Free and Open-Source Teaching: Understanding Exergy Using Thermal Engineering Systems in Python (TESPy)

Abstract

In energy or chemical engineering, a representation of highly complex processes is often only possible through a simulation. Conducting experiments or building demonstrators is far too costly and time-consuming. Applying exergy-based methods is beneficial to reveal thermodynamic inefficiencies and to propose appropriate optimization approaches for energy conversion processes. Therefore, teaching theory and software-based application of such methods are essential in engineering study programs. This paper presents a didactic concept for open educational resources on exergy analysis covering the introduction to the exergy method, its distinction from the energy analysis, and its application to various case studies. The course aims to combine thermodynamic understanding with numerical mathematics and object-oriented programming. Students learn to build and run models of energy conversion systems and conduct respective exergy analyses using the software Thermal Engineering Systems in Python (TESPy). The course material is developed using Jupyter notebooks, which offer a flexible connection between theory and code. Results are reproducible and can be tested and developed further by the open-source community. The advantages of exergy-based methods can be illustrated by evaluating and visualizing real thermodynamic losses using Grassmann or waterfall diagrams. Process understanding can be deepened further by parameter analysis showing their impact on components and the overall process. Finally, the acquired knowledge is transferred to more complex problems with multiple components or more than one product.