Title:

Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – fuel loading and consumption

Author(s):

Walker-Ravena, Carlos; Hadden, Rory M.; Mueller, Eric V.; Campbell-Lochrie, Zakary J.; Gallagher, Michael R.; Cole, Jason A.; Patterson, Matthew M.; Skowronski, Nicholas S.

Publication Year:

2022

How to Cite:

These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the citation below when citing the data product:

Walker-Ravena, Carlos; Hadden, Rory M.; Mueller, Eric V.; Campbell-Lochrie, Zakary J.; Gallagher, Michael R.; Cole, Jason A.; Patterson, Matthew M.; Skowronski, Nicholas S. 2022. Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments – fuel loading and consumption. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2022-0078

Abstract:

The United States Department of Defense (DoD) Strategic Environmental Research and Development Program (SERDP) funded project: "Multi-scale Analyses of Wildland Fire Combustion Processes in Open-canopied Forests using Coupled and Iteratively Informed Laboratory-, Field-, and Model-based Approaches (RC-2641)" small-scale field experiments were designed to investigate how contrasting fuel conditions (e.g., fuel load, particle type, bulk density), fire spread type (e.g., heading vs. backing), and ambient conditions (e.g., seasonality, moisture, flow, temperature) influenced physical processes associated with combustion (e.g., heat transfer, flame propagation, flow) and the scale-dependent coupling of these processes. Additionally, these experiments provide 1) a linkage between small-scale laboratory combustion experiments and large-scale operational prescribed fires, and 2) archived datasets for further model development and evaluation. Our experimental design incorporates complementary approaches, methods, and instrumentation employed at these other scales, to quantify critical properties of the experimental fires’ physics domains (e.g., fuels and ambient conditions) and processes associated with combustion (e.g., heat transfer, flame propagation, flow). The small-scale field experiments include a series of highly instrumented, intermediate-scale experiments conducted on 100 square meter plots at the Silas Little Experimental Forest, New Lisbon, New Jersey.

This dataset contains data from 13 burns collected in 2019 from LAUMAS model ISM75 (SN: M0179216) load cells. Experiments 21-26 contained two load cells located under truss B and C and experiments 27-35 contained two load cells located under truss B. These data were collected at 5 hertz (Hz). The load cell data were used to estimate fuel loading and consumption at specific locations in the plot. Data include a time history of fuel bed mass (grams).

Keywords:

fire behavior; fire spread; combustion; computational fluid dynamics; aerodynamic drag; fuel structure and loading; heat flux; prescribed burn; prescribed fire; prescribed energy release; load cell; fuel loading; consumption; biota; climatologyMeteorologyAtmosphere; environment; Fire; Fire suppression, pre-suppression; Prescribed fire; Smoke; Wildland/urban interface; Silas Little Experimental Forest; New Jersey; Burlington County; Pinelands National Reserve; PNR; Pine Barrens; NJPB; Pinelands

Related publications:

• Gallagher, Michael R.; Skowronski, Nicholas S.; Hadden, Rory M.; Mueller, Eric V.; Clark, Kenneth L.; Campbell-Lochrie, Zakary J.; Walker-Ravena, Carlos, ; Kremens, Robert L.; Everland, Alexis I.; Patterson, Matthew M.; Cole, Jason A.; Heilman, Warren E.; Charney, Joseph J.; Bian, Xindi, ; Mell, William E.; Hom, John L.; Im, Seong-kyun; Kiefer, Michael T.; Zhong, Shiyuan, ; Simeoni, Albert J.; Rangwala, Ali; Di Cristina, Giovanni. 2022. Multi-scale analyses of wildland fire combustion processes: Small-scale field experiments - plot layout and documentation. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2022-0079

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