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System Dynamics Applications: A Modular Approach to Modelling Complex World Behaviour

Alan C. McLucas

This unique book offers an unprecedented opportunity to develop comprehensive practical skills in building models which will enhance understanding of the many problems encountered in a complex and dynamic world. As an enabler to quantitative modelling, systems thinking and qualitative modelling techniques are used to facilitate problem conceptualisation and the formulation of dynamic hypotheses about troublesome systemic problems.

Contents

  1. Blurb
  2. Expected Learning and Skills Outcomes
  3. Preface
  4. 1 COMPLEXITY AND DYNAMIC BEHAVIOUR
    1. 1.1 ABOUT COMPLEXITY AND COMPLEX PROBLEMS
      1. 1.1.1 A Physical Example—The Simple Pendulum
      2. 1.1.2 Extending The Physical Example—Simple Pendulum Becomes A Double Pendulum
      3. 1.1.3 A Simple Bank Account Example
    2. 1.2 WHAT COMPLEX PROBLEM EXAMPLES HAVE IN COMMON
    3. 1.3 THINKING ABOUT AND MODELLING NATURALLY IN THE TIME DOMAIN
    4. 1.4 OVERCOMING OUR SOMETIMES CONSTRAINED VIEW OF THE WORLD
    5. 1.5 ABOUT SYSTEM DYNAMICS MODELLING
      1. 1.5.1 Qualitative Models
      2. 1.5.2 Quantitative Models
    6. 1.6 A SYSTEMS ENGINEERING APPROACH TO MODEL REQUIREMENTS AND MODEL BUILDING
    7. 1.7 THE SYSTEM DYNAMICS MODELLING PROCESS
    8. 1.8 TOP-DOWN COMPARED TO BOTTOM-UP APPROACH TO PROBLEM SOLVING
    9. 1.9 INTEGRATING SOFT SYSTEMS METHODOLOGY, SYSTEMS THINKING, SYSTEM DYNAMICS MODELLING AND SYSTEMS ENGINEERING
    10. 1.10 THE SYSTEMS ENGINEERING ‘VEE’ MODEL APPLIED TO SYSTEM DYNAMICS MODELLING PROJECTS
    11. 1.11 GROUP MODEL BUILDING
    12. 1.12 SUMMARY
  5. 2 WHY MODULES ARE IMPORTANT
    1. 2.1 MODELS AND MODELLING BUILDING BLOCKS
      1. 2.1.1 ‘Hard’ And ‘Soft’ Variables
    2. 2.2 MODELLING METHODOLOGY
      1. 2.2.1 Building Necessary And Sufficient Representations
    3. 2.3 TAKING ACTION TO REMEDY THE PROBLEM SITUATION
      1. 2.3.1 The Model—Its Role And Characteristics
      2. 2.3.2 Why Build Models?
      3. 2.3.3 Art And Science Of Model Building
    4. 2.4 MODEL AS A NECESSARY AND SUFFICIENT REPRESENTATION
    5. 2.5 NECESSARY AND SUFFICIENT REPRESENTATIONS—A HUMAN RESOURCES MANAGEMENT EXAMPLE
      1. 2.5.1 Chicken OR Egg? Understanding The Problem Before Simulating, OR Simulating The Problem To Understand It?
    6. 2.6 THE NEED FOR STRUCTURAL BUILDING BLOCKS—MODULES
    7. 2.7 COMMUNICATING IDEAS ABOUT DYNAMIC HYPOTHESES
      1. 2.7.1 Start Simple—Progressively Add Functionality
    8. 2.8 IMPORTANCE OF STRUCTURE—MODELS AND REAL-WORLD PROBLEMS
      1. 2.8.1 [Common] Modules—Molecules Of Structure
    9. 2.9 SYSTEMS ENGINEERING—COMPONENT AND MODULE RE-USE
    10. 2.10 MODULES TO DELIVER SPECIFIC FUNCTIONALITY
      1. 2.10.1 Model Boundaries And Interfaces
    11. 2.11 COMBINING MODULES—ESSENTIAL CONSIDERATIONS
    12. 2.12 ARRAY MODULES
    13. 2.13 MODULE—EXPANDED DEFINITION
      1. 2.13.1 Module Boundary
    14. 2.14 MODULE DESCRIPTIONS
    15. 2.15 SUMMARY
  6. 3 BUILDING A BASIC POWERSIM™ STUDIO MODEL
    1. 3.1 BACKGROUND
      1. 3.1.1 Basic Representation—Flowing In
      2. 3.1.2 Example Problem To Be Solved
      3. 3.1.3 Solution By Graphical Integration Method
      4. 3.1.4 Determining Contributions To Bathtub Made By Flowing In
      5. 3.1.5 Building The System Dynamics Model
      6. 3.1.6 Flowing In Powersim™ Studio Module
      7. 3.1.7 Verifying Functionality Of Flowing In Module
      8. 3.1.8 Flowing Out Powersim™ Studio Module
      9. 3.1.9 Verifying Functionality Of Flowing Out Module
      10. 3.1.10 Building The Complete Bathtub Model
      11. 3.1.11 Graphical Integration Examples And Challenges
      12. 3.1.12 Further Development Of The Bathtub Model
    2. 3.2 SUMMARY
  7. 4 BUILDING A MODEL TO ANALYSE FEEDBACK DYNAMICS
    1. 4.1 QUALITY THINKING FIRST
      1. 4.1.1 Example Problem—Population Dynamics Of Charmville
      2. 4.1.2 Steps To Be Completed Before Starting The Computer
      3. 4.1.3 Formulate Dynamic Hypotheses
      4. 4.1.4 Conceptual Models—Important Aids To Evolving Dynamic Hypotheses
      5. 4.1.5 Capturing Business Rules
      6. 4.1.6 Dynamic Hypotheses—Birthing
      7. 4.1.7 Dynamic Hypotheses—Dying
      8. 4.1.8 Dynamic Hypotheses—Migrating-In
      9. 4.1.9 Dynamic Hypothesis—Migrating-Out
      10. 4.1.10 Prioritizing Business Rules
      11. 4.1.11 Draw Influence Diagram OR Stock-And-Flow Diagram
      12. 4.1.12 Review Structure And Functioning Of Model
      13. 4.1.13 Identifying The Problem Boundary
    2. 4.2 OUTLINE OF REMAINING STEPS—FROM CONCEPTUAL MODEL TO ANALYTICAL MODEL
      1. 4.2.1 Breaking The Model Down To Individual Modules
      2. 4.2.2 Deciding On The Governing Business Rules To Be Included In The Model
      3. 4.2.3 Definitions Table—Population Model
      4. 4.2.4 Determine Units To Be Assigned
      5. 4.2.5 Determine Project And Simulation Settings
      6. 4.2.6 Create Modelling And Simulation Project
      7. 4.2.7 Developing The Population Model—Demonstrated
      8. 4.2.8 The Birthing Module
      9. 4.2.9 The Dying Module
      10. 4.2.10 The Migrating-In Module
      11. 4.2.11 The Migrating-Out Module
      12. 4.2.12 Integrating The Birthing And Dying Modules Into Population Model
      13. 4.2.13 Integrating The Migrating-In And Migrating-Out Modules Into Population Model
      14. 4.2.14 Integrating All Modules Into Population Model
      15. 4.2.15 Analysing The Behaviour
      16. 4.2.16 Managing Achievement Of Planned 2% Population Growth
      17. 4.2.17 Discussion Of Analysis
      18. 4.2.18 Possible Future Developments Of The Model
    3. 4.3 SUMMARY
  8. 5 BUILDING AN ARRAY MODEL STEP-BY-STEP
    1. 5.1 BACKGROUND TO THIS CHAPTER
      1. 5.1.1 First Task And Basic Data
      2. 5.1.2 Analysis Of Model
      3. 5.1.3 Development Of Array Version
      4. 5.1.4 Working With Arrays Kept Simple
      5. 5.1.5 Start Point—Pipeline Array (Ageing) Module
      6. 5.1.6 Further Development Of The Array Version
      7. 5.1.7 Further Extension Of Array Model Functionality
    2. 5.2 SUMMARY
  9. 6 VERIFICATION AND VALIDATION
    1. 6.1 VERIFICATION—BUILDING THE MODEL RIGHT
    2. 6.2 VALIDATION—BUILDING THE RIGHT MODEL
    3. 6.3 VERIFICATION—CONSIDERATIONS FOR DESIGN OF TESTING
    4. 6.4 VALIDATION—CONSIDERATIONS FOR THE DESIGN OF TESTING
      1. 6.4.1 Structural Tests
      2. 6.4.2 Behavioural Tests
      3. 6.4.3 Logical Tests
      4. 6.4.4 Extreme-Value Tests
      5. 6.4.5 Mass-Balance Tests
      6. 6.4.6 Designing And Applying Logical Tests
      7. 6.4.7 Assuring Integrity Of Units Used In Models
      8. 6.4.8 Flow Calculation Sequence
      9. 6.4.9 Extreme-Value Testing
      10. 6.4.10 Mass-Balance Testing
    5. 6.5 SUMMARY
  10. A CAUSAL LOOP DIAGRAMMING CONVENTIONS
  11. B STOCK-AND-FLOW DIAGRAMMING CONVENTIONS
  12. C INFLUENCE DIAGRAMMING CONVENTIONS
  13. D INFLUENCE DIAGRAMS AND STOCK-AND-FLOW DIAGRAMS
  14. E GENERIC MODULE DEFINED
  15. F MODULES
    1. F.1 MODULE—SIMPLE INFLOW / OUTFLOW
    2. F.2 MODULE—CASCADED STOCKS
    3. F.3 MODULE—TRANSITIONAL (IRREVERSIBLE) FLOW
    4. F.4 MODULE—TRANSITIONAL (REVERSIBLE) FLOW
    5. F.5 MODULE—FIRST ORDER LINEAR POSITIVE FEEDBACK
    6. F.6 MODULE—FIRST ORDER LINEAR NEGATIVE FEEDBACK
    7. F.7 MODULE—FIRST ORDER LINEAR NEGATIVE FEEDBACK—EXPLICIT GOAL
    8. F.8 MODULE—FIRST ORDER DELAY
    9. F.9 MODULE—DELAYED INFLOW
    10. F.10 MODULE—DELAYED IRREVERSIBLE (TRANSITIONAL) FLOW
    11. F.11 MODULE—FIRST ORDER (PIPELINE) DELAY—ATTRITION
    12. F.12 MODULE—FIRST ORDER NON-LINEAR SELF-REFERENCING—FLOWING IN
    13. F.13 MODULE—FIRST ORDER NON-LINEAR SELF-REFERENCING—FLOWING OUT
    14. F.14 MODULE—FIRST ORDER NON-LINEAR SELF-REFERENCING
    15. F.15 MODULE—PIPELINE DELAY ARRAY
    16. F.16 MODULE—FIRST ORDER (PIPELINE) DELAY—ARRAY—ATTRITION
  16. Bibliography

Author

Dr Alan McLucas is a senior lecturer at the University of New South Wales, UNSW@ADFA, the Australian Defence Force Academy. He holds bachelors, masters and doctor of philosophy degrees in engineering, management and operations research respectively.