A 2-D fully nonlinear numerical wave tank (NWT) is developed to investigate the Bragg resonance scattered by submerged multi-array breakwaters for random waves. This model is based on a boundary integral equation method with linear element scheme. The fully nonlinear free surface boundary condition is treated using the Mixed Eulerian-Lagrangian method and the 4th-order Runge-Kutta method. The incident random waves are generated by JONSWAP spectrum at one end of the wave tank. Two damping zones are deployed at both ends of the NWT to absorb the energy of the reflected and transmitted waves. In the regular wave cases, the results of Bragg reflection calculated are in good agreement with that of other experiments and numerical models. In addition, the simulated spectrum of random waves is also verified by the original input spectrum. The results of the random waves have the same trend as those of the Regular waves. The reflection coefficient for random waves at the first peak of resonance is about 70 percent of that of the regular wave, but the frequency of band width of Bragg effect has become wider and this advantage may compensate the peak reduction. Finally, we may conclude that the present model is adequate to use as a tool for coastal protection. Systematic studies for random waves propagating over series submerged breakwaters are conducted. The Bragg reflection will be enhanced with the increase of relative height, the length of bars, the number of breakwaters, and the toe angle of submerged breakwaters. In this study, it also reveals that the frequency of peak reflection for higher breakwaters has down shift phenomenon.

This work investigates the ideal distribution of sensors in networked arrays. MATLAB models these arrays and simulates the results these networks obtain using active and passive sonar. These results determine the ideal sensor placement for optimal parameter detection and estimation of targets. This work's first part focuses on active sonar networks with a fixed number of sensors in a differing number of arrays. MATLAB simulates the data of these sensors taking into account the geometries and velocities of the arrays and targets, then estimates the parameters of the targets using an elliptical filter, a conventional beamformer, a matched filter and one of three fusion methods. This work compares the performance of each network and fusion method. This work shows that the adding more arrays, regardless of size, enhances the overall performance of the network. It also shows the larger arrays obtain more robust parameter estimation. The second part of this work investigates the effects of uncertainty of the array position and orientation using passive sonar. Two networks, one with 2 32-channel arrays and one with 8 2-channel arrays, estimate a sound source's location using a conventional beamformer. MATLAB simulates the data taking into account the geometries of the arrays and the sound source. The results of these simulations show that when uncertainty of position and orientation increases, the better the smaller arrays estimate the location of the sound source compared to the larger arrays. / Master of Science

The detection and localization of important acoustic events in a complex urban environment, such as gunfire and explosions, is critical to providing effective surveillance of military and civilian areas and installations. In a complex environment, obstacles such as terrain or buildings introduce multipath propagations, reflections, and diffractions which make source localization challenging. This dissertation focuses on the problem of source localization in three-dimensional (3D) realistic urban environments. Two different localization techniques are developed to solve this problem: a) Beamforming using a few microphone phased arrays in conjunction with a high fidelity model and b) Fingerprinting using many dispersed microphones in conjunction with a low fidelity model of the environment. For an effective source localization technique using microphone phased arrays, several candidate beamformers are investigated using 2D and corresponding 3D numerical models. Among them, the most promising beamformers are chosen for further investigation using 3D large models. For realistic validation, localization error of the beamformers is analyzed for different levels of uncorrelated noise in the environment. Multiple-array processing is also considered to improve the overall localization performance. The sensitivity of the beamformers to uncertainties that cannot be easily accounted for (e.g. temperature gradient and unmodeled object) is then investigated. It is observed that evaluation in 3D models is critical to assess correctly the potential of the localization technique. The enhanced minimum variance distortionless response (EMVDR) is identified to be the only beamformer that has super-directivity property (i.e. accurate localization capability) and still robust to uncorrelated noise in the environment. It is also demonstrated that the detrimental effect of uncertainties in the modeling of the environment can be alleviated by incoherent multiple arrays. For efficient source localization technique using dispersed microphones in the environment, acoustic fingerprinting in conjunction with a diffused-based energy model is developed as an alternative to the beamforming technique. This approach is much simpler requiring only microphones rather than arrays. Moreover, it does not require an accurate modeling of the acoustic environment. The approach is validated using the 3D large models. The relationship between the localization accuracy and the number of dispersed microphones is investigated. The effect of the accuracy of the model is also addressed. The results show a progressive improvement in the source localization capabilities as the number of microphones increases. Moreover, it is shown that the fingerprints do not need to be very accurate for successful localization if enough microphones are dispersed in the environment. / Ph. D.

Philosophiae Doctor - PhD / A novel monomer (N,N'-Bis-(1H-pyrrol-2-ylmethylene)-benzene-1,2-diamine-BPPD) was derived from the condensation reaction between o-phenylenediamine and a pyrrole derivative. The monomer was polymerized electrochemically to produce the new polymer material - polymerized(N,N'-Bis-(1H-pyrrol-2-ylmethylene)-benzene-1,2-diamine) PBPPD. This novel polymer material was deposited at the surface of a screen-printed carbon electrode, as a thin film, in the development of chemical sensors for the detection of polycyclic aromatic hydrocarbons (PAHs). The monomer material was characterized in terms of its optical (spectroscopy) and thermal properties. The polymer material was characterized in terms of its surface morphology and its redox electrochemistry. Fourier transform infrared spectroscopy (FTIR) was used to confirm the azomethine bond formation during the condensation reaction of an aldehyde and primary amine derivative. / 2020-08-31