Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Fire |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-6255/3/1/4 |
| _version_ | 1818001711952822272 |
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| author | Alexander J. Josephson Troy M. Holland Sara Brambilla Michael J. Brown Rodman R. Linn |
| author_facet | Alexander J. Josephson Troy M. Holland Sara Brambilla Michael J. Brown Rodman R. Linn |
| author_sort | Alexander J. Josephson |
| collection | DOAJ |
| description | 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 <inline-formula> <math display="inline"> <semantics> <mi>μ</mi> </semantics> </math> </inline-formula>m in size. |
| first_indexed | 2024-04-14T03:37:43Z |
| format | Article |
| id | doaj.art-78e7129511c44768bb6a856036412229 |
| institution | Directory Open Access Journal |
| issn | 2571-6255 |
| language | English |
| last_indexed | 2024-04-14T03:37:43Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fire |
| spelling | doaj.art-78e7129511c44768bb6a8560364122292022-12-22T02:14:41ZengMDPI AGFire2571-62552020-02-0131410.3390/fire3010004fire3010004Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate EmissionsAlexander J. Josephson0Troy M. Holland1Sara Brambilla2Michael J. Brown3Rodman R. Linn4Earth and Environmental Sciences Division, Los Alamos National Lab, Los Alamos, NM 87545, USATheoretical Division, Los Alamos National Lab, Los Alamos, NM 87545, USAAnalytics, Intelligence, and Technology Division, Los Alamos National Lab, Los Alamos, NM 87545, USAAnalytics, Intelligence, and Technology Division, Los Alamos National Lab, Los Alamos, NM 87545, USAEarth and Environmental Sciences Division, Los Alamos National Lab, Los Alamos, NM 87545, USAA 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 <inline-formula> <math display="inline"> <semantics> <mi>μ</mi> </semantics> </math> </inline-formula>m in size.https://www.mdpi.com/2571-6255/3/1/4fire simulationsparticle emissionssurrogate modeling |
| spellingShingle | Alexander J. Josephson Troy M. Holland Sara Brambilla Michael J. Brown Rodman R. Linn Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions Fire fire simulations particle emissions surrogate modeling |
| title | Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions |
| title_full | Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions |
| title_fullStr | Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions |
| title_full_unstemmed | Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions |
| title_short | Predicting Emission Source Terms in a Reduced-Order Fire Spread Model—Part 1: Particulate Emissions |
| title_sort | predicting emission source terms in a reduced order fire spread model part 1 particulate emissions |
| topic | fire simulations particle emissions surrogate modeling |
| url | https://www.mdpi.com/2571-6255/3/1/4 |
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