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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Optimal firing rate estimation

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

NASA Discipline Neuroscience↗
DOE OSTI2021

Attribution of the Australian bushfire risk to anthropogenic climate change

Abstract. Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-term observations of heat and drought; and 11 large ensembles of state-of-the-art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30 % in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the likelihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September–February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July–December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and exposure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires.

van Oldenborgh, Geert Jan (ORCID:0000000268989535)↗
DOE OSTI2020

Airborne Release Fractions from Surrogate Nuclear Waste Fires Containing Lanthanide Nitrates and Depleted Uranium Nitrate in 30% Tributyl Phosphate in Kerosene

Airborne contaminants from fires containing nuclear waste represent significant health hazards and shape the design and operation of nuclear facilities. Much of the data used to formulate DOE-HDBK-3010-94, “Airborne Release Fractions/Rates and Respirable Fractions for Nonreactor Nuclear Facilities,” from the U.S. Department of Energy, were taken over 40 years ago. The objectives of this study were to reproduce experiments from Pacific Northwest Laboratories conducted in June 1973 employing current aerosol measurement methods and instrumentation, develop an enhanced understanding of particulate formation and transport from fires containing nuclear waste, and provide modeling and experimental capabilities for updating current standards and practices in nuclear facilities. A special chamber was designed to conduct small fires containing 25 mL of flammable waste containing lutetium nitrate, ytterbium nitrate, or depleted uranium nitrate. Carbon soot aerosols showed aggregates of primary particles ranging from 20 to 60 nm in diameter. In scanning electron microscopy, ~200-nm spheroidal particles were also observed dispersed among the fractal aggregates. The 200-nm spherical particles were composed of metal phosphates. Airborne release fractions (ARFs) were characterized by leaching filter deposits and quantifying metal concentrations with mass spectrometry. The average mass-based ARF for 238 U experiments was 1.0 × 10 -3 with a standard deviation of 7.5 × 10 -4 . For the original experiments, DOE-HDBK-3010-94 states, “Uranium ARFs range from 2 × 10 -4 to 3 × 10 -3 , an uncertainty of approximately an order of magnitude.” Therefore, current measurements were consistent with DOE-HDBK-3010-94 values. ARF values for lutetium and ytterbium were approximately one to two orders of magnitude lower than 238 U. Furthermore, metal nitrate solubility may have varied with elemental composition and temperature, thereby affecting ARF values for uranium surrogates (Yb and Lu). In addition to ARF data, solution boiling temperatures and evaporation rates can also be deduced from experimental data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Estimating the influence of field inventory sampling intensity on forest landscape model performance for determining high-severity wildfire risk

Abstract Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit their utility in decision making. In this study we examined underlying uncertainties in the initial vegetation layer by leveraging a previous study from the Santa Fe fireshed and using new inventory plots from 111 stands to interpolate the initial forest conditions. We found that more inventory plots resulted in a different geographic distribution and wider range of the modelled biomass. This changed the location of areas with high probability of high-severity fires, shifting the optimal location for management. The increased range of biomass variability from using a larger number of plots to interpolate the initial vegetation layer also influenced ecosystem carbon dynamics, resulting in simulated forest conditions that had higher rates of carbon uptake. We conclude that the initial forest layer significantly affects fire and carbon dynamics and is dependent on both number of plots, and sufficient representation of the range of forest types and biomass density.

Science & Technology - Other Topics↗
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2020

Forecasting Global Fire Emissions on Subseasonal to Seasonal (S2S) Time Scales

Fire emissions of gases and aerosols alter atmospheric composition and have substantial impacts on climate, ecosystem function, and human health. Warming climate and human expansion in fire‐prone landscapes exacerbate fire impacts and call for more effective management tools. Here we developed a global fire forecasting system that predicts monthly emissions using past fire data and climate variables for lead times of 1 to 6 months. Using monthly fire emissions from the Global Fire Emissions Database (GFED) as the prediction target, we fit a statistical time series model, the Autoregressive Integrated Moving Average model with eXogenous variables (ARIMAX), in over 1,300 different fire regions. Optimized parameters were then used to forecast future emissions. The forecast system took into account information about region‐specific seasonality, long‐term trends, recent fire observations, and climate drivers representing both large‐scale climate variability and local fire weather. We cross‐validated the forecast skill of the system with different combinations of predictors and forecast lead times. The reference model, which combined endogenous and exogenous predictors with a 1 month forecast lead time, explained 52% of the variability in the global fire emissions anomaly, considerably exceeding the performance of a reference model that assumed persistent emissions during the forecast period. The system also successfully resolved detailed spatial patterns of fire emissions anomalies in regions with significant fire activity. This study bridges the gap between the efforts of near‐real‐time fire forecasts and seasonal fire outlooks and represents a step toward establishing an operational global fire, smoke, and carbon cycle forecasting system.

vapor pressure↗
NASA NTRS2007

ISS Destiny Laboratory Smoke Detection Model

Smoke transport and detection were modeled numerically in the ISS Destiny module using the NIST, Fire Dynamics Simulator code. The airflows in Destiny were modeled using the existing flow conditions and the module geometry included obstructions that simulate the currently installed hardware on orbit. The smoke source was modeled as a 0.152 by 0.152 m region that emitted smoke particulate ranging from 1.46 to 8.47 mg/s. In the module domain, the smoke source was placed in the center of each Destiny rack location and the model was run to determine the time required for the two smoke detectors to alarm. Overall the detection times were dominated by the circumferential flow, the axial flow from the intermodule ventilation and the smoke source strength.

Brooker, John E.↗
NASA NTRS2013

NO PLIF Visualizations of the Orion Capsule in LENS-I

Planar laser-induced fluorescence (PLIF) of nitric oxide (NO) was used to visualize the interaction of reaction-control-system (RCS) jet flows in the wake of a hypersonic capsule reentry vehicle. The tests were performed at the Calspan University at Buffalo Research Center's (CUBRC) LENS-I reflected shock tunnel facility. This was the first application of PLIF to study RCS jets in a large-scale pulsed hypersonic facility. The LENS-I facility allowed RCS jet flows to be studied while varying the flow enthalpy, Reynolds number, angle of attack and jet configuration. The interaction of pitch and roll jets with the flowfield was investigated. Additionally, thin film sensors were used to monitor heat transfer on the surface of the model to detect any localized heating resulting from the firing of the RCS jets. Tests were conducted with the model held at angles of attack of 18deg and 22deg. The nominal Mach number in all tests was 8, while Reynolds number based on model diameter ranged from 2.2x10(exp 6) - 1.5x10(exp 7). Images were processed using the Virtual Diagnostics Interface (ViDI) system developed at NASA Langley Research Center to provide a three-dimensional display of the experimental data.

Combs, C.↗
NASA NTRS1993

Numerical study of the SSME nozzle flow fields during transient operations: A comparison of the animated results with test

A computational fluid dynamics (CFD) model has been applied to study the transient flow phenomena of the nozzle and exhaust plume of the Space Shuttle Main Engine (SSME), fired at sea level. The CFD model is a time accurate, pressure based, reactive flow solver. A six-species hydrogen/oxygen equilibrium chemistry is used to describe the chemical-thermodynamics. An adaptive upwinding scheme is employed for the spatial discretization, and a predictor, multiple corrector method is used for the temporal solution. Both engine start-up and shut-down processes were simulated. The elapse time is approximately five seconds for both cases. The computed results were animated and compared with the test. The images for the animation were created with PLOT3D and FAST and then animated with ABEKAS. The hysteresis effects, and the issues of free-shock separation, restricted-shock separation and the end-effects were addressed.

Wang, Ten-See↗
NASA NTRS1989

Risk-Based Fire Safety Experiment Definition for Manned Spacecraft

Risk methodology is used to define experiments to be conducted in space which will help to construct and test the models required for accident sequence identification. The development of accident scenarios is based on the realization that whether damage occurs depends on the time competition of two processes: the ignition and creation of an adverse environment, and the detection and suppression activities. If the fire grows and causes damage faster than it is detected and suppressed, then an accident occurred. The proposed integrated experiments will provide information on individual models that apply to each of the above processes, as well as previously unidentified interactions and processes, if any. Initially, models that are used in terrestrial fire risk assessments are considered. These include heat and smoke release models, detection and suppression models, as well as damage models. In cases where the absence of gravity substantially invalidates a model, alternate models will be developed. Models that depend on buoyancy effects, such as the multizone compartment fire models, are included in these cases. The experiments will be performed in a variety of geometries simulating habitable areas, racks, and other spaces. These simulations will necessitate theoretical studies of scaling effects. Sensitivity studies will also be carried out including the effects of varying oxygen concentrations, pressures, fuel orientation and geometry, and air flow rates. The experimental apparatus described herein includes three major modules: the combustion, the fluids, and the command and power modules.

Apostolakis, G. E.↗
DOE OSTI2026

Effect of soot concentration on radiative transport in a 2 m JP-8 pool fire

Hubbard et al. (2024) investigated conjugate heat transfer in a 7.9 m JP-8 pool fire, utilizing both heavily sooting and non-sooting fuel models. Their findings indicated that all models produced pool radiative heat fluxes within the measurement uncertainty for large-scale outdoor experiments. This study aims to further investigate the influence of soot concentration on radiative transport. To this end, Large Eddy Simulations (LES) of a 2 m diameter JP-8 pool fire were conducted, employing four turbulent combustion chemistry models: the Eddy Dissipation Concept (EDC) and three variants of flamelet model. Additionally, three variations of the one-equation subgrid scale turbulence kinetic energy model, and multiple mesh resolutions were utilized. The primary validation metrics were pool radiative heat flux and plume radiative fraction, with simulation data compared to experimental results published by Blanchat et al. (2010). The EDC model produced high soot concentrations near the pool surface, resulting in a significant shielding effect. In contrast, the flamelet combustion model has different kinetic limiters for soot production, leading to soot formation higher in the flame, where it can be more readily oxidized. Flamelet models incorporating both acetylene and benzene contributions to soot growth demonstrated better agreement with experimental data. To assess the sensitivity of pool radiative heat flux to soot mass concentration, we used a one-dimensional approximation over a wide range of soot concentrations and compared it to three-dimensional solutions obtained using Discrete Ordinates. Furthermore, this analysis illustrates the impacts of soot shielding and Turbulence Radiation Interactions (TRI), with TRI emission enhancement factors predicted to be in the range of 3–5 near the edges of the plume.

Computational fluid dynamics↗
NASA NTRSDate not supplied

Nodal Modeling of Tank Pressurization and Draining using a Multi-Node-Ullage Approach

The purpose of the pressurization system in liquid rocket propulsion is to control the pressure in the gas space of the propellant tank (known as the ullage space) and the propellant mass flowrate to the engine. A mathematical model is required to predict the amount of pressurant necessary to ensure that pressure and temperature levels inside the tank remain within acceptable limits and that the propellant pressure leaving the tank satisfies the net positive suction pressure (NPSP) requirement of the pump feeding the engine. Nodal codes typically model tank pressurization and draining using a single node to represent the ullage and a single node to represent the propellant. As the tank drains, the ullage node grows and the propellant node shrinks. The heat transfer between ullage to wall and ullage to propellant is governed by natural convection. Designers of liquid propulsion systems often use empirical correlations to estimate the “Collapse Factor” which represents the ratio of pressurant required with heat transfer and the amount of pressurant required without heat transfer. A single node ullage model of tank pressurization was developed using GFSSP to compute the collapse factor reasonably well and later was used to model tank pressurization during test firing of the FASTRAC rocket engine. The predicted tank pressure compared well with the test data. In the early 1970’s, pressurization and drain tests with liquid methane were performed at NASA Lewis Research Center in a vacuum chamber. A 5 ft diameter spherical aluminum tank was tested to drain from 95% to 5% full using gaseous helium, hydrogen, nitrogen and methane as pressurant. Tests were conducted with different pressurant inlet temperatures and drain times. Measured data include pressurant requirement, amount of pressurant condensed, and ullage and wall temperatures at various heights in the ullage space at the end of draining. A single node GFSSP model was developed to simulate helium pressurization of the methane tank. Predicted helium consumption was 8-23% less than measured. The average error of the six test cases was 16%. A single ullage node with multiple solid node model was developed using Thermal Desktop. Predicted helium consumption compares with the test data within 2%. This paper describes the development of a GFSSP multi-node ullage model of the test configuration and compares the predicted pressurant consumption for both helium and autogenous pressurization using gaseous methane with experimental as well as TD predictions.

Nodal Model↗
DOE OSTI2026

On FIRE mode in KSTAR

We report on the status of Fast Ion Regulated Enhancement (FIRE) mode experiments in the Korea Superconducting Tokamak Advanced Research. This regime is being developed for high-performance, steady-state operation which features a stationary ion internal transport barrier, enabling a central ion temperature approaching 10 keV to be sustained for up to 50 s, without the need for delicate profile control and with no significant impurity accumulation. As its key novelty lies in the significant contribution of fast ions that stabilize core turbulence, the regime has been named FIRE mode. To achieve this regime, neutral beam injection is applied at moderate power levels near the L–H power threshold, while maintaining low plasma density to avoid the L–H transition. The scenario is typically established in diverted magnetic configurations. The core features of FIRE mode were investigated through power balance analysis and fluctuation measurements, revealing a clear transport bifurcation in the ion channel. At the plasma edge, FIRE mode occasionally exhibits I-mode characteristics, particularly in unfavorable magnetic null configurations with q 95 ∼ 4, including the presence of weakly coherent modes. In terms of MHD activity, sawtooth oscillations are observed but appear to be stabilized during the high-performance phase. Fast ion-driven Alfvénic eigenmodes (AEs), indicated by strong frequency chirping near 200 kHz, are also observed. Additionally, lower-frequency MHD activities, distinct from the fast ion-driven AEs, are present and have some influence on plasma performance. The enhancement of core confinement is primarily attributed to fast ion effects, which were evaluated with respect to dilution, alpha stabilization, and resonant interactions with turbulence using gyrokinetic analyses. Among these, the dilution effect was found to be the most dominant. The characteristics of FIRE mode were compared with those of other hot ion plasma scenarios, such as supershot and hot ion mode. While they share many similarities, FIRE mode is distinguished by the accessibility to conditions with T i ≈ T e , presence of I-mode edge features, and its long-duration sustainment. Predictive simulations of FIRE mode were performed using integrated transport modeling with TRIASSIC, employing the TGLF anomalous transport model. These simulations confirmed the critical role of fast ions in achieving this regime. The future prospect of FIRE mode for application in fusion reactors is discussed, with an emphasis on possibly extending the regime to higher density operation.

FIRE mode↗
DOE OSTI2025

Physical Review Journal Club: Structural uncertainty assessment for fire-engulfed objects in crosswind: Establishing credibility for a multiphysics wall-modeled large-eddy simulation paradigm

This is an invited presentation for APS's monthly Journal Club where important papers that have recently been accepted for publication are highlighted in a seminar-like setting. The presentation will be "live" (May 1, 2025) and streamed across the world (including an archived recording).

Domino, Stefan Paul [Sandia National Laboratories ↗
NASA NTRS1990

Cirrus cloud properties derived from satellite radiances during FIRE

The sensitivity of the retrieved cloud properties to the cloud radiative transfer model is explored using satellite data taken during the First ISCCP Regional Experiment (FIRE). Several different scattering phase functions are used to create a set of models which relate cloud optical depth to bidirectional reflectance. These models are employed in the analysis of data taken nearly simultaneously from two different satellites over regions containing cirrus clouds. The interpretation of the reflectances using the various models is evaluated through intercomparisons of the results from both satellites and through comparisons with lidar data. The preliminary results indicate that, compared to water-droplet scattering models, ice-crystal scattering models provide a more precise and physically consistent interpretation of visible and infrared radiances for determining cirrus cloud properties.

Minnis, Patrick↗
DOE OSTI2023

Terrestrial carbon dynamics in an era of increasing wildfire

In an increasingly flammable world, wildfire is altering the terrestrial carbon balance. However, the degree to which novel wildfire regimes disrupt biological function remains unclear. Here, we synthesize the current understanding of above and below ground processes that govern carbon loss and recovery across diverse ecosystems. In this study, we find that intensifying wildfire regimes are increasingly exceeding biological thresholds of resilience, causing ecosystems to convert to a lower carbon-carrying capacity. Growing evidence suggests that plants compensate for fire damage by allocating carbon below ground to access nutrients released by fire, while wildfire selects for microbial communities with rapid growth rates and the ability to metabolize pyrolyzed carbon. Determining controls on carbon dynamics following wildfire requires integration of experimental and modeling frameworks across scales and ecosystems. Fire severity is expected to increase as a result of warming. This will potentially amplify climate change due to its impact on the carbon cycle. This Review discusses ecosystem carbon loss and recovery following wildfire, and highlights where further work is needed to inform model predictions.

54 ENVIRONMENTAL SCIENCES↗