Lecture E5 (2022-10-27): Assignment E5 – Creating Limited, Coupled Population Models

In this lecture, we discuss an upcoming assignment in SOS 212 that will provide practice in creating more complex, multi-sector system dynamics models. We review how to create rate formulas for processes like population growth. We review lookup tables. We review ghost primitives/shadow variables. We also introduce how to use modular arithmetic (mod/modulo/modulus) that, when combined with a lookup table, makes seasonal patterns easy to introduce in system dynamics models. This is also covered for both Vensim (from Ventana Software) and Insight Maker.

Lecture E4 (2022-10-25): Chapter 6, The Dynamics of Growth and Diffusion (Morecroft, 2015)

In this lecture, we cover topics discussed by Morecroft (2015, Chapter 6) on the dynamics of growth and diffusion and relate them to other systems with S-shaped growth that we've seen in the past – a simple fishery model as well as epidemic growth. The main focus of this chapter is on the Bass model of innovation diffusion, which includes a contagion-like word-of-mouth loop (similar to the "SI" in an "SIR" model, or similar to population growth in a fishery) as well as an advertising loop to get the process started (like inoculating a population with its first infectious individuals). We then cover embellishments of the Bass model and do a strategic thinking example on one of those embellishments, which relates to strategy for the entry of easyJet as a low-cost airline into an existing marketplace of major carriers.

Lecture E3 (2022-10-20): Epidemic Dynamics

In this lecture, we start to introduce more complex system dynamics models (SDM), as would be implemented in Vensim or Insight Maker, for more complex systems. We focus on the classical SIR (susceptible–infectious–recovered) multi-compartment model from epidemiology. We build up this model as a stock-and-flow diagram from scratch, justifying the expressions/equations that we use and then using simulation to inform us when the equations might have significant flaws. Ultimately, we get to a working SIR model that matches dynamics of basic disease spread, and we go through a strategic thinking/scenario-planning example that shows that the value of quarantine policy is, in most cases, not to reduce spread of a disease but "flatten the curve" and lower (but widen) the infection peak to keep it under a manageable public-health threshold (set by university capacity/etc.).

Lecture E2 (2022-10-18): Making Simulations More Realistic, Part 2 – Delays, Fixed and Smoothing

In this lecture, we continue to add complexity to system dynamics models in Vensim and Insight Maker by introducing two different forms of delays – fixed delays and smoothing/averaging delays. We spend some of the lecture discussing the fundamental difference between these delays, and we spend much of the rest of the lecture discussing how to implement these delays in both Vensim and Insight Maker. We also discuss some other functions (like STEP, for step responses, and PULSE/PULSE TRAIN) as well as how to use lookup tables to insert more arbitrary functions over time as inputs to systems. Finally, we spend some time discussing how higher-order smoothing/averaging delays help mix aspects of both fixed delays and pure smoothing delays.

Lecture E1 (2022-10-14): Making Simulations More Realistic, Part 1 – Units, Sliders, and Lookup-Table Converters

In this lecture, we discuss how to embellish basic System Dynamics Modeling (SDM) simulation models with additional complexity and more efficiently interact with working simulation models. In particular, we introduce units (in both Vensim and Insight Maker) as a tool for the verification and validation of simulation models. We also discuss how to use sliders (in both Vensim and Insight Maker) to quickly adjust parameters (constants) and generate new outputs. We close with a discussion of lookup tables (converters) as well as how to implement them in both Vensim and Insight Maker.