Acoustical engineering

This thesis presents a noise handling technique that attempts to improve the quality of training data for classification purposes by eliminating instances that are likely to be noise. Our approach uses twenty five different classification techniques to create an ensemble of classifiers that acts as a noise filter on real-world software measurement datasets. Using a relatively large number of base-level classifiers for the ensemble-classifier filter facilitates in achieving the desired level of noise removal conservativeness with several possible levels of filtering. It also provides a higher degree of confidence in the noise elimination procedure as the results are less likely to get influenced by (possible) inappropriate learning bias of a few algorithms with twenty five base-level classifiers than with a relatively smaller number of base-level classifiers. Empirical case studies of two different high assurance software projects demonstrate the effectiveness of our noise elimination approach by the significant improvement achieved in classification accuracies at various levels of filtering.

Boundary layers are regions where turbulence develops easily. In the case where the flow occurs on a surface showing a certain degree of roughness, turbulence eddies will interact with the roughness elements and will produce an acoustic field. This thesis aims at predicting this type of noise with the help of the Computational Fluid Dynamics (CFD) simulation of a wall jet using the Reynolds Average Navier-Stokes (RANS) equations. A frequency spectrum is reconstructed using a representation of the turbulence with uncorrelated sheets of vorticity. Both aerodynamic and acoustic results are compared to experimental measurements of the flow. The CFD simulation of the flow returns consistent results but would benefit from a refinement of the grid. The surface pressure spectrum presents a slope in the high frequencies close to the experimental spectrum. The far field noise spectrum has a 5dB difference to the experiments.

This thesis discusses a new approach to tracking the REMUS 100 AUV using a modified version of the Florida Atlantic University (FAU) ultrashort baseline (USBL) acoustic positioning system (APS). The REMUS 100 is designed to utilize a long baseline (LBL) acoustic positioning system to obtain positioning data in mid-mission. If the placement of one of the transponders of the LBL field is known, then tracking the position of the REMUS 100 AUV using a passive USBL array is possible. As part of the research for this thesis, the FAU USBL system was used to find a relative range between the REMUS 100 ranger and a LBL transponder. This relative range was then combined with direction of arrival information and LBL field component position information to determine an absolute position of the REMUS 100 ranger. The outcome was the demonstration of a passive USBL based tracking system.

Simulating the exact chaotic turbulent flow field about any geometry is a dilemma between accuracy and computational resources, which has been continuously studied for just over a hundred years. This thesis is a complete walk-through of the entire process utilized to approximate the flow ingested by a Sevik-type rotor based on solutions to the Reynolds Averaged Navier-Stokes equations (RANS). The Multiple Reference Frame fluid model is utilized by the code of ANSYS-FLUENT and results are validated by experimental wake data. Three open rotor configurations are studied including a uniform inflow and the rotor near a plate with and without a thick boundary layer. Furthermore, observations are made to determine the variation in velocity profiles of the ingested turbulent flow due to varying flow conditions.

The purpose of this thesis is to develop a renewable ocean energy material selection methodology for use in FAU's Ocean Energy Projects. A detailed and comprehensive literature review has been performed concerning all relevant material publications and forms the basis of the developed method. A database of candidate alloys has been organized and is used to perform case study material selections to validate the developed fuzzy logic approach. The ultimate goal of this thesis is to aid in the selection of materials that will ensure the successful performance of renewable ocean energy projects so that clean and renewable energy becomes a reality for all.