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Warning signals for eruptive events in spreading fires

Author(s): Jerome M. Fox, George M. Whitesides
Year Published: 2015
Description:

Spreading fires are noisy (and potentially chaotic) systems in which transitions in dynamics are notoriously difficult to predict. As flames move through spatially heterogeneous environments, sudden shifts in temperature, wind, or topography can generate combustion instabilities, or trigger self-stabilizing feedback loops, that dramatically amplify the intensities and rates with which fires propagate. Such transitions are rarely captured by predictive models of fire behavior and, thus, complicate efforts in fire suppression. This paper describes a simple, remarkably instructive physical model for examining the eruption of small flames into intense, rapidly moving flames stabilized by feedback between wind and fire (i.e., 'wind-fire coupling'-a mechanism of feedback particularly relevant to forest fires), and it presents evidence that characteristic patterns in the dynamics of spreading flames indicate when such transitions are likely to occur. In this model system, flames propagate along strips of nitrocellulose with one of two possible modes of propagation: a slow, structured mode, and a fast, unstructured mode sustained by wind-fire coupling. Experimental examination of patterns in dynamics that emerge near bifurcation points suggests that symptoms of critical slowing down (i.e., the slowed recovery of the system from perturbations as it approaches tipping points) warn of impending transitions to the unstructured mode. Findings suggest that slowing responses of spreading flames to sudden changes in environment (e.g., wind, terrain, temperature) may anticipate the onset of intense, feedback-stabilized modes of propagation (e.g., 'blowup fires' in forests).

Citation: Fox, Jerome M.; Whitesides, George M. 2015. Warning signals for eruptive events in spreading fires. Proceedings of the National Academy of Sciences of the United States of America. 112(8): 2378-2383.
Topic(s): Fire Behavior, Data Evaluation or Data Analysis for Fire Modeling, Simulation Modeling
Ecosystem(s): None
Document Type: Book or Chapter or Journal Article
NRFSN number: 13265
FRAMES RCS number: 19323
Record updated: Jun 13, 2018