Lecture D-E (2022-09-29): Midterm Review

Midterm review session for ASU SOS 212 for Fall 2022.

Lecture D4 (2022-09-27): Chapter 3, Modelling Dynamic Systems (Morecroft, 2015)

In this lecture, we demonstrate how to draw and simulate stock-and-flow diagrams in Insight Maker (a web-based System Dynamics Modeling (SDM) tool), and then we discuss the third chapter of Morecroft (2015), which introduces the reader to stock-and-flow diagrams and numerical simulations of dynamical systems. We go through a simple example modeling the flows of instructors into and out of a university, and then we move to a more complex multi-sector simulation of a community attempting to regulate drug use through the use of police. This latter simulation helps illustrate how to form equations for flows and converter variables, and it also demonstrates how anomalous behaviors that are generated by simulations can help indicate where problems may be in simulation formulas (which should then be updated to make the simulation outputs more realistic).

Lecture D3 (2022-09-23): Stock-and-Flow Diagrams in Vensim and Insight Maker

In this lecture, we start by reviewing numerical integration methods (Euler's method) for approximating solutions to ordinary differential equations in spreadsheets. We use a filling toilet tank as an example of a balancing/negative-feedback system that we can simulate this way. We then pivot to discussing stock-and-flow diagram representations of these systems and then end with a short demonstration about how to use Vensim to draw and simulate these stock-and-flow diagrams, thereby greatly accelerating the numerical integration process done by hand in the spreadsheet. We ran out of time before being able to cover the example in Insight Maker, but we will start with that at the beginning of the next lecture.

Lecture D2 (2022-09-20): Introduction to Numerical Simulation of Dynamical Systems, Part 2

In this lecture, we review the fundamentals of numerical simulation (and Euler's method) for a simple clonal bacteria population system with only births. We then add a death flow in and explore how changing the numerical simulation time step ("dt") affects the results. We then transition to a numerical simulation of a toilet tank (a classic balancing feedback loop).

Lecture D1 (2022-09-15): Introduction to Numerical Simulation of Dynamical Systems, Part 1

In this lecture, we introduce numerical simulation of dynamical systems (coupled ordinary differential equations) within the context of stock-and-flow diagrams for System Dynamics Modeling in strategic thinking. After covering how systems of ODE's capture the underlying "forces" driving change in a system, we review different ways to think about compound interest. This compound interest example motivates "Euler's method" for numerical integration over time. That is, we describe the product of flows and time-step durations as a sort of "interest" earned over each simulation time step ("compounding period" in the bank analogy). We use a bacterial growth example to show how this perspective can let us simulate the (average) growth characteristics of a bacterial population without having to simulate the discrete events where each bacteria reproduces independent of each other bacteria. Overall, this lecture relates the "time step" parameter in tools like Vensim and Insight Maker to calculus-based topics like the definition of the derivative. Furthermore, this lecture uses spreadsheet tools (like Microsoft Excel and Google Sheets) to provide a picture of what goes on inside simulation tools like Vensim and Insight Maker.

Lecture C2 (2022-09-13): "Applying Systems Archetypes" (Kim and Lannon, 1997)

In this lecture, we review the perspectives of Kim and Lannon (1997) toward applying Systems Archetypes in strategic modeling. This involves four approaches – structural pattern templates, lenses, dynamical theories, and predicting future behavior – that capture most of the different ways that Systems Archetypes can be used to propose interventions (or predict hypothetical outcomes from those interventions) in the iterative process of using models to make changes in the world.

Lecture C1 (2022-09-08): Feedback Systems Thinking with CLDs

In this lecture, we start to introduce "systems archetypes" as representing more complex aggregations of loops that give rise to complex (but predictable) behaviors over time. We introduce S-shaped growth as a modification to reinforcing loops, balancing loops with delay as a modification to balancing loops, and growth with overshoot as a combination of the two. We then expose several of the other more complex archetypes as an introduction to the upcoming article on using systems archetypes in the next lecture. The lecture experience closes with groups working on building their own S-shaped growth examples and "shifting goals" examples.

Lecture B3 (2022-09-06): Chapter 2, Introduction to Feedback Systems Thinking (Morecroft, 2015)

In this lecture, we review Chapter 2 (Introduction to Feedback Systems Thinking) from Morecroft (2015). This chapter contrasts event-driven thinking with feedback systems thinking, which are two perspectives on analyzing possible interventions in the world. The former focuses on reacting to problems as they occur, with their causes (as well as the long-term intervention consequences) being outside of the decision-making model. The latter focuses on considering not only the intervention but the possible side effects related to other dynamic forces that are distal from the main problem of interest. A focal road congestion example is used throughout, with the chapter closing on an example about dueling showers ("accidental adversaries") and how they can be viewed as a model for dueling sub-units of a single company with limited capacity to operate both simultaneously.

Lecture B2 (2022-09-01): Drawing Causal Loop Diagrams in Vensim

In this lecture, we review causal loop diagram (CLD) fundamentals and go through a few examples of building and annotating CLDs. We also go over how to draw CLD's in the Vensim PLE system dynamics modeling tool.

Note that due to atypical technological limitations in the classroom at the time of the recording, the video quality is not optimal.