TEXAS A&M INSTITUTE OF DATA SCIENCE

Digital Twin Lab

VIZA 689 (Spring 2024)

Introduction to Digital Twin Technologies

Course Title: SPTP: DIGITAL TWIN TECHNOLOGIES

CRN: 50972
Time: MW 3:00pm – 4:40pm
Location: ARCC 414
Credit Hours: 3

Spring 2024 (01/16/2024 – 05/07/2024)

Description

A digital twin is a virtual representation of real-world entities and processes, synchronized at a specified frequency and fidelity. The concept of digital twins can be traced back to the numerical simulation of physical systems, where theory/data-driven methodologies are adopted to make predictions and optimize physical systems. With the rapid development of sensing, communication, and computing technologies, digital twins have been developed and used to simulate real-world conditions with real-time data, improve operations, and enable optimizations at various scales.

This course will give a comprehensive introduction to digital twins and the technologies to make them possible. Specifically, the course will briefly introduce the tools and techniques for creating representation models and user interfaces for digital twins. It will also cover the basics of the Internet of Things, data science, and theory/data-driven modeling methods that make digital twins useful in practice. The project-based learning method will be adopted throughout this course. The course will be offered as a combination of lectures and lab sessions, providing an intensive and immersive learning environment. Students will work on challenging projects in groups, which engage them in solving problems and working in teams. 

Prerequisites

Familiar with a programming language, such as Python or C++, and capable of finishing assignments with the language in other courses.

Learning Outcomes

Upon the completion of the course, in addition to mastering the concepts and methodology behind digital twins, students should be able to:

  • Use the Unreal Engine and/or other technologies to create simple visual representations for digital twins,
  • Apply machine learning and data analysis techniques to create data-driven models,
  • Integrate the output from theory-driven models for real-time simulations,
  • Use the Internet of Things (IoT) to collect and publish data, and
  • Develop teamwork skills in a multidisciplinary environment.

Textbook and/or Resource Materials

All the materials will be provided. 

Some useful links:

Course Schedule

WeekTopicProject Timeline
1Progress Report #1Select projects and form teams
2Reference models of digital twinsPresent initial concept
3Visual representation of digital twins
4Design and development of UI/UX for digital twinsDigital twin development
5Collecting and connecting data to the visual representation of a digital twinInternet of Things (IoT) and information-sharing frameworks 
6Progress Report #2Testing
7Midterm presentation of projectsPresent project
8Data management and analytics
9Data-driven modeling and machine learning for digital twinsDigital twin development
10Real-time simulation for digital twinsCase studies with real-world digital twin applications
11Digital thread
12Deployment of digital twinTesting
13Case studies with real world digital twin applications
14Final presentation of projectsPresent project
15Wrapup the courseFinal report