http://mechatronics.ucmerced.edu/cosmos-DT/ (under construction)
Instructor
YangQuan Chen. Professor, Departments of Mechanical and Aerospace Engineering, UC
Merced (ychen53@ucmerced.edu) and Dr. Jie Yu, CEO, TwinMaker Analytics LLC
Coursework Prerequisites: The prerequisite for this class is calculus. Students should
also be somewhat familiar with vectors, matrices. Basic exposure to any programming
language is preferred, but not required. However, in an eTort to make this cluster inclusive,
students will be introduced to any relevant Matlab/Simulink programming, hardware-in-
the-loop simulation that is necessary, throughout the course via dedicated modules. It is
expected that students who are new to programming will complete required background
materials provided by the instructors.
Course Description: In the era of digital transformation driven by internet of things, big
data, edge/cloud computing, artificial intelligence/machine learning, cyber-physical human systems etc., digital twins are becoming a core technology that a modern engineer should have.
A digital twin (DT) is a digital representation of the physical asset or process with its behavior
matched to and information exchanged with its physical counterpart. Digital twin enables
awareness of performance and health of the physical twin so that the physical system can
become smarter than before. This 4 week course will prepare engineering oriented high school
students with digital twin basic concepts, digital twin fundamentals (modeling and system
identification, optimization, machine learning, behavior matching), digital twin construction
framework and deployment methods, digital twins enabled capabilities (performance and health
monitoring).
Feature: Very hands-on. Students will be given a MESABox for take home labs/projects.
Final Project: Build a digital twin of a mechatronic system
Field Trip: Tour of MESA (Mechatronics Embedded Systems & Automation) Lab at UCM
