ABSTRACT

The digital twin of a physical system is an adaptive computer analog which exists in the cloud and adapts to changes in the physical system dynamically. This book introduces the computing, mathematical, and engineering background to understand and develop the concept of the digital twin. It provides background in modeling/simulation, computing technology, sensor/actuators, and so forth, needed to develop the next generation of digital twins. Concepts on cloud computing, big data, IoT, wireless communications, high-performance computing, and blockchain are also discussed.

Features:

  • Provides background material needed to understand digital twin technology
  • Presents computational facet of digital twin
  • Includes physics-based and surrogate model representations
  • Addresses the problem of uncertainty in measurements and modeling
  • Discusses practical case studies of implementation of digital twins, addressing additive manufacturing, server farms, predictive maintenance, and smart cities

This book is aimed at graduate students and researchers in Electrical, Mechanical, Computer, and Production Engineering.

chapter 1|20 pages

Introduction and Background

chapter 2|14 pages

Computing and Digital Twin

chapter 3|48 pages

Dynamic Systems

chapter 4|8 pages

Stochastic Analysis

chapter 5|28 pages

Digital Twin of Dynamic Systems

chapter 6|14 pages

Machine Learning and Surrogate Models

chapter 8|32 pages

Digital Twin at Multiple Time Scales

chapter 9|28 pages

Digital Twin of Nonlinear MDOF Systems