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\nArduino TCLab for Engineering Education\n

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\nThe Temperature Control Lab is a plug-and-play Arduino device to teach programming, heat transfer, machine learning, data science, process dynamics, and control with real data. Two heaters and an LED are adjusted with MATLAB or Python....\nThe Temperature Control Lab is a plug-and-play Arduino device to teach programming, heat transfer, machine learning, data science, process dynamics, and control with real data. Two heaters and an LED are adjusted with MATLAB or Python. Two temperature sensors show how much heat is transferred or lost. Thermochromic pigment turns pink when hot and black when it cools off. The take-home lab gives real data so that theory and methods come alive with concrete and tangible examples.

There is course material available to students and instructors thanks to efforts by many professors at universities around the world.

The first course that I’ll highlight is a module for Learning Python for Beginners - it starts at a very basic level to help beginners learn with a Hands-On lab experience.

A more advanced course is Python for Engineers. There are lab activities that help students discover principles of heat transfer by conduction, convection, and thermal radiation. As a culminating experience students use data science, regression, and data visualization to estimate heat transfer and thermal conductivity.

A process control module has activities to model dynamics with an energy balance, determine parameters from a first-order plus dead-time model, and use that model to create and tune a PID controller. There are MATLAB, Simulink, Python, and SimTune templates with detailed instructional videos to help any students along the way.

A final course that I’ll mention is a Machine learning and Dynamic Optimization course that covers advanced modeling, estimation, optimization, and predictive control. It uses deep learning and physics-based approaches to learn the relationship between the multivariate heater and sensor system.

The TCLab is transformative because it gives a take-home device to all students whether they are self-studying or in a large university course. It is hands-on with real data to put theory into practice. The National Science Foundation sponsored a report on Chemical Engineering Academia-Industry Alignment for Expectations about New Graduates. The report identifies a strong industrial need for practical understanding of process control and system dynamics. Industry feedback also suggested more weight on translating theory to practice in a way that is scalable for large class sizes.

I’m pleased to report that the TCLab has already had a big impact. A couple thousand TCLabs are in distribution already. The TCLab is available through distribution channels such as Amazon, Paypal, credit card, or with an invoice and purchase order. Instructors who are evaluating the lab can request a sample device. Several publications and presentations document the experience of instructors in their courses. Awards from the American Institute of Chemicals Engineers CAST division: the 2018 Computing Practice Award and the 2014 David Himmelblau Award for Innovations in Computer-Based Chemical Engineering Education, have recognized contributions to engineering education.

New inexpensive take-home labs are under development. I look forward to sharing in this collaborative effort with you to have a positive impact on engineering students around the world.

TCLab

Begin Python
Learn Scientific Python for Engineers
Process Dynamics and Control with TCLab
Machine Learning and Dynamic Optimization with TCLab\n
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Resource Details

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Not yet Rated
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Media Length
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3:40
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Grade
10th - Higher Ed
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Subjects
Math
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Media Type
Instructional Videos
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Source:
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\nAPMonitor.com\n\n
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Date
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2021
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Language
English
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Audiences
For Teacher Use
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Usage Permissions
Fine Print: Educational Use
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Concepts

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heat transfer, chemical engineering, engineers, hands, data science, coding
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matlab, tune, instructors, report, world, machine learning, process control, learn, order, tc lab, control, theory, activities, module, optimization, python, coder, model, students, engineer, advanced, distribution, programming, engineering education, beginners, excel, experience, programmers, home lab, real data
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