2023 ASEE Annual Conference & Exposition

This is a work in progress aiming to provide a more accessible and efficient approach for studying complex reactor engineering models and associated correlations where the theory, governing model equations, working program code, interactive results, and explanations are all embedded in one medium framework: Jupyter Notebook using Python code. As a starting point, a case study is selected in such a way that it has significant interest from both the reactor model complexity and the application to demonstrate the proposed approach. The case study is a gas-liquid multiphase microreactor model used for studying CO2 capturing with amine-based absorption. The approach is presented as a tutorial format consisting of three sections. The input section provides all necessary background information; the second section is the reactor model and a list of engineering correlations for hydrodynamics, mass transfer, and reaction kinetics; and the final section is the quantified interactive review with sensitivity and evaluation studies. Going through the tutorial as offered in Jupyter notebook, enable asynchronous learning which can be powerful to enhance the learning process and best utilize classroom time. At this stage, the tutorial content has been established but not yet offered and evaluated as part of typical classroom education. What has been done, is offering this tutorial to 5 chemical engineering undergraduate students researching a similar topic, but they did not have a background in reactor modeling and had basic knowledge in Python. Feedback from their study experience has been captured on a one-to-one basis and will be presented in this work. The next plan is to offer this tutorial as an assignment as part of the undergraduate chemical reactor engineering course. Once the evaluation and assessment have been carried out and are successful, the approach can be expanded to cover other reactor types and applications in the future.