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At least 73 records · Page 4

Modeling Low Intensity Fires: Lessons Learned from 2012 RxCADRE

Coupled fire-atmosphere models are increasingly being used to study low-intensity fires, such as those that are used in prescribed fire applications. Thus, the need arises to evaluate these models for their ability to accurately represent fire spread in marginal burning conditions. In this study, wind and fuel data collected during the Prescribed Fire Combustion and Atmospheric Dynamics Research Experiments (RxCADRE) fire campaign were used to generate initial and boundary conditions for coupled fire-atmosphere simulations. We present a novel method to obtain fuels representation at the model grid scale using a combination of imagery, machine learning, and field sampling. Several methods to generate wind input conditions for the model from eight different anemometer measurements are explored. We find a strong sensitivity of fire outcomes to wind inputs. This result highlights the critical need to include variable wind fields as inputs in modeling marginal fire conditions. This work highlights the complexities of comparing physics-based model results against observations, which are more acute in marginal burning conditions, where stronger sensitivities to local variability in wind and fuels drive fire outcomes.

54 ENVIRONMENTAL SCIENCES↗

Sodium Fire Collaborative Study Progress CNWG Fiscal Year 2021

This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year (FY) 2021 and is a continuation of the FY2020 progress report. In this report, we only report the changes made to the current sodium pool fire model in MELCOR. We modified and corrected many control functions to enhance the current model from the FY2020 report. This year’s enhancements relate to better agreement of the suspended aerosol measurement from JAEA’s F7 series tests. Staff from Sandia and JAEA conducted the validation studies of the sodium pool fire model in MELCOR. To validate this pool fire model with the latest enhancement, JAEA sodium pool fire experiments (F7-1 and F7-2) were used. The results of the calculation, including the code-to-code comparisons are discussed as well as suggestions for further model improvement. Finally, recommendations are made for new MELCOR simulations for FY2022.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Sodium Fire Collaborative Study Progress (CNWG Fiscal Year 2022)

This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year (FY) 2022 and is a continuation of the FY 2021 progress report. We only report the changes made to the current sodium pool fire model in MELCOR. We modified and corrected many control functions to enhance the fraction of oxygen consumed that reacts to form monoxide (FO2) parameter in the current model from the FY2021 report. This year's enhancements relate to better agreement of the suspended aerosol measurement from JAEA's F7 series tests. Staff from Sandia and JAEA conducted the validation studies of the sodium pool fire model in MELCOR. To validate this pool fire model with the latest enhancement, JAEA sodium pool fire experiments (F7-1 and F7-2) were used. The results of the calculation, including the code-to-code comparisons are discussed as well as suggestions for further model improvement. Finally, recommendations are made for new MELCOR simulations for FY 2023.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Verification of the naval oceanic vertical aerosol model during FIRE

The value of Naval Oceanic Vertical Aerosol Model (NOVAM) is illustrated for estimating the non-uniform and non-logarithmic extinction profiles, based on a severe test involving conditions close to and beyond the limits of applicability of NOVAM. A more comprehensive evaluation of NOVAM from the FIRE data is presented, which includes a clear-air case. For further evaluation more data are required on the vertical structure of the extinction in the marine atmospheric boundary layer (MABL), preferably for different meteorological conditions and in different geographic areas (e.g., ASTEX).

Davidson, K. L.↗

Modeling Forest Understory Fires in an Eastern Amazonian Landscape

Forest understory fires are an increasingly important cause of forest impoverishment in Ammonia, but little is known of the landscape characteristics and climatic phenomena that determine their occurrence. We developed empirical functions relating the occurrence of understory fires to landscape features near Paragominas, a 35- yr-old ranching and logging center in eastern Ammonia. An historical sequence of maps of forest understory fire was created based on field interviews With local farmers and Landsat TM images. Several landscape features that might explain spatial variations in the occurrence of understory fires were also mapped and co-registered for each of the sample dates, including: forest fragment size and shape, forest impoverishment through logging and understory fires, source of ignition (settlements and charcoal pits), roads, forest edges, and others. The spatial relationship between forest understory fire and each landscape characteristic was tested by regression analyses. Fire probability models were then developed for various combinations of landscape characteristics. The analyses were conducted separately for years of the El Nino Southern Oscillation (ENSO), which are associated with severe drought in eastern Amazonia, and non-ENS0 years. Most (91 %) of the forest area that burned during the 10-yr sequence caught fire during ENSO years, when severe drought may have increased both forest flammability and the escape of agricultural management fires. Forest understory fires were associated with forest edges, as reported in previous studies from Ammonia. But the strongest predictor of forest fire was the percentage of the forest fragment that had been previously logged or burned. Forest fragment size, distance to charcoal pits, distance to agricultural settlement, proximity to forest edge, and distance to roads were also correlated with forest understory fire. Logistic regression models using information on fragment degradation and distance to ignition sources accurately predicted the location of lss than 80% of the forest fires observed during the ENSO event of 1997- 1998. In this Amazon landscape, forest understory fire is a complex function of several variables that influence both the flammability and ignition exposure of the forest.

Alencar, A. A. C.↗

Full-scale flammability test data for validation of aircraft fire mathematical models

Twenty-five large scale aircraft flammability tests were conducted in a Boeing 737 fuselage at the NASA Johnson Space Center (JSC). The objective of this test program was to provide a data base on the propagation of large scale aircraft fires to support the validation of aircraft fire mathematical models. Variables in the test program included cabin volume, amount of fuel, fuel pan area, fire location, airflow rate, and cabin materials. A number of tests were conducted with jet A-1 fuel only, while others were conducted with various Boeing 747 type cabin materials. These included urethane foam seats, passenger service units, stowage bins, and wall and ceiling panels. Two tests were also included using special urethane foam and polyimide foam seats. Tests were conducted with each cabin material individually, with various combinations of these materials, and finally, with all materials in the cabin. The data include information obtained from approximately 160 locations inside the fuselage.

Kuminecz, J. F.↗

Identification of the Space Shuttle Main Engine dynamic models from firing data

A multi-input multi-output system identification technique is used to obtain linearized point models of the Space Shuttle Main Engine (SSME) at five different operating conditions (power levels) from the engine firing data. This study demonstrates that the open-loop dynamics of the SSME can be successfully modeled from the engine firing data. The identified linear models may be used for fault detection studies and control system design and development.

Saravanan, N.↗

The time since land-use transition drives changes in fire activity in the Amazon-Cerrado region

Abstract Deforestation and climate change are expected to alter fire regimes along the Cerrado-Amazon transition, one of the world’s most active agricultural frontiers. Here we tested the hypothesis that the time since land-use transition (age of frontier) and agricultural intensification also drive changes in the region’s fire regimes by reducing fire probability in both drought and non-drought years. We modeled fire probability as a function of the time since land-use transitions based on MapBiomas Project datasets from 1986 to 2020. We find that, while burned area declined as pasturelands aged and croplands advanced, deforestation abruptly increased fire activity before (Amazon: 4 years; Cerrado: 3 years) and after (Amazon: 8 years; Cerrado: 7 years) land clearing for pasture, especially in the Amazon. Additionally, the combination of ignition risk, drought, and air-dryness increased the likelihood of large extents of burned areas associated with deforestation. Incorporating frontier age as a proxy for governance in fire modeling is crucial, given the ecological implications of changing fire regimes despite declining rates of fire probability. Most importantly, protecting against deforestation and preserving native vegetation are vital.

Environmental Sciences & Ecology↗

Modeling aerosol losses and clothing effects in fires

The described modification of a physiochemical fire model predicts physical effects in clothed humans exposed to elevated temperatures as well as gas and aerosol concentrations in the atmosphere of an aerospace vehicle. The modifications involve the reduction in aerosol concentrations caused by settling and some improvements in dealing with mass and heat transfer effects. Predicted skin temperatures are found to be within 2 C of experimental values for the cases studied, and model predictions of total body enthalpy seem to correlate with symptomology observed experimentally.

Cagliostro, D. E.↗

Sodium Fire Collaborative Study Progress -- CNWG Fiscal Year 2020

This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year 2020. First, the current sodium pool fire model in MELCOR, which is adapted from CONTAIN-LMR code, is discussed. The associated sodium fire input requirements are also presented. These input requirements are flexible enough to permit further model development via control functions to enhance the current model without modifying the source code. The theoretical pool fire model improvement developed at Sandia is discussed. A control function model has been developed from this improvement. Then, the validation study of the sodium pool fire model in MELCOR carried out by both Sandia and JAEA’s staff is described. To validate this pool fire model with the enhancement, a JAEA sodium pool fire experiment (F7-1 test) is used. The results of the calculation are discussed as well as suggestions for further model improvement. Finally, recommendations are made for new MELCOR simulations for next fiscal year, 2021.

36 MATERIALS SCIENCE↗

The Global Fire Atlas of Individual Fire Size, Duration, Speed and Direction

Natural and human-ignited fires affect all major biomes, altering ecosystem structure, biogeochemical cycles and atmospheric composition. Satellite observations provide global data on spatiotemporal patterns of biomass burning and evidence for the rapid changes in global fire activity in response to land management and climate. Satellite imagery also provides detailed information on the daily or sub-daily position of fires that can be used to understand the dynamics of individual fires. The Global Fire Atlas is a new global dataset that tracks the dynamics of individual fires to determine the timing and location of ignitions, fire size and duration, and daily expansion, fire line length, speed, and direction of spread. Here, we present the underlying methodology and Global Fire Atlas results for 2003–2016 derived from daily moderate-resolution (500 m) Collection 6 MCD64A1 burned-area data. The algorithm identified 13.3 million individual fires over the study period, and estimated fire perimeters were in good agreement with independent data for the continental United States. A small number of large fires dominated sparsely populated arid and boreal ecosystems, while burned area in agricultural and other human-dominated landscapes was driven by high ignition densities that resulted in numerous smaller fires. Long-duration fires in boreal regions and natural landscapes in the humid tropics suggest that fire season length exerts a strong control on fire size and total burned area in these areas. In arid ecosystems with low fuel densities, high fire spread rates resulted in large, short-duration fires that quickly consumed available fuels. Importantly, multiday fires contributed the majority of burned area in all biomass burning regions. A first analysis of the largest, longest and fastest fires that occurred around the world revealed coherent regional patterns of extreme fires driven by large-scale climate forcing. Global Fire Atlas data are publicly available through http://www.globalfiredata.org (last access: 9 August 2018) and https://doi.org/10.3334/ORNLDAAC/1642, and individual fire information and summary data products provide new information for benchmarking fire models within ecosystem and Earth system models, understanding vegetation–fire feedbacks, improving global emissions estimates, and characterizing the changing role of fire in the Earth system.

global fire atlas↗

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Non-NASA Center↗

The use of computer models to predict temperature and smoke movement in high bay spaces

The Building and Fire Research Laboratory (BFRL) was given the opportunity to make measurements during fire calibration tests of the heat detection system in an aircraft hangar with a nominal 30.4 (100 ft) ceiling height near Dallas, TX. Fire gas temperatures resulting from an approximately 8250 kW isopropyl alcohol pool fire were measured above the fire and along the ceiling. The results of the experiments were then compared to predictions from the computer fire models DETACT-QS, FPETOOL, and LAVENT. In section A of the analysis conducted, DETACT-QS AND FPETOOL significantly underpredicted the gas temperature. LAVENT at the position below the ceiling corresponding to maximum temperature and velocity provided better agreement with the data. For large spaces, hot gas transport time and an improved fire plume dynamics model should be incorporated into the computer fire model activation routines. A computational fluid dynamics (CFD) model, HARWELL FLOW3D, was then used to model the hot gas movement in the space. Reasonable agreement was found between the temperatures predicted from the CFD calculations and the temperatures measured in the aircraft hangar. In section B, an existing NASA high bay space was modeled using the CFD model. The NASA space was a clean room, 27.4 m (90 ft) high with forced horizontal laminar flow. The purpose of this analysis is to determine how the existing fire detection devices would respond to various size fires in the space. The analysis was conducted for 32 MW, 400 kW, and 40 kW fires.

Notarianni, Kathy A.↗

The Fire and Smoke Model Evaluation Experiment—A Plan for Integrated, Large Fire–Atmosphere Field Campaigns

The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models.

54 ENVIRONMENTAL SCIENCES↗

Simulated wildfire burned area over the CONUS during 2001-2020

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM). A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

Liu, Ye↗

The impact of a 2 X CO2 climate on lightning-caused fires

Future climate change could have significant repercussions for lightning-caused wildfires. Two empirical fire models are presented relating the frequency of lightning fires and the area burned by these fires to the effective precipitation and the frequency of thunderstorm activity. One model deals with the seasonal variations in lightning fires, while the second model deals with the interannual variations of lightning fires. These fire models are then used with the Goddard Institute for Space Studies General Circulation Model to investigate possible changes in fire frequency and area burned in a 2 X CO2 climate. In the United States, the annual mean number of lightning fires increases by 44%, while the area burned increases by 78%. On a global scale, the largest increase in lightning fires can be expected in untouched tropical ecosystems where few natural fires occur today.

Price, Colin↗

Analysis of Fire-Induced Circulations during the FireFlux2 Experiment

Despite recent advances in both coupled fire modeling and measurement techniques to sample the fire environment, the fire–atmosphere coupling mechanisms that lead to fast propagating wildfires remain poorly understood. This knowledge gap adversely affects fire management when wildland fires propagate unexpectedly rapidly and shift direction due to the fire impacts on local wind conditions. In this work, we utilized observational data from the FireFlux2 prescribed burn and numerical simulations performed with a coupled fire–atmosphere model WRF-SFIRE to assess the small-scale impacts of fire on local micrometeorology under moderate wind conditions (10–12 m/s). The FireFlux2 prescribed burn provided a comprehensive observational dataset with in situ meteorological observations as well as IR measurements of fire progression. To directly quantify the effects of fire–atmosphere interactions, two WRF-SFIRE simulations were executed. One simulation was run in a two-way coupled mode in which the heat and moisture fluxes emitted from the fire were injected into the atmosphere, and the other simulation was performed in a one-way coupled mode for which the atmosphere was not affected by the fire. The difference between these two simulations was used to analyze and quantify the fire impacts on the atmospheric circulation at different sections of the fire front. The fire-released heat fluxes resulted in vertical velocities as high as 10.8 m/s at the highest measurement level (20 m above ground level) gradually diminishing with height and dropping to 7.9 m/s at 5.77 m. The fire-induced horizontal winds indicated the strongest fire-induced flow at the lowest measurement levels (as high as 3.3 m/s) gradually decreasing to less than 1 m/s at 20 m above ground level. The analysis of the simulated flow indicates significant differences between the fire-induced circulation at the fire head and on the flanks. The fire-induced circulation was much stronger near the fire head than at the flanks, where the fire did not produce particularly strong cross-fire flow and did not significantly change the lateral fire progression. However, at the head of the fire the fire-induced winds blowing across the front were the strongest and significantly accelerated fire progression. The two-way coupled simulation including the fire-induced winds produced 36.2% faster fire propagation than the one-way coupled run, and more realistically represented the fire progression.

Benik, Jeremy T.↗

Upper Troposphere Smoke Injection From Large Areal Fires

Abstract Large areal fires, such as those ignited following a nuclear detonation, can inject smoke into the upper troposphere and lower stratosphere. Detailed fire simulations allow for assessment of how local weather interacts with these fires and affects smoke lofting. In this study, we employ the fire simulation package in the Weather Research and Forecasting (WRF‐Fire) model, Version 4.0.1, to explore how smoke lofting from a fire burning a homogeneous fuel bed changes with varying local winds, relative humidity, and atmospheric boundary‐layer stability for two different‐sized areal fires. The presence of moisture has the greatest influence on the results by raising the altitude of lofting, while faster wind speeds dampen lofting and lower the injection height. Stably stratified conditions inhibit plume propagation compared with neutrally stratified conditions, although the impact of stability is not as strong as that of moisture and winds. These findings highlight the importance of using an appropriate atmospheric profile when simulating large fires, as the local weather can have a meaningful influence on smoke lofting.

54 ENVIRONMENTAL SCIENCES↗