Digital Twin Logo
  • 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

2.3 Video materials

  1. “Lecture on City Digital Twins”
  2. “Intrasectoral balance of the utility infrastructure and energy system of St. Petersburg”. S. Gumerov
  3. “On the city model. Intersectoral balance of St. Petersburg”. I. Albin
  4. “Demonstration of a geoanalytical system for assessing the impact of investment projects on urban development”
  5. “Demonstration of an information modeling system for forecasting regional fuel and energy balances”
  6. “Monitoring and modeling CO2 emissions in the city”. S. Gumerov
  7. “Pipeline Digital Twins. Forecasting and online monitoring of technical condition”

2.3.1 Notes of an applied mathematician

A series of video essays by Sergey Gumerov on the evolutionary purpose of the Digital Twin

  1. “City of New Ideas”
  2. “Sail and Rudder”
  3. “Boxing or Mathematics”
  4. “Understanding the World and Heat Power Engineering”
  5. “Smart City”
  6. “The Country of School Mathematics”
  7. “We Are Not Flying to Mars”
  8. “We Solve Big Problems”