Dissertation Defense Announcements

Candidate Name: Elnaz Haddadi
Title: Mechanical behavior of the materials
 November 10, 2023  3:30 PM
Location: DUKE-308

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.

Candidate Name: Faria Kamal
Title: Resilient Operation and Optimal Scheduling of Networked Microgrids
 October 30, 2023  12:45 PM
Location: Please contact Faria Kamal for the virtual link at fkamal@uncc.edu or Dr. Chowdhury at bchowdhu@uncc.edu

The rapid proliferation and widespread adoption of microgrids (MG) necessitate the
development of new methodologies to holistically model all the active components
within MGs. It’s crucial to focus on specific islanding requirements, especially when
the primary grid power is unavailable. In order to ensure a high level of reliability
in an interconnected MG network, this dissertation presents an optimal scheduling
model designed to minimize the day-ahead costs of the MGs while taking into account
the existing operational constraints.
This problem is thoughtfully decomposed using Bender’s Decomposition method
into two key operating conditions: grid-connected and resilient operations. The ultimate
goal is to ensure that each MG within the network maintains sufficient online
capacity in the event of an emergency islanding situation, such as during extreme
weather events. These events often come with uncertainties regarding their timing
and duration, necessitating the consideration of multiple potential islanding scenarios
for each event.
The primary objective of this thesis is to establish optimal scheduling that guarantees
the feasibility of islanding for all conceivable scenarios of such events, with
load shedding as a last resort. The optimization model has been put into practice
across different layouts of the modified IEEE 123-bus test system, encompassing various
events over a 24-hour period. In addition to proposing a day-ahead scheduling
approach oriented towards resiliency for multiple MGs, a comprehensive cost analysis
and comparisons among all the test cases are also offered. The results convincingly
demonstrate the utility of the proposed day-ahead scheduling algorithm, particularly
for MG owners looking to foster collaborations with neighboring MGs. Lastly, after
comparing with the traditional Single Stage MILP approach, the proposed method
has proven to be computationally faster for practical usage. It has been shown that
decomposing the problem using the proposed model makes it possible to combat real
life events with thousand scenarios, where the single stage approach may fail.

Candidate Name: Stacy B. Moore
Title: Exploring faculty perceptions of active and collaborative learning in one community college’s behavioral and social science department
 December 01, 2023  1:00 PM
Location: Zoom: https://charlotte-edu.zoom.us/j/95998006511

Behavioral and Social Science (BSS) classes in higher education provide students with understandings of human behaviors, motivations, and actions that are crucial to confronting both social and personal problems. Moreover, most community college degrees require that students take at least one BSS class—anthropology, economics, political science, psychology, and/or sociology. While BSS classes are important—both from a philosophical as well as a degree-requirement standpoint—without effective student engagement, that importance may be lost. Oftentimes, BSS classes are still taught largely through didactic instruction. Yet, active and collaborative learning has proven to be a more effective instructional approach. Moreover, the need for active and collaborative learning may be even more crucial in community college BSS classes due to the unique demographics of these institutions. Building on findings that active and collaborative learning in BSS classes is more effective than didactic instruction, the purpose of this study is to better understand BSS instructors’ knowledge of active and collaborative learning and to identify the factors that foster this instructional approach and those that present hurdles. By determining these factors, recommendations can be made for replicating effective active and collaborative learning in BSS classrooms and/or working to minimize the roadblocks to this instructional approach.

Candidate Name: Janet Sanchez Enriquez
 November 10, 2023  9:00 AM
Location: COED 201

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.

Candidate Name: Kuldeep Mandloi
 November 08, 2023  2:30 PM
Location: Duke Centennial Hall

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

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
 November 13, 2023  9:00 AM
Location: https://charlotte-edu.zoom.us/meeting/register/tJ0kcOmoqTouGNwdZbFST2CxDQJFiM46iuF-

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
 November 02, 2023  10:00 AM
Location: https://zoom.us/j/8594156604?pwd=enFiT2pXZ1crcHFaeGNwTUF1dWE3dz09

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
 November 07, 2023  10:00 AM
Location: https://charlotte-edu.zoom.us/j/98080642229?pwd=QXRhZXBBcTF2YmFrVmpkSlBSMkkvQT09

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
 November 09, 2023  10:00 AM
Location: DUKE 324

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.

The Graduate School and the Graduate Admissions office in the Reese Building, Fifth Floor, is temporarily closed to allow contractors to complete some needed work in the space safely.

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