CS382:Fire

From Earlham Cluster Department

(Difference between revisions)
Jump to: navigation, search
(General Education Alignment)
(General Education Alignment)
Line 157: Line 157:
From the [[http://www.earlham.edu/curriculumguide/academics/analytical.html Catalog Description]] ''Courses qualifying for credit in Abstract Reasoning typically share these characteristics:''
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.''
-
** This unit deals almost entirely will quantitative reasoning, and would be hard to expand into the abstract world.
+
** None. 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.''
-
** 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.
+
** Partial. 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.'''''
+
** Partial. The Verification/Validation/Accreditation process teaches the students how to take the procedures they learn using models and apply them to every aspect of scientific discovery. The fire unit attempts to teach students proper use of scientific models to insure that the questions they want answered are being answered by the model they're using.
==== Quantitative Reasoning ====
==== Quantitative Reasoning ====
From the [[http://www.earlham.edu/curriculumguide/academics/analytical.html Catalog Description]] ''General Education courses in Quantitative Reasoning foster students' abilities to generate, interpret and evaluate quantitative information. In particular, Quantitative Reasoning courses help students develop abilities in such areas as:''
From the [[http://www.earlham.edu/curriculumguide/academics/analytical.html Catalog Description]] ''General Education courses in Quantitative Reasoning foster students' abilities to generate, interpret and evaluate quantitative information. In particular, Quantitative Reasoning courses help students develop abilities in such areas as:''
* ''Using and interpreting formulas, graphs and tables.''
* ''Using and interpreting formulas, graphs and tables.''
-
** This unit is intended to teach the student how to gather data using a specific tool and analyze that data to come to some conclusion.
+
** Complete. This unit is intended to teach the student how to gather data using a specific tool and analyze that data to come to some conclusion.
* ''Representing mathematical ideas symbolically, graphically, numerically and verbally.''
* ''Representing mathematical ideas symbolically, graphically, numerically and verbally.''
-
** The student will need to create a lab write-up in which they express why they went about collecting the necessary amount of data. They will also need to include examples of said data and an explanation of what conclusion(s) can be drawn from that data.
+
** Complete. The student will need to create a lab write-up in which they express why they went about collecting the necessary amount of data. They will also need to include examples of said data and an explanation of what conclusion(s) can be drawn from that data.
* ''Using mathematical and statistical ideas to solve problems in a variety of contexts.''
* ''Using mathematical and statistical ideas to solve problems in a variety of contexts.''
-
** While this unit deals almost entirely with a single tool, the idea of parameter sweeping is necessary in every form of simulation and is thus applicable in a wide range of contexts.
+
** Complete. While this unit deals almost entirely with a single tool, the idea of parameter sweeping is necessary in every form of simulation and is thus applicable in a wide range of contexts.
* ''Using simple models such as linear dependence, exponential growth or decay, or normal distribution.''
* ''Using simple models such as linear dependence, exponential growth or decay, or normal distribution.''
-
** This wildfire model clearly shows how the number of burned trees is directly dependent on certain features of the forest (density, wetness, etc) and how minor changes in those features can dramatically change the outcome.
+
** Complete. This wildfire model clearly shows how the number of burned trees is directly dependent on certain features of the forest (density, wetness, etc) and how minor changes in those features can dramatically change the outcome.
* ''Understanding basic statistical ideas such as averages, variability and probability.''
* ''Understanding basic statistical ideas such as averages, variability and probability.''
-
** 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.
+
** Complete. 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.''
-
** 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.
+
** Complete. 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.''
-
** 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.
+
** Complete. 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 ===
=== Scientific Inquiry Requirement ===
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.''
-
** 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.
+
** Partial. 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.''
-
** 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.
+
** Complete. 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.''
-
** The lab portion of this unit is exactly this: gathering numerical data in order to provide the basis for some sort of conclusion.
+
** Complete. 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 00:14, 6 April 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 and TAs

WildFire Modeling (wikipedia)

Agent-based modeling and simulation of wildland fire suppression

Reading Assignments for Students

Cellular Automata (wikipedia)

History of Cellular Automata

Reference Material

Lecture Notes

Lecture 1

Lecture 2

Lab

Nice work!

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 structure of this lab is loosely based on this.

Data should be recorded in a spreadsheet for easy graphing.

Process

  1. Open up NetLogo. Go to the model library and under the Earth Science category, open "Fire".
  2. Experiment with different values for the density.
    1. Try 1%, then 99%. Record the results for each of these. Percent burnout is the result. Where are the results output in Netlogo?
    2. Take a guess at what will happen at 60%, then try it. Record your result.
    3. How close was your guess? How close was your lab partner's?
  3. Start taking some more data:
    1. Record the percent burned at 50%, 60%, 70%.
  4. Graph your data.
  5. What does the graph look like?
    1. Possibilities: logarithmic, linear, exponential We will provide simple graph examples. Will you have covered these earlier, or will you provide examples of each of these so they know what to look for?
  6. What might you be able to conclude from this?
  7. Run it 10 times at {50,60,70}% and record the average for each set.
  8. Now graph the averages
  9. Does it look different?
    1. Will probably be closer to linear.
  10. What new conclusions can you make, if any?
  11. Record results for burning at {50,55,60,65,70}% and graph it when you have all of them.
    1. How did that change your graph?
  12. Again, do this 10 times for {50,55,60,65,70}%, average each, and graph them.
    1. How did that change your graph?

For the teachers and TAs, could you provide examples of what these should look like?

Write-up

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 the all properties of trees into a computer 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

[][]-Added by Vlado (too many of them or if the 'NEED to Be better' comment is addressed - some of them replaced?)

  1. ground slope/shape
  2. wind & wind changes
  3. day/night cycle
  4. high air humidity
  1. 128
  2. 256
  3. 512
  4. 1024
  1. Wind
  2. Ground Slope
  3. Dry Wigs
  4. Large logs

Quiz Questions

Fire's 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. The WildFire model used in this unit provides a brief introduction to the concepts of VVA (Verification/Validation/Accreditation). Specifically, a rough notion of how a WildFire spreads can be obtained using this model, but it should be stressed that this model is nowhere near accurate when compared to one would actually happen.

General Education Alignment

Analytical Reasoning Requirement

Abstract Reasoning

From the [Catalog Description] Courses qualifying for credit in Abstract Reasoning typically share these characteristics:

Quantitative Reasoning

From the [Catalog Description] General Education courses in Quantitative Reasoning foster students' abilities to generate, interpret and evaluate quantitative information. In particular, Quantitative Reasoning courses help students develop abilities in such areas as:

Scientific Inquiry Requirement

From the [Catalog Description] Scientific inquiry:

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

This unit should be able to pique the curiosity of the student, most likely in the form of the question: "Why is that that a single variable can have such a dramatic effect on the output of a system?"

Fire's Mechanics

To Do

Lab Feedback


Comments

Authorship

Personal tools
Namespaces
Variants
Actions
websites
wiki
this semester
Toolbox