2026 ASEE Annual Conference & Exposition

Many engineering students have struggled while taking a thermodynamics course. Students often find the process of determining thermodynamic properties, particularly for substances either experiencing or near a phase transition (such as water/steam and refrigerants), to be confusing and difficult to learn. Struggles with finding thermodynamic properties will result in difficulties for the students when they are working to solve a first law or second law analysis problem, thereby hindering their mastery of those topics as well.

Historically, properties for substances like steam were found using graphs or tables of the property data. More recently, computer programs, Internet websites, and smartphone apps have become readily available to students and engineers for finding property data. This often makes finding the property data easier, but reliance on this method can be problematic when one is using a substance for which property calculation software has not been developed. Much more recently, the possibility of using AI tools such as ChatGPT has become available for finding property data. This has the potential of making finding property data on a larger number of substances easier.

Each of these techniques for finding thermodynamic properties have advantages and disadvantages, both from a pedagogical sense and a user viewpoint. In this paper, these techniques are summarized and the benefits and detriments of each will be explored. Additionally, the results of preliminary trials using AI tools to find thermodynamic property data are presented. Initial work with AI tools has revealed many problems that make the use of AI tools for finding thermodynamic properties unable to be recommended at this time.