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DOE OSTI2025

Impact of grassland fire dynamics on particulate emission factors

Understanding particulate emission factors in grassland fires is critical for improving air quality assessments and refining emissions inventories. This study explores the dynamic and heterogeneous nature of fire processes and their influence on particulate emissions. Traditional emission factor inventories often rely on static values, overlooking the spatially and temporally variable dynamics of fire behavior. Through field experiments conducted at Konza Prairie Biological Station measuring emissions with uncrewed aerial vehicles, and computational modeling using HIGRAD/FIRETEC, this research highlights the dependency of emission production on localized fire dynamics, including ignition patterns, fuel properties, and atmospheric conditions. The results demonstrate a need for fire dynamic considerations to accurately capture emissions variability.

09 BIOMASS FUELS↗

NASA NTRSDate not supplied

Informing Dionaea muscipula (Venus Flytrap) Conservation Through Habitat Modeling and Forecasted Land Cover Change

The carnivorous Dionaea muscipula (Venus flytrap, Droseraceae) is threatened by habitat loss, fire suppression, and poaching. For rare plant species like D. muscipula with specialized habitat requirements and fragmented distribution, habitat suitability modeling is an important method for guiding conservation efforts. To support the D. muscipula conservation, this study: 1) modeled suitable habitat across the extent of the species’ known range and 2) forecasted land cover change due to development in the study area to the year 2050. Habitat modeling was conducted by overlaying high-confidence presence data observed since 1980 (n=292) with environmental predictor variables (n=23). Suitable habitats were then compared with land cover change to identify areas at risk of habitat loss due to human development. According to those models, nearly half (107.1km2) of modeled highly suitable D. muscipula habitat outside of protected lands are likely to face development pressure. On the other hand, 39.4% (139.9km2) of highly suitable habitats overlap with protected lands and may serve as lasting D. muscipula habitat. Results from this study can inform D. muscipula conservation, including targeted seed banking of populations at risk of extirpation, prioritization of habitats for protection and management, and reintroduction to suitable habitats within protected areas.

Kathryn Caruso↗

DOE OSTI2022

Thermochemical characterization of intumescent materials and their application in FEM models using Aria

Intumescent materials are in wide use as protective coatings in fire protection or thermal management applications. These materials undergo chemical reactions occurring from approximately 300°C to 900°C, which outgas and expand the material, providing an appreciable increase in insulative performance. However, the complicated chemical mechanisms and large changes in materials properties complicate the incorporation of these materials into predictive thermal models. This document serves to outline the thermochemical characterization of select intumescent materials, the extraction of relevant parameters, and the incorporation of these parameters into the ChemEQ reaction model implemented in Aria. This work was performed in 2016 and documented in a draft SAND report in March 2017. In 2022, the draft SAND report was discovered and put through R&A.

36 MATERIALS SCIENCE↗

NASA NTRS1978

Simple models for the shuttle remote manipulator system

The investigation is aimed at establishing a series of simple models which can be used to study the forces and moments which occur due to the reaction control system (RCS) jet plume firings during a deployment or retrieval of an IUS type payload. The models considered in this investigation are primarily planar in nature. In this study primary attention is given to the roles the payload play in determining the overall moments on the remote manipulator system arm.

Fowler, W. T.↗

DOE OSTI2016

Assessment of advanced solvent-based post-combustion CO 2 capture processes using a bi-objective optimization technique

We report the optimized performance of two advanced CO 2 capture processes is compared to that of a monoethanolamine (MEA) baseline for a gas-powered CO 2 capture retrofit of an existing coal-fired facility. The advanced temperature-swing processes utilize piperazine and mixed-salt solvents. The mixed-salt treatment involves the use of ammonia for CO 2 absorption and potassium carbonate primarily to control ammonia slip. The processes are represented in terms of energy duty requirements within a modular heat integration code developed for CO 2 capture modeling and optimization. The model includes a baseload coal plant, a gas-fired subsystem containing gas turbines and a heat recovery steam generator (HRSG), and a CO 2 capture facility. A formal bi-objective optimization procedure is applied to determine the design (e.g., detailed HRSG components and pressure levels, gas turbine capacity, CO 2 capture capacity) and time-varying operations of the facility to simultaneously maximize net present value (NPV) and minimize total capital requirement (TCR), while meeting a maximum CO 2 emission intensity constraint. For a realistic scenario constructed using historical data, optimization results indicate that both advanced processes outperform MEA in both objectives, and the mixed-salt process in turn outperforms the piperazine process. Specifically, for the scenario considered, the base case mixed-salt process achieves 16% greater NPV and 14% lower TCR than the MEA process, and 10% greater NPV and 5% lower TCR than the piperazine process. A five-case sensitivity study of the mixed-salt process indicates that it is competitive with the piperazine process and consistently outperforms the MEA process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Machine Learning Analysis of Impact of Western US Fires on Central US Hailstorms

Fires, including wildfires, harm air quality and essential public services like transportation, communication, and utilities. These fires can also influence atmospheric conditions, including temperature and aerosols, potentially affecting severe convective storms. Here, we investigate the remote impacts of fires in the western United States (WUS) on the occurrence of large hail (size: $\geqslant$ 2.54 cm) in the central US (CUS) over the 20-year period of 2001–20 using the machine learning (ML), Random Forest (RF), and Extreme Gradient Boosting (XGB) methods. The developed RF and XGB models demonstrate high accuracy (> 90%) and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide, particularly in four states (Wyoming, South Dakota, Nebraska, and Kansas). The key contributing variables identified from both ML models include the meteorological variables in the fire region (temperature and moisture), the westerly wind over the plume transport path, and the fire features (i.e., the maximum fire power and burned area). Importantly, the results confirm a linkage between WUS fires and severe weather in the CUS, corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

Passive Rocket Diffuser Testing: Performance Similitude Via Nozzle Contour Modification

Subscale rocket testing offers a chance to examine exhaust plume behavior and prove out auxiliary systems early in a development cycle, when the cost of design iteration remains low. Despite the utility of experimentation, perfect similitude between a rocket engine and a scaled model is unobtainable; choices must be made to prioritize the reproduction of certain parameters at the expense of others. The experimentalist’s toolkit contains a variety of techniques to achieve this selective similarity. Determination of the appropriate tool is dependent on a test series’ specific objectives, facility limitations, and financial considerations. Preservation of full nozzle geometry is crucial if its internal flow is of interest. However, subscale thrusters often serve as a simple plume source in the evaluation of adjacent phenomena: vehicle base pressures, retropropulsive flows, supersonic diffuser performance, refractory erosion, deflector cooling, impingement shock structures, etc. In such cases, it may be permissible to rework the nozzle geometry to compensate for discrepancies in subscale propellant pressure, temperature, or chemical composition. Thrust, pressure, Mach number, heat flux, and myriad other parameters can be used to ground the altered designs. Subscale diffuser testing at the full chamber pressure of flight hardware is occasionally infeasible. It is hypothesized that, absent a means of backpressure reduction, comparable performance may be obtained for a prescribed motive fluid by maintaining scaled engine mass flow and nozzle exit geometry at the expense of throat geometry, exit pressure, and Mach number. The present work offers discrete empirical support for this mass-flow-based approach to contour modification.

subscale↗

DOE OSTI2019

The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty

The Community Land Model (CLM) is the land component of the Community Earth System Model (CESM) and is used in several global and regional modeling systems. In this paper, we introduce model developments included in CLM version 5 (CLM5), which is the default land component for CESM2. We assess an ensemble of simulations, including prescribed and prognostic vegetation state, multiple forcing data sets, and CLM4, CLM4.5, and CLM5, against a range of metrics including from the International Land Model Benchmarking (ILAMBv2) package. CLM5 includes new and updated processes and parameterizations: (1) dynamic land units, (2) updated parameterizations and structure for hydrology and snow (spatially explicit soil depth, dry surface layer, revised groundwater scheme, revised canopy interception and canopy snow processes, updated fresh snow density, simple firn model, and Model for Scale Adaptive River Transport), (3) plant hydraulics and hydraulic redistribution, (4) revised nitrogen cycling (flexible leaf stoichiometry, leaf N optimization for photosynthesis, and carbon costs for plant nitrogen uptake), (5) global crop model with six crop types and time-evolving irrigated areas and fertilization rates, (6) updated urban building energy, (7) carbon isotopes, and (8) updated stomatal physiology. New optional features include demographically structured dynamic vegetation model (Functionally Assembled Terrestrial Ecosystem Simulator), ozone damage to plants, and fire trace gas emissions coupling to the atmosphere. Conclusive establishment of improvement or degradation of individual variables or metrics is challenged by forcing uncertainty, parametric uncertainty, and model structural complexity, but the multivariate metrics presented here suggest a general broad improvement from CLM4 to CLM5.

58 GEOSCIENCES↗

DOE OSTI2021

Changes in Hydrogen Concentration and Defect State Density at the Poly-Si/SiOx/c-Si Interface Due to Firing

We determined the density of defect states of poly-Si/SiOx/c-Si junctions featuring a wet chemical interfacial oxide from lifetime measurements using the MarcoPOLO model to calculate recombination and contact resistance in poly-Si/SiOx/c-Si-junctions. In samples that did not receive any hydrogen treatment, the Dit,cSi is about 2 × 1012 cm-2 eV1 before firing and rises to 3–7 × 1012 cm2 eV1 during firing at measured peak temperatures between 620 °C and 863 °C. To address the question of why AlOx/SiNy stacks in contrast to pure SiNy layers for hydrogenation during firing provides better passivation quality, we have measured the hydrogen concentrations at the poly-Si/SiOx/c-Si interface as a function of AlOx layer thickness and compared these to J0 and calculated Dit,c-Si values. We observe an increase of the hydrogen concentration at the SiOx/c-Si interface upon firing as a function of the firing temperature that exceeds the defect concentrations at the interface several times. However, the AlOx layer thickness appears to cause an increase in hydrogen concentration at the SiOx/c-Si interface in these samples rather than exhibiting a hydrogen blocking property.

41 EE - Solar Energy Technologies Office (EE-4S)↗

NASA NTRS1994

North African savanna fires and atmospheric carbon dioxide

The effect of north African savanna fires on atmospheric CO2 is investigated using a tracer transport model. The model uses winds from operational numerical weather prediction analyses and provides CO2 concentrations as a function of space and time. After a spin-up period of several years, biomass-burning sources are added, and model experiments are run for an additional year, utilizing various estimates of CO2 sources. The various model experiments show that biomass burning in the north African savannas significantly affects CO2 concentrations in South America. The effect is more pronounced during the period from January through March, when biomass burning in South America is almost nonexistent. During this period, atmospheric CO2 concentrations in parts of South America typically may increase by 0.5 to 0.75 ppm at 970 mbar, the average pressure of the lowest model layer. These figures are above the probable uncertainty level, as model runs with biomass-burning sources estimated from independent studies using distinct data sets and techniques indicate. From May through September, when severe biomass burning occurs in South America, the effect of north African savanna fires over South America has become generally small at 970 mbar, but north of the equator it may be of the same magnitude or larger than the effect of South American fires. The CO2 concentration increase in the extreme northern and southern portions of South America, however, is mostly due to southern African fires, whose effect may be 2-3 times larger than the effect of South American fires at 970 mbar. Even in the central part of the continent, where local biomass-burning emissions are maximum, southern African fires contribute to at least 15% of the CO2 concentration increase at 970 mbar. At higher levels in the atmosphere, less CO2 emitted by north African savanna fires reaches South America, and at 100 mbar no significant amount of CO2 is transported across the Atlantic Ocean. The vertical structure of the CO2 concentration increase due to biomass burning differs substantially, depending on whether sources are local or remote. A prominent maximum of CO2 concentration increase in the lower layers characterizes the effect of local sources, whereas a more homogeneous profile of CO2 concentration increase characterizes the effect of remote sources. The results demonstrate the strong remote effects of African biomoass burning which, owing to the general circulation of the atmosphere, are felt as far away as South America.

Iacobellis, Sam F.↗

DOE OSTI2019

Random Force Perturbations: A New Extension of the Cell Perturbation Method for Turbulence Generation in Multiscale Atmospheric Boundary Layer Simulations

Coupling between mesoscale and large eddy simulation (LES) is critically important for many atmospheric model applications, from predictions of wind energy to fire propagation. The grid-nesting technique enables bridging between vastly different scales without incurring prohibitive computational costs. Yet, the transition from coarser to finer resolutions often requires a large number of grid points from inflow boundaries for the development of fine-scale turbulence features in the LES domain. Recently, the cell perturbation method (CPM) was developed to reduce the turbulence development region with high computational efficiency. Herein, we explore a new method based on the CPM that uses force perturbations in both the horizontal and vertical directions (Force Cell Perturbation Method) instead of the potential temperature perturbations in the original CPM, as an attempt to further explore the performance of the random perturbation techniques. This method is tested for a neutral and a convective atmospheric boundary layer under idealized conditions. Overall, similar performance is found between the optimal configurations of the CPM and the Force Cell Perturbation Method pointing to the robustness of this family of perturbation methods in accelerating turbulence generation in nested domains. Vertical force perturbations performed better than horizontal force perturbations for both atmospheric stability conditions. The CPM performed best under convective stability conditions. The combination of the force and potential temperature perturbations is found to provide no additional performance improvement over the stand-alone application of the individual methods.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2018

International Space Station Model Correlation Analysis

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Modal Analysis↗

NASA NTRSDate not supplied

Oregon Wildfires: Integrating ECOSTRESS to Map & Analyze Vegetation Moisture for Wildfire Modeling

Wildfire season in the western USA is starting earlier and gaining in intensity. The Bootleg Fire in Southern Oregon began on July 6th, 2021, and burned over 1675 km2 before it was fully contained on August 15th, 2021. Evapotranspiration (ET) is one indicator of vegetation moisture and there is interest in using high-resolution ET products from ECOsystem and Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) in future wildfire modeling. In partnership with the Pacific Northwest National Laboratory and US Forest Service, the team examined ECOSTRESS ET for the two years before the Bootleg Fire and assessed the relationship between ET, topography, and vegetation. Remotely sensed data from Shuttle Radar Topography Mission (SRTM) and Global Ecosystem Dynamics Investigation (GEDI) along with ancillary data from the National Land Cover Database (NLCD) and Landscape Fire Resource Management Planning Tools (LANDFIRE) were incorporated. The team examined data in relation to soil burn severity from the Burned Area Emergency Response (BAER) program. From ET median composites for April 1st – July 5th, 2021 and 2019, the Bootleg Fire area showed a 7 mm/day decrease in ET and a relative 75% decrease in ET between 2019 and 2021. Approximately 6% of the Bootleg Fire area was identified as having a high soil burn severity and these areas were found predominantly in the evergreen forest land cover class and northward facing slopes with a mean ET decrease of 3 mm/day between 2019 and 2021. The team also analyzed ECOSTRESS Water Use Efficiency products as an additional vegetation moisture indicator of pre-fire conditions in the study area. The end products will allow the partners to assess if higher resolution vegetation moisture datasets from ECOSTRESS will improve wildfire modeling for other susceptible areas.

Brenna Hatch↗

DOE OSTI2019

A mathematical programming approach for the optimal placement of flame detectors in petrochemical facilities

Flame detectors provide an important layer of protection for personnel in petrochemical plants, but effective placement can be challenging. A mixed-integer nonlinear programming formulation is proposed for optimal placement of flame detectors while considering non-uniform probabilities of detection failure. We show that this approach allows for the placement of fire detectors using a fixed sensor budget and outperforms models that do not account for imperfect detection. In this study, we develop a linear relaxation to the formulation and an efficient solution algorithm that achieves global optimality with reasonable computational effort. We integrate this problem formulation into the Python package, Chama, and demonstrate the effectiveness of this formulation on a small test case and on two real-world case studies using the fire and gas mapping software, Kenexis Effigy.

47 OTHER INSTRUMENTATION↗

NASA NTRS2016

Fire Detection Tradeoffs as a Function of Vehicle Parameters

Fire survivability depends on the detection of and response to a fire before it has produced an unacceptable environment in the vehicle. This detection time is the result of interplay between the fire burning and growth rates; the vehicle size; the detection system design; the transport time to the detector (controlled by the level of mixing in the vehicle); and the rate at which the life support system filters the atmosphere, potentially removing the detected species or particles. Given the large differences in critical vehicle parameters (volume, mixing rate and filtration rate) the detection approach that works for a large vehicle (e.g. the ISS) may not be the best choice for a smaller crew capsule. This paper examines the impact of vehicle size and environmental control and life support system parameters on the detectability of fires in comparison to the hazard they present. A lumped element model was developed that considers smoke, heat, and toxic product release rates in comparison to mixing and filtration rates in the vehicle. Recent work has quantified the production rate of smoke and several hazardous species from overheated spacecraft polymers. These results are used as the input data set in the lumped element model in combination with the transport behavior of major toxic products released by overheating spacecraft materials to evaluate the necessary alarm thresholds to enable appropriate response to the fire hazard.

microgravity↗

NASA NTRS2016

Fire Detection Tradeoffs as a Function of Vehicle Parameters

microgravity↗

NASA NTRS2008

A VARI-Based Relative Greenness from MODIS Data for Computing the Fire Potential Index

The Fire Potential Index (FPI) relies on relative greenness (RG) estimates from remote sensing data. The Normalized Difference Vegetation index (NDVI), derived from NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery is currently used to calculate RG operationally. Here we evaluated an alternate measure of RG using the Visible Atmospheric Resistant Index (VARI) derived from Moderate Resolution Imaging Spectrometer (MODIS) data. VARI was chosen because it has previously been shown to have the strongest relationship with Live Fuel Moisture (LFM) out of a wide selection of MODIS-derived indices in southern California shrublands. To compare MODIS-based NDVI-FPI and VARI-FPI, RG was calculated from a 6-year time series of MODIS composites and validated against in-situ observations of LFM as a surrogate for vegetation greenness. RG from both indices was then compared in terms of its performance for computing the FPI using historical wildfire data. Computed RG values were regressed against ground-sampled LFM at 14 sites within Los Angeles County. The results indicate the VARI-based RG consistently shows a stronger relationship with observed LFM than NDVI-based RG. With an average R2 of 0.727 compared to a value of only 0.622 for NDVI-RG, VARI-RG showed stronger relationships at 13 out of 14 sites. Based on these results, daily FPI maps were computed for the years 2001 through 2005 using both NDVI-RG and VARI-RG. These were then validated against 12,490 fire detections from the MODIS active fire product using logistic regression. Deviance of the logistic regression model was 408.8 for NDVI-FPI and 176.2 for VARI-FPI. The c-index was found to be 0.69 and 0.78, respectively. The results show that VARI-FP outperforms NDVI-FPI in distinguishing between fire and no-fire events for historical wildfire data in southern California for the given time period.

Schneider, P.↗

NASA NTRS2013

Develop a Model Component

During my internship at NASA, I was a model developer for Ground Support Equipment (GSE). The purpose of a model developer is to develop and unit test model component libraries (fluid, electrical, gas, etc.). The models are designed to simulate software for GSE (Ground Special Power, Crew Access Arm, Cryo, Fire and Leak Detection System, Environmental Control System (ECS), etc. ~.) before they are implemented into hardware. These models support verifying local control and remote software for End-Item Software Under Test (SUT). The model simulates the physical behavior (function, state, limits and 110) of each end-item and it's dependencies as defined in the Subsystem Interface Table, Software Requirements & Design Specification (SRDS), Ground Integrated Schematic (GIS), and System Mechanical Schematic.(SMS). The software of each specific model component is simulated through MATLAB's Simulink program. The intensiv~ model development life cycle is a.s follows: Identify source documents; identify model scope; update schedule; preliminary design review; develop model requirements; update model.. scope; update schedule; detailed design review; create/modify library component; implement library components reference; implement subsystem components; develop a test script; run the test script; develop users guide; send model out for peer review; the model is sent out for verific~tionlvalidation; if there is empirical data, a validation data package is generated; if there is not empirical data, a verification package is generated; the test results are then reviewed; and finally, the user. requests accreditation, and a statement of accreditation is prepared. Once each component model is reviewed and approved, they are intertwined together into one integrated model. This integrated model is then tested itself, through a test script and autotest, so that it can be concluded that all models work conjointly, for a single purpose. The component I was assigned, specifically, was a fluid component, a discrete pressure switch. The switch takes a fluid pressure input, and if the pressure is greater than a designated cutoff pressure, the switch would stop fluid flow.

Ensey, Tyler S.↗