Technique to measure heats of reaction of Ti-B, Al-Ti-B, and Al-Ti-B4C powder blends

In this research, a modification to initiation aid ignition in bomb calorimetry that involves systemically blending levels of boron and potassium nitrate initiation aids with a bulk structural energetic elemental power blend is developed. A regression is used to estimate the nominal heat of reaction for the primary reaction. The technique is first applied to the synthesis of TiB2 as a validation study to see if close proximity to literature values can be achieved. The technique is then applied to two systems of interest, Al-Ti-B, and Al-Ti-B4C. In all three investigations, x-ray diffraction is used to characterize the product phases of the reactions to determine the extent and identity of the product phases and any by-products that may have formed as a result of adding the initiation aid. The experimental data indicates the technique approximates the heat of reaction value for the synthesis of TiB2 from Ti-B powder blends and the formation of TiB2 is supported by volume fraction analysis by x-ray diffraction. Application to the Al-Ti-B and Al-Ti-B4C blends show some correlation with variation of the initiation aid, with x-ray diffraction showing the formation of equilibrium products. However, these blends require further investigation to resolve more complex interactions and rule out extraneous variables.

Landscape and forest structure at moose mortality sites on Isle Royale National Park. A LiDAR based assessment

Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

STUDY OF HYBRID ELECTRIC VEHICLE BATTERY MODELING AND CONTROL USING AUTONOMIE

This report presents the research results of battery modeling and control for hybrid electric vehicles (HEV). The simulation study is conducted using plug-and-play powertrain and vehicle development software, Autonomie. The base vehicle model used for testing the performance of battery model and battery control strategy is the Prius MY04, a power-split hybrid electric vehicle model in Autonomie. To evaluate the battery performance for HEV applications, the Prius MY04 model and its powertrain energy flow in various vehicle operating modes are analyzed. The power outputs of the major powertrain components under different driving cycles are discussed with a focus on battery performance. The simulation results show that the vehicle fuel economy calculated by the Autonomie Prius MY04 model does not match very well with the official data provided by the department of energy (DOE). It is also found that the original battery model does not consider the impact of environmental temperature on battery cell capacities. To improve battery model, this study includes battery current loss on coulomb coefficient and the impact of environmental temperature on battery cell capacity in the model. In addition, voltage losses on both double layer effect and diffusion effect are included in the new battery model. The simulation results with new battery model show the reduced fuel economy error to the DOE data comparing with the original Autonomie Prius MY04 model.

DEVELOPMENT OF A CONCEPTUAL MODEL AND PARAMETERIZATION OF A MATHEMATICAL MODEL FOR SEDIMENT PHOSPHORUS DIAGENESIS, SORPTION AND RELEASE FROM ONONDAGA LAKE SYRACUSE, NEW YORK

Eutrophication is a persistent problem in many fresh water lakes. Delay in lake recovery following reductions in external loading of phosphorus, the limiting nutrient in fresh water ecosystems, is often observed. Models have been created to assist with lake remediation efforts, however, the application of management tools to sediment diagenesis is often neglected due to conceptual and mathematical complexity. SED2K (Chapra et al. 2012) is proposed as a "middle way", offering engineering rigor while being accessible to users. An objective of this research is to further support the development and application SED2K for sediment phosphorus diagenesis and release to the water column of Onondaga Lake. Application of SED2K has been made to eutrophic Lake Alice in Minnesota. The more homogenous sediment characteristics of Lake Alice, compared with the industrially polluted sediment layers of Onondaga Lake, allowed for an invariant rate coefficient to be applied to describe first order decay kinetics of phosphorus. When a similar approach was attempted on Onondaga Lake an invariant rate coefficient failed to simulate the sediment phosphorus profile. Therefore, labile P was accounted for by progressive preservation after burial and a rate coefficient which gradual decreased with depth was applied. In this study, profile sediment samples were chemically extracted into five operationally-defined fractions: CaCO3-P, Fe/Al-P, Biogenic-P, Ca Mineral-P and Residual-P. Chemical fractionation data, from this study, showed that preservation is not the only mechanism by which phosphorus may be maintained in a non-reactive state in the profile. Sorption has been shown to contribute substantially to P burial within the profile. A new kinetic approach involving partitioning of P into process based fractions is applied here. Results from this approach indicate that labile P (Ca Mineral and Organic P) is contributing to internal P loading to Onondaga Lake, through diagenesis and diffusion to the water column, while the sorbed P fraction (Fe/Al-P and CaCO3-P) is remaining consistent. Sediment profile concentrations of labile and total phosphorus at time of deposition were also modeled and compared with current labile and total phosphorus, to quantify the extent to which remaining phosphorus which will continue to contribute to internal P loading and influence the trophic status of Onondaga Lake. Results presented here also allowed for estimation of the depth of the active sediment layer and the attendant response time as well as the sediment burden of labile P and associated efflux.

Development of Optically Based pH Sensing Hydrogel and Controlled Nitric Oxide Release Polymer

Nitric oxide has the potential to greatly improve intravascular measurements by locally inhibiting thrombus formation and dilating blood vessels. pH, the partial pressure of oxygen, and the partial pressure of carbon dioxide are three arterial blood parameters that are of interest to clinicians in the intensive care unit that can benefit from an intravascular sensor. This work explores fabrication of absorbance and fluorescence based pH sensing chemistry, the sensing chemistries' compatibility with nitric oxide, and a controllable nitric oxide releasing polymer. The pH sensing chemistries utilized various substrates, dyes, and methods of immobilization. Absorbance sensing chemistries used sol-gels, fumed silica particles, mesoporous silicon oxide, bromocresol purple, phenol red, bromocresol green, physical entrapment, molecular interactions, and covalent linking. Covalently linking the dyes to fumed silica particles and mesoporous silicon oxide eliminated leaching in the absorbance sensing chemistries. The structures of the absorbance dyes investigated were similar and bromocresol green in a sol-gel was tested for compatibility with nitric oxide. Nitric oxide did not interfere with the use of bromocresol green in a pH sensor. Investigated fluorescence sensing chemistries utilized silica optical fibers, poly(allylamine) hydrogel, SNARF-1, molecular interactions, and covalent linking. SNARF-1 covalently linked to a modified poly(allylamine) hydrogel was tested in the presence of nitric oxide and showed no interference from the nitric oxide. Nitric oxide release was controlled through the modulation of a light source that cleaved the bond between the nitric oxide and a sulfur atom in the donor. The nitric oxide donor in this work is S-nitroso-N-acetyl-D-penicillamine which was covalently linked to a silicone rubber made from polydimethylsiloxane. It is shown that the surface flux of nitric oxide released from the polymer films can be increased and decreased by increasing and decreasing the output power of the LED light source. In summary, an optical pH sensing chemistry was developed that eliminated the chronic problem of leaching of the indicator dye and showed no reactivity to nitric oxide released, thereby facilitating the development of a functional, reliable intravascular sensor.

DENITRIFICATION IN SOILS: FROM GENES TO ENVIRONMENTAL OUTCOMES

Denitrification is an important process of global nitrogen cycle as it removes reactive nitrogen from the biosphere, and acts as the primary source of nitrous oxide (N2O). This thesis seeks to gain better understanding of the biogeochemistry of denitrification by investigating the process from four different aspects: genetic basis, enzymatic kinetics, environmental interactions, and environmental consequences. Laboratory and field experiments were combined with modeling efforts to unravel the complexity of denitrification process under microbiological and environmental controls. Dynamics of denitrification products observed in laboratory experiments revealed an important role of constitutive denitrification enzymes, whose presence were further confirmed with quantitative analysis of functional genes encoding nitrite reductase and nitrous oxide reductase. A metabolic model of denitrification developed with explicit denitrification enzyme kinetics and representation of constitutive enzymes successfully reproduced the dynamics of N2O and N2 accumulation observed in the incubation experiments, revealing important regulatory effect of denitrification enzyme kinetics on the accumulation of denitrification products. Field studies demonstrated complex interaction of belowground N2O production, consumption and transport, resulting in two pulse pattern in the surface flux. Coupled soil gas diffusion/denitrification model showed great potential in simulating the dynamics of N2O below ground, with explicit representation of the activity of constitutive denitrification enzymes. A complete survey of environmental variables showed distinct regulation regimes on the denitrification activity from constitutive enzymes and new synthesized enzymes. Uncertainties in N2O estimation with current biogeochemical models may be reduced as accurate simulation of the dynamics of N2O in soil and surface fluxes is possible with a coupled diffusion/denitrification model that includes explicit representation of denitrification enzyme kinetics. In conclusion, denitrification is a complex ecological function regulated at cellular level. To assess the environmental consequences of denitrification and develop useful tools to mitigate N2O emissions require a comprehensive understanding of the regulatory network of denitrification with respect to microbial physiology and environmental interactions.

INVESTIGATING THE IMPACTS OF STREAMBED HABITAT HETEROGENEITY ON ECOSYSTEM STRUCTURE AND PROCESSES USING BASIC AND APPLIED PERSPECTIVES

Stream restoration often focuses on increasing habitat heterogeneity to reverse ecosystem degradation. However, the connection between heterogeneity and ecosystem structure and processes is poorly understood. We looked to investigate this interaction from both applied and basic science perspectives. For the applied study, we examined two culvert replacements designed to mimic natural stream channels, to see if they were better at maintaining ecosystem processes within as well as upstream and downstream of culverts compared to non-replaced culverts. We measured three ecosystem processes (nutrient uptake, hydrologic characteristics, and coarse particulate organic matter retention) and found that stream simulation culvert restoration improved organic matter retention within culverts, and that there were no differences in processes measured upstream and downstream of both restoration designs. Our results suggest that measurements of ecosystem processes are more likely to show a response to restoration if they match the scale of the restoration activity. For the basic science study, we quantified the longitudinal spatial heterogeneity of physical and biofilm characteristics at microhabitat to segment scales on streams with different streambed variability. We found that all physical characteristics and biofilm characteristics were spatially independent at the macro-habitat scale and greater. Together, these studies demonstrate the importance of scale in ecological interactions and the value of incorporating considerations of scale into restoration activities.

Winning coal at 78° North : mining, contingency and the Chaîne Opératoire in old Longyear City

The purpose of this thesis is to analyze the evolution of an early 20th century mining system in Spitsbergen as applied by Boston-based Arctic Coal Company (ACC). This analysis will address the following questions: Did the system evolve in a linear, technological-based fashion? Or was the progression more a product of interactions and negotiations with the natural and human landscapes present during the time of occupation? Answers to these questions will be sought through review of historical records and material residues identified during the 2008 field examination on Spitsbergen. The Arctic Coal Company’s flagship mine, ACC Mine No. 1, will serve as the focus for this analysis. The mine was the company’s largest undertaking during its occupation of Longyear Valley and today exhibits a large collection of related features and artifacts. The study will emphasize on the material record within an analysis of technical, environmental and social influences that guided the course of the mining system. The intent of this thesis is a better understanding of how a particular resource extraction industry took root in the Arctic.

INNOVATIVE HUMAN-COMPUTER INTERACTIONS TO SUPPORT COGNITIVE COLLABORATIVE GEOSPATIAL ENVIRONMENTS

In the current world geospatial information is being demanded in almost real time, which requires the speed at which this data is processed and made available to the user to be at an all-time high. In order to keep up with this ever increasing speed, analysts must find ways to increase their productivity. At the same time the demand for new analysts is high, and current methods of training are long and can be costly. Through the use of human computer interactions and basic networking systems, this paper explores new ways to increase efficiency in data processing and analyst training.