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  • 1 Digital Twin Open Book
    • 1.1 Company projects
    • 1.2 Competencies
    • 1.3 Solution Prototypes
    • 1.4 Online service platforms
    • 1.5 Platform software infrastructure
    • 1.6 Models under development
      • 1.6.1 Macroeconomic models
      • 1.6.2 Interindustry and sectoral models
      • 1.6.3 Technological and technical models
  • 2 Introduction
    • 2.1 Authors
    • 2.2 Printed publications
    • 2.3 Video materials
      • 2.3.1 Notes of an applied mathematician
  • 3 Basic Concepts
    • 3.1 Abbreviations
    • 3.2 Problems faced in territorial development
      • 3.2.1 Context
      • 3.2.2 Issues
      • 3.2.3 Key reason
    • 3.3 Goals and objectives of DTwin
    • 3.4 A model-based management system
    • 3.5 Experience of cities in building Digital Twins
      • 3.5.1 Intersectoral balance of St. Petersburg
      • 3.5.2 London Simulator
      • 3.5.3 Infrastructure & pipeline Digital Twin
  • 4 Digital Twin Data Hub
    • 4.1 Purpose
    • 4.2 Database description
    • 4.3 Datasets
      • 4.3.1 Data model
      • 4.3.2 Master data
      • 4.3.3 Basic SED indicators
      • 4.3.4 Matrices of socio-economic ties
      • 4.3.5 Management Decisions
    • 4.4 Dataset Subscription Service
  • 5 Processing pipeline
    • 5.1 Purpose
    • 5.2 Underlying technology
    • 5.3 Pipeline objectives
      • 5.3.1 Data preparation
      • 5.3.2 Data processing
      • 5.3.3 Model calibration
      • 5.3.4 Analysis, evaluation, and forecasting
      • 5.3.5 Planning
      • 5.3.6 Data provision
      • 5.3.7 Documentation processes for collecting, processing, and providing
    • 5.4 Current state of the pipeline
    • 5.5 Subject pipeline composition
    • 5.6 Pipeline of technical modules
      • 5.6.1 Data collection module
      • 5.6.2 Data normalization module
      • 5.6.3 Modeling and forecasting module
      • 5.6.4 Results preparation modules
  • 6 Methodology
    • 6.1 The history of the Digital Twin methodology
    • 6.2 Basic approach
    • 6.3 Energy balance
      • 6.3.1 Concept behind the energy balance model
      • 6.3.2 Energy balance goals
      • 6.3.3 Energy balance objectives
      • 6.3.4 General principles
      • 6.3.5 Method
      • 6.3.6 Areas of application
    • 6.4 Management decisions in support of regional transportation systems
      • 6.4.1 Transport balance goals
      • 6.4.2 Transport balance objectives
      • 6.4.3 General principles of transport balance modeling
      • 6.4.4 The TEB indicators
      • 6.4.5 Basic technical and economic indicators
      • 6.4.6 Relative coefficients
      • 6.4.7 Integrated efficiency indicators
      • 6.4.8 Non-published sections of the methodology
    • 6.5 Assessment of the impact of investment projects on the development of the city
      • 6.5.1 Purpose of the methodology
      • 6.5.2 Normative references and literature
      • 6.5.3 Terms and Definitions
      • 6.5.4 Symbols, Abbreviations, and Data Sources
      • 6.5.5 General Provisions
      • 6.5.6 Assessing the Current and Forecasted State of City Development
      • 6.5.7 Integral Assessment of the Investment Potential of Cities
      • 6.5.8 Assessing the Investment Attractiveness of Target Directions (Industries) of the City Economy
      • 6.5.9 Assessing and Ranking Cities for Each Target Direction (Industry) of the City Economy
      • 6.5.10 Assessing the Effectiveness of Investment Project Implementation and Its Impact on City Development Forecast Indicators
    • 6.6 Methodology for calculating time to failure of engineering systems
      • 6.6.1 Integral diagnostic method
      • 6.6.2 Main stages (general scheme) of work within the integral method (using a pipeline as an example)
  • 7 Mathematical basis
    • 7.1 Population forecasting model
      • 7.1.1 Purpose
      • 7.1.2 Main parameters, indicators, and notation
      • 7.1.3 Used formulas and assumptions
      • 7.1.4 Model Input Data
      • 7.1.5 Description of total calculation indicators
      • 7.1.6 Detailed description of the calculation algorithm
      • 7.1.7 Scope of permissible application of the mathematical model
      • 7.1.8 Accuracy assessment of mathematical models
      • 7.1.9 Conclusions
    • 7.2 City system dynamics model
      • 7.2.1 Purpose of the model
      • 7.2.2 Basic form of the model
      • 7.2.3 Description of input variables
      • 7.2.4 Complete description of the calculation algorithm
      • 7.2.5 Scope of permissible application of mathematical models
    • 7.3 Intersectoral balance and economic forecasting model
      • 7.3.1 Investment potential by demand
    • 7.4 Model for assessing the financial performance of an investment project
      • 7.4.1 Purpose of the model
      • 7.4.2 Basic form of the model
      • 7.4.3 Calculation procedure
      • 7.4.4 Description of model input variables
      • 7.4.5 Data sources for variable sets
      • 7.4.6 Description of model result
      • 7.4.7 Model calibration
    • 7.5 Model for assessing the impact of an investment project on socio-economic indicators
      • 7.5.1 Purpose of the model
      • 7.5.2 Terms and Definitions
      • 7.5.3 Basic form of the model
      • 7.5.4 Calculation of IP effects by target indicators
      • 7.5.5 Assessment of IP impact on investment potential dynamics
      • 7.5.6 Description of model input variables
      • 7.5.7 Description of model result
      • 7.5.8 Model calibration
      • 7.5.9 Model development
    • 7.6 Model for assessing the impact of a portfolio of investment projects on socio-economic indicators
      • 7.6.1 Purpose of the model
      • 7.6.2 Basic form of the model
      • 7.6.3 Description of model input variables
      • 7.6.4 Calculation procedure
      • 7.6.5 Output indicators
      • 7.6.6 Model development
    • 7.7 Model for assessing the impact of city parks on socio-economic development and ESG (Ecology, Social, Governance) indicators
      • 7.7.1 Purpose of the model
      • 7.7.2 Basic view of the model
      • 7.7.3 Input data
      • 7.7.4 Output data
      • 7.7.5 Result of model application
      • 7.7.6 Requirements for model support and regularity of recalibration
      • 7.7.7 Assumptions necessary for carrying out calculations
      • 7.7.8 Scope (boundaries) of permissible application of the mathematical model
      • 7.7.9 Appendix 1
    • 7.8 Model for scenario calculation of the socio-economic performance of transport projects using the GIH methodology
      • 7.8.1 Terms and definitions
      • 7.8.2 Purpose of the model
      • 7.8.3 Input data
      • 7.8.4 Output data
      • 7.8.5 Result of model application
      • 7.8.6 Requirements for model support and regularity of recalibration
      • 7.8.7 Assumptions necessary for carrying out calculations
    • 7.9 Model for assessing the provision of public infrastructure
      • 7.9.1 Purpose of the model
      • 7.9.2 Terms and definitions
      • 7.9.3 Basic view of the model
      • 7.9.4 Description of Model Input Variables
      • 7.9.5 Description of the model result
      • 7.9.6 Calibration of the model
      • 7.9.7 Result of model application
      • 7.9.8 Requirements for model support and regularity of recalibration
      • 7.9.9 Assumptions necessary for carrying out calculations
      • 7.9.10 Description of the calculation algorithm
      • 7.9.11 Scope (boundaries) of permissible application of the mathematical model
    • 7.10 Model for assessing commuting migration
      • 7.10.1 Purpose of the model
      • 7.10.2 Terms and definitions
      • 7.10.3 Basic view of the model
      • 7.10.4 Description of Model Input Variables
      • 7.10.5 Description of the model result
      • 7.10.6 Calibration of the model
      • 7.10.7 Result of model application
      • 7.10.8 Requirements for model support and regularity of its recalibration
    • 7.11 Model for assessing the technical condition, wear and tear, and terms of safe operation of infrastructure
  • 8 Software
    • 8.1 Program “Digital Twin of the City”
    • 8.2 Program “Reconstruction and forecasting of intersectoral and fuel and energy balances”
    • 8.3 Program “Digital Twin of the Pipeline”
  • 9 Analytical works
    • 9.1 Analysis of regional emissions: a word for poor Kemerovo
    • 9.2 Analysis of regional emissions: a look into the future
    • 9.3 Links to articles on external resources
  • 10 Performance Management. A Model-Oriented Management System
    • 10.1 Digitalization and the Problems of the Economy
    • 10.2 Goals, Objectives, and Structure of the Model-Oriented Management System
    • 10.3 Digital Transformation Program
    • 10.4 Structure of MOSU
    • 10.5 Integrated CS Model
    • 10.6 Model Deployment Sequence
    • 10.7 Conclusion

City Digital Twin

1.3 Solution Prototypes

  • Digital Twin analytics and services website
  • Enterprise management based on a Digital Twin
  • World energy and distribution of energy potential
  • Fuel-Energy Balance (FEB) and impact on goals
  • Assessing the impact of improvement on ESG indicators
  • Enterprise Strategic Planning Platform
  • Intersectoral balance of the communal infrastructure system
  • International SaaS portal for digital twins of territories
  • Platform for pipeline creation, visualization and analysis