A Python-based lab module to conduct thermodynamic cycle analysis

A Python-based lab activity was developed for a remote Thermodynamics course to add computational thinking to traditional analytical problem solving. Python was selected to conduct the analysis because of its popularity and utility in the broader engineering field. Early exposure to this highly desired engineering skill can provide added benefits to students. Combining Python with an engaging lab experience can have a compounding effect on student learning outcomes. A five-week Python-based lab module was developed for an introductory thermal-fluid science class. The module reinforced fundamental concepts learned in lecture, while expanding on design-related analysis which is often left for advanced courses. The lab module began with an introduction to Python programming and quickly transitioned to the parametric analysis of standard Rankine, Gas Turbine, and Vapor Compression cycles. The lab module was designed to be self-guided with step-by-step instructions presented using Google Colab. This paper details the implementation and the student outcomes. Both direct and indirect assessments were conducted over two semesters of the course. Results indicate a strong positive impact on Python programming learning outcomes. Students acquired a working knowledge of Python programming and experienced how computational tools can be used to solve advanced engineering problems. At the same time, the student feedback indicated students' resistance to open-ended projects and independent learning; even if they are aware of their relevance and benefits to their future careers. Nevertheless, the positive learning outcomes were encouraging. Whether students pursue a career in thermodynamics or in a broader engineering field, this lab experience equipped them with tools that can augment their engineering skills.