CS382:Fire

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(General Education Alignment)
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** Abstract Reasoning - From the [[http://www.earlham.edu/curriculumguide/academics/analytical.html Catalog Description]] ''Courses qualifying for credit in Abstract Reasoning typically share these characteristics:''
** Abstract Reasoning - From the [[http://www.earlham.edu/curriculumguide/academics/analytical.html Catalog Description]] ''Courses qualifying for credit in Abstract Reasoning typically share these characteristics:''
*** ''They focus substantially on properties of classes of abstract models and operations that apply to them.''
*** ''They focus substantially on properties of classes of abstract models and operations that apply to them.''
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**** Analysis of this unit's support or not for this item.
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**** This unit deals almost entirely will quantitative reasoning, and would be hard to expand into the abstract world.
*** ''They provide experience in generalizing from specific instances to appropriate classes of abstract models.''
*** ''They provide experience in generalizing from specific instances to appropriate classes of abstract models.''
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**** Analysis of this unit's support or not for this item.
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**** Parameter sweeping (one of the primary goals of this unit) can be used in almost every instance of computational simulations. In this sense it can be expanded from this specific model to others, yet it is more of a quantitative method of analysis than it is abstract.
*** ''They provide experience in solving concrete problems by a process of abstraction and manipulation at the abstract level. Typically this experience is provided by word problems which require students to formalize real-world problems in abstract terms, to solve them with techniques that apply at that abstract level, and to convert the solutions back into concrete results.''
*** ''They provide experience in solving concrete problems by a process of abstraction and manipulation at the abstract level. Typically this experience is provided by word problems which require students to formalize real-world problems in abstract terms, to solve them with techniques that apply at that abstract level, and to convert the solutions back into concrete results.''
  **** Analysis of this unit's support or not for this item.
  **** Analysis of this unit's support or not for this item.
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**** At the end of this unit the student should be able to understand that one cannot make sufficiently accurate conclusions about a model with only a single data set.
**** At the end of this unit the student should be able to understand that one cannot make sufficiently accurate conclusions about a model with only a single data set.
*** ''Making estimates and checking the reasonableness of answers.''
*** ''Making estimates and checking the reasonableness of answers.''
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**** Analysis of this unit's support or not for this item.
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**** In the beginning of the lab portion of this unit, the student should take a guess at what the result will be when the density of the forest is varied. After running a number of trials, they should be able to easily assess the accuracy of they're answer as well as the reasonableness of their results from the lab.
*** ''Recognizing the limitations of mathematical and statistical methods.''
*** ''Recognizing the limitations of mathematical and statistical methods.''
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**** Analysis of this unit's support or not for this item.
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**** The student should clearly note that this model of wildfires is far from indicative of how they actually happen. It should be stressed that this model is simply proof of concept for showing the profound effect a single variable can have on the overall results.
* Scientific Inquiry Requirement - From the [[http://www.earlham.edu/curriculumguide/academics/scientific.html Catalog Description]] ''Scientific inquiry:''
* Scientific Inquiry Requirement - 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.''

Revision as of 17:22, 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

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

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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