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Investigation of Stress Concentrations in Stereolithographic Modeled Parts
No full textRapid prototyping using additive manufacturing has an ever-increasing presence in industry. Stereolithography (SLA) is a widely utilized form of additive manufacturing that has seen significant adoption in recent years. While SLA offers numerous advantages, there remains a lack of knowledge regarding how specific geometric features, such as notches, influence the mechanical properties of SLA-manufactured components. This study aims to address this gap by investigating stress concentrations induced by circular notches in fully solid (100% infill) SLA parts. The primary purpose is to enhance understanding of how notches affect the mechanical properties of SLA components, where existing knowledge is limited. Previous work focused on Fused Deposition Modeling (FDM), a widely used additive manufacturing technique, have explored how process parameters influence the mechanical properties of printed parts. Research has highlighted a significant knowledge gap regarding the effects of specimen geometry and infill parameters on mechanical performance. To address this, prior work constrained infill to a ‘gyroid’ pattern with densities of 20%, 40%, and 60%, and investigated stress concentrations caused by notches and holes. These studies revealed unexpected results, contradicting traditional solid mechanics theories for predicting failure and crack propagation. Specimen geometries, including v notches, elliptical holes, circular holes, and semi-circular notches, were tested, showing that sharper features like v notches increase maximum stress and crack likelihood compared to smoother curves. Findings also indicated that solid shells in 3D-printed parts reinforce edges, reducing stress concentration factors, influencing the development of failure theories for 3D-printed products
Ascend: Weather Balloon Payloads - Near Space Research
No full textThe ERAU ASCEND! team works alongside numerous universities and high schools across the state of Arizona to launch weather balloon payloads to near-space once a semester, with the help of Arizona Near Space Research (ASN R). The team is comprised primarily of Aerospace Engineers, but prides itself on providing equal opportunities to interested students of any major. Students in ASCEND! are provided the unique opportunity to experience a complete design cycle in each semester, from the initial conceptualization of a payload to the analysis of data after its recovery. Throughout the cycle, team members learn soldering and sensor control, coding and data logging, design proposal processes, trade studies, and computer-aided design. For the past several semesters, a primary objective of ASCE ND has been to live stream video and telemetry from the payload throughout the balloon flight, while simultaneously recording scientific data about the atmosphere. A secondary goal has been to improve the structural characteristics of the payload. To facilitate these goals, the group is divided into three sub-teams. The Structures team is responsible for developing the fiberglass payload shell and 3D-printed internals. Working alongside the Structures team is the Sensors team, which selects and codes the various sensors inside the payload in order to collect data. Finally, the Ground Station team designs and codes tracking stations, which keep high-gain antennas oriented towards the payload. This semester, the Structures and Sensors teams are working to downsize the payload structure to reduce weight while maintaining the same sensing and transmission capabilities. The Ground Station team is designing a new tracking station, which will allow simultaneously reception of telemetry and video data
The FF-influenced Algorithm for the Classification of Large-scale Tasks
No full textRecent advancements in machine learning are exploring alternatives to backpropagation, including the forward-forward (FF) algorithm introduced by Geoffrey Hinton. These two forward passes were conducted: one used positive (real) data, and the other employed negative data generated by the FF algorithm for several small problems. Learning from the FF algorithm, we propose to enhance the goodness of positive data and reduce the low goodness of negative data for classifying images in both the MNIST and CIFAR-10 datasets. We compared the FF-based network with standard backpropagation-based feed-forward neural networks, focusing on the classification of images with accuracy and loss. We show that the FF algorithm achieves comparable accuracy to traditional feed-forward neural networks on the CIFAR-10 dataset, suggesting the feasibility of the FF algorithm for large-scale tasks.
This is a joint work with Brady Heddon, Adam Kuzminski, Kaitlyn Cavanaugh, Jack Dillard, and Sirani M. Perera
Joey\u27s ADHD
Get PDFJoey struggles throughout a haunted house adventure staying focused while his friends trying to are enjoying themselves. This causes frustration and annoyance between Joey and his friends
Development and Evaluation of pH-Sensitive Drug-Polymer Complexes for Targeted IBD Therapy Using Electrospray Technology
Get PDFInflammatory bowel disease presents significant challenges in treatment due to the chronic inflammation of the gastrointestinal tract. Current therapeutic strategies, while effective in managing symptoms, often lead to suboptimal outcomes and undesirable side effects. Nanoparticle-based drug delivery systems offer a potential solution by providing targeted delivery to inflamed tissues, minimizing systemic exposure, and improving drug efficacy. This research aims to develop a novel, pH-sensitive drug-polymer complex using Eudragit S100 and L100 polymers to encapsulate 5-aminosalicylic acid and select flavonoids, targeting inflammation at multiple points along the GI tract. Electrospray technology was employed to fabricate the drug-polymer system, with preliminary tests indicating favorable polymer solubility in ethanol and successful deposition using a single-needle electrospray setup. Preliminary tests confirmed effective solubility of polymers and active compounds in ethanol, with UV spectroscopy optimizing detection wavelengths. Results show polymer concentration significantly influences fiber morphology; low concentrations (0.5–1% w/v) produce droplets, while high concentrations (\u3e10% w/v) yield smooth, bead-free fibers critical for uniform drug loading and controlled release. These findings highlight the potential of the proposed drug-polymer complex as an improved delivery system for IBD therapies. This study will further investigate the creation of a multi-layered polymer complex capable of withstanding the digestive environment for optimal drug release. Additionally, the use of triaxial needles in electrospray will be assessed to enhance encapsulation efficiency and drug delivery precision. The research will employ a variety of characterization techniques, including Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy (ATR-FTIR), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM), to evaluate the physical properties, structural integrity, and drug loading capacity of the developed complexes
Core-collapse Supernovae Particle Physics Interactions within Simulations
Get PDFThis study investigates the role of specific particle physics interactions in simulations of core collapse supernovae, with a focus on understanding how varying levels of inclusion impact the accuracy of gravitational wave predictions and results of simulations. Different research groups often approach these simulations with varying degrees of complexity, cutting corners by omitting certain reactions or simplifying others. This project systematically evaluates the implications of these choices, comparing the particle physics interactions included, the dimensionality of the simulations, and the governing equations used. Our goal is to identify how these factors influence the precision of numerical simulations. By providing a comprehensive analysis of the advantages and drawbacks of including different particle interactions, we aim to improve the development of simulations used by instruments like LIGO (Laser Interferometer Gravitational Wave Observatory)
Never Saw: An Anthology on Remote Warfare
Get PDFIn the 21st century, warfare is becoming more remote, and less intimate, with the introduction of drones and communication technology. Never Saw plays on the fact that servicemember have less direct involvement in fighting an enemy in alternate points of views from the servicemembers and the victims of indirect warfare. The anthology of poems covers multiple professions’ perspectives of indirect warfare, and they inform the readers of the changes to conventional warfare and the effect it has mentally for the new generation of warriors
Reflection of Life
Get PDFThis poetry collection aims to capture the multifaceted nature of the human condition through evocative language and imagery. With themes ranging from the struggles of daily life to the triumph of the human spirit, Reflections of Life offers readers a journey of introspection and contemplation. Through exploring topics such as love, resilience, and the passage of time, the collection seeks to evoke a range of emotions and provoke a wide array of thought on what it means to be human. Each poem within the collection serves a specific purpose, whether it\u27s to inspire, provoke, or simply provide solace in times of uncertainty. By touching on universal themes and experiences, the poems aim to resonate with readers from all walks of life, fostering empathy and understanding in an increasingly fragmented world. The effect of Reflections of Life is to leave readers with a sense of connection to themselves, to others, and to the world around them. Through the power of poetry, the collection invites readers to pause, reflect, and find beauty and meaning amid life\u27s chaos
