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Board 30: Enhancing Core Chemical Engineering Courses with Computationally-Intense Course Modules

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

Page Count

7

Permanent URL

https://peer.asee.org/30003

Download Count

49

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Paper Authors

biography

Kevin D. Dahm Rowan University

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Kevin Dahm is a Professor of Chemical Engineering at Rowan University. He earned his BS from Worcester Polytechnic Institute (92) and his PhD from Massachusetts Institute of Technology (98). He has published two books, "Fundamentals of Chemical Engineering Thermodynamics" and "Interpreting Diffuse Reflectance and Transmittance." He has also published papers on effective use of simulation in engineering, teaching design and engineering economics, and assessment of student learning.

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biography

Ravi P. Ramachandran Rowan University

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Ravi P. Ramachandran received the B. Eng degree (with great distinction) from Concordia University in 1984, the M. Eng degree from McGill University in 1986 and the Ph.D. degree from McGill University in 1990. From October 1990 to December 1992, he worked at the Speech Research Department at AT&T Bell Laboratories. From January 1993 to August 1997, he was a Research Assistant Professor at Rutgers University. He was also a Senior Speech Scientist at T-Netix from July 1996 to August 1997. Since September 1997, he is with the Department of Electrical and Computer Engineering at Rowan University where he has been a Professor since September 2006. He has served as a consultant to T-Netix, Avenir Inc., Motorola and Focalcool. From September 2002 to September 2005, he was an Associate Editor for the IEEE Transactions on Speech and Audio Processing and was on the Speech Technical Committee for the IEEE Signal Processing society. Since September 2000, he has been on the Editorial Board of the IEEE Circuits and Systems Magazine. Since May 2002, he has been on the Digital Signal Processing Technical Committee for the IEEE Circuits and Systems society. His research interests are in digital signal processing, speech processing, biometrics, pattern recognition and filter design.

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biography

Nidhal Carla Bouaynaya Rowan University

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Nidhal Bouaynaya received the B.S. degree in Electrical Engineering and Computer Science from
the Ecole Nationale Superieure de L’Electronique et de ses Applications (ENSEA), France, in 2002, the
MS degree in Electrical and Computer Engineering from the Illinois Institute of Technology, Chicago, in
2002, the Diplome d’Etudes Approfondies in Signal and Image processing from ENSEA, France, in
2003, the M.S. degree in Mathematics and the Ph.D. degree in Electrical and Computer Engineering from
the University of Illinois at Chicago, in 2007. From 2007-2013, she was an Assistant then Associate Professor with the Department of Systems Engineering at the University of Arkansas at Little Rock. Since 2013, she joined Rowan University, where she is currently an Associate Professor with the Department of Electrical and Computer Engineering. Dr. Bouaynaya won the Best Student Paper Award in Visual Communication
and Image Processing 2006, the Best Paper Award at the IEEE International Workshop on Genomic Signal Processing and Statistics 2013 and the runner-up Best Paper Award at the IEEE International Conference on Bioinformatics and Biomedicine 2015. She is also one of the winners of the Brain Tumor Image Segmentation (BRATS) Challenge 2016. Her current research interests are in medical imaging, machine learning, mathematical biology and dynamical systems.

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Abstract

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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