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Phase Field Fracture Simulations of High Burn-Up Uranium Dioxide Under Accident Transients
No full textUranium dioxide stands as the predominant fuel type in contemporary nuclear reactors. Despite its notable utility, there is a desire to enhance its performance in high burn-up scenarios. Such advancements would not only mitigate operational costs within existing reactor fleets but also ensure the long-term sustainability of global nuclear programs. To this end, significant progress has been made concerning the thermal performance of uranium dioxide. One notable advancement has been the use of computer simulations to test the fuel in ways that are difficult to replicate in traditional experiments.
This research introduces a novel variant of the cohesion phase-field fracture model within the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. This model was used to simulate high burn-up uranium dioxide under two specific transient scenarios. The first involves a transient representative of reactor start-up, serving to verify the model and establish a performance baseline. The second scenario involves a high-power ramp transient, simulating an unforeseen accident that could potentially occur at any point during operation. The resulting crack patterns from these transients were systematically studied and subsequently compared with existing literature.
The study of these transients has yielded several significant results. During reactor start-up, a limited number of discrete radial cracks would form at the edge and propagate toward the center of the fuel pellet. Characteristics of these cracks, such as their length and quantity, exhibit correlations with start-up power and fuel heat rate. Additional cracking was observed later in the transient when the fuel temperature was increased. These additional cracks would branch off existing cracks and move in the circumferential direction.
The morphological features of the cracks generated in these simulations are consistent with observations from historical and contemporary experiments. Moreover, the model employed in these simulations demonstrates competitiveness with contemporary counterparts, distinguishing itself by offering greater flexibility and fewer artificial restrictions
The Classical-Nonclassical Polarity of Gaussian States
No full textGaussian states with nonclassical properties such as squeezing and entanglement serve as crucial resources for quantum information processing. Accurately quantifying these properties within multi-mode Gaussian states has posed some challenges. In this work, we first give a detailed review to Gaussian state. To address these challenges, we introduce a unified quantification: the ���classical-nonclassical polarity���, represented by P. For a single mode, a positive value of P captures the reduced minimum quadrature uncertainty below the vacuum noise, while a negative value represents an enlarged uncertainty due to classical mixtures. For multi-mode systems, a positive P indicates bipartite quantum entanglement. We show that the sum of the total classical-nonclassical polarity is conserved under arbitrary linear optical transformations for any two-mode and three-mode Gaussian states. For any pure multi-mode Gaussian state, the total classical-nonclassical polarity equals the sum of the mean photon number from single-mode squeezing and two-mode squeezing. Our results provide a new perspective on the quantitative relation between single-mode nonclassicality and entanglement, which may find applications in a unified resource theory of nonclassical features
Turbulent Spherical Flames in a Constant-Volume Fan-Stirred Vessel
No full textTurbulent flame speed is a measurement of the flame propagation rate in a turbulent flow field, combining chemical kinetics with fluid mechanics. Because turbulence is very influential to the flame propagation rate, it is a challenge to model turbulent combustion. The velocity field and relevant length scales of the test chamber flow must be determined to fully analyze the turbulent combustion. In spherically expanding turbulent flame speed experiments, wrinkles in the flame front form pockets and cause the flame to morph into a non-spherical shape. Because of this random non-spherical propagation, the experimental variability is higher for turbulent flame speed experiments than laminar flame speed experiments. The experiments in this study were conducted inside a fan-stirred flame vessel at Texas A&M University.
In this study, we aimed to verify the new heating system and reestablish the turbulent flame analysis method to prepare for future turbulent experiments. To verify the heating system, we performed laminar flame speed experiments and measured the pre-test temperature distribution with an array of thermocouples. Because of the interest in methane as a rocket propellant, the turbulent experiment matrix used methane as the chosen fuel. Methane-air turbulent flame speed experiments were performed for pressures of 1 and 5 atm; turbulent intensities of 1.4 and 2.8 m/s; and equivalence ratios of 0.8, 1.0, and 1.2. The data confirmed that increased turbulence increases the flame speed due to additional instability at the flame front and increased material transport due to turbulent flow. The experiments at higher turbulence intensity show an increased flame acceleration compared to the lower-turbulence tests. Turbulent flame speed increases with increased pressure due to stronger wrinkles increasing the surface area of the flame front
Environmental Impacts on Precipitation-Anvil Relationships
No full textTropical anvil cloud area response to the environmental effects of increased greenhouse gas emission is expected to be a negative cloud feedback for regulating climate sensitivity, although the magnitude of the effect is highly uncertain. This feedback is hypothesized to be caused by tropical deep convection acting as an iris in which anvil cloud coverage and properties are altered allowing more longwave radiation to escape. Recent studies hypothesize that a temperature dependence of convective aggregation could act as a potential mechanism to increase precipitation efficiency at the expense of anvil area. In this study, a precipitating, deep convection cloud object database is created using Tropical Rainfall Measuring Mission satellite observations from 2003-2014 to assess foundational relationships between the environment and precipitation, anvil cloud, and convective aggregation.
Analysis of the largest and strongest storms that contribute the most to tropical anvil cloud area and precipitation shows that precipitation-anvil relationships are more sensitive to changes in moisture rather than temperature, primarily due to greater sensitivity of convective processes to mid-level moisture. Our proxy for convective aggregation, the number of heavy rain cores in the cloud, had the strongest correlation with mid-level moisture increases which was coupled with greater precipitation increases relative to anvil cloud area. As moisture increases, the fractional contribution of different cloud components in the cloud objects shift, with more cold convection area and a reduction in the fraction of thin anvil area. On a system scale, this analysis is consistent with the mechanism that suggests organization and aggregation of convection results in greater precipitation per unit area of anvil cloud
The Effect of Mechanical Degradation on Sustained Fluoride-Releasing O-Rings: An In-Vitro Study
No full textTraditional methods for caries prevention focus on operator application or patient compliance, but the current study aims to establish a viable alternative to the current white spot lesion prevention techniques. O-rings incorporated with fluoride have been previously studied and assessed for a continuous release of fluoride, however, their ability to release fluoride after being mechanical degraded has not been assessed. The proposed research will provide more evidence on the efficacy of the O-rings and their ability to withstand mechanical degradation.
To assess the mechanical degradation these CaF��� O-rings they were brushed in a toothbrushing simulator for 2-weeks and 8-weeks in DIW at a force of 225g. Control and brushed calcium fluoride O-rings were placed on upper lateral incisor brackets, brushed, weighed, and soaked in distilled water. The amount of released fluoride was tested over a period of 7 weeks.
There were statistically significant differences between the control group and the 2-week and 8-week brushing groups throughout the entire duration of the study. The control and experimental groups dropped below the therapeutic range after the first week. When comparing the control group and experimental groups we see there were statistically significant difference between control and 2-week as well as control and 8-week groups at all time points in the study. All three groups experienced a tapering off of fluoride release. When looking at the cumulative release, the control group showed a statistically significant larger cumulative release of fluoride rate compared to both the 2- and 8-week groups (p<0.001). Weight analysis showed that there is a significant loss of material after mechanical abrasion when compared to before brushing. Additionally, there were several revisions to the protocol that were necessary to produce consistent results.
The 2-week and 8-week groups showed significantly less fluoride release over the duration of the study and had lower release rates when compared to the control, which can be affected by the coating protocol. In the first week of experimentation the 2-week group had a higher release rate, but this difference did not continue for the duration of the study
Amino Acid Type and Concentration Impact on Endothelial Nitric Oxide Synthase in Restructured Hams
No full textThis study investigated amino acid types, either singly or in combination, at varying concentration levels to determine which was most effective as a substrate for the endothelial nitric oxide synthase system (eNOS) enzyme to generate nitric oxide for its evaluation as an alternative curing system. Restructured hams were manufactured with pork semimembranosus muscle with a 20% brine consisting of salt, sugar, phosphate and sodium erythorbate and addition of either L-arginine (Arg), L-citrulline (Cit) or in combination (Arg/Cit) at concentrations of 1000, 3000 or 5000ppm. A nitrite (NaNO2) control (200 ppm) was also included. Hams were cooked to (71��C), chilled, vacuum packaged and analyzed on day 1, 7, 28 and 56 of refrigerated (4��C) storage for residual nitrate (RNO3) nitrite (RNO2) and nitroslyhemochromagen (NO-Heme). Sensory panel and textural attributes were analyzed on day 28. For RNO3 values an interaction (p=0.0001) was observed for amino acid type and concentration. Trends suggested 1000ppm concentration for amino acid treatment combinations resulted in higher NO3 values. The main effects of amin acid type and concentration did not affect RNO2 values in the restructured hams however all amino acid treatments produced ~2/3 of the amount of RNO2 than nitrite control. An amino acid type x concentration interaction (p=0.01) NO-Heme values. An amino acid x storage day interaction (p=0.001) NO-Heme values was observed, however, no amino acid treatment or concentration was more effective at generating NO-Heme values. Amino acid type influenced Cured Ham ID (p=0.004) and Ham Flavor Aftertaste (p=0.006) with Arg exhibiting scores closest in value to the nitrite control. Amino acid type also affected Soured Aromatic (p=0.03) and Chemical/Medicinal/Metallic (p=0.001) with Cit treated ham having the highest values for both attributes. An amino acid x concentration (p=0.0001) interaction was observed for objective Hardness values with Arg treated hams values increasing as concentration increased and exhibiting closest values to nitrite control. The data from this study suggests that Arg most effectively cures restructured hams by activation of the eNOS system to generate NO and that a concentration of 1000ppm may be sufficient
Data and Code for: Comparative feeding and defecation behaviors of Trypanosoma cruzi-infected and uninfected triatomines (Hemiptera: Redu-viidae) from the Americas
No full textEnhancing the Nutritional Quality of Red Leaf Lettuce by Optimizing End-of-Production Supplemental LED Lighting
No full textRed leaf lettuces (Lactuca sativa) are commercially significant leafy vegetables grown both in open fields and controlled-environment facilities such as greenhouses and indoor farms. These plants produce anthocyanins, a group of secondary metabolites that enhance their red coloration and nutritional value. However, low light levels in controlled environments can reduce the biosynthesis of anthocyanins and other key phytochemicals such as phenolics, ascorbic acid, and carotenoids. The light conditions in controlled environments could be optimized by leveraging the light-emitting diodes (LED) technology, potentially improving phytochemical accumulation. This research had two primary objectives: 1) to assess whether a higher intensity, shorter duration blue light would increase anthocyanin production more than a lower intensity, longer duration blue light, given the same total cumulative amount of supplemental blue light applied at the end of production (EOP), and 2) to compare the effectiveness of different light spectra, including red, blue, violet, ultraviolet-A (UVA), and ultraviolet-B (UVB), on enhancing anthocyanins and total phenolics in red lettuce during EOP. Our results indicated that a medium intensity of blue light applied over a medium duration resulted in the highest anthocyanin levels when the same amount of supplemental blue light was applied at varying intensities and durations. In evaluating various monochromatic light treatments, we found that supplemental violet light resulted in the highest leaf expansion and biomass, while UVB radiation (3 ��mol m^- �� s^-1 ), despite its lower intensity compared to other light spectra (60 ��mol m^- �� s^-1 ), was most effective at enhancing the accumulation of phytonutrients such as anthocyanins and phenolics but caused yield reductions. We caution that the tradeoff between enhanced crop nutritional quality and reduced crop yield must be carefully considered in commercial applications
Multiphysics Models to Predict the Peformance and Reliability of Electroadhesive Surface Haptic Devices
No full textHaptics refers to the sense of touch, and surface haptics is the branch of haptics that deals with the generation of tactile effects on touch surfaces to make user experiences more immersive and realistic. Electroadhesive surface haptic devices make use of electroadhesion to apply electrostatic forces at the human-device interface, which is then modulated to modulate the interfacial friction forces and generate tactile effects.
Devices that incorporate such state-of-the-art technology often face several reliability and performance issues in their nascent stages that need to be resolved to enable their successful commercialization. Predictive models play an important role in the development of such devices because they provide designers with efficient tools to explore a wide design space to find solutions, as opposed to relying on an inefficient and expensive trial-and-error approach. In this study, we investigate a few such challenges associated with electroadhesive haptic devices. We will identify the key mechanisms causing visible preferential deposition of fingerprint residue on specific regions of the surface of commercial electroadhesive haptic touchscreens and develop a multiphysics predictive model that can be used to explore solutions to tackle this issue. We will then develop a finger mechanics model that can predict the roughness perception produced by distributed haptic devices. This model will provide insights into which mechanics properties trigger the mechanoreceptors that contribute to roughness perception. Finally, we will develop a multiphysics model that couples the contact mechanics, capillary, and electrostatic phenomena at the interface and can provide fast and accurate predictions about the interfacial friction force ��� an important parameter than needs to be accurately represented to make correct predictions about the device performance. Together, these models will provide useful tools to haptic device designers to build better haptic devices in a quick and cost-effective way
AI and Machine Learning Using Wearables for Diabetes Care
No full textThe emergence of Internet of things (IoT) devices and technological advances have revolutionized healthcare, particularly the advent of AI-based wearables have enabled frequent monitoring of glucose levels in patients. This is critical for an incurable disease like diabetes which can only be managed through frequent monitoring of glucose values. Despite the progress made, making AI-based solutions more patient-centric remains a challenge. To address this, we present methods for efficient application of AI/ML solutions for improving diabetes care with an emphasis on patient needs.
This dissertation has two primary objectives: (1) To build robust machine learning models to improve diabetes care, and (2) develop alternatives to current glucose monitoring technologies to enhance the accessibility and reduce the intrusiveness. To achieve the Objective 1, we focus on developing machine learning algorithms for prediction of impending hypoglycemia risk in patients. A feature-based machine-learning model is built based on previous CGM values that gives real-time predictions for hypoglycemia risk, enabling patients to take intervening actions. We subsequently work on improving the quality of hypoglycemia predictive alerts in a real-world setting by focusing on predictive alerts that are based on sustained hypoglycemia. This drastically reduces instances of false alerts, a major deterrent for technology adoption among patients.
Machine learning models with robust performance rely on large corpus of data for training. However, healthcare data is sensitive, and its accessibility is restricted with many regulations in place. To this, we develop FedGlu, a machine learning model trained in a federated learning framework that simultaneously addresses the dual challenge of data availability and model performance. FedGlu also incorporates a customized loss function that improves the model���s predictive capabilities in the glycemic excursion regions.
CGM devices are valuable, but accessibility is limited as they are expensive and also available based only on prescriptions. In addition, they are invasive which can be painful for patients. In Objective 2, as an alternative to CGM devices, we extend the use of IoT based noninvasive wearables for glucose monitoring. For this, we evaluate hyperglycemia detection along with hypoglycemia detecting using ECG and accelerometer signals that are collected noninvasively. We comprehensively evaluate the proposed algorithms on people with and without diabetes and demonstrate the efficacy of the proposed approach. In closing, a summary of the contributions and directions of future work are presented