Comparison of Period- or Height-Dependent, Sea-State Parameters From a Theoretical Model With Observation at Sea

1978 ◽  
Vol 18 (04) ◽  
pp. 233-238
Author(s):  
M. Arhan ◽  
R. Ezraty ◽  
M. Laurent

Abstract A joint theoretical probability density for individual wave heights and periods, originally developed to describe storm conditions, is compared with about 2,000 routine wave recordings in the Bay of Biscay. From this joint probability density, all other mean sea-state parameters (HT 1/3, - TH 1/3, T 1/3 . . .) can be computed using H 1/3, T, and, the spectrum width parameter. The systematic discrepancy existing between theory and observation can be corrected empirically if necessary. Introduction Cartwright and Longuet-Higgins predicted the height of sea waves and computed the significant wave height, h 1/3, or similar variables, h 1/n, as well as the expectancy of the maximum, E(h max), of a given number of waves. They started with mo and, the total energy and the width parameter of the spectrum, respectively.To describe a sea state, a characteristic period and characteristic height are necessary. In the "zero-up-crossing" wave analysis the following periods usually appear: (1) T 1/3 is the mean of the periods usually appear:T 1/3 is the mean of the highest third of the zero-up-crossing periods,TH 1/3 is the mean of the periods connected to the waves used to compute H 1/31 andThis the mean of the zero-up-crossing periods.In the same way, T 1/n and TH 1/n also can be defined. Wiegel found empirical relationships between these characteristic periods, based on observation at sea. Our theoretical model is based on the theory of Gaussian noise as established by Rice and leads to an explicit formula for the joint probability density of wave heights and periods. probability density of wave heights and periods. This density is fixed when given these parametersa characteristic height, a characteristic period, and epsilon. Then, by appropriate integrations, we can relate the different average heights to the associated average periods that describe a given sea state. Although the narrow-band spectrum hypothesis is not always satisfied, computed values of mean quantities from observations at sea remain close to their theoretical equivalents. Any systematic discrepancy can be corrected if necessary. THE THEORETICAL MODEL A model was developed using as a starting point, the joint probability density for a Gaussian noise signal with a maximum value, 1, and a second derivative with respect to time, 3, as ........................................(1) We have assigned to each positive maximum a sinusoidal wave with amplitude 1 and period T given by SPEJ p. 233

2014 ◽  
Vol 16 (2-3) ◽  
pp. 227
Author(s):  
Y. Hu ◽  
E. Gutheil

A transported joint probability density function (PDF) model for turbulent spray flows is presented, where a one-point one-time statistical description of the gas-phase mixture fraction and the gas velocity is used. This approach requires the closure of the molecular mixing, which is achieved through use of the extended interaction-by-exchange-with-the-mean (IEM) model and a simplified Langevin model for the closure of the gas velocity both of which are extended through additional terms accounting for spray evaporation. These equations require the solution of the turbulent time scales and the mean pressure field through a Eulerian description. The numerical approach includes a Lagrangian Monte Carlo method for the solution of modeled joint PDF equation with a Eulerian finite-volume algorithm to determine the turbulent time scale and the mean pressure field. For the dispersed liquid phase, Lagrangian equations are used to describe the droplet heating, evaporation, and motion in the framework of a discrete droplet model. The convective droplet evaporation model is employed, and the infinite conductivity model with consideration of non-equilibrium effects based on the Langmuir-Knudsen law is used. The droplet turbulent dispersion is modeled with two different Lagrangian stochastic models. The resulting spray evolution equations are solved by a Lagrangian discrete droplet method using the point source approximation for a dilute spray. The numerical results are compared with experimental data of Gounder et al. [1], where the experimental set B of the acetone spray flows SP2 and SP6 are simulated. Comparison of numerical and experimental results includes droplet size, liquid volume flux as well as the mean and fluctuating velocities. Generally, good agreement is achieved, although the radial droplet dispersion is somewhat under-predicted by the computations. The droplet fluctuating velocities show sensitivity to the different dispersion models.


Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 472
Author(s):  
Jue Lin-Ye ◽  
Manuel García-León ◽  
Vicente Gràcia ◽  
María Ortego ◽  
Piero Lionello ◽  
...  

Storm surges are one of the main drivers for extreme flooding at the coastal areas. Such events can be characterized with the maximum level in an extreme storm surge event (surge peak), as well as the duration of the event. Surge projections come from a barotropic model for the 1950–2100 period, under a severe climate change scenario (RCP 8.5) at the northeastern Spanish coast. The relationship of extreme storm surges to three large-scale climate patterns was assessed: North Atlantic Oscillation ( N A O ), East Atlantic Pattern ( E A W R ), and Scandinavian Pattern ( S C ). The statistical model was built using two different strategies. In Strategy #1, the joint probability density was characterized by a moving-average series of stationary Archimedean copula, whereas in Strategy #2, the joint probability density was characterized by a non-stationary probit copula. The parameters of the marginal distribution and the copula were defined with generalized additive models. The analysis showed that the mean values of surge peak and event duration were constant and were independent of the proposed climate patterns. However, the values of N A O and S C influenced the threshold and the storminess of extreme events. According to Strategy #1, the variance of the surge peak and event duration increased with a fast shift of negative S C and a positive N A O , respectively. Alternatively, Strategy #2 showed that the variance of the surge peak increased with a positive E A W R . Both strategies coincided in that the joint dependence of the maximum surge level and the duration of extreme surges ranged from low to medium degree. Its mean value was stationary, and its variability was linked to the geographical location. Finally, Strategy #2 helped determine that this dependence increased with negative N A O .


Author(s):  
A. K. Banik ◽  
T. K. Datta

The stochastic response and stability of a two-point mooring system are investigated for random sea state represented by the P-M sea spectrum. The two point mooring system is modeled as a SDOF system having only stiffness nonlinearity; drag nonlinearity is represented by an equivalent linear damping. Since no parametric excitation exists and only the linear damping is assumed to be present in the system, only a local stability analysis is sufficient for the system. This is performed using a perturbation technique and the Infante’s method. The analysis requires the mean square response of the system, which may be obtained in various ways. In the present study, the method using van-der-Pol transformation and F-P-K equation is used to obtain the probability density function of the response under the random wave forces. From the moment of the probability density function, the mean square response is obtained. Stability of the system is represented by an inequality condition expressed as a function of some important parameters. A two point mooring system is analysed as an illustrative example for a water depth of 141.5 m and a sea state represented by PM spectrum with 16 m significant height. It is shown that for certain combinations of parameter values, stability of two point mooring system may not be achieved.


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