Dissertation Defense Announcements

Candidate Name: Kuldeep Mandloi
Title: INVESTIGATION OF THERMAL AND FLUID FLOW CHARACTERISTICS OF AM SURFACES WITH DIFFERENT BUILD ORIENTATIONS THROUGH CFD AND EXPERIMENTS
 November 08, 2023  2:30 PM
Location: Duke Centennial Hall
Abstract:

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.



Candidate Name: Gaston Abel Ayon Munguia
Title: The Effect of Natural Space from Parks on The Perception of Wellbeing Among Latinos Of Mecklenburg County, North Carolina
 November 02, 2023  10:00 AM
Location: McEniry Building 441 Geography Department
Abstract:

This dissertation embarks on a comprehensive exploration of the intricate dynamics surrounding access to and appreciation of natural environments within urban parks among the Latine population in Mecklenburg County. The central goal is to explore how Latine communities engage with urban natural spaces, affecting their perceived well-being. Through rigorous research, it investigates how human-environmental interactions in urban green spaces influence perceptions of well-being and their potential to mitigate disparities in access to such spaces and health outcomes. This study contributes significantly to the understanding of the interplay between urban green spaces, cultural perspectives, and well-being within the Latine community, addressing broader issues of environmental equity and health disparities. It enhances the geography literature by examining human-environmental interactions in urban parks within ascending Latine communities in the southern region. By integrating Michel Foucault's power and biopolitics theories and Landscape Theory. The research sheds light on the mechanisms of social control, access, and the cultural dimensions of landscapes. This research has implications for policy development, urban planning, and environmental management, aiming to promote equitable access to urban green spaces such as parks and improve health outcomes for marginalized communities.



Candidate Name: Abdollah Mohammadi
Title: OPTIMAL GROUP PURCHASING DECISIONS UNDER SUPPLY CHAIN CONTRACTS AND COMPETITION
 November 13, 2023  9:00 AM
Location: https://charlotte-edu.zoom.us/meeting/register/tJ0kcOmoqTouGNwdZbFST2CxDQJFiM46iuF-
Abstract:

Group purchasing (GP) is a procurement strategy by which the retailers can negotiate better prices by increasing their negotiation power through collaboration with each other. GP problem can be modeled as a generalized newsvendor problem, although it is more realistic to model this problem with stochastic demand, current literature on GP is mostly focused on problems with deterministic demand. Comparing the single retailer newsvendor vs. a newsvendor problem with multiple retailers, there has been more attention paid to the newsvendor problem with single retailer. When there are multiple retailers, competition would be another important aspect to consider, which is lacking in parts of the literature and will be considered in this research. Different contracting scenarios such as revenue-sharing and buyback contracts are other aspects which can be considered in the GP problem which has not been studied so far. Given that; four research questions are defined to investigate in this study: 1) the first question investigates the newsvendor problem with quantity discount pricing from supplier by exploring an analytical approach to solve this problem building on existing solutions from the literature; next a second novel solution approach is proposed which solves the problem in fewer steps; answering this question makes the foundation for our subsequent research questions. 2) the second research question studies the GP problem with multiple symmetric retailers; this research question is an extension of the first research question which investigates the GP supply chain consisting of multiple symmetric retailers. 3) third research question explores the solution to GP with multiple asymmetric retailers and suppliers; since this problem is complex to solve, the GP problem is divided into two sub-problems, retailers’ problem, and suppliers’ problem which are solved separately and then brought together to provide an answer to the overall GP problem, and 4) finally, fourth research question introduces different supply chain contracts to the GP problem and investigates studying the effect of these contracts on the retailers’ profit. Mathematical results as well as managerial insights are provided for each model through sensitivity analysis and numerical experiments.



Candidate Name: Torie Wheatley
Title: #RATCHETQUEERTEACHER: SOCIAL, EMOTIONAL WELL-BEING AND LIBERATION THROUGH MINDFULNESS AND HIP HOP THERAPY
 November 02, 2023  10:00 AM
Location: https://zoom.us/j/8594156604?pwd=enFiT2pXZ1crcHFaeGNwTUF1dWE3dz09
Abstract:

There is a growing mental health concern among Black Ratchet queer womxn in educational and criminal justice realms and the Covid-19 pandemic has left the educational climate in a state of high stress and anxiety. Consequently, Black Womxn in education are quitting from burnout. According to research, teacher burnout has been a concern for more
than 30 years, but currently there is a crisis. According to research “This is a five-alarm crisis. We are facing an exodus as more than half of our nation’s teachers and other school staff are now indicating they will be leaving education sooner than planned.: (Jotkoff, 2022).
Covid-19 has caused an increase in depression, anxiety, suicide ideation, and other health concerns in this population. External hindrances including racism, sexism, homophobia, and other ideologies rooted in America; negatively influence their mental well-being. Black queer womxn and girls are restricted from obtaining proper access to mental health services that take into consideration how identities are critical factors in mental well-being. This analysis will provide a rationale for utilizing culturally relevant mindfulness practices for Black queer womxn in educational sectors.



Candidate Name: Seethalakshmi Gopalakrishnan
Title: BUILDING COMPUTATIONAL REPRESENTATIONS OF MEDICAL TEXTS USING LARGE LANGUAGE MODELS
 November 07, 2023  10:00 AM
Location: https://charlotte-edu.zoom.us/j/98080642229?pwd=QXRhZXBBcTF2YmFrVmpkSlBSMkkvQT09
Abstract:

This dissertation explores the potential of natural language models, including large language models, to extract causal relations from medical texts, specifically from Clinical Practice Guidelines. The outcomes of causality extraction from Clinical Practice Guidelines on gestational diabetes are presented, marking a first in the field. We also release, the first of its kind, an annotated corpus of causal statements in the Clinical Practice Guidelines.
We address the challenge of classifying causal sentences with a small amount of annotated data at the inter-sentence level by treating it as a cross-domain transfer learning problem. Obtaining these classified sentences is the first step in extracting causality. Furthermore, we delve into the importance of modal verbs and the degree of influence from cause to effect. We show the capability of three models (BERT, DistilBERT, and BioBERT) to identify the degree of influence in the text.
Lastly, we tackle the challenge of sparse annotated data for the causality extraction from Clinical Practice Guidelines by, again, using transfer learning. We investigate the correlation between data similarity and the efficacy of transfer learning. We also investigate a zero-shot and few-shot approach to cross-domain transfer learning and quantify the link between data similarity and success rates. With the cross-domain few-shot transfer learning, we achieve an F1-score of 81%, which suggests transfer learning as a possible solution to address the limited availability of annotated data.



Candidate Name: Fangjian Chen
Title: KNEE BIOMECHANICS AND ELECTROMYOGRAPHY ANALYSIS FOR PATIENTS WITH TOTAL KNEE ARTHROPLASTY PATIENTS DURING DAILY ACTIVITIES
 November 09, 2023  10:00 AM
Location: DUKE 324
Abstract:

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.



Candidate Name: Melissa Hall
Title: Reexamining Intra Team Conflict: A Dyadic Perspective
 November 08, 2023  8:00 AM
Location: https://charlotte-edu.zoom.us/j/93463095351?pwd=RUk3d01PS0lLZ054andDaXpVN2ZhZz09
Abstract:

ABSTRACT

Reexamining Intra Team Conflict: A Dyadic Perspective

Conflict is seen as an emergent process when looking at the construct of the team as a whole. Researchers have investigated the interpersonal dynamics that contribute to intrateam conflict. According to researchers, intrateam conflict may be the result of conflict that arises from interactions between members of the team on a dyadic level. The dyadic perspective works under the assumption that conflicts can arise between individual members of a team. Researchers have focused on the perspective of the team rather than the dyadic perspective. In fact, many previous studies have concentrated on conflict and the causes of conflict within the team. However, more recently, there have been studies that lend support to the idea that dyadic conflict is one of the primary sources of conflict within teams. There is a possibility that various members of the same team will experience varying degrees of conflict with the other members of the team. It is possible that members of the team will perceive an increase in the amount of conflict between one another. This research contributed to the perception of generalized and dyadic reciprocity among the members of the team. The Social Relations Model (SRM) round robin design will be utilized in the execution of this study, which will take place in a real-world environment. This study will address the dyadic relationship between team members by using this design. It will rate the team members individually as well as the team as a whole, and it will report on each individual team member. In addition, the survey will include information on demographics, questions to assess dyadic task and relationship conflict, as well as questions regarding Jehn and Mannix's research on team level conflict. The results will be analyzed using the TripleR package in R statistical analysis software.

Keywords: Dyadic conflict, Conflict, Team level construct, Social Relations Model



Candidate Name: Md Ariful Islam Juel
Title: Development and Optimization of Virus Concentration and Detection Methods for tracking SARS-CoV-2 and its Variants in wastewater
 November 08, 2023  2:30 PM
Location: EPIC 3344
Abstract:

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.



Candidate Name: Kenya Louise Smith
Title: Understanding the impact of corporate expansions, job creation, and wages paid by the firm on small business creation and failure in the United States: A county-level analysis
 November 08, 2023  4:00 PM
Location: Please contact Dr. Webb for Zoom link at jwebb62@uncc.edu
Abstract:

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.



Candidate Name: Veronica Westendorff
Title: URBAN HEAT ISLANDS AND COOLING STRATEGIES: A COMPREHENSIVE ASSESSMENT OF CHARLOTTE, NC AND NATIONAL COMPARISONS
 November 01, 2023  9:30 AM
Location: EPIC conference room 3224
Abstract:

The increasing threats posed by climate change and urbanization have elevated the importance of addressing Urban Heat Island (UHI) phenomenon, a critical concern impacting cities across the United States. This dissertation comprises three articles that collectively investigate the effectiveness of trees and greenspaces in managing UHI, creating a Heat Health Score (HHS) to identify areas experiencing UHI effects and investigate the perceived effectiveness of policies and programs aimed at reducing UHI in cities, while providing recommendations for Charlotte, NC in particular. Article 1 shows that urban greenspaces consisting of trees can help reduce the UHI effect by creating shade and cooling spaces, potentially reducing energy costs, improving human living conditions, providing food and habitat to wildlife, and improving aesthetics and land values. In Article 2, measures to mitigate the effect of UHI are evaluated from select cities and a ratio of daily average high temperature between locations and the corresponding difference in land cover of tree and shrub areas, create the Heat Health Score (HHS) (a unique metric) which allows municipalities and community groups to gauge the heat health between locations. These results show that most urban locations remain hotter and with lower vegetative cover than their suburban or rural counterparts, however, changes in tree and shrub cover can impact these results in a positive way. Results from Article 3 elucidate the perceived successes and challenges of current policies through a qualitative survey. These responses offer practical recommendations for policymakers across the US but for Charlotte, NC in particular.
These results draw from the real-world experiences and lessons uncovered in the three articles, in aggregate, these provide a valuable resource for city leaders and policymakers striving to create a more sustainable and climate-resilient city. It stresses the importance of urban greenspaces and urban trees in particular, provides community leadership with an easily accessible, not previously defined tool to discern urban heat health through the use of free, open-source data to score heat health, and provides insight into the perceived effectiveness of policies and programs used to mitigate UHI in cities in the United States.




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