Abstract
UCL Chemical Engineering ensures graduates are digitally literate by integrating computational tools like gPROMS, Aspen Plus, and GAMS into the undergraduate curriculum. Students in the first year of undergraduate program use GAMS to solve simple simulation and optimization problems and gPROMS for solving ordinary differential equations (ODEs) in reactor design problems. In the second year, students start using Aspen Plus to simulate more complex chemical process units, interpret and discuss results obtained and justify any differences observed between experimental data and computational results. They use GAMS to simulate and optimize a process flowsheet with considerations of the implications of proper initialization procedures and strategies for obtaining optimal parameters and gPROMS for advanced reactor and separator problems. The computational knowledge acquired in the first two years prepares students for the third-year capstone design project where they use the various tools in designing and simulating their processes during the preliminary, conceptual and detail designs. The computational resources available to students and the additional supports provided by educators help the students succeed on the design project in the third year. This work outlines strategies for delivering the computational tools required for modules in the first two years of the undergraduate program and the application of the knowledge in the third-year design project. It demonstrates how complex process systems engineering (PSE) problems are taught, student support and resources available, and feedback for continuous improvement. It presents some challenges faced due to the use of generative AI tools and how this can be addressed.