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ganguli ranjan; adhikari sondipon; chakraborty souvik; ganguli mrittika - digital twin
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Digital Twin A Dynamic System and Computing Perspective

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

CRC Press

Pubblicazione: 04/2023
Edizione: 1° edizione





Note Editore

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.




Sommario

Chapter 1 Introduction and Background1.1 Introduction1.2 Modeling and Simulation1.3 Sensors and Actuators1.4 Signal Processing1.5 Estimation Algorithms1.6 Industry 4.01.7 Applications Chapter 2 Computing and Digital Twin2.1 Digital Twin Use cases and the Internet of things (IOT)2.2 Edge Computing2.3 Telecom and 5G2.4 Cloud2.5 Big Data2.6 Google Tensorow2.7 Blockchain and digital twin Chapter 3 Dynamic Systems3.1 Single-degree-of-freedom undamped systems3.2 Single-degree-of-freedom viscously damped systems3.3 Multiple-degree-of-freedom undamped systems3.4 Proportionally damped systems3.5 Non-proportionally damped systems3.6 Summary Chapter 4 Stochastic Analysis4.1 Probability theory4.2 Reliability4.3 Simulation methods in UQ and reliability4.4 Robustness Chapter 5 Digital Twin of Dynamic Systems5.1 Dynamic model of the digital twin5.2 Digital twin via sti ness evolution5.3 Digital twin via mass evolution5.4 Digital twin via mass and sti ness evolution5.5 Discussions5.6 Summary Chapter 6 Machine learning and Surrogate Models6.1 Analysis of Variance Decomposition6.2 Polynomial Chaos Expansion6.3 Support Vector Machines6.4 Neural Networks6.5 Gaussian Process6.6 Hybrid polynomial correlated function expansion Chapter 7 Surrogate based digital twin of dynamic system7.1 The dynamic model of the digital twin7.2 Overview of Gaussian process emulators7.3 Gaussian process based digital twin7.4 Discussion7.5 Summary Chapter 8 Digital Twin at Multiple Time Scales8.1 The problem statement8.2 Digital twin for multi-timescale dynamical systems8.3 Illustration of the proposed framework8.4 Summary Chapter 9 Digital twin of nonlinear MDOF systems9.1 Physics based nominal model9.2 Bayesian ltering algorithm9.3 Supervised machine learning algorithm9.4 High delity predictive model9.5 Examples




Autore

Dr. Ranjan Ganguli is currently a Senior Research Engineer at Viasat Inc. in Phoenix, USA. He received his MS and PhD degrees from the Department of Aerospace Engineering at the University of Maryland, College Park, USA in 1991 and 1994, respectively, and his B.Tech degree in Aerospace Engineering from the Indian Institute of Technology, Kharagpur, in 1989. He was a Professor in the Aerospace Engineering Department of the Indian Institute of Science, Bangalore from 2000-2021. He worked in Pratt and Whitney on engine diagnostics using machine learning during 1998-2000. He has completed sponsored research projects for companies such as Boeing, Pratt and Whitney, Honeywell, HAL and others. His research is published in refereed journals and conferences. He has authored books titled "Isospectral Vibrating Systems", "Gas Turbine Diagnostics", and "Engineering Optimization", among others. He is a Fellow of the American Society of Mechanical Engineers, an Associate Fellow of the American Institute of Aeronautics and Astronautics, a Senior Member of the IEEE and a Fellow of the Indian National Academy of Engineering. He also received the Alexander von Humboldt Fellowship and the Fulbright Fellowship in 2007 and 2011, respectively. He has held visiting scientist positions in Germany, France and South Korea. Sondipon Adhikari holds the position of Professor of Engineering Mechanics at the James Watt School of Engineering of the University of Glasgow. He received his PhD as a Jawaharlal Nehru Memorial Trust scholar at the Trinity College from the University of Cambridge. He was awarded the prestigious Wolfson Research Merit Award from the Royal Society (UK academy of sciences). He was an Engineering and Physical Science Research Council (EPSRC) Advanced Research Fellow and winner of the Philip Leverhulme Award in Engineering. He was the holder of the inaugural Chair of Aerospace Engineering at the College of Engineering of Swansea University. Before that, he was a lecturer at Bristol University and a Junior Research Fellow in Fitzwilliam College, Cambridge. He was a visiting Professor at the Ecole Centrale Lyon, Rice University, University of Paris, UT Austin, IIT Kanpur and a visiting scientist at the Los Alamos National Laboratory. Professor Adhikari’s research areas are multidisciplinary and include uncertainty quantification in dynamic systems, computational nano-mechanics, dynamics of complex systems, inverse problems for linear and non-linear dynamics and vibration energy harvesting. He has published five books, more than 350 international journal papers and 200 conference papers in these areas. Professor Adhikari is a Fellow of the Royal Aeronautical Society, an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and a member of the AIAA Non-Deterministic Approaches Technical Committee (NDA-TC). He is a member of the editorial board of several journals such as Advances in Aircraft and Spacecraft Science, Probabilistic Engineering Mechanics, Computer and Structures and Journal of Sound and Vibration. Dr. Souvik Chakraborty is currently working as an Assistant Professor at the Department of Applied Mechanics, IIT Delhi. He also holds a joint faculty position at the Yardi School of Artificial Intelligence, IIT Delhi. Dr. Chakraborty’s research spans across a wide variety of topics including Scientific Machine Learning (SciML), stochastic mechanics, uncertainty quantification, reliability analysis, design under uncertainty, and Bayesian statistics, and has published over 55 articles in peer reviewed journals. Dr. Chakraborty received his PhD degree from Indian IIT Roorkee in 2017, and B. Tech and M. Tech degree from National Institute of Technology Durgapur and Bengal Engineering and Science University Shibpur (currently known as Indian Institute of Engineering Science and Technology Shibpur) in 2010 and 2013, respectively. Prior to joining IIT Delhi in 2020, he has worked as a postdoctoral researcher at University of Notre Dame, U.S.A. and University of British Columbia, Canada from 2017 – 2019. Mrittika Ganguli is a Principal Engineer and Director, Cloud Native Pathfinding in Intel’s Network and Edge Architecture (NEX OCTO) team. She has 25+ years of experience in cloud hardware and software management, network and storage processing control and data plane, cloud orchestration, telemetry QOS and scheduling Architecture. She is active in CNCF and Open Infra opensource initiatives and initiated a Service Mesh Performance (SMP) index called Meshmark. She has a MS in CS and 70+ patents and multiple IEEE papers in this area.










Altre Informazioni

ISBN:

9781032213620

Condizione: Nuovo
Dimensioni: 9.25 x 6.25 in Ø 1.39 lb
Formato: Copertina rigida
Illustration Notes:78 b/w images, 5 tables, 2 halftones and 76 line drawings
Pagine Arabe: 240
Pagine Romane: xii


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