability of the technique.

The Relationship between Sea-Swell Bound Wave Height and Wave Shape

The nonlinear wave shape, expressed by skewness and asymmetry, can be calculated from surface elevation or pressure time series using bispectral analysis. Here, it is shown that the same analysis technique can be used to calculate the bound superharmonic wave height. Using measured near-bed pressures from three different field experiments, it is demonstrated that there is a clear relationship between this bound wave height and the nonlinear wave shape, independent of the measurement time and location. This implies that knowledge on the spatially varying bound wave height can be used to improve wave shape-induced sediment transport predictions. Given the frequency-directional sea-swell wave spectrum, the bound wave height can be predicted using second order wave theory. This paper shows that in relatively deep water, where conditions are not too nonlinear, this theory can accurately predict the bispectrally estimated bound superharmonic wave height. However, in relatively shallow water, the mismatch between observed and predicted bound wave height increases significantly due to wave breaking, strong currents, and increased wave nonlinearity. These processes are often included in phase-averaged wind-wave models that predict the evolution of the frequency-directional spectrum over variable bathymetry through source terms in a wave action balance, including the transfer of energy to bound super harmonics. The possibility to calculate and compare with the observed bound super harmonic wave height opens the door to improved model predictions of the bound wave height, nonlinear wave shape and associated sediment transport in large-scale morphodynamic models at low additional computational cost.

Ship As a Wave Buoy: Estimating Full Directional Wave Spectra From In-Service Ship Motion Measurements Using Deep Learning

The ocean wave directional spectrum is an important wave characteristic for maritime safety and navigation. Accurate estimation of directional spectra in real-time is a challenge. In this study we aim to reconstruct the directional spectra from ship motions using a deep convolutional encoding-decoding neural network. In-service measurements of ship motions and wave spectra from a WAMOS II wave scanning radar were used to train the neural network. The data was collected from a frigate type ship for a period of two years. We demonstrate that the deep convolutional encoding-decoding neural network is successful in predicting the directional spectra in real-time. At the same time, we conclude that more data is needed for a better prediction performance, including a more complete coverage of operational conditions.