Digital Twin Technologies in Transportation Infrastructure Management

Preface
Contents
Abbreviations
Chapter 1: Introduction to Digital Twin Technologies in Transportation Infrastructure Management (TIM)
	1.1 Definition and Concept of Digital Twin
		1.1.1 The History and Evolution
		1.1.2 Literature Review
	1.2 Transportation Infrastructure Management
		1.2.1 The History and Evolution
		1.2.2 Technological Development in Transportation Infrastructure Management
	1.3 Digital Twin in TIM
	1.4 The Benefits and Potential Impact of Digital Twins on TIM
	1.5 The Current State of Digital Twins Technology in Transportation Infrastructure and Future Developments
	1.6 Integration of Digital Twins with Other Emerging Technologies in TIM
	1.7 Emerging Needs and Challenges to Digital Twin in TIM
		1.7.1 Emerging Needs
		1.7.2 Challenges in Digital Twin
		1.7.3 Challenges in TIM
	1.8 Incompatibilities of DT in TIM
	1.9 Summary
	References
Chapter 2: Digital Twins Technologies
	2.1 Digital Twin
		2.1.1 Types of Digital Twin
		2.1.2 Digital Twin Aspects
		2.1.3 Characteristics of Digital Twin Technology
	2.2 Technologies and Platforms
		2.2.1 Building Information Model (BIM)
			2.2.1.1 Introducing BIM Application in TIM/Civil Engineering
			2.2.1.2 How Does BIM Support Digital Twin?
		2.2.2 Artificial Intelligence Within DT
		2.2.3 Cyber-Physical System
			2.2.3.1 CPS Concept and Characteristics
		2.2.4 Sensors
	2.3 Data and Digital Twin Technologies
		2.3.1 Data Management
		2.3.2 Data Integration
		2.3.3 Data Sources and Collection Methods
		2.3.4 Data Collection Tools
		2.3.5 Data Integration and Management Challenges
	2.4 Model Component Integration
	2.5 Implementation of Digital Twin Technology
		2.5.1 Design Stage
		2.5.2 Production Stage
		2.5.3 Service Stage
		2.5.4 Challenges to Implement Digital Twin
	2.6 Digital Twin Technology Deployment Strategies
	2.7 Best Practices and Guidelines for Digital Twin Technology Deployment
	2.8 Applications of Digital Twins
	2.9 Summary
	References
Chapter 3: Transportation Infrastructure Management
	3.1 What Is TIM?
		3.1.1 Planning
		3.1.2 Design
		3.1.3 Construction and Maintenance
		3.1.4 Project Management
		3.1.5 Sustainability and Resilience
	3.2 Importance of TIM
		3.2.1 Characteristics of Transportation Infrastructure
		3.2.2 The Multiple Impacts of Transportation Infrastructure
		3.2.3 Goals of Transportation Infrastructure Management
	3.3 Modeling Approaches
		3.3.1 Physical Modeling
		3.3.2 Analytical Modeling
		3.3.3 Digital Twin Modeling
		3.3.4 Empirical Approach
		3.3.5 Agent-Based Simulation Approaches (ABM)
		3.3.6 System Dynamics Approach
		3.3.7 Economic Theory-Based Approaches
		3.3.8 Network-Based Approaches
	3.4 Applications of Modeling and Simulation in TIM
	3.5 Inventory
	3.6 Life Cycle Assessment for TIM
	3.7 Computer-Aided Technologies for TIM
	3.8 Challenges and Limitations
	3.9 Recent Advancements and Some Examples
	3.10 Summary
	References
Chapter 4: Digital Twin in TIM
	4.1 Introduction to Digital Twin in TIM
		4.1.1 Planning and Design
		4.1.2 Construction and Maintenance
		4.1.3 Project Management
	4.2 Importance and Benefits of Using Digital Twin in TIM
		4.2.1 Importance of Digital Twin in TIM
		4.2.2 Benefits of Digital Twin in TIM
	4.3 Typical Digital Twins Architecture for TIM
	4.4 Data Challenges of DT in TIM
		4.4.1 Data Acquisition
		4.4.2 Data Processing
		4.4.3 Data Analysis
		4.4.4 Data Management
		4.4.5 Data Visualization
	4.5 Data-Driven Decision-Making Approaches in TIM
	4.6 Implementation and Deployment of Digital Twin Technologies in TIM
		4.6.1 Challenges to Implement Digital Twins in TIM
	4.7 Digital Twin for Infrastructure Resilience and Sustainability
		4.7.1 Resilience and Sustainability in Infrastructure Systems
		4.7.2 Digital Twin Applications for Infrastructure Resilience and Sustainability
		4.7.3 Examples of Digital Twin Applications for Resilience and Sustainability
	4.8 Overview of DTs’ Applications in Infrastructure Management
	4.9 Summary
	References
Chapter 5: Digital Twins in Design and Construction
	5.1 Introduction to Digital Twins in Design and Construction
		5.1.1 Digital Twin in Design
		5.1.2 Digital Twin in Construction Planning and Management
		5.1.3 Digital Twin in Site Safety and Quality Control
		5.1.4 Digital Twin in Facility Management and Maintenance
	5.2 Background of Digitalization in Construction
		5.2.1 Construction 4.0
		5.2.2 Intelligent Construction
		5.2.3 Construction Machine Learning
		5.2.4 Construction Monitoring Technologies
	5.3 Digital Twin Aspects in Design and Construction
	5.4 Construction Managed by Systematic Methods
		5.4.1 Key Benefits of Construction Managed by Systematic Methods
		5.4.2 The Meaning of Systematic Techniques
		5.4.3 The Fundamental Elements of Systematic Methods
		5.4.4 The System of Roadway Structures
		5.4.5 The System of Artificial Intelligence
		5.4.6 The System of Intelligent Construction Technologies
		5.4.7 The Information Technology System for Data Sharing
	5.5 Advantages of Digital Twins in Design and Construction
	5.6 Limitations of Digital Twins in Construction
	5.7 Application of DT in Construction and Design
	5.8 Summary
	References
Chapter 6: Digital Twins in Operation and Maintenance(O&P)
	6.1 Introduction to Digital Twins in Operation and Maintenance
	6.2 Digital Twins Offer a Range of Benefits in Operation and Maintenance, Including
		6.2.1 Reactive Maintenance
		6.2.2 Preventive Maintenance
		6.2.3 Condition-Based Maintenance
		6.2.4 Predictive Maintenance
		6.2.5 Prescriptive Maintenance
		6.2.6 Data Model for Operation and Maintenance
	6.3 Predictive Maintenance Concepts and Techniques
		6.3.1 Predictive Maintenance and Decision-Making Using Digital Twin
		6.3.2 Digital Twin Applications in Predictive Maintenance
		6.3.3 Predictive Maintenance and Decision-Making Using Digital Twin
		6.3.4 Predictive Maintenance Examples and Applications
	6.4 Role of Machine Learning and AI in Digital Twin for O&M
	6.5 Transportation Infrastructure Operation and Maintenance Challenges
	6.6 Applications of DT in the Operation and Maintenance Phase
	6.7 Summary
	References
Chapter 7: Future Digital Twin in Infrastructure Management
	7.1 Motivation and Aim
	7.2 Advancements in Digital Twin Technology
		7.2.1 Increased Use of Artificial Intelligence and Machine Learning
		7.2.2 Integration of More Data Sources
		7.2.3 Emerging Trends and Innovations in Digital Twin Technology
	7.3 Future Challenges and Limitations of Digital Twin Technology in TIM
		7.3.1 Challenges
		7.3.2 Opportunities
	7.4 Some Examples and Future Developments of Digital Twins in Transportation
		7.4.1 Examples
			7.4.1.1 Digital Twin of the San Francisco Bay Bridge
			7.4.1.2 Digital Twin of the Las Vegas Monorail
			7.4.1.3 Digital Twin of the Hong Kong-Zhuhai-Macao Bridge
		7.4.2 Future Developments
			7.4.2.1 Integration with Artificial Intelligence and Machine Learning
			7.4.2.2 Expansion to Public Transit Systems
			7.4.2.3 Expansion to Smart Cities
	7.5 Research and Development Directions for Digital Twin Technology in TIM
		7.5.1 Enhanced Modeling and Simulation
		7.5.2 Predictive Maintenance
		7.5.3 Integration with Edge and Cloud Computing
		7.5.4 Machine Learning and Artificial Intelligence
		7.5.5 Cybersecurity and Privacy
		7.5.6 Standards and Interoperability
		7.5.7 Multi-Modal Integration
	References