Board 30: Enhancing Core Chemical Engineering Courses with Computationally-Intense Course Modules
2018 ASEE Annual Conference & Exposition
This paper will present two new course modules that have been developed for junior-level Chemical Engineering core courses: Chemical Reaction Engineering and Chemical Engineering Thermodynamics II. As currently offered, both of these courses integrate simulation and computer lab activities in which students devise models of key physical systems, and then interrogate the model to study cause-and-effect in these physical systems. These activities are designed to be completed in one 165 minute lab period. While these labs are an integral part of the courses, the single-period scope limits the complexity of the models that can be used.
The course modules described in this paper were developed by XXX University undergraduate students as an Engineering Clinic project, and will be used for the first time during the Spring 2018 semester. The Chemical Reaction course module involves a rigorous mechanistic model of hydrocarbon pyrolysis, based upon a published mechanism. A single simulation using the model takes hours to run on a conventional modern PC. The project team executed numerous simulations spanning a range of values for key parameters such as temperature, reactant concentration and reaction time. These results will form the basis of an inductive class activity in which students (1) model the pyrolysis process using a simpler model that they are capable of developing in a single class period, (2) discuss the limitations of the model and how to develop a rigorous model, (3) qualitatively predict what the results from the rigorous model will look like and (4) see the actual results and compare with their predictions. The Chemical Engineering Thermodynamics II module, which was developed by the same Clinic project team and will be used in an analogous way, involves using the Wilson model for vapor-liquid equilibrium.
The Chemical Engineering course module development described here is a sub-project within an NSF-sponsored project to use high-performance computing and big data to enhance engineering curriculum.
Dahm, K. D., & Ramachandran, R. P., & Bouaynaya, N. C. (2018, June), Board 30: Enhancing Core Chemical Engineering Courses with Computationally-Intense Course Modules Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/30003
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