(29e) Slow Dynamics As a Warning Signal for Eruptive Events in Forest Fires | AIChE

(29e) Slow Dynamics As a Warning Signal for Eruptive Events in Forest Fires

Authors 

Fox, J. M. - Presenter, University of Colorado, Boulder
Whitesides, G. M., Harvard University

Many complex systems are multistable and can, when sufficiently perturbed, undergo critical transitions in which they shift abruptly between dynamically distinct states (e.g. the onset of climatic shifts, the collapse of ecosystems). Forest fires represent a multistable system for which warning signals for critical transitions could aid in the development of improved fire intervention practices.  In forest fires, feedback between wind and spreading flames (i.e. “wind-fire coupling”) can spontaneously trigger the formation of blowup fires, large fires with multiplied rates of energy output.  Such events, which are not captured by operative models of fire behavior, enhance the unpredictability of spreading fires, pose enormous risks to fire response teams, and complicate fire suppression efforts. To examine the onset of blowup fires in the context of critical transitions, we constructed a physical model for these events based on a bistable combustion system.  In this system, flames propagate along contoured strips of nitrocellulose with one of two possible modes of propagation: a structured mode, which burns slowly, and an unstructured mode, which, as a result of wind-fire coupling, burns rapidly.  Using this model, we identified conditions where the onset of the second mode was more likely, and by examining dynamics under those conditions, we demonstrated that the system exhibited slower responses to perturbations as it approached a bifurcation point (a phenomenon referred to as “critical slowing down” in dynamical systems theory). This result suggests that, in forest fires, slower responses to terrain, wind, and/or other environmental factors may presage the onset of blowup fires and other dangerous ignition events resulting from wind-fire coupling.  With this work, we introduce a simple, experimentally tractable system for examining critical transitions in forest fires and other complex multi-stable systems.

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