Digital Twin: A Dynamic System and Computing Perspective

Digital Twin

A Dynamic System and Computing Perspective
 
Edition number: 1
Publisher: CRC Press
Date of Publication:
 
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Product details:

ISBN13:9781032213620
ISBN10:10322136211
Binding:Hardback
No. of pages:252 pages
Size:234x156 mm
Weight:440 g
Language:English
Illustrations: 78 Illustrations, black & white; 2 Halftones, black & white; 76 Line drawings, black & white; 5 Tables, black & white
613
Category:
Short description:

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.

Long description:

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.

Table of Contents:
1. Introduction and Background. 2. Computing and Digital Twin. 3. Dynamic Systems. 4. Stochastic Analysis. 5. Digital Twin of Dynamic Systems. 6. Machine learning and Surrogate Models. 7. Surrogate based digital twin of dynamic system. 8. Digital Twin at Multiple Time Scales. 9. Digital twin of nonlinear MDOF systems.