CS382:Fire

From Earlham Cluster Department

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(General Education Alignment)
(Scientific Inquiry Requirement)
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* From the [[http://www.earlham.edu/curriculumguide/academics/scientific.html Catalog Description]] ''Scientific inquiry:''
* From the [[http://www.earlham.edu/curriculumguide/academics/scientific.html Catalog Description]] ''Scientific inquiry:''
** ''Develops students' understanding of the natural world.''
** ''Develops students' understanding of the natural world.''
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*** Analysis of this unit's support or not for this item.
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*** After the completion of this unit, the student should understand the world's dependence on a surprisingly small number of variables even though this model is far from accurate.
** ''Strengthens students' knowledge of the scientific way of knowing — the use of systematic observation and experimentation to develop theories and test hypotheses.''
** ''Strengthens students' knowledge of the scientific way of knowing — the use of systematic observation and experimentation to develop theories and test hypotheses.''
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*** Analysis of this unit's support or not for this item.
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*** The entirety of this lab is to change a variable, observe the results, and repeat, eventually leading to having enough data to make reasonable theories on the model.
** ''Emphasizes and provides first-hand experience with both theoretical analysis and the collection of empirical data.''
** ''Emphasizes and provides first-hand experience with both theoretical analysis and the collection of empirical data.''
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*** Analysis of this unit's support or not for this item.
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*** The lab portion of this unit is exactly this: gathering numerical data in order to provide the basis for some sort of conclusion.
== Scaffolded Learning ==
== Scaffolded Learning ==

Revision as of 17:33, 7 March 2009

Return to Insilico - Discrete Modeling Development

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

WildFire Modeling (wikipedia)

Agent-based modeling and simulation of wildland fire suppression

For Students

Cellular Automata (wikipedia)

History of Cellular Automata

Reference Material

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

* A question.

Fire Metadata

Scheduling

This should be very early in the semester as it is a fairly simple and short topic. Given its simplicity, it should only be a single week.

Concepts and Techniques

This unit should teach the basics of using someone else's model, as well the importance of conducting multiple runs with different parameters in order to gain an accurate understanding of the effect of the model.

General Education Alignment

Analytical Reasoning Requirement

Abstract Reasoning

*** Analysis of this unit's support or not for this item.

Quantitative Reasoning

Scientific Inquiry Requirement

Scaffolded Learning

The NetLogo model(s) in question are easy to use and easy to witness the effect of changing parameters to obtain different results. As well there are fairly clear extensions for the student inclined towards taking those steps.

Inquiry Based Learning

Some prose.
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