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Modelling, Additive Manufacturing, and Testing of Knitted Materials
No full textKnitting is a centuries-old textile fabrication technique utilizing a method of “interlooping,” where loops are pulled through each other until the final product is created. Certain patterns curl in on themselves, which can allow for unique self-actuating properties. Though this property may be a nuisance for someone creating a textile that is intended to be flat, it can be manipulated by engineers to create self-supporting structures. While this manipulation has been proven with fabric samples, it has not been applied to more rigid materials, such as thermoplastics commonly used in 3D printing. This research will further explore fabricating knit specimens with 3D printing. The geometry of a knit stitch was established, then used to create a 3D model that can be duplicated to form a specimen of a stockinette pattern. This specimen was 3D printed without the need for support material. Several baseline specimens were fabricated using PLA with a consumer-grade 3D printer. Additionally, several specimens with altered parameters were fabricated to further characterize the behavior of an additively manufactured knit specimen. Additional parametric variation was provided by altering boundary conditions to allow or disallow contraction. The printed specimens were then tested in tensile extension or cyclic patterns with a universal testing machine. The results are presented and compared with load-extension graphs. The load-extension graphs of each specimen were compared, and it was noted that specimens exhibited energy dissipation and had anisotropic behavior
Creating Grid-Based Machine Learning Severe Weather Guidance for Watch-to-Warning Lead Times in the Warn-on-Forecast System
Get PDFThe Warn-on-Forecast System (WoFS) is a rapidly updating convection-allowing ensemble focused on providing numerical guidance at watch-to-warning lead times (0-6 hours). Previous studies (e.g., Flora et al. 2021; Clark and Loken 2022) have incorporated machine learning (ML) to take advantage of the unique benefits of the WoFS and produce skillful guidance for severe weather hazards at lead times of 0-3 hours. This study evaluates the use of multiple ML architectures to produce 2-6 hour severe weather guidance using data from the WoFS. This represents the first use of machine learning to produce WoFS-based guidance at these lead times and the first use of deep learning to produce severe weather guidance using WoFS data.
Predictors are created using WoFS forecasts from the 2018-2023 Hazardous Weather Testbed Spring Forecasting Experiments. Data from forecast hours 2 through 6 are processed into predictors of multiple scales, incorporating both storm and environmental fields. We utilize three ML architectures: logistic regression, histogram-based gradient boosting trees, and U-nets. These models are trained to predict severe wind, severe hail, tornadoes, or any-severe hazard during the 2-6 hour window. Target data comes from the NOAA Storm Events database. The four-hour ML guidance is compared to rigorous baselines consisting of optimized Neighborhood Maximum Ensemble Probabilities for each hazard.
All ML methods evaluated outperform the NMEP baselines with tree-based methods achieving the highest performance of the traditional architectures. The largest improvement occurs for severe wind, followed by severe hail, tornado, and any-severe. Feature ablation shows that skill primarily comes from the intrastorm predictors and that the inclusion of multi-scale features exhibits little effect on skill. Despite the inclusion of additional features, the U-nets are unable to surpass the skill of the tree-based architectures. Similar to prior studies, this work shows the benefits of using the WoFS and ML to produce skillful guidance during the watch-to-warning period
Insights on Cultural Worldviews and Public Support for Renewable Energy
Get PDFWe explore the relationship between cultural worldviews and support for renewable energy focusing on how individual worldviews of egalitarianism, individualism, hierarchy, and fatalism affect attitudes toward increasing solar and wind energy and decreasing fossil fuel usage. We find that egalitarianism is positively correlated with support for renewable energy and reducing fossil fuel consumption, while individualism is negatively correlated with these policies. Hierarchy emerges as a predictor of opposition
to decreasing fossil fuels usage in the U.S. The cultural theory of risk provides a framework for interpreting these results, suggesting that an individuals' perceptions of the balance between nature and society shape their attitudes toward environmental risks, and therefore climate change mitigation strategies such as energy preference. This research demonstrates the importance of considering cultural worldviews when trying to understand the challenges and opportunities associated with energy
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Tracing Desires, Finding Utopia: Examining 2SLGBTQIA+ Students’ Queer Worldmaking in Higher Education Through Participatory Art-Based Research
Get PDFHigher education holds the potential to positively impact 2SLGBTQIA+ students, yet they often face discrimination and violence. Drawing upon Tuck’s (2009) desire-based approach and Muñoz’s (2009) concept of queer utopia, this study focuses on the lived experiences and desires of 2SLGBTQIA+ students. It aims to explore how they navigate, resist, and reimagine higher education through queer and trans ways of knowing. Utilizing queer methodologies, specifically participatory action research and visual methods, the study investigates how queer and trans students envision thriving within institutions. Findings reveal dynamic and subjective experiences of queer thriving, shaped by their desires and challenges. Despite encountering violence, students engage in worldmaking and freedom dreaming for a queer utopia, both individually and collectively. This study illuminates the gap in research on queer thriving and worldmaking in higher education, calling for further examination of these dynamic processes and the nuanced experiences of 2SLGBTQIA+ students. It underscores the need for ethical leadership and a shift towards a thriving-centered approach in higher education, supporting and challenging queer and trans students in their identity and personal development
How do teachers with different certification statuses describe their ability to deliver Culturally Responsive Instruction? A qualitative inquiry
Get PDFCulturally Responsive Teaching is an approach that attempts to integrate students’ cultural backgrounds and experiences into learning processes. Some education reformers argue that student needs are best met when teachers utilize Culturally Responsive Teaching Practices (CRTP). In recent years, traditional teacher preparation programs have also begun to incorporate CRTP into pre-service teacher coursework, whereas alternative and emergency certified teachers are thought to have less formal training in CRTP. Yet very few empirical studies have investigated how prepared teachers of different certification statuses feel when it comes to delivering CRTP. The purpose of this study is to investigate how teachers with different certification statuses describe their ability to deliver CRTP. The data for this research was collected by drawing on a stratified random sample of teachers with traditional, alternative, and emergency certifications as well as snowball sampling (n=30). The main findings from this study suggest that traditional preparation programs increase a teacher’s ability to deliver CRTP. However, certification pathway was not the only factor that teachers identified. Teachers also described mentorship experiences, school district structures and culture, as well as personal experiences that influence preparedness to deliver CRTP. This study advances existing literature by bringing nuance to the literature on perceived preparation based on different teaching certification statuses. It may also help inform supports that leaders provide to teachers of varying certification statutes
Signal Processing Techniques for Spatial and Frequency-Varying Wave Propagation Through Multi-Layer Stack-Ups
Get PDFRadar is classically used over optical sensors to sense objects regardless of weather or daylight conditions. In this case, a waveform is transmitted through the air and reflects off the outside of an object back to the radar. Radar has since been extended to sense within objects. Common applications are non-destructive evaluation, ground penetrating radar, and remote sensing. In this case, the incident wave is reflected by the contrast of electrical properties between materials. More recently, radar has been leveraged for biomedical applications, such as vital sign sensing and imaging within the body. Biomedical imaging radar (BIR) is a promising non-ionizing method to sense within the body. Some potential features to extract could be tumors, brain bleeds, or foreign objects.
A general assumption in radar operation is that the reflected waveform has the same structure as the transmitted waveform. The wave's velocity of propagation is dependent upon the medium and the frequency. Thus, if the reflected wave has traveled through a medium other than air, the received waveform is more stretched out in time than the transmitted waveform. Applying a traditional matched filter in this case yields a degraded range profile, and the returns do not appear at the correct physical location. If the wave only travels through air and one other non-dispersive medium, the range calculation can be easily adjusted. This scenario is commonly encountered in remote sensing. However, more complex scenes such as the human body, are composed of several media with electrical properties that vary across frequency at different rates. Existing techniques are not able to fully leverage radar's pulse compression gain in this case.
In this research, the challenge of radar wave propagation through multiple media is addressed. First, the wave propagation mechanics are studied to understand how the received waveform is distorted. Then, a matched filter is adapted to compensate for this spatial and frequency-dependent distortion in the frequency-modulated continuous wave (FMCW) radar case. The compensation scheme is demonstrated in simulation, and then an FMCW prototype system is built to apply the velocity correction to measured data. The proposed compensation technique is successfully applied to measure a scene with a metal plate placed immersed in a box of oil at various ranges, and more advanced range profile enhancement is explored. The proposed technique is shown to overcome a crucial challenge faced by a BIR
Analyzing Heat Waves Experienced by Underrepresented Communities Living in Low-Income Neighborhoods of Oklahoma City, Oklahoma
Get PDFAccording to the United States (U.S.) National Weather Service, extreme heat was the most fatal weather phenomena in 2022. As climates change around the U.S. and, more specifically, across the Southern Great Plains, extreme heat events are projected to increase in intensity, duration, and frequency. Past research demonstrates that heat-related mortality has increased throughout the state of Oklahoma in recent years, and that heat-related deaths are disproportionately represented by Black people, senior citizens, males, and single individuals.
To examine the impacts of extreme heat in a low-income and racially diverse community in the northeastern quadrant of Oklahoma City, Oklahoma, this qualitative research study employed focus groups to address two research questions: 1) how do extreme heat conditions influence the lives of people living in Oklahoma City neighborhoods identified by significant social vulnerability?, and 2) what are the best practices for mitigating heat stress that can be implemented in Oklahoma City without harming the natural and social landscape that already exists? The focus groups were composed of four separate groups of people: 1) seniors, 2) youth, 3) mixed-aged adults, and 4) community leaders. Each group was asked the same set of questions, and the resulting discussions were transcribed to form the research dataset. To analyze the collected data, a thematic analysis was performed using three coding stages (open, axial, and selective). Five themes emerged from the data analysis: 1) adaptation, 2) communication/awareness, 3) health, 4) infrastructure, and 5) resources.
In response to the first research question, participants discussed being burdened by the high cost of utility bills and disadvantaged by the lack of amenities, such as pools, splash pads, shade trees, and bus shelters. In response to the second research question, participants listed many ways they employed self-agency to stay cool, such as staying in cooled buildings, using fans, and preventing outdoor heat from penetrating inside their homes using shading equipment. Findings also showed that community members could benefit from local programs that offer financial assistance for cooling expenses and educational materials to inform the public of heat-health coping strategies and available resources
Disparities within K-12 Educational Building Environments: A Framework for Designing Educational Spaces for Health & Wellbeing In and Out of the Classroom
Get PDFIntroduction: Students endure social, economic, and environmental impacts that affect their behavior, mental health, and cognitive development. Evidence-based research and design are required to provide proficient design strategies as students continue their education. These strategies should ensure positive mental health environments. This study obtains multiple perspectives from professionals within varying fields of design and education to address the disparities in and out of the classroom. This will allow designs to be redeveloped to achieve improved student mental well-being in K-12 settings.
Literature Review: The reviewed literature explores the gaps that lie within existing research regarding the disparities of youth in academia, educational buildings connection to socio-economic status, and school design’s impact on student well-being and building performance. The literature gap highlights the need for interdisciplinary research to implement equitable mental health resources through design strategies within school buildings.
Methods: To gain insight on professional perspective from those who design and teach in K-12 buildings a qualitative study was conducted. Total of 18 professionals, including ten experienced designers with experience in K-12 design and eight K-12 educators participated in a 20-minute online questionnaire via Qualtrics Survey Software. The survey consisted of 20 questions, including demographic, Likert-scale, and open-ended questions. This allowed for an inductive thematic analysis to be performed, gathering keywords using NVivo 14 software. A biopsychosocial (BPS) theoretical model was used throughout the study that aids in the interdisciplinary approach that addresses inclusivity and equity. To ensure professionals experiences are represented, an online survey was implemented.
Results: A thematic analysis identified overarching themes that were prevalent in improving mental health within K-12 environments. Key themes included: community, trauma-informed design, inclusive design, student motivation, special needs, and engagement modes. Connections were formed between themes found within existing research and those obtained from the survey in comparison to whether or not participants agreed with specific notions that could affect student mental health.
Conclusion: Design strategies should not be implemented as last minute options; however, should prioritize ideas that provide users the option to choose spaces and design elements that adhere to biological, social, psychological, and environmental needs. This requires all stakeholders to understand that mental health differs for each student along with the various barriers that several students face on a daily basis. Learning environments could incorporate adequate strategies that allow students to feel comfortable and understood. Designers must reinforce the importance of collaboration and ongoing evaluation in implementing design strategies and note each school and student requires different needs and none are exactly the same
Enhanced Assessments of Tornado Locations and Damage Using Geospatial Technologies
Get PDFTornado climatologies represent an important tool for understanding the genesis, behavior, and dissipation of tornados and tornadic storms. The current tornado record is imperfect, but nevertheless useful. I undertook a study to construct a tornado climatology for the state of Alabama in order to test theories about the influence of surface heterogeneities on tornadogenesis as well as human-caused bias. Support was found for the notion that tornados may occur atop higher elevations more frequently in Alabama, but other orographic effects were more difficult to discern. The most strongly correlated variable tested was road proximity, suggesting that accessibility to surveyors has an outsized influence on where tornadogenesis points are recorded. In an effort to explore additional ways of detecting tornadic damage, a second study was undertaken to explore the utility of Sentinel-2 derived disturbance index imagery. The disturbance index was shown to be positively correlated with damage intensity across all land cover types. Actual values of disturbance index for a given damage intensity were highly variable, even within a land cover classification. The lower threshold of detectability was somewhere between higher end EF1 and lower end EF2 events. While this does not represent an improvement in detectability threshold over previous studies, the methodology presented, in conjunction with the use of Sentinel-2, has several advantages such as only requiring a single post-event image for analysis and increased spatial detail in the output compared to previous studies. The results were summarized across land cover type and damage intensity and predictive performance was much better in the types of forested areas for which the DI was designed. Although this is a limitation overall, the strengths of the methodology counterbalance the weaknesses of traditional ground-based survey methods
