Bridging Theory and Practice: Digital Twin Simulation of a Heat Exchanger in Laboratories for Engineering Students

Digital twins serve as virtual replicas of physical systems. They can be used as a tool for engineering education by revealing the underlying principles behind unit operations. The project aimed to integrate digital twins into university engineering lab courses, complementing traditional methods by bridging the gap between experimentation and the underlying physical phenomena behind this unit operation. An intuitive application was created using Python, enabling Chemical Engineering students to perform computational fluid dynamics (CFD) simulations with Ansys while experimenting, connecting the app with the laboratory heat exchanger. Unlike conventional approaches limited to discrete temperature measurements, these simulations provided comprehensive visualizations of temperature profiles across the entire equipment. The app is successfully implemented, delivering reliable simulations that accurately reflect experimental conditions. One of the main challenges consists of the time‐intensive nature of the calculations, due to high computational demands. Despite this, this work shows that digital twins can help transform engineering education by incorporating digital solutions. This method could improve educational outcomes and could be extended to other unit operations, although improving computational efficiency will be necessary in future iterations. This project is presented as a technical infrastructure to enable future large‐scale educational assessment.