23671 research outputs found
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Modeling and comparing the efficiency of quadcopter drone designs
No full textPresented to the 24th Undergraduate Research and Creative Activity Forum (URCAF) held in Woolsey Hall, Wichita State University, April 25, 2025.Traditional quadcopter drones use pitch control to achieve forward flight. However, pitching the drone body causes inefficiencies in the form of downforce and drag. This study looks to compare the efficiency of traditional and alternative drone designs. To achieve this end, A numerical model was built from wind tunnel data of rotor characteristics at varying angles of attack. The model measures the thrust and pitching moments of individual rotors to determine the combination of rotor speeds to keep the drone's pitch and altitude stable. This model uses the determined rotor RPM to estimate the power consumption of the drone. The study focuses on comparing the traditional free-to-pitch design to a variable CG drone; 5 rotor, fixed-pitch drone; and a tiltrotor, fixed-pitch drone. Power consumption is measured for drones of varying weight, cruise velocity, and center of gravity location. The study found that all drones perform similarly at cruise velocities below 3 meters per second. The 5 rotor, fixed-pitch drone and tiltrotor, fixed- pitch drone show power savings upwards of 15% at cruise velocities greater than 8 meters per second. Further research and additional wind tunnel data is needed to corroborate the power saving qualities of the alternative designs at velocities greater than 9 meters per second
The heredity hoax: Challenging flawed genetic theories of human development
No full textClick on the DOI link to access this article at the publishers website (may not be free).This innovative and thought-provoking book integrates both new, authored material and reprints of existing literature that, together, provide a compelling narrative that reveals the fatally flawed science associated with genetic reductionist accounts of human behavior and development. Through an interdisciplinary lens, it illuminates the dynamic nature of human development, empowering readers to question established notions, and embrace the complexity of our potential. Across the book, the work of top-tier scientists, from developmental, comparative, educational, and biological science illuminates theory and research converging on the conclusion that the multiple egregiously flawed work of genetic reductionists should be expunged from research pertinent to human development. The book challenges the prevailing reductionist narratives and their application to social policies, programs, and uses in media. Theoretically based and empirically rigorous, this multidisciplinary approach to human development will shine a light on the inequities in individuals or groups that suggest that specific genes do not enable them to succeed in life. The Heredity Hoax invites graduate programs and advanced undergraduate courses on human development, human potential, epigenetics, and more to delve into the intricate interplay between genes, environment, and personal growth. This will also serve as an unimpeachable source of evidence for researchers, educators, and social policymakers. © 2025 Richard M. Lerner and Gary Greenberg. All rights reserved
Designing a low-background solar neutrino detector
No full textPresented to the 21st Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Rhatigan Student Center, Wichita State University, April 11, 2025.Research completed in the Department of Mathematics, Statistics and Physics, Fairmount College of Liberal Arts and Sciences.INTRODUCTION: Neutrinos are elusive, low-energy subatomic particles mostly produced in solar fusion. Because they have minimal mass and no electric charge, they rarely interact with matter, often necessitating large underground detectors to reduce backgrounds and detect their infrequent signals.
PURPOSE: This research aims to develop and test a novel detector capable of distinguishing neutrino interactions in high-background environments, such as those found in space or near nuclear reactors.
METHODS: We use the MARLEY simulation framework to estimate neutrino interactions on 71Ga and to characterize the particles emitted. These results are then fed into Geant4, which models realistic particle interactions within prospective detector geometries. By refining the geometry and materials, we optimize the detector for neutrino detection while rejecting uncorrelated backgrounds. To validate the simulations, we constrain them with experimental data from small, prototype GAGG (Gadolinium Aluminum Gallium Garnet) detector segments tested with various radioactive sources in our laboratory.
RESULTS: MARLEY predicts that half of the relevant neutrino signals feature a time-delayed signature of approximately 100 ns, while the remaining half can be reliably detected only if there is a clear spatial separation between particles. These findings indicate that a highly segmented detector with optically isolated volumes less than 10 mm in size is optimal. Tests with prototype GAGG segments yielded a 3.61 ± 0.07% energy resolution at 137Cs and confirmed reliable detection of 57Co double-pulse decays in the 80–1,150 ns range.
CONCLUSION: In summary, our preliminary results demonstrate that a finely segmented, GAGG-based detector design can effectively identify low-energy neutrino signals amidst complex backgrounds. Continued refinement of the geometry, materials, and data analysis techniques will further enhance detection efficiency and resolution, advancing our capabilities in low-energy neutrino physics.Graduate School, Academic Affairs, University Librarie
Department of Dental Hygiene Class of 1980
No full textFirst row (left to right): Virginia Goral, Chairperson; Mary Ann Clark, Instructor; Kathy Coughneour, Instructor; Diane Huntley, Instructor; Mary Martha Stevers, Instructor; Linda Wolf, Instructor; Dr. Bradley, Supervising DentistSecond row (left to right): Pam Clancy, President; Jill Hand, Secretary/Treasurer; Mary Wessling, Social Chairman; Cindy Bobb, Jane Bailie, Linda Burke, Leah DunnThird row (left to right): Maria Ebel, Kris Engelland, Vicki Farney, Marla FeldtFourth row (left to right): Gwen Griffey, La Vena Hill, Peggy Howard, Caraleta Huslig, Susan Johnson, Barie Krehebiel, Dana Martindale, Monica MilardFifth row (left to right): Joanne Miller, Roberta Opliger, Robin Ricks, Janise Robertson, Pam Swift, Janice Whitman, Teresa York, Susan YoungDigitized by University Libraries' Technical Services Institutional Repository & Digitization group.Personal and non-profit use only
Modeling electric vehicle charging load on power grid considering travel behavior
No full textClick on the DOI link to access this article at the publishers website (may not be free).Electric vehicle (EV) usage increases every year, yet there is no accurate model to predict traveling or charging behavior. Current working models present inaccurate data as well as showing the same daily demand at different locations. These models do not consider the variations of human behavior and differences in geographic areas. However, an agent-based modeling (ABM) system is able to track individuals in a simulation to predict their behavior. NetLogo is an ABM platform implemented to show the behavior of EVs. Through the ABM simulation, travelers were simulated and recorded to predict their future load demand realistically and accurately on the grid. This simulation showed different peak times and load amounts between locations and slight differences in each iteration as expected. These results show a more accurate prediction of future EV load demand based on the input data such as vehicle type ratio, number of vehicles, and average range of city. © 2025 IEEE
Detection of acoustically matched defects in fiber-reinforced composites using through-transmission ultrasound
No full textThesis (Ph.D.)-- Wichita State University, College of Engineering, Dept. of of Industrial, Systems and Manufacturing EngineeringDetecting acoustically matched defects (AMD) in fiber-reinforced composites (FRC) remains a challenge for traditional through-transmission ultrasound (TTU) techniques, which rely on manual thresholding and lack time-of-flight data. This limitation creates a noticeable research gap that this dissertation directly addresses through advanced classification methods. First, a novel root-mean-square (RMS) classifier leverages the frequency-domain transformations and confidence intervals to establish robust thresholds. Compared with amplitude, the RMS classifier improved the detection accuracy by 21.34% and increased the signal-to-noise ratio (SNR) to 7.01. Second, we trained neural networks (NN) on domain-specific features extracted from the TTU waveform signals. Globally trained models achieved Macro-F1 scores of 0.96 (time-domain), 0.97 (frequency-domain), and 0.62 (wavelet-domain). A comparative analysis in Chapter 4, using regional heat maps and probability of detection (POD) curves, further demonstrated the superiority of both the RMS and NN classifiers over amplitude classifiers. The RMS and regionally trained NN classifiers consistently achieved regional recall rates exceeding 94% across all ply counts and defect depths, with regions achieving a 100% recall. Notably, the wavelet-domain model significantly improved when trained regionally (Macro-F1 score of 0.94). The regional Macro-F1 scores achieved 28–30% relative to the baseline amplitude classifier, highlighting their robustness in detecting AMDs in laminate regions, where traditional methods often fail. Together, these contributions provide a validated framework for detecting AMDs in FRC laminates using TTU, supporting more reliable automated defect detection and advancing nondestructive evaluation (NDE) capabilities in high-performance composite manufacturing
Department of Dental Hygiene Class of 1996
No full textFirst row (left to right): Barbara M. Gonzalez, RDH, MHS, Clinical Instructor; Pamela Bumpurs, RDH, Clinical Educator; Diane E. Huntley, RDH, PhD., Associate Professor; Dr. Steven Twietmeyer, Supervising Dentist; Thomas J. Foley, DDS, Supervising Dentist; Salme Lavigne, RDH, MS, Associate Professor/Director; Denise Maseman, RDH, MS, Assistant Professor; Stephanie Jones, Clinic CoordinatorSecond row (left to right): Mara Stegman, Secretary; Donna Dewey, President; Catherine Killian, Vice President; Gina Kasselman, Class LiaisonThird row (left to right): Heather Calhoun, Vonda Stueven, Social Chairman; Stacey Smalley, Treasurer; Christina Henson, Social Chairman; Wendy Callahan, Karen ColemanFourth row (left to right): Jenni Douglas, Heather East, Amy Fowler, Amy Harmon, Michelle Harp, Jennifer Hughes, Terri Jacoby, Ender Kocatürk, Nancy Krehbiel, Carmen LavigneFifth row (left to right): Suzi Marksberry, Dina Mills, Kimberly Riggins, Janice L. Schoenhofer, Tara Scobee, Kerri Stucky, Sherry Wakefield, Angela Walters, Nancy Winters, Jacquelyn ZillnerDigitized by University Libraries' Technical Services Institutional Repository & Digitization group.Personal and non-profit use only
