(232d) Reinforcing Computational Thinking throughout Chemical Engineering Curriculum with Matlab and Simulink | AIChE

(232d) Reinforcing Computational Thinking throughout Chemical Engineering Curriculum with Matlab and Simulink


Rao, S., MathWorks
Chemical engineering students learn various computational tools either in dedicated programming courses offered by chemical engineering departments and in mass courses offered by other departments. Some of the computational tools and programming languages used in chemical engineering programs are AspenPlus, ChemCAD, HYSYS, MATLAB, Python, C, C++, FORTRAN. MATLAB is a high-level technical computing language and Simulink is a graphical environment to design, simulate and test systems. MATLAB and Simulink are widely used in industry and academia. Industrial user stories/videos on how MATLAB is used in chemical engineering applications will be discussed as an instruction tool to motivate students learn programming and create a vision of what students can do with computational tools when they join the workforce.

Using computational tools frequently throughout to curriculum helps students retain their computational skills. This talk describes examples of how MATLAB and Simulink can be integrated to fluid dynamics, heat transfer, reaction kinetics, mass and energy balances, process control curriculum and how computation can be introduced in introductory chemical engineering courses with free, self-paced, online tutorials created by MathWorks.

Offering students hands-on, laboratory experience is crucial for chemical engineering education. Novel technologies such as “Internet of Things” help students gain hands-on experience by accessing data from remote devices. ThingSpeak is an Internet of Things (IoT) platform with MATLAB analytics. With ThingSpeak, programming, hardware and data analysis with real-world data can be introduced to chemical engineering laboratory courses as well as statistics/data analysis courses. With interactive machine and deep learning apps in MATLAB chemical engineering students can rapidly gain data science skills that are on high demand and instructors can apply flipped classroom techniques using self-paced, free Machine Learning and Deep Learning tutorials developed by MathWorks. Project-based learning can easily be introduce to chemical engineering curriculum with hardware projects based on ThingSpeak and MATLAB Mobile.

With growing classroom sizes, offering fast feedback to students become challenging in programming assignments. To address this challenge, MathWorks developed an automated grading tool, MATLAB Grader. Use of MATLAB Grader to assess chemical engineering programming problems will be demonstrated and tools to create interactive lecture content (MATLAB Live Editor) will be reviewed. A self-paced tutorial to train instructors and teaching assistants on teaching and learning tools created by MathWorks will be presented.


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