Analysis of WACSIS data using a directional hybrid wave model

by Zhang, Shaosong

Abstract (Summary)
This study focuses on the analysis of measured directional seas using a nonlinear model, named Directional Hybrid Wave Model (DHWM). The model has the capability of decomposing the directional wave field into its free wave components with different frequency, amplitude, direction and initial phase based on three or more time series of measured wave properties. With the information of free waves, the DHWM can predict wave properties accurately up to the second order in wave steepness. In this study, the DHWM is applied to the analyses of the data of Wave Crest Sensor Inter-comparison Study (WACSIS). The consistency between the measurements collected by different sensors in the WACSIS project was examined to ensure the data quality. The wave characteristics at the locations of selected sensors were predicted in time domain and were compared with those recorded at the same location. The degree of agreement between the predictions and the related measurements is an indicator of the consistency among different sensors. To analyze the directional seas in the presence of strong current, the original DHWM was extended to consider the Doppler effects of steady and uniform currents on the directional wave field. The advantage of extended DHWM originates from the use of the intrinsic frequency instead of the apparent frequency to determine the corresponding wavenumber and transfer functions relating wave pressure and velocities to elevation. Furthermore, a new approach is proposed to render the accurate and consistent estimates of the energy spreading parameter and mean wave direction of directional seas based on a cosine-2s model. In this approach, a Maximum Likelihood Method (MLM) is employed. Because it is more tolerant of errors in the estimated cross spectrum than a Directional Fourier Transfer (DFT) used in the conventional approach, the proposed approach is able to estimate the directional spreading parameters more accurately and consistently, which is confirmed by applying the proposed and conventional approach, respectively, to the time series generated by numerical simulation and recorded during the WACSIS project.
Bibliographical Information:

Advisor:Zhang, Jun; Battle, Guy; Edge, Billy; Kim, Moo-hyun

School:Texas A&M University

School Location:USA - Texas

Source Type:Master's Thesis

Keywords:nonlinear directional wave data analysis


Date of Publication:12/01/2005

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