48440 research outputs found
Sort by
Design of a Digital Twin Apparatus
No full textMachine learning presents a promising approach for tackling complex tasks, offering the advantage of streamlining otherwise difficult calculations of traditional analytical methods while delivering reasonably accurate outcomes. In this study, machine learning techniques were employed within the framework of an MQP to develop a digital twin capable of replicating full-field Laser Doppler Vibrometer (LDV) displacement measurements for a jet engine blade undergoing low-frequency excitation, using sparse strain measurements as an input. The primary objective was to train a machine learning model to accurately predict and extrapolate LDV displacement readings for the entire plate based on these limited strain measurements. Additionally, this project aimed to harness existing software and resources to develop a scalable framework for future integrations and enhancements. By harnessing the potential of machine learning, this MQP sought to enhance structural analysis by being able to produce results similar to a Laser Vibrometer using less expensive equipment
Fabricating Flamenco: Leveraging Local Music to Promote Artistic Approaches to STEM
No full textOur team utilized modern engineering design and fabrication techniques at the University of Cádiz FabLab to manufacture a cajón, castanets, and a guitar solera – traditional components of Flamenco performance and instrument fabrication. We conducted interviews with local musicians, educators, and Flamenco experts to provide humanitarian context throughout our technical processes. Finally, we documented the fabrication through pictures and videos shared on Instagram, offering an accessible resource for students to become interested in creative, interdisciplinary approaches to STEM education and careers
Breaking the Culture of Silence: How Can Digital Education Challenge Romania's Communist Nostalgia?
No full textThe goal of this project is to combat communist nostalgia in Romania’s current sociopolitical climate. To address this goal, we collaborated with the Muzeul Ororilor Comunismului în România to create an interactive, educational tool that encourages critical engagement with Romania’s communist history. We interviewed survivors, museographers, teachers, and students to uncover aspects of life under Nicolae Ceaușescu’s regime, sources of nostalgia, gaps in students’ knowledge, and effective curation strategies. Our application was tested by student participants, 89% of whom indicated they would recommend it to peers. This project offers a tangible solution for preserving and disseminating historical knowledge and survivors’ voices in a rapidly evolving political landscape
Intelligent Drone-Based GPR for Root-Zone Soil Moisture Characterization: Data Collection and Analysis
No full textThis project focuses on creating an advanced method for moisture characterization using drone-mounted radar technology and data analysis. As climate change continues to present challenges, efficient water management in agriculture has become increasingly important. Farmers need accurate data to optimize irrigation, reduce water wastage, and maintain soil health. To address this, our project utilizes radar systems mounted on drones to map moisture levels in the root zone. By analyzing the reflected radio frequency (RF) signals from Ground Penetrating Radar (GPR) systems, we aim to offer large-scale, non-invasive soil moisture measurements through the use of moisture maps. This approach provides quick and precise assessments that are crucial for making informed decisions in agriculture, environmental monitoring, and hydrological studies. With the development of custom radar hardware and software, combined with innovative data analysis methods, we aim to create a dependable and scalable solution for detecting soil moisture. Our results have the potential to transform agricultural practices, improving water management and promoting sustainability in food production
Expanding Opportunities for the Cerrito School Community to Pilot Drones
No full textIn collaboration with Fundación Paraguaya’s Escuela Agrícola Cerrito in Benjamín Aceval, Paraguay, the team designed and implemented an introductory course in piloting small drones. The project aimed to equip participants with essential skills for the growing field of agricultural technology. The team continuously improved the course by collecting and incorporating feedback after each lesson. Additionally, the team developed a business plan with recommendations to help the school prepare their students for future careers and advancements involving agricultural drones
NASA Lunabotics '24-'25
No full textThe National Aeronautics and Space Administration (NASA) Lunabotics Challenge tasks university students to develop, test, and fabricate a lunar robot that will complete simulated lunar mission challenges. Student groups will compete against one another using different engineering skills through the design and operation of their robot. The Lunabotics competition is scored on several metrics, autonomous navigation, obstacle avoidance, and regolith berm construction efficiency. This year, the WPI team inherited a robot and elected to enhance its design and autonomous behavior specifically in the robot’s storage, drivetrain, gearboxes, and autonomy design to maximize scoring opportunities based on the Lunabotics rulebook while simultaneously refining existing systems. This enabled the team to develop diverse skills within their prospective majors, beyond their majors, and outside the classroom to meet testing goals and development objectives for this year’s Lunabotics Challenge and robot, Mooncake
Autonomous Ball Catching Drone
No full textThis MQP project presents the design, development, and evaluation of an autonomous quadcopter drone capable of intercepting and catching a ball mid-flight. The system integrates real-time trajectory prediction and control algorithms to track a moving ball and calculate a path for interception. This project utilizes a motion capture system to track the ball and robot. Physics modeling helps us estimate the ball trajectory and compute the desired robot control actions for optimal interception. Through developing this procedure the team went through multiple iterations of trajectory estimation methods and control implementations to determine the most reliable and rapid technique for this aerial robotic system. This work demonstrates the culmination of work between three Robotics Engineering seniors through this past academic year and of the experience gained over their undergraduate degrees
Soft Robotic Eel
No full textSoft robotics offers a compelling approach to underwater locomotion, combining flexibility with bioinspired movement capabilities to navigate environments that challenge traditional rigid systems. This project aimed to create a cable-driven soft robotic eel based on, and seeking to improve upon, an earlier design developed by our advisor, Dr. Robin Hall. Building on this foundation, we focused on enhancing the eel’s modularity, mechanical performance, and future expandability through iterative refinement of its segment architecture, actuation mechanism, and internal layout to support additional components. The robot consists of modular, 3D-printed accordion segments fabricated from thermoplastic elastomer filament, actuated using fishing line routed through each segment and wound around servo-driven spools to produce undulatory motion. This modular design facilitates straightforward customization, repair, and extension of the body. The system also includes a watertight head enclosure for electronics, soft passive fins, and a compliant tail to support natural swimming dynamics. The robot was tested in tank and pool environments to evaluate swimming speed and general operability in conductive, chlorinated water. While still requiring further development, this soft robotic eel establishes a modular and adaptable platform with strong potential for future research in bioinspired locomotion, environmental sensing, and underwater exploration
Investigating Endothelial Responses to Tissue Under In-Vitro Flow: System Development for the Preclinical Evaluation of Draper’s LEAP Valve
No full textA low-cost, imaging-compatible parallel plate flow chamber was developed to study endothelial responses to valve graft tissue under a target shear stress of 4 dynes/cm², matching conditions in pediatric patients with Tetralogy of Fallot. Made from acrylic and designed for 1 mm-thick opaque tissue, the system offers reproducible, controlled flow in a compact, sterile, and biocompatible setup for preclinical testing. It supported 48-hour flow experiments and real-time imaging to assess cell attachment. Results showed no significant change in cell density before and after flow (t ≈ 0.02, d ≈ 0.012), confirming the system’s ability to maintain viable, adherent cells. This platform enables early safety evaluation of pediatric valve grafts in tissue-based devices such as Draper’s LEAP valve
Characterizing the Effects of HIV Accessory Proteins on NK Ligand Expression Across Different HIV Strains
No full textBackground: Human Immunodeficiency Virus (HIV) is a retrovirus that infects approximately 40 million people globally. HIV targets the immune system by infecting CD4+ T cells and macrophages. While Natural Killer (NK) cells contribute to immune defense, they are unable to fully control acute infection, and in vitro studies have shown incomplete killing of infected CD4+ T cells. Previous studies have shown that the HIV accessory proteins (Nef, Vpu, Vpr, and Vif) can alter the expression of key NK cell ligands, thereby interfering with NK cell-mediated killing. However, the extent to which these effects are conserved across different HIV-1 strains remains unclear. This study investigates the strain-specific effects of accessory proteins on NK ligand expression using three Clade B HIV-1 strains: 89.6, AD8, and JR-CSF. Hypothesis: HIV accessory proteins regulate NK cell ligands in a strain-specific manner. Methods: Lentiviruses overexpressing individual HIV-AD8 accessory proteins and replication-competent mutant viruses lacking specific accessory genes (in AD8 and JR-CSF) were generated. Jurkat and primary CD4+ T cells were transduced or infected, and NK ligand expression was assessed via flow cytometry. Western blotting confirmed accessory protein expression in modified cells. Results: While accessory proteins were expressed in Jurkats, they failed to express in lentivirally transduced CD4+ T cells. In contrast, mutant virus infections revealed Nef and Vpu as primary regulators of key ligands, including HLA-A, HLA-B, NTB-A, and ICAM-1. These effects were largely conserved across AD8, 89.6, and JR-CSF strains, though some strain-specific differences emerged. Conclusions: These findings highlight the regulation of NK ligands by HIV accessory proteins, with Nef and Vpu emerging as key modulators in the AD8 strain. While some strain specific effects were observed (HLA-C, HLA-E, NTB-A, HVEM), many of the trends were consistent across AD8 and 89.6 strains. Continued exploration across diverse HIV strains and improved delivery methods for accessory protein overexpression in primary cells will be essential to fully understand the mechanisms of NK cell evasion and identify broadly applicable therapeutic targets