According to a 1999 Federal Highway Administration statistic, the U.S. has around 8.2 million lane-miles of roadways that need to be maintained and rehabilitated periodically. Therefore, in order to reduce rehabilitation costs, pavement engineers need to optimize the rehabilitation procedure, which is achieved by accurately knowing the existing pavement layer thicknesses and localization of subsurface defects. Currently, the majority of departments of transportation (DOTs) rely on coring as a means to estimate pavement thicknesses, instead of using other nondestructive techniques, such as Ground Penetrating Radar (GPR). The use of GPR as a nondestructive pavement assessment tool is limited mainly due to the difficulty of GPR data interpretation, which requires experienced operators. Therefore, GPR results are usually subjective and inaccurate. Moreover, GPR data interpretation is very time-consuming because of the huge amount of data collected during a survey and the lack of reliable GPR data-interpretation software. This research effort attempts to overcome these problems by developing new GPR data analysis techniques that allow thickness estimation and subsurface defect detection from GPR data without operator intervention. The data analysis techniques are based on an accurate modeling of the propagation of the GPR electromagnetic waves through the pavement dielectric materials while traveling from the GPR transmitter to the receiver. Image-processing techniques are also applied to detect layer boundaries and subsurface defects. The developed data analysis techniques were validated utilizing data collected from an experimental pavement system: the Virginia Smart Road. The layer thickness error achieved by the developed system was around 3%. The conditions needed to achieve reliable and accurate results from GPR testing were also established. / Ph. D.

3D time-lapse seismics, also known as 4D seismics, have great potential for monitoring the migration of CO2 at underground storage sites. This thesis focuses on time-lapse analysis of 3D seismic reflection data acquired at the Ketzin CO2 geological storage site in order to improve understanding of the reservoir and how CO2 migrates within it. Four 3D seismic surveys have been acquired to date at the site, one baseline survey in 2005 prior to injection, two repeat surveys in 2009 and 2012 during the injection period, and one post-injection survey in 2015. To accurately simulate time-lapse seismic signatures in the subsurface, detailed 3D seismic property models for the baseline and repeat surveys were constructed by integrating borehole data and the 3D seismic data. Pseudo-boreholes between and beyond well control were built. A zero-offset convolution seismic modeling approach was used to generate synthetic time-lapse seismograms. This allowed simulations to be performed quickly and limited the introduction of artifacts in the seismic responses. Conventional seismic data have two limitations, uncertainty in detecting the CO2 plume in the reservoir and limited temporal resolution. In order to overcome these limitations, complex spectral decomposition was applied to the 3D time-lapse seismic data. Monochromatic wavelet phase and reflectivity amplitude components were decomposed from the 3D time-lapse seismic data. Wavelet phase anomalies associated with the CO2 plume were observed in the time-lapse data and verified by a series of seismic modeling studies. Tuning frequencies were determined from the balanced amplitude spectra in an attempt to discriminate between pressure effects and CO2 saturation. Quantitative assessment of the reservoir thickness and CO2 mass were performed. Time-lapse analysis on the post-injection survey was carried out and the results showed a consistent tendency with the previous repeat surveys in the CO2 migration, but with a decrease in the size of the amplitude anomaly. No systematic anomalies above the caprock were detected. Analysis of the signal to noise ratio and seismic simulations using the detailed 3D property models were performed to explain the observations. Estimation of the CO2 mass and uncertainties in it were investigated using two different approaches based on different velocity-saturation models.

Multiple Sclerosis (MS) is a neurological autoimmune disease characterized by demyelination of central nervous system tissue and one way this is presented is in the demyelination of the retinal nerve, causing vision disturbance and loss (Munger et al., 2006). The thinning of the retinal nerve fiber layer (RNFL) can be measured and visualized using a noninvasive technique called Optical Coherence Tomography (OCT), which is also used to measure relative MS severity (Petzold et al., 2010). One environmental factor that has been found to have a relationship with MS is vitamin D; research findings suggest that sufficient levels of vitamin D may reduce the risk of developing MS, decrease MS severity, and may slow its progression (Ascherio et al., 2010; Munger et al., 2006; Muris et al., 2013). The mechanism by which vitamin D affects certain symptoms requires deeper investigation. This research examines the relationship between serum concentrations of 25-hydroxyvitamin D and retinal nerve fiber layer thicknesses in patients with MS. It was hypothesized that patients with sufficient vitamin D levels would have less demyelination of the retinal nerve caused by MS, and therefore would have a thicker RNFL in both eyes based on the proposed immunomodulatory role of vitamin D found in other studies. Blood samples were assayed to measure the concentration of 25-hydroxyvitamin D and OCT was used to measure RNFL thicknesses in patients with MS at the Harbor-UCLA Medical Center Neurology Clinic. Patients with sufficient levels of 25-hydroxyvitamin D had a greater mean global RNFL thickness in both eyes than in patients with insufficient levels of 25-hydroxyvitamin D; however the differences were not significant. Further research is necessary in order to determine whether or not there is a correlation between vitamin D and RNFL thickness and what role vitamin D plays in MS presentation.

No description available.

The interest for additive manufacturing techniques have in recent years increased considerably because of their association to good printing resolution, unique design possibilities and microstructure. In this master project, 316L stainless steel was printed using metal laser powder bed fusion in an attempt to find process parameters which yield good productivity while maintaining as good material properties as possible. Laser powder bed fusion works by melting a powder bed locally with a laser. When one slice of the material is done, the powder bed is lowered, new powder is added on top, and the process is repeated, building the components layer by layer. In this thesis, samples produced with a powder layer thickness of 80 μm and 100 μm has been investigated. Process parameters like laser power, scanning speed and hatch spacing were investigated in order to establish clear processing windows where the highest productivity and lowest porosity are obtained. The most common defects in all sample batches were lack of fusion, gas pores, and spatter related pores. The best samples with regard to both porosity and build rate were obtained at normalized build rates between 1,3-1,6 and porosity-values in the 0,01-0,1 % range.

The thesis deals with the dependence of mechanical characteristics on the anisotropy of polymers Nylon 12 and Ultem 9085 made by a 3D printing technology Fused Deposition Modeling (FDM). The evaluation of the material characteristics was performed on the basis of tensile and non-instrumental impact tests. It was proven that the material characteristics are strongly dependent on anisotropy, i.e. on layer thickness and raster angle for both types of polymers.

Coherent plane-wave compounding (CPWC) ultrasound is an important modality enabling ultrafast biomedical imaging. To perform CWPC image reconstruction for a stratified (horizontally layered) medium, one needs to know how the speed of sound (SOS) varies with the propagation depth. Incorrect sound speed and layer thickness assumptions can cause focusing errors, degraded spatial resolution and significant geometrical distortions resulting in poor image reconstruction. We aim to determine the speed of sound and thickness values for each horizontal layer to accurately locate the recorded reflection events to their true locations within the medium. Our CPWC image reconstruction process is based on phase-shift migration (PSM) that requires the user to specify the speed of sound and thickness of each layer in advance. Prior to performing phase-shift migration (one layer at a time, starting from the surface), we first estimate the speed of sound values of a given layer using a cosine similarity metric, based on the data obtained by a multi-element transducer array for two different plane-wave emission angles. Then, we use our speed estimate to identify the layer thickness via end-of-layer boundary detection. A low-cost alternative that obtains reconstructed images with fewer phase shifts (i.e., fewer complex multiplications) using a spectral energy threshold is also proposed in this thesis. Our evaluation results, based on the CPWC imaging simulation of a three-layer medium, show that our sound speed and layer thickness estimates are within 4% of their true values (i.e., those used to generate simulated data). We have also confirmed the accuracy of our speed and layer thickness estimation separately, using two experimental datasets representing two special cases. For speed estimation, we used a CPWC imaging dataset for a constant-speed (i.e., single-layer) medium, yielding estimates within 1% of their true values. For layer thickness estimation, we used a monostatic (i.e., single-element) synthetic-aperture (SA) imaging dataset of the three-layer medium, also yielding estimates within 1% of their true values. Our evaluation results for the low-cost alternative showed a 93% reduction in complex multiplications for the three-layer CPWC imaging dataset and 76% for the three-layer monostatic SA imaging dataset, producing images nearly similar to those obtained using the original PSM methods. / Graduate

Indiana University-Purdue University Indianapolis (IUPUI) / Background: Non-cavitated caries lesions form due to acid diffusion and demineralization of enamel subsurface with an intact surface layer (SL). Caries lesions progress when the outcome of demineralization and remineralization processes over time is net mineral loss. Lesions that continue to demineralize are called active, while those that display no evidence of further demineralization are called inactive. Micro-computed-tomography (µCT) analysis provides objective non-destructive measurements of the thickness of the surface layer (SL) and severity of caries lesions. Aims: 1) To investigate if visual/tactile suspected active non-cavitated early white spot lesions present a thinner surface layer than inactive ones; 2) To investigate if there is an association between the thickness of the surface layer (SLT) and caries activity, as determined by QLF during dehydration (△QD); 3) To determine lesion severity by comparing lesion volume and maximum depth correlation with △Q value at 15 s from QLF during dehydration. Materials and Methods: Thirty extracted human premolars exhibiting non-cavitated approximal white spot early lesions stored in 0.1.-percent thymol/4C and treated with 5.0-percent NaOCl/30 min were included in the study. Fifteen active and 15 inactive lesions were determined by visual/tactile examinations by consensus of two experienced examiners. Roughness measurements (Ra) were acquired using non-contact optical profilometry. Two-dimensional minimum (2D-min), maximum (2D-max), average (2D-avg) SL and three-dimensional (3D) analyses, volume and depth of lesions were determined from µCT image analysis. A series of fluorescence images were acquired at baseline (hydrated), at 1 s, at 5 s, at 10 s and at 15 s by QLF. During image acquisition, surfaces were dehydrated with continuous-compressed-air. △Q and △Q/s (△QD) were calculated. Data were analyzed using two-sample t-tests and Pearson correlation coefficients (p < 0.05). Results: Surface roughness of active and inactive lesions was not significantly different (p > 0.08). Overall lesion volume and depth in dentin were significantly larger in active lesions (p = 0.022, p = 0.009). SL thickness of active and inactive lesions was not significantly different (2D = 0.121, 3D = 0.080, 2D-avg = 0.446, 2D-min = 0.197, 2D-max = 0.122). △QD at 1s was significantly larger for active lesions (p = 0.046). ΔQ at 15 s of dehydration had a moderate positive association with lesion volume (r = 0.56). △QD had a weak negative association with SL thickness (2D-avg) and (2D-min). Conclusions: 1) Active and inactive non-cavitated lesions show no difference in SL thickness; 2) QLF during dehydration (△QD) does not correlate well with SL thickness; 3) ΔQ at 15 s of dehydration correlates moderately well with lesion volume and is consistent with caries activity assessed by visual/tactile examination.

No description available.

About 100 years ago, groups of European beech were reintroduced into Norway spruce stands in some parts of Germany as a restoration approach. The aim of this approach was to maintain or rehabilitate the ecological function of soil fertility and the regeneration option of beech for the next generation. The effect of beech groups on surrounding spruce stands was studied in the Ore Mountains by recording natural regeneration of beech and humus layer thickness and form. Point pattern statistics were used to analyse the spread of beech regeneration and to determine factors influencing its establishment. It was found that the density of regeneration decreases with increasing distance from the beech group. However, beech regeneration was found up to distances of 69 m. Furthermore, it becomes evident that PAR radiation (maximum regeneration densities at PAR values of 35 W/m²) and fencing (3.41 times higher regeneration density compared to unfenced areas) against deer have a positive influence on beech regeneration density. Ordered categorical models were used to model humus form and non-linear models were used to model humus layer thickness. It could be proven that the most bioactive humus forms and lowest humus layer thicknesses were found within the beech group. With increasing distance to the beech group, the total humus layer thickness and the proportion of mormoder in the spruce stand increased. The positive influence of the beech group on the humus composition extends to about 40 m from the centre of the beech group. Due to the former arrangement of the beech groups in the terrain, the effects can also extend to the spruce stands in between. The hypotheses on the restoration approach of reintroducing groups of beech into spruce stands formulated by foresters 100 years ago can thus be confirmed. For future restoration approaches of spruce stands, groupwise mixtures of beech should be established with a distance of 40–50 m.