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.&nbsp;

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Computational Fire Acoustics: Numerical Modeling of Fire-Generated Infrasound Using 3D Finite-Difference Time-Domain Methods

UNC Libraries
Process Optimization and Integration
article

Computational Fire Acoustics: Numerical Modeling of Fire-Generated Infrasound Using 3D Finite-Difference Time-Domain Methods

article en

Abstract

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.&nbsp;

UNC Libraries
University of North Carolina at Chapel Hill (US)
Sustainable cities and communities
Openalex Percentile: Top 47%
Process Optimization and Integration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.