Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions
Abstract
A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- Defense Threat Reduction Agency (DTRA); USDOE National Nuclear Security Administration (NNSA); USDA, Forest Service
- OSTI Identifier:
- 1604009
- Report Number(s):
- LA-UR-19-30781
Journal ID: ISSN 2571-6255
- Grant/Contract Number:
- 89233218CNA000001; DTRA1002725370; 17IA11221633164
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Fire
- Additional Journal Information:
- Journal Volume: 3; Journal Issue: 1; Journal ID: ISSN 2571-6255
- Publisher:
- MDPI
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; fire simulations; particle emissions; surrogate modeling
Citation Formats
Josephson, Alexander Jon, Holland, Troy Michael, Brambilla, Sara, Brown, Michael John, and Linn, Rodman Ray. Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions. United States: N. p., 2020.
Web. doi:10.3390/fire3010004.
Josephson, Alexander Jon, Holland, Troy Michael, Brambilla, Sara, Brown, Michael John, & Linn, Rodman Ray. Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions. United States. https://doi.org/10.3390/fire3010004
Josephson, Alexander Jon, Holland, Troy Michael, Brambilla, Sara, Brown, Michael John, and Linn, Rodman Ray. Tue .
"Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions". United States. https://doi.org/10.3390/fire3010004. https://www.osti.gov/servlets/purl/1604009.
@article{osti_1604009,
title = {Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions},
author = {Josephson, Alexander Jon and Holland, Troy Michael and Brambilla, Sara and Brown, Michael John and Linn, Rodman Ray},
abstractNote = {A simple, easy-to-evaluate, surrogate model was developed for predicting the particle emission source term in wildfire simulations. In creating this model, we conceptualized wildfire as a series of flamelets, and using this concept of flamelets, we developed a one-dimensional model to represent the structure of these flamelets which then could be used to simulate the evolution of a single flamelet. A previously developed soot model was executed within this flamelet simulation which could produce a particle size distribution. Executing this flamelet simulation 1200 times with varying conditions created a data set of emitted particle size distributions to which simple rational equations could be tuned to predict a particle emission factor, mean particle size, and standard deviation of particle sizes. These surrogate models (the rational equation) were implemented into a reduced-order fire spread model, QUIC-Fire. Using QUIC-Fire, an ensemble of simulations were executed for grassland fires, southeast U.S. conifer forests, and western mountain conifer forests. Resulting emission factors from this ensemble were compared against field data for these fire classes with promising results. Also shown is a predicted averaged resulting particle size distribution with the bulk of particles produced to be on the order of 1 μm in size.},
doi = {10.3390/fire3010004},
journal = {Fire},
number = 1,
volume = 3,
place = {United States},
year = {2020},
month = {2}
}
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