CS382:Fire

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Contents

Fire

Overview

This short unit about the spreading of forest fires is intended to teach some of the basics of using a simple pre-made model/simulation. While there are many benefits to using this model, the ability to physically verify the results proves to be difficult. It turns out that the rudimentary simulation of a wild fire spreading through a forest of varying densities can be implemented in a wide range of tools including NetLogo, AgentSheets, Vensim, Excel, and possibly others. Thus, this single model can teach the basics of simulation techniques like agent modeling, cellular automata, and systems dynamics without requiring students to relearn or rediscover what results to expect and allows them to focus on the methods and the techniques.

Background Reading

For Teachers/TAs

For Students

Reference Material

WildFire Modeling (wikipedia)

Agent-based modeling and simulation of wildland fire suppression

Cellular Automata (wikipedia)

History of Cellular Automata


Lecture Notes

Lecture 1

Lecture 2

Lab

This lab will consist of learning how to use NetLogo's wildfire model to see how minor changes in parameters can, under certain circumstances, producing wildly different results.

The student should first see the tediousness of the process of:

  1. Set the desired parameter to some value
  2. Run the model
  3. Record the proper results into a spreadsheet
  4. Increment the parameter and repeat steps (2-4)

The next step is to learn how to use NetLogo's parameter sweep ("Behavior Space") functionality to automate this process.

Ideally, when they run the manual parameter sweep they'll get results that tell them very little about how the density of the affects how much of it gets burnt. This will stress the importance of taking representative data sets to be able to accurately analyze the model.

A continuation of the lab would be to use one of the extended models (likely written by one of the TAs) and run parameter sweeps to understand how the different features can dramatically change the results.

Software

Bill of Materials

As long as the students don't try to actually burn down a forest to validate these models, there is no cost for this lab.

Evaluation

CRS Questions

  1. A technique called "systematic dynamical conflagration"
  2. Going out back campus and ....
  3. Coding all the properties of wood into a program
  4. A technique called "cellular automata"
  1. Automated Telecomune
  2. Tessellation Automata
  3. Biological Automated Simulation
  4. Systems Dynamics
  1. Stephen Wolfram
  2. John von Neumann
  3. Alan Turing
  4. Stanislaw Ulam

Quiz Questions

Fire Metadata

This section contains information about the goals of the unit and the approaches taken to meet them.

Scheduling

A note about early, late or doesn't matter, dependencies.

Concepts and Techniques

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General Education Alignment

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Scaffolded Learning

Some prose.

Inquiry Based Learning

Some prose.
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