Computational Fire Acoustics: Numerical Modeling of Fire-Generated Infrasound Using 3D Finite-Difference Time-Domain Methods
Wildfires pose an increasing risk to forested and urban areas. Combustion related to fire has been shown to generate low-frequency acoustic waves and infrasound (sound below 20 Hz) (Marcillo et al., 2025). Here, acoustic waves from a semi-realistic linear fire source are modeled in a 3x3km simulated forest medium using infraFDTD, a 3-D numerical solver for the acoustic<br />wave equation using the Finite-Difference Time-Domain (FDTD) method (Kim and Lees, GRL 2011). The model is validated by comparing it to acoustic observations from a prescribed burn at Eglin Air Force Base in March 2023 (Marcillo et al., 2025). Model parameters are altered to constrain the source dimensions, geometry, and source-time function necessary to create an observable and distinct acoustic signal from a plume during a fire. Results show that the dimensions, intensity, and source function of firelines have a significant effect on signal strength<br />and frequency. All frequencies are constrained from 0-25 Hz. Longer firelines produce prolonged high-amplitude, low-frequency signals, with dominant signals in the 0-4 Hz range. More intense fires produce fewer low-amplitude, high-frequency signals (6-14 Hz) and stronger, longer-lasting signals in the 0-4 Hz range. Dominant frequencies of a semi-realistic fire signal range from 0-5 Hz, with weaker signals in the 5-15 Hz range, and higher frequencies (15-25 Hz) produced by noise. Comparative analysis with literature also confirms that fires with extensive flame fronts<br />produce stronger infrasound signals at 0.1 Hz. By utilizing modeling to give constraints on source properties, fires can be better identified from acoustic observations in the field. Additionally, back-propagation modeling using the Reverse Time Migration (RTM) technique (Kim and Lees, GJI 2015) demonstrates the potential for imaging the acoustic source of fires from observation stations below 15 Hz.
Institutions
- University of North Carolina at Chapel Hill (US)
Publication Details
- Journal
- UNC Libraries
- Published
- 2025-06-18
- DOI
- https://doi.org/10.17615/gk3m-f572
- Primary Topic
- Process Optimization and Integration
- Type
- article
- Field-Weighted Citation Impact
- 0.00