A Foley catheter is a common medical device that helps a patent empty their bladder. It is inserted into the patient’s urethra and secured with a balloon in the bladder. The undue removal of Foley urinary catheters by patients is a critical issue in pediatric care that can cause significant pain, medical complications and additional hospital costs. To minimize this risk of urethral trauma, the team designed a device that automatically deflates the retention balloon when sufficient force is applied.

This modified pediatric catheter utilizes a plug and tether safety release mechanism. Excess force on the tether pulls the plug beyond its resting position, causing sterile water to flow from the balloon to the bladder. This deflates the balloon, allowing the catheter to be removed easily. The team optimized the deflation lumen’s flow rate and egress mechanism’s response threshold using computational fluid dynamics simulations to predict fluid flow.

Iterative prototyping methods – including stereolithography, fused deposition modeling, and extrusion simulations – supported the design decisions. Optimization ensured reliable deflation while maintaining normal functionality. The team completed a production run with prototype tooling and conducted verification testing including tensile force and flow rate testing to confirm performance. This device will soon undergo FDA approval for use in health care.

Many modern medical devices, such as indwelling catheters, incorporate drug-eluting coatings to prevent potentially life-threatening complications. Controlled drug release from PLGA microparticles enables prolonged therapeutic effects. This reduces the need for frequent and persisting interventions. In this project, the team aimed to optimize the microparticle fabrication process by analyzing key processing parameters and their influence on particle morphology – the study of particles’ shape, size and surface characteristics – and drug encapsulation efficiency.

The team chose a fabrication design that uses a microfluidic double T-junction system to precisely control emulsion droplet formation while a syringe pump delivers active and continuous phases at optimized flow rates. This produces microparticles ranging in size from 5 to 50 μm. After production, the team
implemented various drying techniques, including lyophilization, to enhance particle smoothness and consistency.

Once the fabrication process was complete, the team used scanning electron microscopy for microparticle characterization to validate morphology and uniformity. By refining the process parameters, such as solvent selection and stir rates, the team established a reliable method for producing high-quality drug-loaded microparticles. These findings are a critical step toward advancing medical technology and improving patient outcomes.

AOCs are essential for high-speed data transmission in modern data centers. However, they are difficult to install. Traditionally, routing these fragile cables requires technicians to climb ladders and manually guide them through overhead trays. This poses safety risks and is inefficient. For this project, the team developed a pulley system that alleviates these problems.

The design features three main assemblies: the mounting assembly, the cable interface and the deployment system. The mounting assembly securely attaches to the standard 24-inch-wide cable tray to ensure stability during operation. The cable interface, designed to protect the delicate transceivers located at the end of AOCs, uses a boat-like structure with magnets and Velcro for secure transportation. Finally, the deployment system incorporates a pulley mechanism – which can be operated manually or with a power tool – to efficiently move cables along the trays. When these three components are combined, operators can use the system to safely and efficiently install AOCs by loading the cable transceivers in the cable interface and pulling it to its designated location using the deployment system.

Ensuring situational awareness during ground operations is critical in modern aviation. This is especially true at busy airports where limited visibility increases collision risks. To address this need, the team developed CASA. It is a system that enhances safety and efficiency by providing a real-time bird’s-eye view of an aircraft’s surroundings using multiple high-resolution cameras strategically placed around the airframe. A Jetson Nano AI computer processes and fuses the camera feeds into
a seamless 360-degree display that highlights nearby objects – such as vehicles, equipment and personnel – while generating real-time alerts for potential hazards.

The team implemented CASA on a scaled aircraft model and tested it in a simulated airport environment. This test confirmed CASA’s ability to eliminate blind spots and assist pilots and ground crews in navigation. CASA also provides environmental and sustainability benefits by preventing ground fuel spills and aircraft damage caused by operational incidents. By improving efficiency and reducing operational costs, the system presents a scalable and cost-effective solution for both business jets and commercial airliners.

CTS affects 1% to 5% of adults globally (between 81 and 405 million people). It occurs when the median nerve in the wrist is compressed and leads to symptoms such as pain, numbness, tingling and weakness. CTS presents a significant challenge as there are currently no noninvasive technologies that specifically and quantifiably treat it.

This team aimed to relieve symptoms of CTS by designing a wearable brace that could apply 10 to 12 N of force to the carpal arch while stabilizing the thumb to prevent hand collapse. The design emphasizes simplicity, ergonomic comfort and affordability. It also accommodates a wide range of hand sizes and determines the applied force without user input.

The brace consists of a solid piece which wraps around the hand leaving a gap on the lateral side for the force applicator. This is a triangular structured force design. The end result of this project is the carpal arch space augmentation (CASA) wearable brace. It is constructed from 3D-printed thermoplastic polyurethane filament and a medical wrap and offers an effective and comfortable solution for alleviating the symptoms of CTS over an extended period of time.

The COVID-19 pandemic underscored the critical need for advanced personal protective equipment (PPE) to shield health care workers and individuals in high-risk environments. The team developed a fully enclosed, self-sterilizing face shield designed to mitigate pathogen exposure and improve respiratory protection. This shield incorporates an integrated sterilization system featuring 222 nanometer light, a range of far-UVC light with germicidal properties. The shield automatically disinfects
the external surface at timed intervals, reducing contamination risks and eliminating the need for manual cleaning.

The light effectively inactivates pathogens while remaining safe for human exposure, unlike traditional 254 nanometer UVC light. Additionally, the face shield fully encloses the user’s face and includes a built-in powered air-purifying respirator that achieves 99.97% filtration efficiency. This ensures continuous airflow while filtering out airborne contaminants.

The team’s engineering efforts focused on optimizing the light dosage for maximum pathogen inactivation while maintaining user safety. The final prototype demonstrates a practical and innovative solution for pandemic preparedness, offering sustainable protection for health care workers, laboratory personnel and frontline responders while reducing reliance on disposable PPE.

The primary mission for this project was to develop better ways to deploy divers, submersibles and other payloads at sea. Secondary missions include maritime surveillance and search and rescue. To reach this goal, the team investigated the aerodynamic characteristics of two configurations of a BWB amphibious cargo seaplane: a baseline design and a variant equipped with catamaran-style floats. These configurations are intended for long-range offshore mission support, so the team optimized the design to meet these performance requirements and to maximize the coefficient of lift and minimize the coefficient of drag.

The team quantified the drag penalty introduced by the floats with computational fluid dynamics simulations and low-speed wind tunnel testing with a force balance and 3D-printed models. The students evaluated aerodynamic performance over a range of angles of attack at constant Reynolds numbers, which yielded key metrics such as lift, drag, pitching moment coefficients, and lift-to-drag ratios.

The team also explored alternate strategies for drag reduction and improved longitudinal stability. The results of these tests highlighted the aerodynamic penalties of float configurations and revealed opportunities for reducing drag while enhancing lift and stability through design refinements. These findings demonstrate the feasibility of optimizing the BWB seaplane concept for improved performance in future iterations.

The 309th Aerospace Maintenance and Regeneration Group (AMARG) at Davis-Monthan Air Force Base oversees a “boneyard” of decommissioned military aircraft. These aircraft sit on large wooden modules in storage. The modules are effective but outdated. In this multifaceted project, the team conducted a life cycle study on the current modules, developed a novel additive-manufactured replacement for the block, and reported on the feasibility of replacing the current modules with the
new design.

The team first explored the cost of materials, production and implementation of the current modules. One of the key findings was that the current wooden module was designed under the limitations of additive manufacturing at the time. Conducting a trade study comparing cost, strength and environmental resistance of the current module and new materials, the team determined that acrylonitrile styrene acrylate, a thermoplastic polymer, is an optimal replacement material.

The team then carried out finite element analysis and topology studies to optimize material mass and mechanical strength. Finally, the team tested the new design and completed a feasibility study to determine whether the replacement is fiscally responsible. AMARG can use these results to inform their decision about which module design is better suited for their goals.

Plastic waste is a major problem in academic makerspaces such as the Engineering Design Center at U of A. Novice users often employ incorrect material settings. This leads to failed prints, wasted material, excess material for recycling and additional time spent on cleanup and reprinting. This project aims to reduce plastic waste by developing a filament verification system for 3D printers.

The team designed a spectroscopy system to identify common filament materials used in 3D printing like PLA, ASA and PETG. Once it determines what material is loaded into the printer, the system checks for mismatches between the filament and the user’s selected print settings. These settings include material, nozzle temperature, bed temperature and print speed.

If the system detects a mismatch, it will automatically adjust the printer settings and notify the user. Ensuring the loaded material matches the print settings will improve print success rates and reduce waste. Additionally, since the primary focus of this project is makerspaces, the team will share the project as an open-source resource for the maker community as a cost-effective, efficient and sustainable solution for makers to replicate.

Weed overgrowth on golf courses presents a significant challenge to turf management. It requires frequent maintenance that is both labor-intensive and costly. Traditional methods rely on manual labor or widespread herbicide application. Both of these methods can be inefficient and environmentally harmful. To address these challenges, the team developed SPIDER, an autonomous, data-driven agriculture robot. SPIDER can streamline turfgrass maintenance with precise weed detection and
elimination, particularly for environments like golf courses.

SPIDER’s system uses both software and hardware to enable autonomous movement, object avoidance and weed detection. Its mechanical assembly includes a main body that houses all electronic components and four legs on each side of the main body for mobility. A mechanical arm mounted on a rotational surface atop the main frame operates within a 90-degree arc between the front legs for precise weed removal. The weed detection software uses machine learning technology with PyTorch’s ResNet18 model. It is integrated with the mechanical elimination system by the repository running on an NVIDIA Jetson Nano AI platform to ensure seamless communication between software and hardware components.