SHAREOK Repository
Not a member yet
49261 research outputs found
Sort by
3D printed object topography analysis and the viability for forensic examination
Get PDFWith the recent surge of advanced commercially available 3D printing technologies, individuals have the ability to create virtually untraceable firearm components from the comfort of their home. As these untraceable firearms are becoming more popular, there is a need to determine viable methods of source identification of these 3D printed objects. Both the printer hot end nozzle and print bed surfaces leave distinct characteristics that are observable upon the surfaces of the 3D printed objects. It is hypothesized that the thermoplasticity of the polymers used for printing inherits the characteristics present on the print bed surface and microscopic characteristics of the hot end nozzles used to print the objects. There have been few studies on the topic of the forensic analysis of 3D printer related evidence, and fewer that use advanced algorithms to objectively determine the similarity of 3D printed evidence. The goal of this research was to determine whether toolmarks found on 3D printed objects are distinct enough to identify or exclude a 3D printed object as originating from a specific source. To test this, 150 printed objects were created with ten different print beds and ten different nozzles, with 15 prints for each bed-nozzle pair. 3D scans of the top and bottom surfaces of each object were made using the Cadre Forensics TopMatch-GS system. Cadre’s pattern-matching algorithms were then applied to the 3D scans, which gave each comparison a score between 0 and 1.0 depending on how similar the surfaces are. All bottom and top layer scans were intercompared, resulting in a total of 11,175 comparisons for each top and bottom surface. The data was analyzed using receiver operating characteristic (ROC) curves and area under curve (AUC) scores. AUC scores demonstrated that the algorithm was able to consistently and correctly differentiate between same and different source printed objects. This study demonstrates that source identification of 3D printed objects using toolmarks may be viable for forensic examination
Numerical modeling studies of deep convection: 1-km ensemble forecasting, secondary ice production, and aerosol-cloud interactions
Get PDFThis dissertation presents numerical modeling studies of deep convection triggered by sea breezes, which remains a challenge for operational numerical weather prediction (NWP) models due to the fine scale of sea breeze circulation, uncertainties in large-scale forcings, model uncertainties innate to physics parameterizations, and varying aerosol conditions. This research is organized into three parts. Part I describes a 24-hour, 1-km, 48-member convection-allowing ensemble (CAE) produced with the Weather Research and Forecasting (WRF) Model during the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field campaign near Houston, Texas, in June 2022. This CAE incorporates three initial/boundary conditions (ICs/BCs), four microphysics schemes, two planetary boundary layer (PBL) schemes, and two aerosol loadings. Ensemble precipitation forecasts are evaluated against observations for eight SBC cases. It is shown that ensemble diversity, especially through varied ICs/BCs, improves forecasts of light-to-moderate precipitation, though rare and extreme rainfall remains difficult to capture. An optimal single-physics configuration (Thompson microphysics with the Mellor–Yamada–Nakanishi–Niino PBL) achieves ensemble skill scores but retains precipitation biases, emphasizing the need for continued model physics parameterization development. Part II expands the Thompson microphysics scheme to include three secondary ice production (SIP) mechanisms, which exert strong influences on convection and precipitation but have remain underrepresented in NWP models for decades. The three SIP mechanisms are: Hallett-Mossop (HM), ice–ice collisional breakup (IICOL), and fragmentation of freezing raindrops (FFD). Idealized simulations of a continental supercell and a tropical mesoscale convective system are performed to investigate the impacts of SIP on precipitation in deep convection. Results show that SIP systematically reduces precipitation by redistributing condensate from liquid to ice and from low to high levels, primarily suppressing the warm-rain pathway. Detailed analyses of SIP impacts on cloud microphysics, thermodynamics, dynamics, and convection intensity, as well as interactions among different SIP mechanisms, are also presented. Part III investigates the combined effects of SIP and aerosols on deep convection and precipitation using the SIP-included, aerosol-aware Thompson scheme in the WRF Model and a cloud tracking technique. An SBC case observed during ESCAPE is reproduced. Results show divergent, and even opposite outcomes when SIP is included, compared to previous studies. Overall, the findings highlight the dual importance of SIP and aerosols in shaping convective cloud microphysics, thermodynamics, and precipitation, underscoring the need to incorporate SIP and realistic aerosol treatments in NWP models to improve precipitation forecasts
Make-It-Yours: Black Male Student-Athletes Recount Their Division II Experiences
Get PDFBlack male student-athletes (BMSAs) at Historically White Institutions (HWIs) navigate theintersections of race, athletics, and higher education. While most research focuses on NCAA Division I, little examines their experiences at the Division II level. This qualitative study fills that gap by exploring how Division II BMSAs navigate academic, athletic, and social environments, highlighting the challenges and opportunities that shape their journeys. Grounded in Critical Race Theory (CRT) and Critical Race Methodology (CRM), this study amplifies BMSAs' voices to expose systemic inequities in collegiate athletics and higher education. Through semi-structured interviews with six participants, the findings are organized into four key themes: Rethinking Athletic Success, Division II as a Supportive Family, Sports Don’t Last Forever: Developing a Plan for Success and Navigating Hostile Territory at HWIs. Findings reveal that Division II BMSAs face limited resources, racial microaggressions, and underrepresentation among faculty and coaches. However, they persist through mentorship, peer support, and self-advocacy. Participants emphasized strategic academic and career planning, the supportive nature of Division II athletics, and the enduring impact of systemic racism. This study broadens the understanding of BMSAs' experiences at Division II HWIs, offering insights for policy, institutional practices, and future research to foster more equitable and supportive environments
CONTINUOUS FIBER 3D PRINTING USING UV-CURE EPOXY RESIN
Get PDFIn this thesis, a continuous fiber single epoxy inline impregnation 3D printer head using UV cure epoxy resin is developed and manufactured. Through the design process, the final design of the printer head was achieved, and it was able to print three 3-layer fiberglass laminate composites, as well as two carbon fiber composites. Both printed composite types were compared with a hand-layup composite, serving as a benchmark. Through visual observation with the naked eye, the printed composites showed more consistency than the benchmark composites. This was further proven through microscopic imaging. Comparing the composites under 20x+ magnification showed a significant difference between void sizes in the hand-layup carbon fiber composite sample and the printed carbon fiber composite sample. The printed composite sample had significantly less voids and smaller voids than the hand-layup composite sample. In addition, the printed fiberglass composites showed to have less excess epoxy on the bottom of the composite compared to the fiberglass hand-layup composite. This is visible when looking at it and some of the spot sizes were characterized using the microscope. All in all, this proof-of-concept prototype 3D printer head using UV cure epoxy was researched, completed, and functioned as designed, capable of manufacturing multilayer laminate composite samples
Knights of the Plains, Decor for the Home: Conceptualizing the Cowboy in Tabletop Bronzes and Western Novels of Turn-of-the-Twentieth-Century America
Get PDFThis thesis traces the development of Frederic Remington and Owen Wister’s conceptions of the American cowboy by placing key cultural works in historical context. The first chapter centers on a discussion of Wister’s 1895 article, “The Evolution of the Cow-Puncher,” with illustrations by Remington, notably, The Last Cavalier. This chapter considers how Remington and Wister’s idea of the cowboy in this moment draws on narratives of a knightly past and questions if Remington’s sculpture, The Broncho Buster, created the same year, can also be viewed as a knightly figure. The second chapter examines how Remington and Wister’s depictions of the cowboy changed from 1895 to 1902, through an analysis of two works by created the artist and author in the later year: Wister’s The Virginian and Remington’s Coming Through the Rye. This thesis argues that Remington and Wister worked concurrently to construct the ideal of the cowboy as an integral part of U. S. national identity. At certain points, artists and authors rooted the cowboy in a European cultural past as a version of the medieval knight or chivalrous cavalier. In capitalizing on this relationship, the cowboy becomes positioned as heir to European warriors of the past, a narrative which filled a gap for the young American nation seeking to form its own sense of cultural heritage. The means by which these artists and authors conveyed the idea of the cowboy – through tabletop bronzes and novels – shows how culture cultivated in private informs public culture at large
The mediating role of hope in linking perceived organization support to lower job burnout among child welfare professionals
Get PDFFinancial support was provided by the University of Oklahoma Libraries' Open Access Fund.Job burnout occurs when employees feel exhausted or overwhelmed by workplace demands (Maslach, 2003). Burnout has a negative impact on employees and organizations, contributing to higher turnover and lower service quality (Salvagioni et al., 2017). In child welfare, burnout consistently predicts workforce turnover (Chernesky & Israel, 2008; Kim & Kao, 2014; Leake et al., 2017). Emotional exhaustion is a stable predictor of turnover in this field (Boyas & Wind, 2010; Boyas et al., 2013; Travis et al., 2016). This study examines a three-variable model in which hope mediates burnout, shaped by perceptions of organizational support among child welfare workers.Ye
Seismic Stratigraphy, Geomorphology, and Lithology Prediction of Fluvial and Deepwater Systems, North Malay and Delaware Basins.
Get PDFHigh-frequency seismic sequence stratigraphy and quantitative seismic interpretation are essential for characterizing subsurface reservoirs' architecture and heterogeneity. Although significant advances in the theoretical understanding and research methods of fluvial and deepwater turbidite reservoirs, the inherent complexity of depositional architecture and the variability of reservoir properties continue to pose significant challenges for accurate seismic interpretation. This study addresses these limitations by integrating seismic sequence stratigraphy, seismic geomorphology, seismic inversion, and limited well data, all guided by geological prior knowledge. The aim is to enhance seismic interpretation and lithological prediction in the North Malay and Delaware Basins. The investigation focuses on the falling-stage systems tract (FSST) developed in two contrasting depositional environments, coastal plain and deepwater. First, a high-frequency seismic sequence stratigraphic analysis of the Pleistocene strata in the Northern Malay Basin is conducted, with particular attention paid to the FSST interval. This analysis reveals the internal fill architecture of two distinct types of incised valleys associated with the FSST. Then, seismic geomorphological analysis, using coherence attributes and spectral decomposition, is employed to characterize various mud-filled abandoned channels in fluvial systems spanning multiple FSSTs within the Pliocene–Pleistocene strata. These mud plugs are shown to impact reservoir connectivity significantly. Lastly, in the Delaware Basin, the study applies machine learning techniques and integrated well-seismic Bayesian lithology inversion to predict lithology and assess heterogeneity in mixed siliciclastic–carbonate turbidite reservoirs within the FSST of the Bone Spring Formation. The insights gained from these multi-disciplinary approaches can be broadly applied to improve the quantitative seismic interpretation of analogous reservoir systems
BLOOD AND WATER, SURVIVANCE AND KINSHIP: HOW ANISHINAABE CULTURE IN TRACKS REVEALS THE POWER OF CHOSEN FAMILY
Get PDFBecause family is so immediate to us, it has enormous capability to be the source of struggle in our lives– and when family fails, the consequences can be cataclysmic. Louise Erdrich’s 1988 novel Tracks demonstrates the ways Anishinaabe kinship structures become threatened by settler-colonial violence. I analyze historical 20th-century Anishinaabe values and practices and connect them to character relationships in the novel. I also discuss how Erdrich’s novel can be seen as a response to then-President Reagan’s callback to family values which was modeled on the short-lived but powerfully nostalgic family values of the 1950s. Tracks can be viewed as a forceful intervention full of acceptance, belonging, and sovereignty that stands in stark contrast to the sought-after family values that are rigid, private, and individualistic. I encapsulate these kinds of settler-colonial family structures with the phrase “blood runs thicker than water.” This paper also focuses on how characters use Native practices like story-telling to stay resilient, connected, and tradition-based. Stories preserve memory, reflect on events, and instill wisdom. Stories by the very people who directly experience the impacts of myths perpetuated by colonialism can combat them, tell them, and create their own stories that are more reflective of Native peoples realities. Because they are so integral to culture and because of the colonial violence actively working against Native Americans, having stories and people to share them with is a direct form of survivance and a crucial part of kinship
MInutes of a Regular Meeting, The University of Oklahoma Board of Regents, Monday and Tuesday, September 8-9, 2025
Get PDFField Calibration Development and Comparative Evaluation of Machine Learning and Physics-based Wind Estimation Methods for the Weather-sensing CopterSonde UAS
Get PDFThe precise measurement of wind within the planetary boundary layer (PBL) is essential for enhancing weather forecasts, comprehending atmospheric phenomena, and facilitating various applications,. Traditionally, researchers have depended on radiosondes, tower-mounted instruments, and remote sensing technologies like Doppler lidar to get kinematic and thermodynamic characteristics of the lower atmosphere. While these methodologies yield significant data, they are frequently limited by cost, mobility, or temporal resolution, resulting in limitations in our knowledge of the PBL's intricate and swiftly changing circumstances. Uncrewed Aircraft System (UAS) present a viable option owing to their adaptability, cost-effectiveness, and capacity for precise and targeted in situ measurements. Nevertheless, affixing wind sensors to small drones may result in weight and aerodynamic drawbacks, in addition to being vulnerable to disturbances or flow distortion around the aircraft. The CopterSonde, a drone developed by meteorologists and engineers at the University of Oklahoma, has been designed and optimized for kinematic and thermodynamic measurements of the PBL. Unlike conventional multicopter platforms, the CopterSonde employs a model-based 3D wind estimation technique that relies on mathematical models. This method uses aerodynamic principles to infer wind vectors from the drone’s own response against wind and control inputs. Early phases of the presented study, building on the foundation of previous works, focused on refining parameters of the model-based methods by calibration through the use of Differential Evolution Optimizer (DEO), a cost function optimization technique. Calibration was performed using a combination of Doppler wind lidars, providing a robust reference for validation. These efforts highlighted the DEO method's ability to optimize the CopteSonde's dynamic model, yielding wind estimates with accuracy comparable to Doppler wind lidars. by minimizing the root mean square error (RMSE) between the ground truth and the CopterSonde’s estimations. The integration of a Linear Extended State Observer (LESO) into the model helped to reduce the influence of autopilot-induced perturbations and enhance the overall quality of the wind estimates. Extending upon this previous research, the presented work introduces advanced machine learning (ML) approaches to avoid reliance on complex mathematical models, offering a platform-agnostic and data-driven characterization of UAS for wind estimation. A selection process to determine an adequate machine learning method was described and implemented. After evaluating several candidate techniques based on predictive accuracy and computational efficiency, machine learning techniques were employed to analyze and learn patterns and relationships in an extensive pre-collected dataset that model-based methods fail to capture. ML methods may offer a better way to distinguish wind perturbations from coupled UAS dynamics. The resulting ML models not only refined the CopterSonde’s 3D wind estimation capabilities but also provided a new perspective on how to integrate data-driven methods with mathematical models. The combined efforts in this study present a comprehensive evaluation of various wind estimation techniques, from initial drag coefficient refinement using DE to advanced ML implementations. This holistic approach not only highlights the progress made in enhancing wind-sensing accuracy but also provides valuable insights and guidelines for future applications to avoid reliance on complex mathematical models, offering a platform-agnostic and data-driven characterization of UAS for wind estimations. Through a comparison of different methodologies, the work establishes a solid foundation for ongoing research in wind estimation and sets the stage for future advancements in UAS technology