Detecting deterministic chaos in a high-complexity fire model
| Authors: | Jenna Sjunneson McDanold, Alex Jonko, Kara Yedinak, Rod Linn, Sophie Bonner, Alexander Josephson, Nishant Malik |
| Year: | 2026 |
| Type: | Scientific Journal |
| Station: | Northern Research Station |
| DOI: | https://doi.org/10.1063/5.0306306 |
| Source: | Chaos: An Interdisciplinary Journal of Nonlinear Science |
Abstract
Sensitivity to wind behaviors has been observed in marginal fire behavior in the field and using high-complexity fire models. Here we use the coupled atmospheric hydrodynamic-fire behavior model FIRETEC to simulate a marginal fire and develop 2028 one-dimensional time series from the temperature of the solid fuel, the convective heat transfer, the magnitude of the horizontal winds, and the vertical wind velocity on and around the leading edge of the fireline. We test each of these time series for chaotic signals using the Chaos 0-1 test that distinguishes between chaotic and non-chaotic time series. We analyze the spatial relationships with the leading edge by including series built from in front of and behind the leading edge of the fireline. We find that the length of the time step can cause a break in the determinism and, therefore, test the series for stochasticity using permutation entropy. We find the leading edge of the fireline to be highly chaotic and spatially correlated. We discuss some challenges in simplifying the time series for application with existing one-dimensional algorithms and discoveries that will lead to future work.