Digital Twin : Fundamentals and Applications

• Autore: Sabri Soheil
• Pubblicazione: Cham : , : Springer, , 2025; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (273 pages)
• Altri autori: AlexandridisKostas LeeNewton
• Nota di contenuto: Intro -- Foreword -- Preface -- Acknowledgments -- Contents -- Contributors -- 1 Introduction to Digital Twins -- 1.1 Introduction -- 1.2 Digital Twin Evolution -- 1.3 Digital Twin Development Approaches -- 1.3.1 Digital Twin Systems of Systems -- 1.3.2 Model-Driven Engineering -- 1.4 Digital Twin Application Areas -- 1.5 Digital Twins in Institutional Context -- 1.6 Digital Twin Skill Set Development and Education -- 1.7 Discussion and Conclusions -- References -- 2 Fundamentals of Digital Twins, Modeling Approaches, and Governance -- 2.1 Introduction -- 2.2 Characterization -- 2.2.1 The ``Twin'' Concept -- 2.3 Enabling Technologies -- 2.4 Digital Twin Definition and Development-Key Considerations -- 2.5 Modeling the Digital Twin -- 2.5.1 Purely Physics-Based Modeling Approaches -- 2.5.2 Purely Data-Driven Modeling Approaches -- 2.5.3 Hybrid Approaches -- 2.5.4 Additional Modeling Considerations -- 2.6 Governance, Security, and Non-functional Aspects -- 2.7 Driving Policies and National Initiatives -- 2.8 Discussion and Conclusion -- References -- 3 DISCS: An Approach for Accelerating the Development of Digital Twins for Smart Cities -- 3.1 Introduction -- 3.2 The Smart City Innovation Space -- 3.2.1 Smart Cities and Digital Twin -- 3.2.2 Digital Twin -- 3.2.3 Testbeds -- 3.2.4 Living Labs -- 3.2.5 DISCS -- 3.2.6 Stakeholder and End-User Engagement -- 3.2.7 Security, Standards and Regulation -- 3.2.8 Data and Insights -- 3.2.9 Sustainability -- 3.2.10 Visualisation -- 3.2.11 Risks -- 3.2.12 Limitations -- 3.3 Four Potential Scenarios Within DISCS -- 3.3.1 Energy Management -- 3.3.2 Sustainable Mobility -- 3.3.3 Water Resource Management -- 3.3.4 Disaster Response -- 3.4 Digital Twins Tools -- 3.4.1 Digital Twin Capability Periodic Table -- 3.4.2 Digital Twin Platform Stack Reference Architecture -- 3.5 Architecting the Digital Twin System. ; 3.5.1 Scenario 1: Energy Management -- 3.6 Composed Digital Twin System Architecture -- 3.7 Conclusion -- References -- 4 A System of Systems Foundation for Digital Asset Lifecycle Management -- 4.1 Introduction -- 4.2 Reference Concepts -- 4.2.1 System of Systems -- 4.2.1.1 System of System (SoS) Characteristics -- 4.2.1.2 Difference Between Systems and System of Systems -- 4.2.2 Digital Twin Concepts -- 4.2.2.1 Digital Twin Origin -- 4.2.2.2 Asset Digital Twin. A System of Systems Approach -- 4.3 Reference Architecture for Digital Asset Lifecycle Management -- 4.4 SoS Foundation for Digital Asset Lifecycle Management -- 4.4.1 Oil and Gas Assets Characteristics, Complexities and Challenges -- 4.4.2 Enabling Strategies -- 4.4.3 Enabling Systems -- 4.4.4 SoSDT Data and Information Links -- 4.4.5 System of Systems Engineering -- 4.4.6 SoSDT for DALM Requirement Specification Overview -- 4.4.6.1 Business/Enterprise Requirement Specification -- 4.4.6.2 Stakeholders Needs and Requirement Specification -- 4.4.6.3 System Requirement Specification -- 4.4.6.4 Verification and Validation -- 4.5 Innovative Operation and Business Models -- 4.6 Use Case Example: Digital Lifetime Management of Subsea Production Systems -- 4.7 Discussions and Conclusions -- References -- 5 Model-Based Engineering of Multi-Purpose Digital Twins in Manufacturing -- 5.1 Introduction -- 5.2 Background and Related Work -- 5.2.1 Definitions and Background -- 5.2.2 State-of-the-Art in Modeling and Model-Driven Engineering of Digital Twins -- 5.2.2.1 Reference Architectures for Digital Twins -- 5.2.2.2 Model-Driven Engineering -- 5.2.2.3 Modeling of Digital Twin Architectures -- 5.2.2.4 Model-Driven Engineering of Digital Twins -- 5.2.3 Used Technology Stack -- 5.3 Reference Architecture Components of Digital Twin. ; 5.4 Model-Driven Engineering of Digital Twins: How to Derive Innovative Products -- 5.5 Exemplary Use Cases for a Digital Twin in Injection Molding -- 5.6 Discussion -- 5.6.1 Relation to Reference Architectures and Main Concepts -- 5.6.1.1 Digital Twin Consortium Reference Architecture -- 5.6.1.2 RAMI 4.0 and the Asset Administration Shell -- 5.6.1.3 ISO-23247-Digital Twin Framework for Manufacturing -- 5.6.1.4 Other Approaches -- 5.6.2 Model-Driven and Low-Code Approaches for Digital Twins -- 5.6.3 Digital Twins in the Life Cycle of the System -- 5.7 Conclusion -- References -- 6 Digital Twins for Assessing the Impact of Autonomous Vehicles on Built-Environment Changes -- 6.1 Introduction -- 6.2 Literature Review -- 6.2.1 An Overview on the Impact of AVs on BEs -- 6.2.2 Data Used for Assessing the Impact of AVs on BEs -- 6.2.3 Analysis Methods Used for Assessing the Impact of AVs on BEs -- 6.2.3.1 Modeling, Simulation, and Analytics -- 6.2.3.2 The Application of AI and ML -- 6.2.4 Issues in the Existing Literature -- 6.3 Digital Twins for Urban Transport Planning and Autonomous Vehicles -- 6.3.1 Digital Twin for Autonomous Vehicles -- 6.4 Creating a System to Support Decision-Making -- 6.4.1 Requirement to Create a Digital Twin for Assessing the Impact of AVs on BEs -- 6.5 Discussion and Conclusion -- References -- 7 Human Digital Twins to Support Nurse Practitioners' Clinical Decision-Making Using Multimodal Data: A Theoretical, Methodological, and Analytical Framework -- 7.1 Extending the Current Landscape of Digital Twins and Human Digital Twins -- 7.2 Nurse Practitioners' Clinical Decision-Making (CDM) and Human Digital Twins at the Human-Technology Frontier -- 7.2.1 Future Nurse Practitioners -- 7.2.2 Future Work -- 7.2.3 Future Technology. ; 7.3 Integrative Interdisciplinary Research Approach to Designing, Testing, and Implementing Human Digital Twins of Expert Human Preceptors -- 7.3.1 Co-design and Development of DTHEPs -- 7.3.2 Test the Effectiveness of the HDT Preceptor on NPs' Clinical Decision-Making Skills and Other Outcomes -- 7.4 Conclusions and Future Work -- References -- 8 Conceptualising the Application of Digital Twins in Supply Chain Management: A Path Towards Supply Chain Resilience -- 8.1 Introduction: Understanding the Real-World Problem of Supply Chain Disruption -- 8.2 Defining Digital Twin -- 8.3 Unpacking Supply Chain Resilience -- 8.3.1 Case Study: XMPro -- 8.3.2 Case Study: Supply Chain Disruption in the Healthcare Sector due to Climate Change -- 8.4 The Value of Digital Twin in Creating Supply Chain Resilience -- 8.5 Conclusion -- References -- 9 Digital Twins for Creating Value Through ``Buildings as Batteries'' Using a Mass Customization Network -- 9.1 Introduction -- 9.2 Literature Review -- 9.2.1 Smart Grids -- 9.2.2 Buildings as Batteries and P2P Energy Trading -- 9.2.3 Distributed Energy Grid Challenges -- 9.2.4 Digital Twins and Smart Grids -- 9.2.5 Critical Analysis of the Current Studies -- 9.3 Buildings as Batteries -- 9.3.1 Developing a Business Support System -- 9.3.2 The 2030 Districts Website: Navigating to the Fractal Marketplace -- 9.3.3 Building a Composable Digital Twin for the Sample MCN -- 9.3.4 Building the Operational Support System -- 9.4 Discussion and Conclusion -- Appendix: Glossary of Acronyms -- References -- 10 Social and Human Dimensions of Digital Twin Technologies in Formal and Informal Institutional Settings -- 10.1 Introduction -- 10.1.1 Framing Opportunities and Challenges -- 10.1.1.1 Conceptional and Design Considerations -- 10.1.1.2 Data Management and Data Science -- 10.1.1.3 Operational and Engineering Workflows. ; 10.1.1.4 Data Analytics and Visualization -- 10.1.1.5 Programming and Analysis Workflows -- 10.1.1.6 Collaborations and Broad Partnerships -- 10.2 Institutional Settings and Digital Twins -- 10.2.1 Formal vs. Informal Institutional Change -- 10.2.2 Institutional Framework for Digital Twins -- 10.3 Addressing the Digital Divide -- 10.3.1 Digital Twin Capacity and Capability Framework -- 10.3.2 Digital Divide in Context -- 10.4 Operationalizing Digital Twin Governance -- 10.4.1 Inclusiveness, Equality, and Empowerment -- 10.4.2 Citizen Participation from the Ground-Up -- 10.5 Discussion and Conclusions -- 10.5.1 Guiding Principles for Digital Twin Development -- 10.5.2 Conclusions -- References -- 11 Digital Twins and Their Role in Reengineering Engineering Education -- 11.1 Introduction -- 11.2 The Rise of Digital Twins -- 11.2.1 Types of Digital Twins -- 11.2.2 Digital Twins and Simulations -- 11.3 Digital Transformation -- 11.4 Black, White, and Grey Box Problem Solving -- 11.5 Current State of University Education -- 11.5.1 Not Adequately Preparing Graduates for Jobs in Industry -- 11.5.2 No Room in Courses for New Capabilities -- 11.5.3 Courses that Unnecessarily Weed Out Engineering Students -- 11.6 Reengineering Engineering Curriculums -- 11.6.1 Industry Involvement in Curriculum -- 11.6.2 Digital Twin and Digital Transformation Freshman Survey Class -- 11.6.3 Integrate Math Into Engineering -- 11.6.4 Engineering and the Ilities: Multidisciplinary and Integrative -- 11.6.5 Knowledge ``I'' Model Versus ``T'' Model in Engineering Education -- 11.6.6 Flipped Classroom -- 11.6.7 Stacked DT Certificates -- 11.6.8 Internships -- 11.7 Conclusion -- Appendix -- References -- Index.
• Titolo autorizzato: Digital Twin
• ISBN: 9783031677786; 3031677781
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910917790603321
• Lo trovi qui: Univ. Federico II