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Materials science aims to explore the properties and behaviors of different materials, from metals to advanced carbon structures. This dissertation focuses on three distinct areas of study: Inconel Alloy 740H, polycrystalline graphene, and tetragraphene (TG).
The first part of this work concentrates on developing and validating a Chaboche unified constitutive model. This model incorporates both nonlinear isotropic and kinematic hardening rules to accurately predict the stress-strain behavior of Inconel Alloy 740H, a high-temperature nickel-based superalloy. The material parameters of the model are determined and its accuracy validated through experimental data obtained from uniaxial strain-controlled loading tests across a wide temperature and strain ranges.
The second part explores the mechanical properties of polycrystalline graphene, bridging scales from nanoscale to macroscale through a multiscale molecular dynamics (MD)–finite element (FE) modeling approach. By studying the behavior of graphene sheets with different grain boundaries and atomic structures, insights are gained into the influence of grain size on mechanical properties like the Young modulus and fracture stress.
The third part of this dissertation investigates the mechanical properties of tetragraphene (TG), a quasi-2D semiconductor carbon allotrope, with a focus on addressing graphene's limitations in electronic applications. Through MD simulations, the research examines TG's fracture properties under mixed mode I and II loading, considering variables such as loading phase angle, crack structure, and temperature.
Since the early 1980s, American educational reformers have tried to improve schools through standards, high-stakes tests, and punishments for those schools that failed to meet the mark. In North Carolina, many schools with diverse populations and low socioeconomic status have struggled to succeed, receiving the state performance grade of D or F and the consequent “low-performing” label. Meanwhile, some teachers in these schools have achieved at high levels and attempted to improve not only their classrooms, but their schools and districts. Few researchers have sought the opinions and expertise of high-performing teachers in order to better understand their experiences, their role as change agents, and their recommendations for other so-called “low-performing” schools. This qualitative multiple case study used in-depth interviews with these high-performing teachers in “low-performing” elementary schools in North Carolina. Specifically, this research gathered information about their backgrounds, their actions for school transformation, and their lessons learned about education and equity. Findings from the study indicated that high-performing elementary teachers tried to reform their “low-performing” schools through teacher agency but were blocked by multiple factors. School administrators and district officials reduced teacher agency and opportunities for school improvement. North Carolina’s “low-performing” schools policy harmed children, reinforced school failure, and produced discriminatory and inequitable results. Teacher agency theory provided a promising approach for the state to change course and improve failing schools.
Recent advancements in deep learning have significantly propelled the field of computer vision, especially in 3D human model recovery from monocular images. This work is centered on developing efficient deep learning models for digitizing human subjects, thereby laying a solid foundation for various subsequent applications. 3D human mesh estimation from monocular images often requires complex deep learning models. In addressing this, we propose a hybrid approach combining deep learning models with analytical inverse kinematics to precisely estimate 3D pose and shape.
Our precise 3D pose estimations facilitate three high-impact downstream applications. Firstly, we aim to create a real-time biomechanics analysis system that provides low-cost, real-time, and accurate estimations of kinematic sequences for managing joint human health-performance. Herein, our system integrates mobile modular 3D pose estimation with model-based inverse kinematics optimization seamlessly. The next downstream task entails skeleton-based human action recognition (HAR), with extensive applications in smart homes, cities, and retail. By rendering 3D pose sequences as RGB images and utilizing conventional CNN architectures alongside various data augmentation schemes, we have achieved results comparable to sophisticated Graph Neural Network models. Lastly, in scenarios where visual cues are scarce yet human monitoring is essential, radar-based sensing offers a non-intrusive solution for tracking human movements and vital signs. Given the paucity of extensive radar datasets, we introduce a "virtual radar" framework in our third downstream task. This framework, driven by 3D pose and physics-informed principles, generates synthetic radar data, presenting a novel avenue towards a nuanced understanding of human behavior through privacy-preserving radar-based methodologies.
Autism Spectrum Disorders (ASD) are characterized by pervasive impairments, inhibiting social interaction and learning opportunities, often with ensuing behavior challenges. Studies estimate that 25-30% of children with ASD do not develop flexible and consistent language. Communication skills are essential to supporting individuals with ASD to communicate their needs, navigate their chosen environments independently, and establish relationships. Fortunately, researchers have identified several practices to address social communication challenges. Naturalistic teaching (NT) and parent-mediated intervention (PMI) are two practices derived from applied behavior analysis that are evidence-based and highly effective language acquisition methods. Caregiver-implemented interventions, often facilitated via coaching, provide families with supportive practice to increase their children’s language within natural contexts. By equipping parents with tools, strategies, and support, these interventions leverage the strength of the family unit to facilitate language-rich learning opportunities. Despite empirically-supported communication models for ASD and solid evidence supporting NT and PMI, insufficient access to high-quality interventions remains a barrier for families. Barriers such as inequalities in access to services, challenges in customizing training, schedule constraints, and family pressures remain significant concerns for caregivers.
The purpose of this study was to examine the effects of a naturalistic caregiver coaching package on the accuracy of parents' implementation of Referent-Based Instruction (RBI), evaluate their children's verbal behavior repertoires subsequent to intervention, and explore caregivers’ experiences in participating in RBI. Results suggest that caregivers improved their fidelity and implementation of RBI procedures following the introduction of the coaching package. Child participants' communicative repertoires increased after caregivers participated in the intervention, and they reported their experiences in this training as highly positive.
A key component of team performance is participation among group members. One widespread organizational function that provides a stage for participation is the workplace meeting. With the shift to remote work, roughly half of all meetings are now conducted virtually (Cisco, 2022). In this new context, meeting participation is mediated through technology – which presents new challenges and opportunities for meeting leaders and attendees. One encouraging opportunity that can elevate meeting participation is the use of written chat during virtual meetings. Text-based chat offers a second avenue of participation during a meeting, where attendees can synchronously contribute to the conversation through writing, in a manner that typically does not disrupt the verbal discussion. The current study leverages research and theory on (a) individual differences (i.e., status characteristics theory), (b) employee perceptions of psychological safety and (c) work group participation in a virtual context to explore potential antecedents of engaging in chat during virtual meetings. Results suggest women and those high in job level participate in the meeting chat more frequently than their counterparts. We find perceptions of psychological safety moderate the relationship between job level and chat participation. Employees low in job level who have high perceptions of psychological safety participate in chat more frequently compared to their counterparts who report low perceptions of psychological safety. Results contribute to our understanding of written communication in virtual meetings, unpacking the individual differences in chat participation in a technology-mediated space. Further, our findings enhance our understanding of psychological safety; and how creating a psychologically safe environment can influence one’s method of participation in virtual meetings.
Total knee arthroplasty (TKA) is a prevalent solution for severe knee osteoarthritis, yet the comparative efficacy between posterior stabilized (PS) and bi-cruciate stabilized (BCS) implants remains undefined, as does performance variance in daily activities. In this study, sixty individuals (20 per group in PS-TKA, BCS-TKA, and controls) were recruited and evaluated at pre-op and six-month post-op. Human motion analysis was performed during five daily activities, such as level walking. Knee joint biomechanics, muscle activities, and a newly formulated Knee Biomechanics Index (KBI), along with clinical assessment, were compared among three groups.
Patients exhibited significant functional improvement at post-op, more pronounced in level walking, with stair climbing remaining problematic. Both TKA groups demonstrated comparable performance enhancements and pain relief, albeit with nuanced distinctions in joint range of motion during stair ambulation. Notably, unilateral TKA patients still experienced bilateral discrepancies at six-month post-op, evident in strenuous tasks due to enduring imbalances in knee forces and muscle activities. There were noticeable differences in performance and persistent bilateral differences at post-op between TKA groups. These insights are critical for surgeons in tailoring implant choices and for therapists in optimizing rehabilitation strategies, ensuring focused recovery plans that cater to individual patient needs and activity-specific demands.
Sexually transmitted infections (STIs) affect an estimated 347 million people worldwide. These diseases can potentially incur significant long-term negative health outcomes, including lifetime treatment regimens, cancer, or infertility. Outcome severity, clinical manifestations, and acquisition rates show a sexually dimorphic variability, with women experiencing a higher disease burden than men. While the exact mechanism for this disparity is unknown, it is likely due to a combination of biological and social influences disproportionately affecting the sexes. This study investigates some of these gendered variables, particularly those involving birth control and sexual healthcare, and their relationship with STI acquisition. Data analysis using the National Health and Nutritional Examination Survey, and a cross-sectional sexual health survey disseminated to college women concluded that women in the United States follow the classic gendered trend with higher rates of STIs. Our cross-sectional sexual health survey included information from 522 sexually active women. We found significant associations regarding a positive self-reported STI history with sexual partner number and inconsistent screening frequency. We also found associations between women who do use some form of hormonal contraceptive with condom use, STI screening frequency, and age. Free-response questions also gave us qualitative insight regarding comfort with sexual health physicians, feelings regarding positive STI diagnosis, and physician’s approach toward their positive STI history. This study addressed several variables associated with women's sexual health care and outcomes and was able to identify several risk factors that may influence the gendered disparity we see in STI prevalence.
This dissertation proposal examines the relationship between corporate growth/expansions and entrepreneurial start-up activity and failures, the number of jobs created, and wages paid by the corporate relocation. Using data sourced from the North Carolina Secretary of State, Census Bureau, and Job Development Investment Grant, I set out to evaluate changes in entrepreneurial startup activity and failures, tax incentive payouts, and salaries arising from large (greater than 251 employees) corporate expansions located in the state of North Carolina. The analysis suggests that expansions of existing corporations directly affect entrepreneurial start-up activity and failures. We conclude by highlighting the study's theoretical contributions to help further the conversation and direct startup and failure business strategies for small businesses.
Wastewater-based epidemiology (WBE) has drawn significant attention as an early warning tool to detect and predict the trajectory of COVID-19 cases in a community, in conjunction with public health data. This means of monitoring for outbreaks has been used at municipal wastewater treatment centers to analyze COVID-19 trends in entire communities, as well as by universities and other community living environments to monitor COVID-19 spread in buildings. Precise and accurate quantification of viral copies in wastewater is a prerequisite for a successful WBE surveillance project. Accurate quantification of SARS-CoV-2 is dependent on the choice of an effective and reliable virus concentration method. Sample concentration is crucial, especially when viral abundance in raw wastewater is below the threshold of detection by RT-qPCR analysis. The first objective of my dissertation is the performance evaluation of a rapid ultrafiltration-based virus concentration method using InnovaPrep Concentrating Pipette (CP) Select and how it compares with the electronegative membrane filtration (HA) method. The criteria of the evaluation were based on the SARS-CoV-2 detection sensitivity, surrogate virus recovery rate, and sample processing time. Results suggested that the CP Select concentrator was more efficient at concentrating SARS-CoV-2 from wastewater compared to the HA method. About 25% of samples that tested SARS-CoV-2 negative when concentrated with the HA method produced a positive signal with the CP Select protocol. The optimization of the CP Select protocol by adding AVL lysis buffer and sonication increased Bovine Coronavirus (BCoV) recovery by 19%, which seems to compensate for viral loss during centrifugation. Filtration time decreased by approximately 30% when using the CP Select protocol, making this an optimal choice for building surveillance applications where quick turnaround time is necessary.
The inherent limitation of most of the current virus concentration methods is capable of processing small volumes of wastewater ranging from 20 – 250 mL. While small volume-based virus concentration methods can be successful for detecting and quantifying SARS-CoV-2 viruses during high community infection, these methods may not be informative, especially during the early stage of community infections. The second objective is to develop a large-volume filtration-based virus concentration method for increased sensitivity of molecular detection of SARS-CoV-2 and application in sequencing techniques. A dead-end hollow fiber ultrafilter (UF) and electronegative membrane filtration (HA) were used as primary and secondary concentration methods for concentrating viruses from wastewater. This study found that a modified UF-HA method, incorporating sonication and centrifugation, showed 100% SARS-CoV-2 positive detection in low COVID-19 infection periods compared to only 9% positive detection with the HA method and 63% with the UF alone. During the high COVID-19 infection period, no significant difference in SARS-CoV-2 detection and quantification was observed among the alternatives. The hollow UF-based primary method showed higher BCoV recovery compared to the combined method and HA method. The combined method (UF-HA_soni) can be used to identify the early stages of COVID-19 infection by detecting SARS-CoV-2 viruses from the low-tittered wastewater which can help prevent future outbreaks. Either the combined method or the UF-based primary method can be used to monitor SARS-CoV-2 viruses during the high COVID-19 infection period.
We also aim to apply digital droplet PCR to track the transmission dynamics of the Omicron variants by assessing the relative proportion of the strains circulating in Charlotte, North Carolina. We applied Digital Droplet Polymerase Chain Reaction (ddPCR) technology to detect and quantify Omicron variants using three different mutation assays targeting the S gene (N764K and N856K). Using these two assays, we first detected the Omicron variants on December 6, 2021, from the wastewater sample of Mecklenburg County which was earlier than the first clinical detection on December 10, 2021. The relative abundance of Omicron VOCs determined by the RT-ddPCR from wastewater was strongly and positively correlated with the clinically reported VOCs (r = 0.98, p = < 0.0001). This surveillance method for the variant analysis can give a near real-time transmission dynamic of the Omicron variants enabling quick administrative intervention such as awareness, preparedness, and control measures.
Additive manufacturing (AM), particularly laser powder bed fusion (LPBF), is of great interest to the aerospace community as it can be used to manufacture parts with complex internal and external geometries. This is in contrast to conventional manufacturing methods that limit the complexity of part designs. Of particular interest are the manufacture of parts with cooling channels consisting of complex surface topographies designed to improve thermal performance of the channels. While conventional machining can reduce the roughness of external surfaces, most surface treatment processes cannot be applied to internal channels, especially when the dimensions are a millimeter or submillimeter scale. Additive manufacturing offers an alternative that has the potential to overcome this limitation.
For a successful industrial adoption of AM for parts requiring complex cooling channels, an understanding of the relationship between the as-built surface finish and heat transfer is needed. In LPBF, there are numerous build parameters, such as part orientation during the build, that affect the final part surface topography and hence heat transfer. The classic literature on the impact of surface roughness on heat transfer (Moody's diagram) uses a simplified treatment of surface roughness, while powder bed fusion processes generate complex surfaces with strong anisotropic features, spatter, and surface and subsurface defects, all of which may affect heat transfer and fluid flow.
The primary focus of this work is to study the effects of AM roughness characteristics (build orientations, density of spatter deposits and their sizes, amplitudes/wavelengths, etc.) on heat transfer from the corresponding AM surfaces and pressure drop across cooling channels. Both numerical and experimental investigations are carried out for this purpose. Computational Fluid Dynamics (CFD) models for mini-channels using StarCCM+ (a commercial CFD code) were developed by acquiring the roughness data from real AM surfaces with various roughness parameters. To explore the correlation between sand-grain modeled roughness and AM surface roughness with 90° build orientation, CFD simulations for the entire system model (experimental setup) were employed. Further, CFD modeling of mini-channels with different wavy surfaces helped in determining the suitable dimensions for the mini-channel experimental set-up and the range of Reynolds numbers necessary for carrying out relevant experiments. Based on CFD findings, an exchangeable experimental setup was developed and on the basis of roughness characterizations, the AM parts with three critical orientations (0°, 45°, and 90°) were fabricated and then machined to the required shape and size to fit into the set-up. In addition, an Inconel part with a smooth surface has been machined from a forged Inconel-625 circular bar to serve as the baseline control condition.
Both CFD and experimental results were compared for different Reynolds numbers. The experimental results validated the CFD findings. Significant differences in the Nusselt numbers and pressure drops were observed across the different AM surfaces, with the surface with 90° build orientation performing best in terms of heat transfer. Based on these results, further investigation on the effects of 90° weld tracked surfaces in a circular form was also carried out. For this exploration, two aluminum (Al-6061) channels - one with a smooth surface and the other with internal threads serving as artificial waviness, similar to an AM surface with a 90° build orientation to the fluid flow direction - were conventionally manufactured and both CFD and experimental investigations were carried out for different mass flow rates. Both CFD and experimental results show that the artificial waviness (structured surfaces) has a significant impact on heat transfer and leads to a high cooling efficiency with a Nusselt number approximately 3x larger for various flow conditions compared to the smooth channel. However, the intentional structured surface also leads to larger pressure drops and may require extra pumping power, depending upon the application.
