The team designed a noninvasive medical diagnostic device that uses a spinning platform to conduct medical diagnostics on a microliter scale. This device can accept a whole blood input, separate whole blood into plasma and cellular components, conduct a white blood cell differential count and detect protein biomarker concentrations. The microfluidic channels on the disk can conduct the required analyses with minimal manual intervention. A direct-current motor rotates the assay disk to create centrifugal force that manipulates blood flow through the microfluidic architecture. A magnetic bead-based purification method isolates the desired cells (granulocytes and lymphocytes), which are then channeled into their respective imaging chambers. Protein biomarkers are detected using enzyme-linked immunosorbent assay in a lateral-flow immunoassay and imaged separately. The captured images are then exported and processed to yield cell and protein biomarker counts. The analyzer features a user-friendly graphical user interface.

There are no current medical or surgical treatments to restore osteoarthritic joints to their native condition, and osteoarthritis patients commonly require joint replacement. Scientists have used stem cells to produce cartilage-like tissues as a new treatment for damaged cartilage. One approach to improving the quality of tissue-engineered cartilage is to apply a load to the engineered tissues while they are developing. The team analyzed and modeled a variety of force applicators (primarily motors and gear systems) to develop a final optimized system that ensures the application of exacting and controllable forces.Additionally, the team developed a strain gauge and microcontroller feedback system to provide even more precise control of the forces. The system designed produces axial and shear loads that replicate the pattern of strain that occurs in vivo. An Arduino board and some other microcontroller components control the system. The system’s forces, torque and accuracy exceed all requirements. The system also supplies a sterile environment in which cells can grow. This will allow further testing of methods to improve the quality of engineered tissues via the application of mechanical loading.

This project is a continuation of a 2018 senior design project to replace the Caterpillar 7495 electric rope shovel as the primary method for surface mining excavation. The new design focuses specifically on the machine’s material removal (boom, stick and bucket) and material transport (conveyor and feeder) subsystems. The design optimizes the mining process, reducing the time spent in the swing cycle by existing rope shovels by introducing continuous mining methods. The machine’s primary requirement was to achieve a material loading rate of 200 tons per minute while operating in an environment requiring a 70-foot horizontal reach and a 30-foot vertical reach. The team conducted extensive research, trade studies, CAD modeling and analysis to verify the system design and performance. They demonstrated the machine geometry of structural components with 3D models.

Underground mines require continuous communication with mine equipment and personnel. Fiber optic or other wired communication infrastructure works in most mines, but for the advancing face, or “last mile,” it is difficult to provide effective and reliable coverage due to the close proximity to drilling and blasting events. A lack of reliable communication results in delayed reactions to unexpected events, safety concerns and slowed production. The team created a small, easy-to-install communication network that can be readily deployed to the “last mile” between blasting events. Taking into consideration the mines’ environmental
conditions and possible signal interference underground, the team developed a portable mesh network that consists of various battery-powered nodes that act as gateway devices, transmitters and receivers in a network based on Wi-Fi and Zigbee. The mesh network is self-configuring and self-healing in the event that a node fails. This ensures that the relay of data and communication is not interrupted. The combination of Wi-Fi and Zigbee in each node allows for minimal power usage and maximum signal amplification for the entire mesh system.

3D printing using ABS or PLA produces waste that is typically thrown away and presents an environmental issue. The designed plastic waste recycler is composed of a grinder that shreds the plastic waste and an injector that melts and injects the plastic shreds into a removable mold. The injector’s heating bands adjust to user input to maintain the user’s desired temperature. This allows the user to set melting temperatures besides those of ABS and PLA. The injector also features a display of the measured temperature of the heating bands. The mold is exchangeable, with a universal nozzle. Proper safety standards are set in place with multiple emergency stops, temperature regulation of both the grinder and injector, and LED indicators. The team built a prototype of the plastic waste recycler and tested it on campus with several molds, creating usable products from non-recyclable waste.

The purpose of the natural gas aerator is to remove any potential harm that saturated gas can cause if left untapped. This project integrates new ideas in vacuum generation and noise mitigation to efficiently and safely remove the natural gas using only compressed air. The design uses the Venturi effect to create a vacuum strong enough to pull trapped natural gas from the ground. The aerator is designed to be modular, allowing for the use of different nozzles the team designed and tested using computational fluid dynamics software. The project focuses on delivering safe-to-handle materials, accessible and compatible auxiliary equipment, a powerful nozzle design for vacuum generation and noise mitigation, and a design that uses fully developed flow to lower noise emissions and provide optimal diffuser angles.

The increase in the availability and popularity of hobby unmanned aircraft has become a dangerous security issue for small private airports and concert arenas. The designed drone-detection system detects unmanned aircraft within 35 seconds and notifies system operators via PC so they can act to avoid the unmanned aircraft. The system displays the location of unmanned aircraft by giving the height and azimuth bearing of the unmanned aircraft relative to the system. The system covers a full 30-degree field of regard at up to 400 meters.The system uses a lidar rangefinder as the beam source and distance-measurement device for unmanned aircraft detection. Two motors scan the detecting beam across a 30-degree field of regard. The system sits atop an electrical box housing the microcontroller and support circuit used to power and steer the motors, as well as collect recordings from the lidar. The position and readings are output from the microcontroller to the user’s PC for verification and display on the graphical user interface. The software package is written in C++ and inputted into a Matlab script which generates a user-friendly display and interface for field use.

Raytheon conducts rapid prototyping on a large scale, so it needs away to quickly test the quality and reliability of its newly fabricated parts before use.The team developed a fully automated scanning system that measures and documents mandatory inspection points as defined by Raytheon’s part specifications. The system does this by creating a 3D model of the product, comparing it to an optimal model and finding significant differences between the models. This allows for identification of defects in real time and minimizes human error by cutting out touch-intensive processes, all while achieving equivalent accuracy to current industry practices.The user uploads a 3D model of the ideal part into Autodesk, then places their 3D-printed part onto the rotary table. The rotary table spins 360 degrees, and the structure sensor generates a 3D model of the part. The 3D scanner then communicates this model to Autodesk so that the software can compare the two models. After comparison, the system generates a data package to send to the user’s PC detailing how similar the actual product is to the ideal model.

The mesh network envisioned uses unmanned aircraft to deploy solar-powered beacons in regions lacking Wi-Fi or cellular coverage. Designing the beacons required analysis of battery life using solar panels, mechanical housing survivability and longevity of electronic components. The team prototyped and tested six beacons, all with minimal size and weight so they could be dropped by drone. A mobile application allows users to send emergency requests, display their location, and receive and display incoming responses from the main station. The main station is responsible for receiving and responding to emergency requests, monitoring the beacons and keeping a log of the system. The beacons are responsible for handling these requests. With no cellular service, the main station communicates with the beacons over the radio mesh network.

The ground-based optical target tracking system is an autonomous tracker designed to be used by two or more persons. The system tracks a full-size target vehicle moving at approximately 28 kilometers per hour at distances ranging from 100 to 300 meters. The system is composed of six principal parts: a camera, a PC, a microcontroller, a motor driver, a stepper motor and a laser pointer. The camera sends target images to the PC for image processing while the target remains in the camera’s field of view. The image-processing algorithm determines changes in target position between two separate images and converts this to an angle that the pointer must move to remain pointing at the target. The microcontroller receives the angle input and converts it to a frequency value to send to the stepper driver –while incorporating error values like time delay into the final frequency. The driver reads this value and produces a frequency pulse to drive the stepper motor. The stepper motor then rotates a turntable that the pointer is mounted to. The pointer remains on the target vehicle until it exits the camera’s field of view.