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Development of a Constant-Volume Bomb Experiment for the Study of Lithium-Ion Battery Thermal Runaway and Its Associated Hazards
No full textLithium-ion battery (LIB) thermal runaway (TR) has increasingly become a serious concern for consumer safety. As a result, many different LIB TR experiments have been developed to study this phenomenon. The present study outlines the development of a LIB TR experiment that seeks to improve upon the preexisting methodologies. The experiment centers around a constant-volume vessel with a programmable heating controller and external gas system to allow for complete control of testing parameters. The results for representative tests of a single cell are presented to illustrate the experiment���s fidelity. Two different LIBs were utilized for these tests which were performed in air at standard ambient conditions and heated at a rate of ~5 ��C /min. The first test was an LG INR18650 cell at 100% state-of-charge (SoC) which had a TR onset temperature of 142 ��C to 175 ��C and produced 0.18 �� 0.004 moles of gas. These values and the composition of the gas were consistent with literature.
The next three tests were performed with Panasonic NCR 18650b cells at 0%, 50%, and 100% SoC. It was found that increasing the SoC of the battery led to increased reactivity and agreed with relevant literature. Particles ejected from these batteries were also characterized using scanning electron microscopy (SEM), energy-dispersive x-ray spectroscopy (EDS), x-ray diffraction (XRD), and x-ray photoelectron spectroscopy (XPS). The 0% SoC battery produced no ejected particles, so the debris was collected from the 50% and 100% tests. Additionally, the particles collected from the 50% test were sieved into the following size ranges: (1) > 212 ��m; (2) 75-212 ��m; (3) 25-75 ��m; and (4) ��� 25 ��m. Qualitative and quantitative sizing of SEM images taken from these samples found particles ranging from the microscale to nanoscale. It was found that approximately 75% of the particles in the ��� 25 ��m were less than 8 ��m. The EDS, XRD, and XPS techniques identified various compounds created from reactions which took place between the different battery components. Future testing efforts seek to further validate the processes developed for this experiment and continue investigating the hazards associated with LIB TR
International Trade Impact on Milk Product Market in the U.S. and LCA with Economic Analysis on Converting Lignin Waste to Sustainable Products
No full textThis dissertation investigates some economic issues regarding international trade and the production of byproducts in lignocellulosic ethanol production. This work is reported in three essays.
The first essay addresses how recent expansions in international trade affect Class I spatial milk price differentials in the U.S. Five international trading scenarios were simulated using a milk sector movement and processing model. The results reveal notable regional differences in the spatial characteristics of farm-level raw milk prices. We find the greatest effects are in the Eastern U.S. where we see significantly higher prices. We also see domestic milk price disparities, in areas like Idaho and New Mexico. Furthermore, the influence of international trade is clearly seen in prices of U.S. milk products that are exported or imported, especially for the products like Cheddar Cheese and Butter. The study emphasizes the need for a possible update in spatial milk price differentials considering the growing impacts of a globally interconnected market.
The second essay examines the net greenhouse gas emissions and market penetration implications of using the lignin byproduct from a lignocellulosic biorefinery to make carbon fiber. The results show that using lignin as a precursor for producing carbon fiber leads to a reduction in CO2 emissions compared to the conventional process of producing carbon fiber. We also analyzed the price and size of the market if the lignin-based carbon fiber was entered into existing carbon fiber markets under various elasticities. Here we found large scale production would lead to substantial carbon fiber price declines.
The third essay examines alternative choices for lignin utilization across a set of alternative downstream products. Namely, lignin can be used to make carbon fiber, asphalt binder modifier, PHA, and biodiesel lipids, when this is done our analysis finds a number of substantial economic and environmental benefits, most notably in reducing CO2 emissions. Market analysis under various scenarios, including the consideration of carbon emission prices, indicates that the optimal market entry of these products depends on production costs and carbon pricing. The findings suggest a strategic approach to lignin utilization, where prioritizing lignin-based carbon fiber production and adjusting outputs based on carbon emission costs can lead to maximum profitability while contributing positively to environmental sustainability
The Role of Reactive Oxygen Species in Response to Chronic Ischemia and Exercise Training Within the Coronary Microcirculation of Swine
No full textThe overall goal of this thesis was to explore adaptations in the contribution of reactive oxygen species (ROS) to coronary microvascular function in response to chronic ischemia and exercise training. The main hypothesis of this study was that superoxide and NADPH oxidase (NOX)-derived ROS would contribute to vasodilation of coronary arterioles and that the contributions of these ROS would be impaired by chronic ischemia and ameliorated with exercise training. These studies utilized a swine model of chronic ischemia via occlusion of the proximal portion of the left circumflex artery with an ameroid occluder while exercise adaptations were examined via the completion of a 14-week progressive (5 days/week) treadmill regimen. Functional pressure myography experiments were performed on isolated arterioles from occluded and nonoccluded regions of sedentary and exercise-trained swine. Additionally, microvascular endothelial cells and arterioles were isolated for high performance liquid chromatography (HPLC) to examine superoxide anion levels and immunoblot to evaluate protein levels of superoxide dismutase (SOD), p22phox, and NOX isoforms.
Functional microvascular studies demonstrated that exercise training produced a rightward shift in vasodilation to the endothelium-dependent agonist, bradykinin, when scavenging superoxide with tempol, independent of occlusive treatment. Further experiments with the NOX1/4 inhibitor, GKT136901, revealed attenuated dilation after exercise training plus occlusion, but not with either exercise or occlusion alone. HPLC revealed that there were no differences in the basal or bradykinin-stimulated production of superoxide anion, regardless of occlusion or exercise. Furthermore, immunoblot analyses revealed decreased NOX2 protein after exercise with no differences found in NOX1, NOX4, p22phox, or SOD protein levels.
Together, these studies demonstrate that exercise-training stimulates independent contributions of both superoxide and NOX1/4-derived ROS to endothelium-dependent, bradykinin-mediated dilation of swine coronary arterioles. It is evident that exercise training produces cellular adaptations within the coronary microcirculation resulting in the contribution of ROS to vasodilation, and subsequently, increases in coronary blood flow. While we determined that ROS play a role in exercise-induced adaptations in the coronary microcirculation, additional study of specific sources and downstream effectors of these ROS are warranted
Experimental Studies on Measurements in Oil-Gas-Water Flow and Turbulent Flow Field in Wind Generated Water Waves
No full textThis thesis presents experimental studies in multiphase flows with two main topics: (1) measurements in oil-gas-water flow using the fiber optic reflectometer (FOR) technique; (2) turbulent flow field in wind generated water waves.
The application of the single-probe fiber optic reflectometer (FOR) technique has been investigated to determine the velocities and size of oil droplets rising in a static water column. The droplet velocity, residence time, and chord length measurements were validated by comparing with the results from high-speed images using the bubble image velocimetry (BIV) technique and the image gradient method. Subsequently, the application of the FOR technique has been extended to oil-gas-water three-phase flows by investigating the accuracy of phase discrimination and measuring the velocity and size of bubbles and droplets. The technique was expanded to identify water, air bubbles, and oil droplets and to quantify the velocity and size of bubbles and droplets in an oil-gas-water three-phase flow through the processing of acquired signals.
In the second part of this thesis, the turbulent flow field in wind generated waves has been studied. The experiments were performed in a wind-wave-current flume with three freestream wind speeds using a particle image velocimetry (PIV) technique. The Bond number and the shear velocity-fetch based Reynolds number were found to correlate the wind wave regimes well. The turbulent dissipation rates were determined based on spatial gradient of instantaneous velocities and one-dimensional velocity spectrum in temporal space. In addition, the turbulent kinetic energy (TKE) budget including its production, dissipation, advection, and turbulent transport was presented. The production-dissipation ratio increased significantly as the wind speed increased, likely attributed to the increased roughness over the substantial coverage of micro-breaking waves. Subsequently, the turbulent flow filed beneath the water surface has also been investigated under the same experimental conditions used for airflow measurements. The friction velocities were estimated from both air- and water- side measurements with the mean velocity profile and the eddy-correlation methods. The result from the comparison of different methods is useful in determining the scaling of water side turbulence such as dissipation rate of turbulence kinetic energy with the air side velocity measurements, or vice versa
John Bickham field notebook: AK19001-AK19500.pdf
No full textBound book, each page corresponds to a karyotype slide data.Data pages for AK19501-AK20000 corresponding to unique identifiers of specimens/samples examined for biological research. Specimens are primarily housed at Texas A&M University; Biodiverstiy Research and Teaching Collection
Disparities of Flood Risk in Urban Areas and Historically Marginalized Populations in Sarasota County, FL
No full textDisaster vulnerability and risk assessments typically focus on socioeconomic characteristics and physical hazards, often omitting factors such as risk perception. Assessing disaster risk using physical and standardized demographic data (i.e., census data) can limit risk assessment accuracy, as the results do not fully encapsulate the complexity of disaster vulnerability, risk, and resilience contexts. Risk perception is essential when planning for disasters because it directly affects how people and communities prepare for, respond to, and recover from disasters. Examining how a community perceives and reacts to a hazard can help planners develop more accurate risk assessments and help decision-makers more equitably allocate disaster resources and develop/implement community-relevant mitigation strategies. Flooding is the most common natural hazard and the leading cause of natural hazard fatalities in the US. For these reasons, it is crucial to develop a more accurate baseline of flood risk identification in addition to analyzing the geosocial relationships to vulnerability by analyzing risk perception, socioeconomic demographics, and urban growth. Finally, the capacity to recover from disasters is often directly correlated to socioeconomic inequality, historic marginalization, and the current structure of the political system. Communities with higher percentages of black, indigenous, and people of color (BIPOC) or low income per capita are often the last to see disaster recovery or risk reduction resources and, even then, are often underfunded and underserved. Historically marginalized demographics are also more likely than their white, affluent counterparts to live with higher exposure and vulnerability to flood hazard. Findings within this study have identified discrepancies within FEMA DFIRMs within smaller urban communities, and a reclassified floodplain better represented underestimated areas within Sarasota County. This reclassified floodplain allowed a further analysis into a geocoded risk perception survey to observe disparities of vulnerability based on sociodemographic variables and exposure to flood. This analysis showed significant positive correlation between perceived vulnerability to damage from flood and women exposed to flood. Additionally, while statistical significance was lacking for multiple relationships, regression models succeeded in showing relationship trends between marginalized groups and how their vulnerability to flood is affected by exposure to flood
John Bickham field notebook: AK13001-AK13500.pdf
No full textBound book, each page corresponds to a karyotype slide data.Data pages for AK13501-AK14000 corresponding to unique identifiers of specimens/samples examined for biological research. Specimens are primarily housed at Texas A&M University; Biodiverstiy Research and Teaching Collection
An Examination of Texas Virtual Teachers' Understanding of Self-Efficacy and Perception of Students' Self-Efficacious Behaviors in a Digital Learning Environment
No full textSelf-efficacy, or one���s ability to achieve the desired result on a task, is a key factor in student
success, particularly in virtual learning contexts. Self-efficacy has been linked to students���
persistence, levels of effort, and goal-setting, as well as their self-regulatory behaviors, such as
time management. The purpose of this study was to explore what virtual middle school teachers
know about self-efficacy, what misconceptions they have, and how teachers believe virtual
students exhibit behaviors of persistence, effort, and goal-setting in asynchronous digital learning
environments. A case study of four teachers from a virtual school in Texas was conducted.
Through qualitative semi-structured interviews and review of lessons, thematic analysis revealed
that virtual teachers had nearly equal amounts of knowledge and misconceptions about self-efficacy. Teachers were able to correctly link self-efficacy to motivation and self-regulation, and they used methods to increase student self-efficacy consistent with the literature in their teaching practice. Teachers had misconceptions about what causes digital learners to develop self-efficacy and around the relationship between self-efficacy and other concepts. Finally, virtual teachers determined that their virtual students do demonstrate behaviors of persistence and effort but did not autonomously exhibit the behavior of goal-setting. This study provides recommendations for increased professional learning through instructional materials to increase teachers��� knowledge of self-efficacy, and therefore inform their practice
In Tlilli, in Tlapalli ���The Black Ink, The Red Ink���: Indigenous Experiences in Society and Healthcare from an Indigenous Philosophy
No full textThis dissertation consists of three articles that will address aspects of the Indigenous social and medical experience within United States society. Elevating Indigenous epistemologies and criticisms of standard epistemological traditions in concert with an Indigenous focused and crafted research method informs the overall methodology and analysis of the project. This focuses the paper to be an explicitly Indigenous focused research project created by an Indigenous person utilizing Indigenous millennia knowledge.
Indigenous peoples interact with healthcare systems just as much as any other social or ethnic group in the U.S., however they are unique since the U.S. government is obligated by treaty to provide healthcare for Indigenous communities through the Indian Health Service (IHS). Indigenous people are the only racialized ethnic group in the U.S. to be guaranteed such healthcare which creates a complex system where a colonial government and bureaucracy are directly responsible for some of the most important, sensitive, and life-threatening aspects of a racialized group���s lives. The first section will provide a discussion of the white racial framing and anti-Indigenous subframing of Indigenous people in the U.S. The second section will provide a brief tee-up for the third section by providing an overview and discussion of Indigenous history in the U.S., the scholarly defined eras of Indigenous history, and a comparison of Indigenous and Western bioethics. The final section will address how the history of anti-Indigenous framing has impacted the Indian Health Service and the federal government���s shocking mismanagement of the IHS, however it will also highlight how Indigenous nations are taking back their healthcare and fulfilling hard-fought principles of sovereignty
Machine Learning for Design Space Exploration
No full textDesign space exploration is a crucial, yet time-intensive aspect of the silicon design lifecycle. With the increasing focus on domain-specific architectures, companies are engaged in evaluating, developing, and verifying a growing number of designs [1]. Performance architects face the challenge of identifying the optimal design within an ever-expanding design space, compounded by the complexity of modern microarchitecture designs. Architects perform design space exploration (DSE) after the microarchitecture has been finalized. DSE typically entails utilizing a scatter approach, where architects explore different configurations of parameters believed to return optimal performance numbers. This is guided by their intuition, borne out of extensive experience in the field from having designed numerous processors. Alternatively, they may perform parameter sweeps, fixing certain values, while experimenting with a subset of parameters to observe the outcomes. Architects must optimize for a wide suite of workloads, including SPEC [2], where each benchmark exhibits a unique program structure and flow, leading to an exponential design space. Additionally, cycle accurate simulators such as ChampSim [3], although faster than EDA flows and RTL models, can still take hours to run a configuration over many benchmarks. Another key issue of any simulation is the serial nature of how processors work, with running simulations, either a RTL or a C/C++ model, requires a serial processing of the instructions to simulate on the hardware. The combination of time consuming simulations with a large number of workloads makes design space exploration a costly and time consuming process.
Design space exploration in microprocessor design is an ideal candidate for the application of machine learning, considering the lengthy simulation times and the complexity of the optimization problem at hand. The rise of machine learning presents an opportunity to apply these optimization and techniques towards design space exploration. These techniques aim to teach models to find correlations through training on large amounts of data. This not only assists less experienced individuals in finding optimal solutions but also complements the expertise of seasoned architects. The proposed work aims to explore the use of machine learning for simulation predictions to shorten the total simulation time. The results can then be used to train optimization algorithms to find an optimal configuration within a design space exploration