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Although it is well established that spacing of piles within a pile group influences the lateral load resistance of that group, additional research is needed to better understand trends for large pile groups (greater than three rows) and for groups in sand. A 15-pile group in a 3x5 configuration situated in sand was laterally loaded and data were collected to derive p-multipliers. A single pile separate from the 15-pile group was loaded for comparison. Results were compared to those of a similar test in clays. The load resisted by the single pile was greater than the average load resisted by each pile in the pile group. While the loads resisted by the first row of piles (i.e. the only row deflected away from all other rows of piles) were approximately equal to that resisted by the single pile, following rows resisted increasingly less load up through the fourth row. The fifth row consistently resisted more than the fourth row. The pile group in sand resisted much higher loads than did the pile group in clay. Maximum bending moments appeared largest in first row piles. For all deflection levels, first row moments seemed slightly smaller than those measured in the single pile. Maximum bending moments for the second through fifth rows appeared consistently lower than those of the first row at the same deflection. First row moments achieved in the group in sand appeared larger than those achieved in the group in clay at the same deflections, while bending moments normalized by associated loads appeared nearly equal regardless of soil type. Group effects became more influential at higher deflections, manifest by lower stiffness per pile. The single pile test was modeled using LPILE Plus, version 4.0. Soil parameters in LPILE were adjusted until a good match between measured and computed responses was obtained. This refined soil profile was then used to model the 15-pile group in GROUP, version 4.0. User-defined p-multipliers were selected to match GROUP calculated results with actual measured results. For the first loading cycle, p-multipliers were found to be 1.0, 0.5, 0.35, 0.3, and 0.4 for the first through fifth rows, respectively. For the tenth loading, p-multipliers were found to be 1.0, 0.6, 0.4, 0.37, and 0.4 for the first through fifth rows, respectively. Design curves suggested by Rollins et al. (2005) appear appropriate for Rows 1 and 2 while curves specified by AASHTO (2000) appear appropriate for subsequent rows.

Stone column treatment is commonly used to mitigate liquefaction hazard in sandy soils. Research and experience indicate that this method is effective for clean sands but that it may not be effective for silts and sands with fines contents greater than 15-20%. An alternative to the stone column method involves supplementing stone column treatment with pre-fabricated vertical wick drains installed prior to the stone columns installation. Although this method is used in practice, there has not been a formal academic study of its effectiveness. This thesis evaluates seven different case histories where wick drains were used and one where wick drains were not used, for comparison purposes. The site locations varied as well as the soil properties and treatment plans. CPT testing was done at 3 sites and SPT testing was performed at the other 5 sites. CPT data were correlated to SPT data to facilitate comparisons. One of the case histories includes a unique study in which three different variations of the stone column treatment were applied at the same site, providing a direct comparison of the effectiveness of each method. A 26% area replacement ratio (Ar) with drains was determined to be more effective overall than a 26% Ar without drains and more effective in increasing low initial blow counts than the 34% Ar without drains. The areas with drains were more likely to exceed the minimum project criteria consistently throughout the site. Significant scatter were observed in the results and probable causes for the scatter are noted. Final blow count coefficients of variation ranged from 28% to 77%. Increased fines contents required increased Ar in order to maintain similar average final blow counts. Site improvements were evaluated separately and collectively. Individual site results were compared to clean sand curves developed by Baez (1995). Sites with average fines contents less than 20% which were improved using drains and an 11-15% Ar treatment were comparable to clean sand sites without drains and with 5-10% Ar. To achieve similar improvement at sites with 40-46% fines necessitated drains and Ar values of 23-26%. Design recommendations are provided.

Penstemon gibbensii and Penstemon haydenii are two rare, perennial forbs inhabiting remote areas of the western United States. P. gibbensii is listed as a sensitive species by the Bureau of Land Management (BLM) in Colorado, Utah, and Wyoming (Heidel, 2009). P. haydenii was designated as Endangered by the U.S. Fish and Wildlife Service in 1987 (Heidel, 2012). This thesis research was geared toward helping land managers in their efforts to protect and rehabilitate these species by providing understanding on different aspects of their seed ecology. My first study was a laboratory experiment performed on P. gibbensii and P. haydenii seed germination response to moist chilling and dry after-ripening. Wild harvested seeds were subjected to moist chilling at 2-4 °C for 0, 4, 8, 12, and 16 weeks and held in dry storage for approximately 2 years to determine effective methods for breaking primary dormancy. P. gibbensii seed germination increased consistently with increased length of chilling up to 16 weeks and exhibited habitat-correlated variation in this response. P. haydenii seed germination increased from 1 to 100% germination with 4 weeks of chilling. P. haydenii germination was greatest (96%) when incubated under a cool, diurnally-fluctuating temperature regime (10-20 °C) and responded positively to dry storage, increasing germination from 0 to 15%. My second study was an in situ field study designed to characterize the active seed bank of P. haydenii. We set up a transect line across a P. haydenii population and measured the number of seeds entering the seed bank, lost to predation post-dispersal, and persisting in the seed bank. P. haydenii does not appear to form an ecologically significant seed bank. Approximately 140 seeds/ 10m2 could potentially enter the seed bank but only 1 seed in the upper 10cm of sand persisted. Heavy post-dispersal insect predation resulted in a decrease in viability of nearly 30% in exposed P. haydenii seeds after just 12 hours. My third study explored the effects of burial by sand on P. haydenii. Wild-harvested seeds were planted in pots at 1, 2, 4, 6, 8, and 10cm deep in sand and incubated at 10-20 °C. Seed germination and mortality and seedling emergence were measured. The response of dormant seeds to post-burial incubation was determined. Burial depth decreased seedling emergence and seed germination. Shallow burial appears to induce secondary dormancy for seeds that don't germinate quickly, whereas deep burial appears to impose enforced dormancy in burial.

Sand casting is used to manufacture large metal workpieces. The processing is executed by pouring molten metal into a sand mold. During the process, the mold is subjected to mechanical and thermal stress. It is of economic interest to inspect the molds for defects that can affect casting results, in the worst case leading to discarded products. This thesis investigates and proposes an automated solution for inspecting surface cracks in sand molds. A hybrid solution using image processing and convolutional neural networks has been developed. The first is to find and implement a crack detection method that can perform equally well or better than a human. The second objective is to investigate the amount of training data needed. Twenty-one machine learning models have been trained to evaluate the impact training data size along with transfer learning, fine-tuning, data augmentation, and image processing have on performance. As a result, it was found that the image processing part of the method is not effective in finding cracks in its current form. However, the convolutional neural network still achieves good performance. The method has been trained and tested on sand mold core images captured with a test workbench along with images of concrete walls and pavement acquired from the SDNET2018 data set. Sand mold images achieve 82% accuracy and 79% recall when training on 90 images while testing on 28 images separate from training. A maximal performance of 97.9% accuracy and 99.7% recall is achieved when training on 5400 SDNET2018 images and then testing on 608 images. When training on 100 SDNET2018 images and tested on the same 608 images, a performance of 86.0% and 96.7% recall is achieved. It is concluded that the proposed solution is feasible. Transfer learning and data augmentation are essential techniques to achieve good performance if a small amount of data is available, while fine-tuning may give a slight performance boost. Further work should be performed considering the impact of curved geometry on performance. Investigating alternative structures of the convolutional neural network and testing alternative hyperparameters may improve generalization performance. The image processing performance may be improved if the manufacturing process is more precisely defined, as parameters can be more optimally tuned.

In recent years the nutrient levels of the Upper Floridan aquifer have been increasing (USGS, 2008). An example of this is found in Ocala, Florida where Silver Springs nitrate concentrations have risen from 0.5 mg/L in the 1960 s to approximately 1.0 mg/L in 2003 (Phelps, 2004). Because stormwater is a contributor to surficial and groundwater aquifer recharge, there is an increasing need for methods that decrease nitrogen and phosphorus levels. A laboratory column study was conducted to simulate a retention pond with saturated soil conditions. The objectives of the column studies reported in this thesis were to investigate the capabilities of a natural soil and soil augmentations to remove nitrogen and phosphorus for a range of concentrations at three different temperatures. An analytical attempt to model the columns through low order reaction kinetics and derive the corresponding temperature conversion constant to relate the rate constants is also presented. The Media Mixes were selected through a process of research, preliminary batch testing and then implemented in column studies. Three columns measuring three feet in length and 6 inches outer diameter were packed with a control and two media mixes. Media Mix 1 consisted of 50% fine sand, 30% tire crumb, 20% sawdust by weight and Media Mix 2 consisted of 50% fine sand, 25% sawdust, 15% tire crumb, 10% limestone by weight. The control column was packed with natural soil from Hunter s Trace retention pond located in Ocala, Florida. The reaction rates for nitrate are best modeled as first order for Media Mix 1, and zero order for the Control and Media Mix 2. The reaction rates for orthophosphate are best modeled as zero order, second order and first order for the Control, Media Mix 1, and Media Mix 2 respectively. The best overall media for both nitrate and orthophosphate removal from this study would be Media Mix 1. Media Mix 2 does have the highest average orthophosphate removal of all the mixes for all of the temperatures; however Media Mix 1 outperforms Mix 2 for the other two temperatures. The best column for Nitrate removal is the Media Mix 1 column. The temperature conversion factors for nitrate were found to be 1.11, 1.1, and 1.01 for Media Mix 1, the Control and Media Mix 2 respectively. The temperature conversion factors for orthophosphate were found to be 1.02, 0.99, and 0.95. As well as temperature conversion factors, the activation energies and frequency factors for the Arrhenius Equation were investigated. Average values corresponding to each column, species, and temperature would be inaccurate due to the large variation in calculated values.

Introduction: Production systems go through changes over time and there are different factors driving the change. Metal Additive manufacturing (AM) could be a factor with industries that already havetaken interest in the manufacturing technique. Qualification and standards of manufacturing guide consistent product quality and could face challenges when implementing AM. However,most publications about metal AM are currently posted from a material point of view. This requires more publications with comprehensive overviews of metal AM and dive deeper into metal AMs industry applications, limitations and challenges. Purpose: The purpose of this thesis is to identify challenges that may arise in the implementation of AM. The intention is also to compare the conventional method of sand casting with AM for metal production targeted at excavators. This is accomplished by specifically highlighting the metallurgical benefits of AM. Research Questions: RQ1: What challenges arise when qualifying AM products for excavators? RQ2: What are the metallurgical benefits of an AM produced product in comparison to a Sand Casted product for excavator bucket teeth? Method: An inductive approach has been taken, with a literature, empirical and case study conducted.The construction of the theoretical framework used information from scientific articles and books. The findings of the empirical study arrived from information gathered through observations and experimentation, with help and interpretation from the case companies. The empirical findings will assist in answering the research questions. The case study consisted of metallurgical testing in form of porosity analysis, microstructure examination, hardness- and chemical composition test. Conclusion: Several challenges were discovered that will impact the qualification of AM products. These can affect the results derived from the case study, providing incorrect data. It can however be seen as beneficial as it provides knowledge of how to reduce or eliminate their impact withfuture analyses.The AM products tested, displayed positive metallurgical properties in comparison with sand casted products. A standout trait was the consistency in the dimension and density of the AM products, displaying how AM can create nearly identical products.

<p> Cobequid Bay is a macrotidal embayment with a large intertidal sand bar complex at the east end, located at the head of the Bay of Fundy. Two sand bars were sampled in order to observe variations in impact pit densities on the surfaces of quartz sand grains, and to identify the pattern of grain size distribution over two intertidal bedforms. </p> <p> V pit densities obtained by viewing the quartz grain surfaces at magnifications of 10,000 and 5,000X with a scanning electron microscope indicate a linear correlation with grain size. The number of small V's appears to be consistent for all grain sizes, with the result that V's larger than approximately 1/5 micrometer produce the linear variation noted. Two trends of V pits formation combine to produce a "plateau", in which two grain size classes have similar V pit densities. This plateau corresponds to the break-point between the traction population and the intermittent suspension population. Trend one consists of the bombardment of large, well exposed grains (transported in the traction layer), by smaller saltating grains, while trend two consists of grain impacts between smaller grains in the concentrated "rheological layer". </p> <p> Two different grain size patterns were discovered on the two sampled bedforms. A fining upward trend toward the crest on both the stoss and slip faces was observed on an ebb dominated megaripple on Selmah Bar. The exact opposite pattern was noted on an ebb dominated sandwave from East Noel Bar. On this bedform, an upward coarsening trend toward the crest was discovered on both the stoss and slip faces. These two patterns correspond to the patterns observed by Dalrymple (1977) in his studies of intertidal bedforms. </p> / Thesis / Bachelor of Science (BSc)