1. Fire!! Simulating a Forest Fire. Statistics and probability.

Explore different probability settings and different locations where the fire starts. Number of neighbors of the trees is key idea.

2. Fire: Estimating Percent. This exercise can be used to gather data and compare the error amount, like least squares regression. How far was the estimate from the actual?

Exercise in Upward Bound Math and Science statistics class using Estimating Percent and different sample sizes to come up with logistic elongated S curve and graph it.

3. Try a Monte Carlo Method to determine the area between two functions. Such as f(x) = 2*sin(x) + 5 and what area is above the x-axis and below the function between 0 and 6.2830? Can you guess this area? Use the Function Flyer tool for this.

Use the function flyer tool to explore the initial guess of the students as to what the function looks like for percent of forest burned and the density of the trees.

4. Fire Statistics over the decades versus over the centuries.

5. Netlogo has a Fire Model. In the Model library under Earth Science category. The presence of a non-linear threshold or critical parameter. Could do a graph of this from student's data.

6. Excel VBA macro to remove the duplicates from an AgentSheets Plot exported simulation so it can be imported to Interactivate GraphIt package.

Use the Interactivate GraphIt package to graph the ordered pairs for the 40 students samples for the intervals of different densities, as done on the first day of the Calvin NCSI conference.

7. Modeling and Simulation Adding Fire-Resistance to trees in a LOGO turtlegraphics model. See slide #19. Develop and play with NetLogo model.

8. The http://www.shodor.org/talks/ncsi/ URL.

9. National Computational Science Institute and SC09 Summer Workshops Surveys.

10. Shiflet-Fire Spreading of Fire modeling - 12 assignments.

Based on #11 assignment:

```Develop a fire simulation in which a tree that catches fire in one
time step takes five additional time steps to burn.

The fire can spread from the burning tree to a neighboring tree with a
certain probability only on the second, third, and fourth time steps after
the lightning strike.

The first step the tree, the fire is not yet extensive enough to transfer
to a neighboring tree.

The last step the tree that has almost finished burning is just becoming
embers with less flames and there is no chance of reaching a neighboring
tree that has been lucky enough to not catch fire during steps 2, 3, and 4
of the fire.
```
11. Parallel version of the model eventually using the MPI parallel programming protocol.
```See Chapter 12 High-Performance Computing

Simpler forest fire model.

1. Will use the 8 nearest neighbors.

2. Probability of a tree catching fire if a neighbor is on fire will be
.1, .2, .3, ..., .9 so there are only 10 different levels of
probability.

3. When the given forest is input and one tree catches fire,
every possible outcome will be explored and the metrics
for it will be obtained and stored.

4. Algorithm will use a stack to store the configuration of the fire
and forest state.

5. Available processors will check stack and grab a configuration
initially whenever they are finished with a process or waiting

6. Algorithm will be implemented in Excel VBA language with a delay
built in to each step so that the students can see the backtracking
when a fire burns out to try another option from that configuration.

7. With 8 nearest neigbors for each tree to check, we have 256 possible
configurations to check for a tree that is surrounded by 8 trees.

00000000 represents none of the 8 neighbors catching fire.
11111111 represents all of the 8 neighbors catching fire.

```
12. The Introduction to Computational Science textbook by Shiflet and Shiflet.

13. Forensics projects from Shodor. Case studies, Lab Experiments, etc.

14. Project SUCCEED curriculum: SHODOR Project SUCCEED lessons and workshops.

15. The Excel Models from Shodor, including the Game of Life.