Digital Twin
Regular price
€61.50
A01=ittika Ganguli
A01=Ranjan Ganguli
A01=Sondipon Adhikari
A01=Souvik Chakraborty
additive manufacturing systems
advanced digital twin modeling applications
Age Group_Uncategorized
Age Group_Uncategorized
Author_ittika Ganguli
Author_Ranjan Ganguli
Author_Sondipon Adhikari
Author_Souvik Chakraborty
automatic-update
Category1=Non-Fiction
Category=UYM
Category=UYW
cloud analytics
computational engineering
Computing
COP=United Kingdom
Covariance Kernel
Cumulative Distribution Function
Delivery_Pre-order
Digital Twin
Direct Monte Carlo Simulation
Edge Computing
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Fiber Bragg Grating Sensor
Freedom Systems
GP Emulator
GPR Model
IoT
Kalman Filter
Language_English
Limit State Function
Modeling
Natural Frequency
Nominal Model
Nonlinear MDOF Systems
Observation Time Window
PA=Not yet available
PCE
Physical Twin
predictive maintenance methods
Price_€50 to €100
PS=Forthcoming
SDOF System
sensor integration
Sigma Points
Signal Processing
SMC Sampler
softlaunch
SS
Stiffness Evolution
Stochastic Analysis
Surrogate Models
UKF
UKF Algorithm
uncertainty quantification
Unobserved Regime
White Gaussian Noise
Product details
- ISBN 9781032213637
- Weight: 470g
- Dimensions: 156 x 234mm
- Publication Date: 29 Nov 2024
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
- Language: English
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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:
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- Provides background material needed to understand digital twin technology
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- Presents computational facet of digital twin
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- Includes physics-based and surrogate model representations
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- Addresses the problem of uncertainty in measurements and modeling
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- 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.
Ranjan Ganguli, Mrittika Ganguli
