The objective of this research was to derive an empirical equation that estimates the acoustical shadow zone length (SZL) of roadway noise barriers. The acoustical shadow zone is the area behind a noise barrier of reduced sound levels, generally to some stated level at or near background. The ability to predict the SZL can be used as a method to evaluate the performance, and possibly the design, of roadway noise barriers. The current federally required roadway noise model is the Federal Highway Administration (FHWA) Traffic Noise Model (TNM). TNM uses insertion loss (IL) to evaluate the effectiveness of a barrier. Insertion loss is the difference in sound level between the "no barrier" and the "with barrier" case. One major limitation with TNM is that the reported IL does not take into account how background noise levels influence the mitigated sound levels. Background noise can be defined as the noise present at a barrier location in the absence of roadway noise. The shadow zone represents a region behind the noise barrier where the barrier is effective at reducing noise levels and takes into account how background noise affects the IL and thus the SZL. The inclusion of background noise becomes significant in evaluating barrier effectiveness because as the distance from the barrier increases, background noise begins to overtake roadway noise as the dominate noise source. The derivation of the empirical equation began by collecting in-situ noise measurements at 18 noise barrier locations across Florida. The measured noise data was supplemented by noise data obtained from computer modeling. After a sufficient quantity of measured and modeled IL data was obtained, a contour of equal IL (IL = 5 dB) was plotted for each barrier location. The area defined by the contour is called the shadow zone. All the SZLs were statistically compared to several variables that were expected to influence it. Regression modeling showed that the background noise level, noise barrier height, the distance from the roadway to the noise barrier, and percent of heavy truck traffic volume were statistically significant as useful predictors of SZL. Two empirical equations were derived, one from linear regression and one from polynomial regression, and are referred to as the Shadow Zone Equations.

Vortex motion plays an important role in the transport properties of high Tc superconductors. In the presence of a sufficiently large applied current vortices will drift creating an ohmic resistance in the material, while defects in the material will tend to inhibit their motion. Some types of material defects are more effective at pinning then others, and therefore, above the depinning threshold, may effect the motion of vortices differently. To investigate their motion, voltage noise generated by moving vortices is studied for different material defect types using a nonequilibrium Metropolis Monte Carlo simulation. The current-voltage (I-V) characteristics obtained from the simulation for various vortex densities and defect types show features similar to those obtained in experiments. The power spectra generated for point and columnar disorder are then compared for increasing vortex density. Above, but near the depinning threshold, broadband noise associated with plastic vortex flow is observed for columnar defects at low vortex densities, while for higher densities a triangular lattice is obtained along with a washboard signal and higher harmonics. For point defects a washboard signal with higher harmonics is always observed in the region investigated. These results suggest that power spectra for both point and columnar defects are qualitatively similar for higher vortex densities (larger magnetic fields). A second comparison is made by observing, on the one hand, the power spectra for finite linear defects increasing in length and, on the other hand, increasing point defect strength. Power spectra and structure factor results are very similar for these results as well. Both show a trend from an ordered to a disordered system with a washboard peak first increasing and then decreasing in power with increasing pinning efficiency. For both defect types the power spectrum is eventually dominated by broadband noise indicating the approach to the pinned glassy phases. / Ph. D.

<p> Previous studies on subjective response to noise have been conducted during the summer months. These studies have served as the basis for noise standards and legislation; therefore an implicit assumption has been made that response to noise is similar in summer and winter. Whether or not this applies equally well to the winter months, which represent approximately one-half of the year, warranted investigation. Data on summer and winter responses to comparable noise levels were collected and hypotheses were tested for differences in response to overall noise levels and to specific noise sources. The results indicated that there were no significant differences between summer and winter responses.</p> / Thesis / Master of Arts (MA)

Underwater noise pollution is a significant environmental issue that can have detrimental effects on marine ecosystems. One of the main sources of underwater noise pollution is ship traffic, which has been shown to negatively impact marine animals by masking communication signals, altering their behaviors, and even causing hearing loss. In the Red Sea, ships are the main contributor to underwater noise pollution, particularly in areas with high shipping traffic. This thesis aims to understand the spatial and temporal distribution of underwater ship noise in the Red Sea using an acoustic propagation model, namely the Range-dependent Acoustic Model (RAM). RAM takes into account anthropogenic and environmental inputs including water temperature, salinity, and bathymetry to predict sound propagation in the Red Sea. By running RAM with inputs of ship traffic data, maps of underwater ship noise in the Red Sea were generated. These maps are important tools for policymakers and marine resource managers to identify areas of high noise pollution, target mitigation efforts accordingly, and guide future research on the effects of underwater noise pollution on marine life in the Red Sea.

A longstanding question in studies of cortical stimulation has been how does stimulation affect brain functioning and cognition, and what are its mechanisms of action. Brain stimulation has been traditionally seen either as a disrupting intervention or as a procedure to enhance cortical excitability and promote improvement in various modality from motor to visual performance. In vision, several hypotheses have been proposed and many experimental paradigms have been used to study how transcranial magnetic stimulation (TMS) and direct current stimulation, particularly transcranial random noise stimulation (tRNS) affect visual discrimination. Psychophysical paradigms are particularly useful to measure visual performance, whereby a stimulus is progressively changed from easy to difficult to perceive it, and accuracy threshold can be measured by titrating the stimulus discriminability. Stimuli that vary in contrast are typically used to study low-level visual functions and it is well known that neurons within the early visual areas in the brain, and primarily V1, are tuned to stimuli involved in contrast discrimination. Here we used an orientation discrimination task to study changes in contrast detection by varying stimulus contrast across different levels (Experiment 1, Chapter 2). We used neuro-navigated single-pulse TMS at different intensities to determine whether behavioral response changed linearly as a function of stimulus discriminability independently of TMSintensity, or whether TMS affected behavior depending on TMS intensity and contrast level. Moreover, we tested whether TMS had an effect selective for the field contralateral to stimulation or whether effects could be seen across the entire visual field. Single pulse TMS was delivered to left V1 while participants performed a 2-alternative forced choice orientation discrimination (OD) of one of two Gabor patches presented on either side of fixation at 5 contrast levels and 4 TMS intensities. Participants' performance on OD increased at all contrast levels in the right visual field (contralateral to stimulation) at 80% of phosphene thresholds (PT, individually measured at baseline). Furthermore, when TMS was delivered at 60% of PT, we found improved performance in the right visual field that was selective for the medium contrast, while performance increased at the highest contrast irrespective of TMS intensity, in the field ipsilateral to stimulation, thus both visual fields were affected by TMS, albeit differently. Since the improvement effects might be explained as the result of added noise to the system that paradoxically improves performance for justbelow threshold stimuli (middle contrasts), in Experiments 1 and 2 (Chapter 3) we used transcranial random noise stimulation, a neuromodulation procedure known to enhance cortical excitability when delivered at high frequencies, to further test the hypothesis that brain stimulation might work through a mechanism of stochastic resonance, whereby adding noise to a nonlinear system, the brain in our case, might paradoxically promote better performance by enhancing stimulus discriminability. This might happen only for selective stimulus intensities and stimulation strength. Based on previous successful work, we tested contrast discrimination changes as a function of four different tRNS low intensity levels of stimulation, and we found a decrease in performance selective for the condition with subthreshold stimuli and at .750 mA stimulation intensity. This result might indicate that low intensity stimulation is not enough to promote enhancement of stimuli under the stochastic mechanism effect, thereby suggesting that higher ranges of stimulation are necessary to create the optimal conditions for improvement.

Neighbor noise has repeatedly been proven to have a detrimental effect on multi-unit residential buildings (MURBs) residents’ physical and mental health. Impact noises have been shown to cause the most indoor noise annoyance amongst residents. Moreover, lightweight assemblies are known for their general poor sound insulation and are becoming increasingly popular as an alternative to concrete and steel structures in North America and Europe. Floating toppings have been used to control impact noise, but the effect of the source-receiver interaction is often neglected when they are modelled by engineers in the industry. More research needs to be done to determine the actual influence of the source-receiver interaction on floor assemblies with floating toppings. Studying the source-receiver interaction is fundamental to tackling the issue of structure-borne noise in MURBs because it has been shown to influence the first of five factors of impact sound transmission: the power injected. The power injected into a floor due to an impact source has been shown to depend on the mechanical mobility match (or the source-receiver interaction) between the impact source and the impacted floor. However, many questions remain around the significance of the source-receiver interaction. This project investigates the significance of the source-receiver interaction for structure-borne sound sources on floor assemblies with floating toppings, and how much it varies from one source-floor combination to another.

The noise generated by jet engines represents a significant environmental concern that still needs to be addressed. Accurate and efficient numerical predictions are a key step towards reducing jet noise. The current standard in highidelity prediction of jet noise is large eddy simulation (LES), which resolves the large turbulent scales responsible for the low and medium frequency noise and models the smallest turbulent scales that correspond to the high frequency noise. While LES requires significant computational resources to produce an accurate solution, it fails to resolve the noise in the high frequency range, which cannot be simply ignored. To circumvent this, in this dissertation the Coupled LES-Synthetic Turbulent method (CLST) was developed to model the missing frequencies that relate to un-resolved sub-grid scale fluctuations in the flow. The CLST method combines the resolved, large-scale turbulent fluctuations from very large eddy simulations (VLES) with modeled, small-scale fluctuations from a synthetic turbulence model. The noise field is predicted using a formulation of the linearized Euler equations (LEE), where the acoustic waves are generated by source terms from the combined fluctuations of the VLES and the synthetic fields. This research investigates both a Fourier mode-based stochastic turbulence model and a synthetic eddy-based turbulence model in the CLST framework. The Fourier mode-based method is computationally less expensive than the synthetic eddy method but does not account for sweeping. Sweeping and straining of the synthetic fluctuations by large flow scales from VLES are accounted for in the synthetic eddy method. The two models are tested on a Mach 0.9 jet at a moderately-high Reynolds number and at a low Reynolds number. The CLST method is an efficient and viable alternative to high resolution LES or DNS because it can resolve the high frequency range in the acoustic noise spectrum at a reasonable expense.

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