2019 Science Fair Project
In the United States, every year since 2000, there have been, on average, 73,200 forest firesthat have burned a staggering 6.9 million acres of land. Within these acres, numerous public areasand homes burned down, displacing the lives of thousands of people, who then found it extremelydifficult to assimilate back into society. Perhaps the most elusive aspect of fires is that they canbe started by the most minute of factors and go unnoticed until they become too large to contain.In a situation where the fire can’t be contained in an adequate amount of time, the most importantconsideration for firefighters is to figure out which direction would be most effective to containthe fire from. The proposed solution is a Cellular Automata based mathematical model that willconsider, holistically, factors such as fuel amount, wind patterns and topographical features to sim-ulate them so as to accurately predict the spread of a fire. Similar models have been developed byother researchers, but they have not taken into account all of the aforementioned factors in the con-text of a Cellular Automata based model. Traditionally Partial Differential Equation (PDE) based mathematical models are used to simulate gas movement, fire spread and other similar dynamicalsystems in nature. These approaches are computationally intensive and often times very expensiveto solve to fit the field data. The Cellular Automata model is capable of modeling very complex dy-namical systems with simpler mathematical formulae and are therefore computationally friendly.The ultimate goal with this model is to empower firefighters to choose where it would be mostbeneficial to focus their resources and contain the fire as quickly as possible. Additionally, bysuccessfully predicting the spatial and temporal spread of forest fires, evacuation can be managedmore efficiently.
