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Wind-Induced Gravel Blow-Off: Experimental Investigations and Predictive Modeling for Resilient Roof Design
Get PDFRoof gravel blow-off during severe windstorms is a major hazard, leading to roof damage and significant downwind impacts. Understanding the initiation mechanisms for gravel blow-off is critical for improving building design and mitigating windborne debris risks. Existing experimental data on the wind speed required to initiate gravel blow-off have been collected from high-speed, full-scale tests at wind tunnels. While these tests form the basis of current design guidelines, they are expensive and can lack generalizability. As a result, rooftop gravel is frequently blown off at wind speeds below the design thresholds. This dissertation investigates the onset of rooftop gravel motion, integrating full-scale wind tunnel data with advanced predictive modeling to provide a comprehensive framework for assessing blow-off initiation criteria.
The experimental program consisted of three phases. In the first phase, pressure and shear stress measurements were conducted on the surface of a smooth, impermeable roof of a mid- to low-rise square-plan building. These tests were performed at the FIU Wall of Wind Experimental Facility (WOW-EF) using Irwin probes. Measurements were taken for seven parapet heights and nine wind angles. The collected pressure data aligned well with previously published data for similar building geometries, confirming the reliability of the Irwin probes, even in highly separated flow conditions. Classic V-shaped patterns were observed in both the pressure and shear stress data for cornering flows.
The second phase extended these measurements to a gravel-covered roof, revealing that both pressure and shear stress magnitudes were consistently lower on the gravel-covered roof compared to the smooth roof. Notably, the highest mean shear stress values occurred in the zero-parapet condition and decreased steadily with increasing parapet height. This trend aligns with the observed blow-off wind speeds, which were lowest for zero parapet height and increased as the parapet height increased.
In the third phase, destructive blow-off tests were conducted to determine the wind speeds required to initiate continuous gravel scour. During these tests, the roof was covered with gravel, and wind speeds were incrementally increased until sustained blow-off was observed. Although the tests were conducted for a limited range of cases, analysis of the data identified a critical non-dimensional shear stress value that governed blow-off initiation across various parapet heights and wind angles. This critical value enables the prediction of gravel blow-off wind speeds using surface shear stress coefficients and gravel properties, eliminating the need for costly and time-intensive destructive testing.
To further advance predictive capabilities, a convolutional neural network (CNN) model was developed to estimate gravel roof shear stress distributions from smooth roof pressure data. Validated using small-scale blow-off tests at the Clemson University Boundary Layer Wind Tunnel (CUBLWT), the model demonstrated strong predictive capabilities, providing a scalable and cost-effective tool for engineering applications.
This integration of empirical and computational approaches has the potential to transform predictive modeling for wind-driven debris phenomena, paving the way for safer and more cost-effective design practices
Grid Forming Inverters for Microgrid Operation Enhancement
Get PDFModern electric power systems are confronted with several major challenges including the increasing frequency and severity of weather events, aging infrastructure, high material costs, cyber-attacks, and substantial delays in global supply chains. Microgrids provide a solution to these challenges by insulating customers from the power outages occurring in their local distribution system. A microgrid is a small independent power system with its own power generation and energy storage resources that can supply customers’ electricity needs. When an outage occurs, a circuit breaker will disconnect the microgrid from the distribution system. Successful operation of the microgrid requires one or more devices to provide a continuous stable voltage, which would normally be provided by the distribution system; these are known as grid-forming devices. This dissertation describes how direct current to alternating current inverters can be used as these grid-forming devices in microgrids. Investigation of several use cases demonstrated the unique characteristics of inverters that improve the operation of microgrids as compared to more conventional grid forming devices (e.g., back-up diesel generators). In spite of these benefits, inverters are more vulnerable to damage from temporary overcurrent and overload conditions, degrading the resilience of microgrids that rely upon inverters to be the grid-forming devices. This dissertation presents a solution that allows inverters to act as grid-forming devices while preventing temporary overcurrents and overloads. This solution enables the benefits of grid-forming inverters to be realized without compromising microgrid resilience
Advancing Efficiency of Unstructured Mesh Processing With Localized Data Structures
Get PDFUnstructured meshes are widely used to represent complex shapes and data in visualization tasks, such as medical imaging, engineering design, and geometric modeling. However, their unevenly distributed elements make them memory-intensive and time-consuming to process, especially as mesh sizes grow. This research focuses on improving the efficiency of processing large unstructured meshes by reducing memory usage and speeding up computations. This doctoral dissertation introduces three methods to address these challenges. The first approach divides the mesh into smaller partitions and processes it piece-by-piece, reducing memory requirements by up to 10 times. The second approach uses the processor\u27s parallel computing capabilities to accelerate the processing speed, achieving up to 3 times faster performance while keeping low memory usage. The third approach combines the power of both the processor and the graphics card to further improve performance by offloading some computational tasks to the graphics card, resulting in nearly 3 times faster than previous methods. Together, these advancements make it easier and faster to work with large unstructured datasets in fields like medicine, engineering, geography, and material science. By improving the efficiency of unstructured mesh processing, this research enables scientists and engineers to analyze data more effectively, leading to better insights and discoveries
Robust and Efficient Solvers for Physics-Based PDE’s
Get PDFThis work was partially supported by the U.S. Department of Energy under award DE- SC0025292, by NSF grant DMS 2152623, and by NSF grant DMS 2011490.
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Mathematical Multifaceted Integrated Capability Centers (MMICCs) program, under Field Work Proposal 22-025291 (Multifaceted Math- ematics for Predictive Digital Twins (M2dt)), Field Work Proposal 23-020467, and Computing and Information Sciences (CIS) investment area in the Laboratory Directed Research and Development program at Sandia National Laboratories. This written work is authored by an employee of NTESS. The employee, not NTESS, owns the right, title and interest in and to the written work and is responsible for its contents. Any subjective views or opinions that might be expressed in the written work do not necessarily represent the views of the U.S. Government.
The publisher acknowledges that the U.S. Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this written work or allow others to do so, for U.S. Government purposes. The DOE will provide public access to results of federally sponsored research in accordance with the DOE Public Access Plan
Rhetorics of Vigilance: Refracting Discourses in Technologies of Self-Managed Health & Wellness
Get PDFRhetorics of Vigilance explores the limits of feminist health rhetorics by examining technologies that promote women’s self-managed health and wellness practices. By establishing a corpus of personal health technologies and associated texts including mobile health applications, pelvic floor training devices, and perimenopause information shared on social media, this dissertation analyzes how discourses refract––redirected and often distorted––to implicate women in persistent self-monitoring. Drawing from interdisciplinary scholarship on women’s health from feminist rhetorical studies, rhetorics of health and medicine, science and technology studies, and digital studies, I theorize rhetorics of vigilance as a framework through which women understand and interpret issues of health and wellness and conceive of action to address those issues. This framework explains why mechanisms of control and discipline in women’s health endure despite medical advances and shifting social attitudes, and it uncovers how these mechanisms function rhetorically in everyday health practices. In the case of self-managed health technologies, rhetorics of vigilance divert messages of self-efficacy and empowerment to reinscribe health and wellness as a relentless process of attentive care. By revealing these patterns, this dissertation both critiques the demands of self-managed health and calls for alternative feminist health frameworks that prioritize collective care, embodied knowledge, and systemic change over individualized responsibility and constant self-surveillance
Integrating Applied History and Artificial Intelligence (AI) Into City Planning Practice
Get PDFHistory matters. History provides a vital foundation for shaping present decisions and future planning. By understanding a city’s past, cities can make more thoughtful, informed choices to guide development and policy with greater intention and impact.
Greenville, South Carolina, is a unique city planning case study and learning laboratory. Greenville’s Downtown revitalization since the 1980s demonstrates how historical insights can be integrated into contemporary policymaking to create vibrant, human-centered, and citizen-focused urban environments. Greenville’s evolution from a deserted, forgotten Main Street to one of the world’s most livable cities is an example of community development worthy of emulation from other cities.
This study redefines planning practice by integrating history with advanced technologies, particularly Artificial Intelligence (AI) and Natural Language Processing (NLP). Using a three-journal article dissertation format, this study explores the applied history approach in city planning, emphasizing the importance of local historical knowledge and AI tools to enhance accessibility and decision-making; It uses AI applications to analyze historical and contemporary planning documents, demonstrating NLP\u27s potential to uncover trends, streamline complex analyses, and create tools that make the past accessible. Finally, it explains the visual evolution of urban planning thought through professional planning journal cover analysis, revealing shifts in focus from abstract U.S.-centric perspectives to globally grounded representations.
Using Greenville as a planning case study, the research highlights how integrating historical insights with AI-driven frameworks enables more connected city planning and offers actionable recommendations to advance urban planning practice
The Spectral Asymptotics of Toeplitz Operators on Hilbert Spaces of Analytic Functions
Get PDFMany physical systems, whether they are ocean waves or particles moving through space, can be described using the mathematical language of “partial differ- ential equations.” In many circumstances, it is useful to study how these equations amplify an input to the equation, in which case the amplification factor is called an “eigenvalue.” The usefulness of these amplification factors is that they can be used to describe properties of the physical system. In this dissertation, I have studied this amplification factor for a related set of equations called “Toeplitz operators.” In par- ticular, I have studied eigenvalues using statistical techniques. The methods I have used to develop these results are novel and improve on existing methods
An Investigation of Genetics in Ovulatory Dysfunction Related Infertility
No full textThe purpose of this dissertation research was to identify biomarkers associated with ovulatory dysfunction-related infertility and to assess if the disruption of known functions of these biomarkers are reflected in the outcomes of patients undergoing infertility treatment due to ovulatory dysfunction. Three separate research projects were performed to investigate the dissertation research aim, each with different study designs: a comparative analysis derived from real-world clinical data, a scoping review, and a genome-wide association study with a case-control study design. Genetic testing is not routinely used in the diagnostic setting of infertility at this time; thus, these research efforts were curated to increase genetic knowledge of patients with ovulatory dysfunction-related infertility with the intention of aiding in the development of diagnostic technology. This dissertation research successfully delivered several tools for advancements in this area, including a comprehensive list of ovulatory dysfunction-related infertility genes and four novel SNPs associated with anovulatory infertility
Am I Woke Enough to Serve in Healthcare: A Secondary Analysis of Pre-health Students’ Personal and Professional Growth by Engaging in Cultural Competency Assessments
Get PDFHealthcare providers must be equipped to serve an increasingly diverse population, yet cultural competence remains underemphasized in undergraduate pre-health education. This study explored how embedded cultural competency training influences undergraduate pre-health students’ perceptions of personal and professional growth. Using a qualitative descriptive design, the research incorporated intercultural assessments, the Intercultural Development Inventory (IDI), and the Global Competence Certificate (GCC), along with qualitative reflections from students enrolled in three versions of a cultural competence course: a year-long course, a semester-long course, and a short-term study abroad immersion six-week course. Findings revealed that students demonstrated measurable growth in cultural awareness, knowledge, communication, and empathy. Extended exposure to intercultural content and reflection was especially influential in fostering development and awareness. Students described cultural competence not only as a clinical tool, but as an ethical responsibility linked to global citizenship and healthcare equity. The results support the integration of intentional, longitudinal cultural competence education into undergraduate health curricula as foundational preparation for equitable, patient-centered care
Determinants of Resilenece: How Black Students in Greenville, South Carolina Navigated the School Desegregation Process
No full textThis replication study explores the oral histories of Black community members in Greenville County, focusing on the cultural capital Black students utilized to navigate school desegregation in Greenville, SC. Using oral history methodology, the research addresses the fol-lowing questions: What forms of capital existed in the segregated Black communities of Green-ville County? How did these forms of cultural capital support Black students during the school desegregation process? The study also incorporates literature on Black history, Black education, critical epistemologies, and community cultural wealth to challenge the notion that Black stu-dents enter educational institutions with a cultural deficit. By applying community cultural wealth as a theoretical framework, the study aims to ameliorate the traditional historical narra-tive of Black education and demonstrate that solutions to many of the educational challenges facing Black students can be found within oral histories in Black communities. The findings from this study reveal that Greenville’s Black students had access to di-verse forms of cultural capital as they navigated desegregation. Furthermore, these students were influenced by the high expectations set by Black teachers and community members, the strong guidance from their segregated Black teachers, and the unintended consequences of Jim Crow segregation. The dissertation concludes that the narrators possessed significant forms of cultural capital when they entered educational institutions. The implications of these findings are also discussed