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NASA NTRS2004

Fire Detection Organizing Questions

Verified models of fire precursor transport in low and partial gravity: a. Development of models for large-scale transport in reduced gravity. b. Validated CFD simulations of transport of fire precursors. c. Evaluation of the effect of scale on transport and reduced gravity fires. Advanced fire detection system for gaseous and particulate pre-fire and fire signaturesa: a. Quantification of pre-fire pyrolysis products in microgravity. b. Suite of gas and particulate sensors. c. Reduced gravity evaluation of candidate detector technologies. d. Reduced gravity verification of advanced fire detection system. e. Validated database of fire and pre-fire signatures in low and partial gravity.

Source record↗

NASA NTRS2007

Fire Fighting from High Altitude

A viewgraph presentation on high altitude fire fighting is shown. The topics include: 1) Yellowstone Fire - 1988; 2) 2006 Western States Fire Mission Over-View; 3) AMS-Wildfire Scanner; 4) October 24-25 Mission: Yosemite NP and NF; 5) October 24-25 Mission MODIS Overpass; 6) October 24-25 Mission Highlights; 7) October 28-29 Mission Esperanza Fire, California; 8) Response to the Esperanza Fire in Southern California -- Timeline Oct 27-29 2006; 9) October 28-29 Mission Esperanza Fire Altair Flight Routing; 10) October 28-29 Mission Esperanza Fire Altair Over-Flights; 11) October 28-29 Mission Highlights; 12) Results from the Esperanza Fire Response; 13) 2007 Western States Fire Mission; and 14) Western States UAS Fire Mission 2007

Cobleigh, Brent↗

NASA NTRS2006

The Relationship of Forest Fires Detected by MODIS and SRTM Derived Topographic Features in Central Siberia

Fires are a common occurrence in the Siberian boreal forest. The MOD14 Thermal anomalies product of the Terra MODIS Moderate Resolution Spectroradiometer) product set is designed to detect thermal anomalies (i.e. hotspots or fires) on the Earth's surface. Recent field studies showed a dependence of fire occurrence on topography. In this study MODIS thermal anomaly data and SRTM topography data were merged and analyzed to evaluate if forest fires are more likely to occur at certain combinations of elevation, slope and aspect. Using the satellite data over a large area can lead to better understanding how topography and forest fires are related. The study area covers a 2.5 Million krn(exp 2) portion of the Central Siberian southern taiga from 72 deg to 110 deg East and from 50 deg to 60 deg North. About 57% of the study area is forested and 80% of the forest grows between 200 and 1000 m. Forests with pine (Pinus sylvestris), larch (Larix sibirica, L. gmelinii), Siberian pine (Pinus sibirica), spruce (Picea obovata.) and fir (Abies sibirica) cover most of the landscape. Deciduous stands with birch (Betula pendula, B. pubescens) and aspen (Populus tremula) cover the areas of lower elevation in this region. The climate of this area is distinctly continental with long, cold winters and short hot summers. The tree line in this part of the world is around 1500 m in elevation with alpine tundra, snow and ice fields and rock outcrops extending up to over 3800 m. A 500 m resolution landcover map was developed using 2001 MODIS MOD13 Normalized Vegetation Index (NDVI) and Middle Infrared (MIR) products for seven 16-day periods. The classification accuracy was over 87%. The SRTM version 2 data, which is distributed in 1 degree by 1 degree tiles were mosaiced using the ENVI software. In this study, only those MODIS pixels were used that were flagged as "nominal or high confidence fire" by the MODIS fire product team. Using MODIS data from the years 2000 to 2005 along with the improved Shuttle Radar Topographic Mission (SRTM) version 2 data at 100 m resolution, the distribution of hot spots was examined by elevation, slope and aspect as well as by forest type. The results show that more forest area burns at lower elevations but a larger percentage of the available forest area burns at higher elevations. This is probably because steep slopes occur at higher elevations. Fires are only more common on slopes with a southern exposure if the slope is steeper than 15 degrees. The next step in this study will be to monitor areas where the risk of fire is high (steep slopes with a southern exposure) and to refine this method by incorporating anthropogenic features for more accurate fire disturbance monitoring.

Ranson, Jon K.↗

NASA NTRS2008

Global Characterization of Biomass-Burning Patterns using Satellite Measurements of Fire Radiative Energy

Remote sensing is the most practical means of measuring energy release from large open-air biomass burning. Satellite measurement of fire radiative energy (FRE) release rate or power (FRP) enables distinction between fires of different strengths. Based on a 1-km resolution fire data acquired globally by the MODerate-resolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites from 2000 to 2006, instanteaneous FRP values ranged between 0.02 MW and 1866 MW, with global daily means ranging between 20 and 40 MW. Regionally, at the Aqua-MODIS afternoon overpass, the mean FRP values for Alaska, Western US, Western Australia, Quebec and the rest of Canada are significantly higher than these global means, with Quebec having the overall highest value of 85 MW. Analysis of regional mean FRP per unit area of land (FRP flux) shows that a peak fire season in certain regions, fires can be responsible for up to 0.2 W/m(sup 2) at peak time of day. Zambia has the highest regional monthly mean FRP flux of approximately 0.045 W/m(sup 2) at peak time of day and season, while the Middle East has the lowest value of approximately 0.0005 W/m(sup 2). A simple scheme based on FRP has been devised to classify fires into five categories, to facilitate fire rating by strength, similar to earthquakes and hurricanes. The scheme uses MODIS measurements of FRP at 1-km resolution as follows: catagory 1 (less than 100 MW), category 2 (100 to less than 500 MW), category 3 (500 to less than 1000 MW), category 4 (1000 to less than 1500 MW), catagory 5 (greater than or equal to 1500 MW). In most regions of the world, over 90% of fires fall into category 1, while only less than 1% fall into each of categories 3 to 5, although these proportions may differ significantly from day to day and by season. The frequency of occurence of the larger fires is region specific, and could not be explained by ecosystem type alone. Time-series analysis of the propertions of higher category fires based on MODIS measured FRP from 2002 to 2006 does not show any moticeable trend because of the short time period.

Ichoku, Charles↗

NASA NTRS2007

Multiple-Parameter, Low-False-Alarm Fire-Detection Systems

Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.

Hunter, Gary W.↗

NASA NTRS2011

Persistent Effects of Fire Severity on Early Successional Forests in Interior Alaska

There has been a recent increase in the frequency and extent of wildfires in interior Alaska, and this trend is predicted to continue under a warming climate. Although less well documented, corresponding increases in fire severity are expected. Previous research from boreal forests in Alaska and western Canada indicate that severe fire promotes the recruitment of deciduous tree species and decreases the relative abundance of black spruce (Picea mariana) immediately after fire. Here we extend these observations by (1) examining changes in patterns of aspen and spruce density and biomass that occurred during the first two decades of post-fire succession, and (2) comparing patterns of tree composition in relation to variations in post-fire organic layer depth in four burned black spruce forests in interior Alaska after 10-20 years of succession.Wefound that initial effects of fire severity on recruitment and establishment of aspen and black spruce were maintained by subsequent effects of organic layer depth and initial plant biomass on plant growth during post-fire succession. The proportional contribution of aspen (Populus tremuloides) to total stand biomass remained above 90% during the first and second decades of succession in severely burned sites, while in lightly burned sites the proportional contribution of aspen was reduced due to a 40- fold increase in spruce biomass in these sites. Relationships between organic layer depth and stem density and biomass were consistently negative for aspen, and positive or neutral for black spruce in all four burns. Our results suggest that initial effects of post-fire organic layer depths on deciduous recruitment are likely to translate into a prolonged phase of deciduous dominance during post-fire succession in severely burned stands. This shift in vegetation distribution has important implications for climate-albedo feedbacks, future fire regime, wildlife habitat quality and natural resources for indigenous subsistence activities in interior Alaska.

Shenoy, Aditi↗

NASA NTRS2011

Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data

Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.

Morton, Douglas C.↗

NASA NTRS2013

Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

airborne scanner↗

NASA NTRS2017

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity from Landsat.

Alonzo, Michael↗

NASA NTRSDate not supplied

Quantifying Post-fire Vegetation Recovery on the Colorado Front Range

Forest composition and structure in the Colorado Front Range has been altered by changing wildfire regimes, particularly in response to increased fire severity. Subsequent reductions in post-fire tree regeneration can result in chronic impacts to ecological function and water quality. This project partnered with the U.S. Forest Service to estimate tree canopy recovery from 15 to 21 years after four Colorado Front Range fires that burned between 1996 and 2002— the Bobcat, Buffalo Creek, Hayman, and High Meadows fires—using Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI). First, we evaluated relationships between recovery metrics derived from spectral vegetation indices (i.e. post-fire vegetation, normalized burn ratio, percent unrecovered vegetation) and field-collected counts of post-fire tree seedling regeneration. Then, we used high-resolution imagery paired with Landsat timeseries spectral and geomorphometric data to map forest canopy cover 15-21 years post-fire. Finally, we assessed ecological drivers of recovery including topography, climate, soils, and fire severity using Random Forest. While we found that basic vegetation index metrics failed to distinguish field-measured tree regeneration, our data showed that both aspect and burn severity were important drivers of vegetation recovery. North-facing aspects tended to have higher pre-fire Normalized Difference Vegetation Index (NDVI) and thus higher burn severities. However, areas that burned at high severity experienced slower vegetation recovery, regardless of aspect suggesting that high severity fire can mute favorable site conditions on north-facing aspects (i.e. moister, more developed soils). While this work propels our understanding of variables that influence vegetative recovery, vegetation type, forest conversion, and watershed function, more work should focus on what vegetation indices identifying areas of recovery indicate across different forest types and burn severities.

NASA DEVELOP↗

NASA NTRS2021

Colorado Front Range Disasters: Understanding the Impact of Forest Management on the Cameron Peak and CalWood Fire

Along the Colorado Front Range, forest management has gained significant attention due to uncharacteristically large fires that burned late in 2020. The Cameron Peak Fire (largest in Colorado recorded history) and the CalWood Fire collectively burned an estimated 219,019 acres from August through December of 2020. Project partners at the Coalition for the Poudre River Watershed, Colorado State Forest Service, Ben Delatour Scout Ranch, The Nature Conservancy, Colorado Forest Restoration Institute, and Colorado State University were interested in understanding the effectiveness of previous forest treatments in reducing burn severity within the Cameron Peak Fire and the CalWood Fire. We first collated a forest treatment dataset from pre-existing datasets by reclassifying over 29,000 treatments, which occurred across the Northern Colorado Front Range between 1970-2020. Secondly, we mapped three burn severity indices using Landsat 8 OLI and Sentinel-2 MSI Earth observations and compared them to soil burn severity field data. Thirdly, a total of 35 topographic, disturbance, forest structure, and treatment predictor variables were generated across the fires. Finally, we assessed relationships between these predictor variables and burn severity using the random forest algorithm. Model results indicate that the primary drivers of burn severity were elevation and distance to treatment edge for the Cameron Peak Fire and fire area and forest canopy cover for the CalWood Fire. Further analysis of these variables paired with field data is necessary to understand the relationship between burn severity and treatments to guide future restoration efforts, improve forest resiliency, and mitigate fire risks.

Neal Swayze↗

NASA NTRSDate not supplied

Future Pathways for Arctic Forest Fires

Wildfires are expected to become more common and more severe in the Arctic states due to climate change. Main cause for the fires is human activity, even in the boreal and Arctic forests. Therefore, activities such forest management and tourism, together with firefighting capacity and readiness, can have a significant impact on future wildfire risks and impacts. To assess the impacts of these factors we have created pathways for future wildfires up to 2050 for the Arctic states. We explore high and low fire activity and risk pathways for all the Arctic states and suggest most our best guess pathways for each state separately. The low activity and fire risk pathway assumes active fire suppression via population participation and official land management, efficient fuel treatments to reduce fire risk, and active firefighting. The high activity and fire risk pathway assumes the opposite due to lack of government and community response, with addition of lacking response to climate-driven changes to wildfire risks. In the Nordic countries, human ignition sources, such as timber extraction, tourism, summer cottages, and expanding wildland-urban intermix due to exurban growth may increase. In addition to these in Canada and Alaska, expansion of agriculture increases the likelihood of open burning of agricultural waste, increasing risk of the fire spreading to wildlands. Drier fuels due to climate change increase the risk of fires, and there is a growing risk of extreme heat conditions, creating favorable conditions for extreme wildfires from any ignition source. Throughout the Arctic lightning is expected to increase, increasing the risk of tundra (specifically grassland) fires, with potential to occur in hard-to-reach locations for firefighting. In short, policy actions and education play a crucial role in future wildfire management and adaptation.

Future↗

NASA NTRSDate not supplied

CONUS and Global Carbon Consumption Database for Wildland Fire

Fire plays a significant role on both national and global scales, profoundly impacting landscapes shaped by human activity as well as wildlands. Even though fire can be devastating, wildland fire is a natural and integral force on our landscapes. Fires can also serve to reduce fuels to mitigate wildfire risk and maintain healthy ecosystem functions. However, the smoke produced by fires, regardless of their size or purpose, can pose adverse effects on human health when inhaled downwind. Understanding the influence of smoke on air quality and human well-being necessitates the quantification of emissions that fires release into the atmosphere. In response to this need, we have developed a carbon consumption database for the Continental United States (CONUS) and are developing a global carbon consumption database, both of which are directly link to distinct fuels within various fire danger categories. Fuel Characteristic Classification System (FCCS) fuels are used to parameterize biomass, and consumption is broken down into five Fire Danger categories (Low, Moderate, High, Very High, Extreme), for both ‘new’ and ‘residual’ burning scenarios. Residual burned area is defined as burning in areas that have recently burned. We implemented the FCCS 30-meter CONUS fuelbed dataset during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign to estimate daily carbon emissions. Our emissions estimates were rigorously compared against in-situ measurements of CO2, CO, and black carbon aerosols, revealing a robust agreement between the two datasets. The 300-meter global database builds upon the foundations of the Pettinari, M. Lucrecia (2015) Global Fuelbed database, a global fuel map with standardized FCCS biomass parameters. These products can serve as valuable tools when used in conjunction with burned area data to rapidly and accurately estimate carbon consumed and released into the atmosphere.

FCCS↗

NASA NTRS2016

Operation and Development Status of the Spacecraft Fire Experiments (Saffire)

Since 2012, a series of Spacecraft Fire Experiments (Saffire) have been under development by the Spacecraft Fire Safety Demonstration (SFS Demo) project, funded by NASA's Advanced Exploration Systems Division. The overall objective of this project is to reduce the uncertainty and risk associated with the design of spacecraft fire safety systems for NASA's exploration missions. The approach to achieving this goal has been to define, develop, and conduct experiments that address gaps in spacecraft fire safety knowledge and capabilities identified by NASA's Fire Safety System Maturation Team. The Spacecraft Fire Experiments (Saffire-I, -II, and -III) are material flammability tests at length scales that are realistic for a spacecraft fire in low-gravity. The specific objectives of these three experiments are to (1) determine how rapidly a large scale fire grows in low-gravity and (2) investigate the low-g flammability limits compared to those obtained in NASA's normal gravity material flammability screening test. The experiments will be conducted in Orbital ATK's Cygnus vehicle after it has unberthed from the International Space Station. The tests will be fully automated with the data downlinked at the conclusion of the test before the Cygnus vehicle reenters the atmosphere. This paper discusses the status of the Saffire-I, II, and III experiments followed by a review of the fire safety technology gaps that are driving the development of objectives for the next series of experiments, Saffire-IV, V, and VI.

Fire Safety↗

NASA NTRSDate not supplied

An Analysis of Fire Dynamics Inside and Outside Indigenous Territories and Protected Areas in a Brazilian Agricultural Frontier

Sustainable land management, including protected areas, is integral to conserving tropical ecosystems and reducing carbon emissions in the Brazilian Amazon. In disturbed Amazon landscapes fire is commonly used to clear land or old fields for agriculture or pastureland. Human-set fires are the most common driver of deforestation and carbon emissions in Amazonia. Evidence suggests that indigenous groups have also used fire for land management since Pre-Columbian times. However, when used unsustainably, fires in this biome can result in degradation of forest ecosystems, decreased ability to store carbon, and health impacts resulting from smoke and particulate matter. Due to the uptick in fire occurrences in 2019, more restrictions on fire use were implemented in 2019 and 2020. Presidential decrees 9.992/2019 and 10.424/2020 banned fire use completely for periods of 60 and 120 days respectively, except by indigenous communities or authorities. Despite these bans, fire use remained high in both years. In the state of Mato Grosso, agricultural activity and expansion influences the anthropogenic fire regime. Indigenous and protected areas cover approximately 25% of its land area.

remote sensing↗

NASA NTRS2024

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗

NASA NTRS1979

Application of the relative energy release criteria to enclosure fire testing

The five relative energy release criteria (RERC) which are a first step towards formulating a unified concept that can be applied to the development of fires in enclosures, place upper bounds on the rate and amount of energy released during a fire. They are independent, calculated readily, and may be applied generally to any enclosure regardless of size. They are useful in pretest planning and for interpreting experimental data. Data from several specific fire test programs were examined to evaluate the potential use of RERC to provide test planning guidelines. The RERC were compared with experimental data obtained in full-scale enclosures. These results confirm that in general the RERC do identify the proper limiting constraints on enclosure fire development and determine the bounds of the fire development envelope. Plotting actual fire data against the RERC reveals new valid insights into fire behavior and reveals the controlling constraints in fire development. The RERC were calculated and plotted for several descrpitions of full-scale fires in various aircraft compartments.

Roschke, E. J.↗

NASA NTRS1988

Spacecraft Fire-Safety Experiments for Space Station: Technology Development Mission

Definitions, overall descriptions, and preliminary apparatus and instrumentation requirements are presented for three spacecraft fire-safety experiments appropriate for inclusion in a growth-version of the Space Station. The experiments are as follows: 1. Combustion and Flame Spread of Typical Spacecraft Materials in a Low Velocity Convective Flow in Low Gravity 2. Fire and Fire-Extinguishant Interactions with Various Fire Scenarios in Low Gravity 3. Smoldering and Deep-Seated Combustion in Low Gravity. The experiments were selected from an assessment of recommendations for advanced technologies for prevention, detection, and control of fires in spacecraft. The experiments and their facilities are intended to constitute a portion of a Spacecraft Fire Safety Technology Development Mission (TDM). Basic requirements for the mission study are that the Space Station is essential for the accomplishment of the experimental objectives and that the technology being developed is appropriate for the growth version of the Space Station. The advantages of these three experiments are that, not only do they explore problems relevant to the Space Station operation and utilization, but also they constitute tests adaptable to two multiuse facilities installed in the Space Station laboratory module, the Combustion Tunnel Facility and the Combustion Facility. Three additional spacecraft fire-safety experiments, essential precursors to the TD M for near-term performance, are also described as follows: 1. Near-Term Testing of Materials for Combustion and Flame Spread 2. Near-Term Extinguishment of Fires in a Low-Gravity Test Bed 3. Post-Fire Recovery of Sensitive Electrical and Electronic Equipment. For all the experiments, the study defines accommodations in terms of first-order space, mass, power, consumables, and crew-time estimates. The study also reviews the key problems to be addressed, namely experiment safety hazards, non-intrusive diagnostics development and waste-products disposal. A preliminary task and time schedule for design, development, and experiment fabrication is proposed.

Youngblood, Wallace W.↗