DCU Expo 2023 Final Year Projects

92 198. Investigate the Current Structural Safety Analysis for Overhead Electricity Poles to Improve the Structural Analysis Accuracy and Efficiency The project investigates the current calculators used to determine the structural safety of overhead electricity poles. It includes a static analysis to validate the current model as well as a calculator remodel with updates and recommendations of possible neglected factors. It studies if the current calculators are justifiable and where revisions may need to be made. Class Mechanical andManufacturing Engineering (Year 4) Project Area Telecommunications, Mechanical Structural Analysis Project Technology Excel/VB Student Name(s) Emily O’Reilly Email emily.oreilly54@mail.dcu.ie Supervisor Dr Paul Young 199. Carpooling4Students A carpooling application designed towards students traveling to campus daily. The idea is to pair those that already drive to the campus with those in similar locations or along driving routes over an official interface to create the carpooling experience. We look to create a web-based application with an optimal front end designed towards a user-friendly interface. We hope to integrate the GoogleMaps API into our code based and work with its functionality to bring amore illustrative look to our application. Class Enterprise Computing Project Area Data Analytics, Device Design, Environmental Mapping, GPS/GIS, Internet of Things, Network Applications, Social Networking, Software Development, Web Application Project Technology HTML5, Java, JavaScript, MySQL, Python, SQL, Django Student Name(s) Luke Nolan  |  AdamThorpe Email luke.nolan45@mail.dcu.ie   |  adam.thorpe2@mail.dcu.ie Supervisor Dr JohnMcKenna 200. Study on theModelling of a Particle Lift Off and Loss aroundWeld Spot in AdditiveManufacturing Process This study investigates lift and particle loss around weld spots during additive manufacturing. Simulation results show that particle lift-off and loss are affected by several factors, including laser power and noble gas inlet velocity. The model predicts the formation of a cloud of particles around the weld spot, followed by loss of particles due to gravity and airflow. Challenges associated with particle dispersion modelling are discussed, such as accurately capturing complex fluid dynamics and interpreting complex particle- particle and particle-bed pressure interactions. Finally, the potential of usingmachine learning techniques to optimize printing process parameters and reduce defects is discussed. Class Mechanical andManufacturing Engineering (Year 5) Project Area 3-DModelling, AdditiveManufacturing, FluidMechanics, Simulation Project Technology ANSYSWorkbench Student Name(s) Prince Tony Email prince.tony2@mail.dcu.ie Supervisor Dr CornéMuilwijk