<?xml version="1.0" encoding="UTF-8"?><eml:eml xmlns:eml="https://eml.ecoinformatics.org/eml-2.2.0" xmlns:stmml="http://www.xml-cml.org/schema/stmml-1.1" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" packageId="doi:10.60594/W46K5C" system="wfsi-data-portal" xsi:schemaLocation="https://eml.ecoinformatics.org/eml-2.2.0 https://eml.ecoinformatics.org/eml-2.2.0/eml.xsd"><dataset><alternateIdentifier>https://github.com/ritambhara1234/Physics-Based-Dynamic-FMC</alternateIdentifier><shortName>YAGHOOBIANN_2025-04-21_2AFC</shortName><title>A Physics-Based Model of Thermodynamically Varying Fuel Moisture Content for Fire Behavior Prediction</title><creator id="2782824662073856"><individualName><givenName>Ritambhara</givenName><surName>Dubey</surName></individualName><organizationName>Florida State University</organizationName><positionName>Ph.D. student</positionName><electronicMailAddress>rrd20z@fsu.edu</electronicMailAddress><userId directory="https://orcid.org">https://orcid.org/0000-0002-8097-0394</userId></creator><creator id="9388075832550848"><individualName><givenName>Neda</givenName><surName>Yaghoobian</surName></individualName><organizationName>Florida State University</organizationName><positionName>Associate Professor</positionName><address><deliveryPoint>2003 Levy Ave. Rm 220</deliveryPoint><city>Tallahassee</city><administrativeArea>FL</administrativeArea><postalCode>32310</postalCode><country>United States</country></address><phone phonetype="voice">8506450142</phone><electronicMailAddress>nyaghoobian@fsu.edu</electronicMailAddress><userId directory="https://orcid.org">https://orcid.org/0000-0002-3399-8650</userId></creator><abstract><para>Fuel moisture content (FMC) is a critical parameter in fire and plume behaviors, showing diurnal and spatial variations influenced by local meteorological conditions, soil characteristics, and fuel properties. In low-intensity fires, small-scale FMC variations intensify, leading to an amplification of their effects on fire physics. In an effort to capture these variations, we developed a physics-based model that couples a thermodynamic-based FMC prediction model for dead fuels with the Fire Dynamics Simulator of the National Institute of Standards and Technology. The model accuracy is validated against several existing experimental datasets, showing improvements over the baseline model, which uses the kinetic-based Arrhenius drying approach. A case study of flame propagation in a small fuel bed is also presented, indicating the improved performance of the new model and its novel capabilities in capturing complex processes of fuel drying and moisture flux exchanges between the fuel and ambient atmosphere.</para><para>The details of the model and its validation studies can be found in: "Dubey, R. R., &amp; Yaghoobian, N. (2024). A physics-based model of thermodynamically varying fuel moisture content for fire behavior prediction. Environmental Modelling &amp; Software, 179, 106111". The instructions on how to run the code can be found in the README file included in the dataset.</para><para>These codes and data are identical to https://github.com/ritambhara1234/Physics-Based-Dynamic-FMC (commit 43f79df4298592d63c82f8c1d91196dc2e6f9900).</para></abstract><keywordSet><keyword>Dead fuel</keyword><keyword>Fire Dynamics Simulator</keyword><keyword>Fuel moisture content</keyword><keyword>Fire Behavior modeling</keyword><keyword>Low-intensity fires</keyword><keyword>Plume dynamics</keyword><keyword>Thermodynamic-based modeling approach</keyword><keyword>FDS</keyword><keyword>FMC</keyword><keywordThesaurus>None</keywordThesaurus></keywordSet><intellectualRights><para>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.</para></intellectualRights><contact id="7321420797762678"><individualName><givenName>Neda</givenName><surName>Yaghoobian</surName></individualName><organizationName>Florida State University</organizationName><positionName>Associate Professor</positionName><address><deliveryPoint>2003 Levy Ave. Rm 220</deliveryPoint><city>Tallahassee</city><administrativeArea>FL</administrativeArea><postalCode>32310</postalCode><country>United States</country></address><phone phonetype="voice">8506450142</phone><electronicMailAddress>nyaghoobian@fsu.edu</electronicMailAddress><userId directory="https://orcid.org">https://orcid.org/0000-0002-3399-8650</userId></contact><methods><methodStep><description><para>The details of the model and its validation studies and data can be found in: "Dubey, R. R., &amp; Yaghoobian, N. (2024). A physics-based model of thermodynamically varying fuel moisture content for fire behavior prediction. Environmental Modelling &amp; Software, 179, 106111". The instructions on how to run the code can be found in the README file included in the dataset.</para></description></methodStep></methods><project><title>Funding Award RC20-1298: The Role of Vorticity and Fuel Moisture on the Near-Field Plume Structure and Ember Dynamics</title><personnel id="1706762879897957"><individualName><givenName>Bryan</givenName><surName>Quaife</surName></individualName><organizationName>Florida State University</organizationName><electronicMailAddress>bquaife@fsu.edu</electronicMailAddress><userId directory="https://orcid.org">https://orcid.org/0000-0002-9186-8926</userId><role>Principal Investigator</role></personnel><award><funderName>U. S. Department of  Defense (DoD), Strategic Environmental Research and Development Program (SERDP)</funderName><funderIdentifier>http://dx.doi.org/10.13039/100013316</funderIdentifier><awardNumber>RC20-1298</awardNumber><title>The Role of Vorticity and Fuel Moisture on the Near-Field Plume Structure and Ember Dynamics</title></award></project><otherEntity id="wfsi-20250430T152030030-d9a8ea073718dab"><entityName>CHANGES.md</entityName><entityType>text/markdown</entityType></otherEntity><otherEntity id="wfsi-20250421T223929676-a5f2f6353fc83cd"><entityName>Dynamic_FMC_model__1_.f90</entityName><entityType>application/octet-stream</entityType></otherEntity><otherEntity id="wfsi-20250421T223929657-7fee62b7e23bc94"><entityName>Air_temperature.csv</entityName><entityType>text/csv</entityType></otherEntity><otherEntity id="wfsi-20250421T223929654-98fd4a64b344dbe"><entityName>Pressure.csv</entityName><entityType>text/csv</entityType></otherEntity><otherEntity id="wfsi-20250421T223929648-9c48a0391b9f229"><entityName>Rainfall.csv</entityName><entityType>text/csv</entityType></otherEntity><otherEntity id="wfsi-20250421T223929643-ea031e3a42ca6a2"><entityName>Relative_humidity.csv</entityName><entityType>text/csv</entityType></otherEntity><otherEntity id="wfsi-20250421T223929639-f113311b54a10be"><entityName>Solar_radiation.csv</entityName><entityType>text/csv</entityType></otherEntity><otherEntity id="wfsi-20250421T223929635-739fd7dcbdf0c96"><entityName>Wind_speed.csv</entityName><entityType>text/csv</entityType></otherEntity><otherEntity id="wfsi-20250421T223929626-37ee0e66d56333e"><entityName>README.md</entityName><entityType>application/octet-stream</entityType></otherEntity><otherEntity id="wfsi-20250426T203055746-6791284a5464eda"><entityName>Coupled_model_validation_3.pdf</entityName><entityType>application/pdf</entityType></otherEntity><otherEntity id="wfsi-20250426T203055753-cbacef85a83304f"><entityName>Coupled_model_validation_2.pdf</entityName><entityType>application/pdf</entityType></otherEntity><otherEntity id="wfsi-20250426T203055757-6c48416abede014"><entityName>Coupled_model_validation_1.pdf</entityName><entityType>application/pdf</entityType></otherEntity></dataset></eml:eml>