Integrating AI-Enabled, Student-Created Design Projects in Fluid Mechanics and Mechanical Design Courses

Proceedings (Faculty180)

cited authors

  • Cioc, Carmen; Cioc, Sorin; Haughton, .. A

description

  • <p>Abstract: </p> <p>This paper describes the recent design and implementation of two AI-enabled midterm projects developed for upper-level Mechanical Engineering Technology (MET) courses in Applied Fluid Mechanics (MET 4100), and Mechanical Design II (MET 4200). The projects, done individually or in groups, were designed to enhance critical thinking, design learning, and responsible use of emerging tools. Both projects positioned students as problem creators rather than solely problem solvers, requiring them to generate and analyze engineering systems using AI tools of their choice in combination with computational software (Excel, HydroFlo, MATLAB, etc.).</p> <p>In MET 4100, students designed and analyzed real-world pipeline systems for water. Each team used AI to develop design scenarios, perform head-loss and energy analyses, select pumps or turbines from manufacturer data, and evaluate economic performance and optimization strategies. In MET 4200, students used AI to create unique shaft design problems involving power transmission, material selection, and loading conditions. In both cases, students were also asked to compare the AI-generated solutions with their own solvers developed using the technical knowledge gained in class, and to participate in a structured peer review evaluating the clarity and accuracy of their classmates’ work.</p> <p>Results show that most students viewed AI integration positively, while a small but notable subset expressed skepticism. Additionally, several students experimented with using AI to help in the peer review process, revealing both innovative and problematic uses of the technology for evaluation.</p> <p>Overall, students improved their ability to connect theory with computation and increased their awareness of AI’s limitations. The projects also highlighted the need for explicit guidance on AI ethics, verification, and boundaries of appropriate use. Together, these experiences illustrate a scalable approach to developing AI literacy, engineering judgment, and reflective practice across the MET curriculum.</p>

authors

publication date

  • 2026

presented at event