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NASA NTRS2009

Ikhana: Unmanned Aircraft System Western States Fire Missions. Monographs in Aerospace History, Number 44

In 2006, NASA Dryden Flight Research Center, Edwards, Calif., obtained a civil version of the General Atomics MQ-9 unmanned aircraft system and modified it for research purposes. Proposed missions included support of Earth science research, development of advanced aeronautical technology, and improving the utility of unmanned aerial systems in general. The project team named the aircraft Ikhana a Native American Choctaw word meaning intelligent, conscious, or aware in order to best represent NASA research goals. Building on experience with these and other unmanned aircraft, NASA scientists developed plans to use the Ikhana for a series of missions to map wildfires in the western United States and supply the resulting data to firefighters in near-real time. A team at NASA Ames Research Center, Mountain View, Calif., developed a multispectral scanner that was key to the success of what became known as the Western States Fire Missions. Carried out by team members from NASA, the U.S. Department of Agriculture Forest Service, National Interagency Fire Center, National Oceanic and Atmospheric Administration, Federal Aviation Administration, and General Atomics Aeronautical Systems Inc., these flights represented an historic achievement in the field of unmanned aircraft technology.

Western States fire missions↗

NASA NTRSDate not supplied

Multiscale Modeling of the Uptake of Hydrogen Chloride on Anodized Aluminum in Relevance to Spacecraft Fire Safety

Fire safety is a critical component of space missions. An electrical fire within the spacecraft often produces gaseous hydrogen chloride (HCl) from the smoldering of wire insulation. These gases tend to stick to the interior materials of the spacecraft, which is often comprised of treated aluminum. Determining the rate of uptake for HCl by aluminum helps the safe design of the spacecraft to reduce catastrophic mission risk. Our previous studies showed that a one-step global reaction model for adsorption of HCl on aluminum is incapable of predicting the experimentally measured HCl uptake of anodized aluminum, compared to other treatments with thinner oxide layers. X-ray photoelectron spectroscopy revealed that aluminum chloride is found deep in the oxide layer of the anodized aluminum, implying that the transport of HCl within the oxide layer covering the aluminum surface must be considered. This work uses a multiscale modeling approach to predict the uptake of HCl. A pore model is developed wherein the HCl reacts with the aluminum oxide pore walls to create an aluminum chloride layer. The HCl then diffuses through that layer for further reaction, until the diffusion resistance grows too large, and the surface is said to be saturated. The pore model is then coupled with the reactor-scale model to predict overall HCl uptake. Results show that this new multiscale approach predicts the uptake of HCl far more accurately than previously used single-scale models.

Modeling↗

DOE OSTI2024

Electric Vehicle Fire Primer for Fleet Managers

The U.S. Department of Energy's Vehicle Technologies Office provides project assistance through Clean Cities, technical expertise, and funding to help stake-holders implement alternative fuels and electric vehicles (EVs). Fleet managers considering EVs can learn about the potential for EV fires and measures to help reduce fire risk.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

Revealing important nocturnal and day-to-day variations in fire smoke emissions through a multiplatform inversion

We couple airborne, ground-based, and satellite observations; conduct regional simulations; and develop and apply an inversion technique to constrain hourly smoke emissions from the Rim Fire, the third largest observed in California, USA. Emissions constrained with multiplatform data show notable nocturnal enhancements (sometimes over a factor of 20), correlate better with daily burned area data, and are a factor of 2–4 higher than a priori estimates, highlighting the need for improved characterization of diurnal profiles and day-to-day variability when modeling extreme fires. Constraining only with satellite data results in smaller enhancements mainly due to missing retrievals near the emissions source, suggesting that top-down emission estimates for these events could be underestimated and a multiplatform approach is required to resolve them. As a result, predictions driven by emissions constrained with multiplatform data present significant variations in downwind air quality and in aerosol feedback on meteorology, emphasizing the need for improved emissions estimates during exceptional events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Simulations of flaming combustion and flaming-to-smoldering transition in wildland fire spread at flame scale

Our objective in the present study is to provide basic insights into the coupling between external-gas and solid biomass vegetation processes that control the dynamics of flame spread in wildland fire problems. Here we focus on a modeling approach that resolves processes occurring at vegetation and flame scales, i.e., the formation of flammable vapors due to the thermal degradation of the solid biomass, the subsequent combustion in ambient air, the thermal feedback to the biomass through radiative and convective heat transfer, and the possible transition from flaming combustion (taking place outside of the solid biomass) to smoldering combustion (taking place inside the solid biomass). The capability uses a multiphase combustion framework and treats external-gas processes through a Large Eddy Simulation solver and solid biomass processes through a discrete particle model. The discrete particle model adopts a one-dimensional porous medium formulation, includes descriptions of drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation, as well as a description of the external-gas-to-solid-biomass diffusion of oxygen mass; the discrete particle model thereby provides a treatment of in-depth oxidative processes and allows the simulation of smoldering combustion. The modeling capability is applied to the simulation of fire spread across a surrogate biomass vegetation bed corresponding to a discrete array of cylindrical-shaped, vertically-oriented, pine wood sticks, characterized by a monomodal size distribution, in horizontal flat terrain and under wind-aided conditions. The numerical results demonstrate that the model can simulate successful flaming-to-smoldering transition followed by complete biomass consumption.

01 COAL, LIGNITE, AND PEAT↗

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↗

DOE OSTI2023

Creating an Advanced Sensor Network to calculate real-time, mass-weighted flue gas composition and air heater leakage of a coal-fired utility boiler under dynamic operating conditions

Utilization of renewable energy sources to minimize the environmental impact of energy production has changed the way utility boilers operate, requiring frequent load cycling between full load and partial loads as low as 30%. Dynamic operation of coal-fired utility boilers significantly reduces boiler efficiency when compared to steady state at full load. Data-driven plant optimization has shown success with coal-fired utility boilers under dynamic operating conditions. The purpose of this work was to create an Advanced Sensor Network (ASN) to provide more extensive real-time data to inform dynamic plant optimization of Net Unit Heat Rate (NUHR). The ASN consists of gas sampling grids in the convective pass of the boiler and downstream of the air heater. These sampling grids allow for quantification of spatial variation of flue gas within the boiler and calculation of mass-weighted composition of flue gas through the combination of composition, velocity, and temperature measurements. The comparison of O 2 between the inlet and outlet of the air heater is used to calculate air leakage in real time. Flue gas composition and air heater leakage are both important factors in boiler efficiency and NUHR. Further, the results of this work support the value of mass-weighted averages for determining flue gas composition accurately. The measurements from the ASN show increased composition stratification during dynamic operation, with an average standard deviation 38% higher than observed during steady-state operation. Air heater leakage was also observed to increase from 2.8% to 5.1% following a load change. Prior to the installation of the ASN, these data would not have been available for dynamic control. These real-time data will be leveraged to calculate and optimize for NUHR during dynamic operation in future work.

42 ENGINEERING↗

DOE OSTI2024

Intense formation of secondary ultrafine particles from Amazonian vegetation fires and their invigoration of deep clouds and precipitation

New particle formation (NPF) in fire smoke is thought to be unlikely due to large condensation and coagulation sinks that scavenge molecular clusters. We analyze aircraft measurements over the Amazon and find that fires significantly enhance NPF and ultrafine particle (UFP < 50 nm diameter) numbers compared to background conditions, contrary to previous understanding. We identify that the nucleation of dimethylamine with sulfuric acid, which is aided by the formation of extremely low volatility organics in biomass-burning smoke, can overcome the large condensation and coagulation sinks and explain aircraft observations. We show that freshly formed clusters rapidly grow to UFP sizes through biomass-burning secondary organic aerosol formation, leading to a 10-fold increase in UFP number concentrations. Here, we find a contrasting effect of UFPs on deep convective clouds compared to the larger particles from primary emissions for the case investigated here. UFPs intensify the deep convective clouds and precipitation due to increased condensational heating, while larger particles delay and reduce precipitation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Enzymatic Biocontrol of Fire Blight ( Erwinia amylovora ) Using an Engineered Glycosyl Hydrolase

Current management of fire blight, caused by Erwinia amylovora , relies heavily on streptomycin a practice that has contributed to the emergence of antibiotic-resistant strains and raised environmental and regulatory concerns. Enzyme-based biocontrol agents offer a promising antibiotic-free approach that combines target specificity with environmental compatibility. This study evaluates CAase, a bacteriophage-derived glycosyl hydrolase, for its ability to disrupt E. amylovora biofilms and reduce disease severity. Biochemical assays and scanning electron microscopy confirmed that CAase efficiently degraded the extracellular polysaccharide (EPS) matrix, releasing cells from biofilms. Gas chromatography–mass spectrometry (GC–MS) linkage analysis of EPS isolated from two Erwinia amylovora strains demonstrated that CAase preferentially cleaves galactan-rich amylovoran produced by strain EA273, while exhibiting only limited activity toward the levan-rich EPS from strain EA1430. Functional assays revealed that CAase reduced bacterial viability by nearly 2 orders of magnitude at higher enzyme concentrations, strongly suppressed surface motility, and induced ultrastructural damage visible by transmission electron microscopy. Importantly, field trials showed that CAase significantly lowered blossom and shoot blight incidence under orchard conditions. These results highlight CAase as a potent enzyme-based strategy for reducing the virulence of E. amylovora and demonstrate its potential as a sustainable alternative to antibiotics in fire blight management.

antibiotic resistance↗

DOE OSTI2023

Anthropogenic climate change impacts exacerbate summer forest fires in California

Record-breaking summer forest fires have become a regular occurrence in California. Observations indicate a fivefold increase in summer burned area (BA) in forests in northern and central California during 1996 to 2021 relative to 1971 to 1995. While the higher temperature and increased dryness have been suggested to be the leading causes of increased BA, the extent to which BA changes are due to natural variability or anthropogenic climate change remains unresolved. Here, we develop a climate-driven model of summer BA evolution in California and combine it with natural-only and historical climate simulations to assess the importance of anthropogenic climate change on increased BA. Our results indicate that nearly all the observed increase in BA is due to anthropogenic climate change as historical model simulations accounting for anthropogenic forcing yield 172% (range 84 to 310%) more area burned than simulations with natural forcing only. We detect the signal of combined historical forcing on the observed BA emerging in 2001 with no detectable influence of the natural forcing alone. In addition, even when considering fuel limitations from fire-fuel feedbacks, a 3 to 52% increase in BA relative to the last decades is expected in the next decades (2031 to 2050), highlighting the need for proactive adaptations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Cyber Friendly Fire: Research Challenges for Security Informatics

This paper addresses cognitive implications and research needs surrounding the problem of cyber friendly fire (FF). We define cyber FF as intentional offensive or defensive cyber/electronic actions intended to protect cyber systems against enemy forces or to attack enemy cyber systems, which unintention-ally harms the mission effectiveness of friendly or neutral forces. Just as with combat friendly fire, maintaining situation awareness (SA) is paramount to avoiding cyber FF incidents. Cyber SA concerns knowledge of a system’s topology (connectedness and relationships of the nodes in a system), and critical knowledge elements such as the characteristics and vulnerabilities of the components that comprise the system and its nodes, the nature of the activities or work performed, and the available defensive and offensive countermeasures that may be applied to thwart network attacks. Mitigation strategies to combat cyber FF— including both training concepts and suggestions for decision aids and visualization approaches—are discussed.

cyber friendly fire↗

DOE OSTI2012

Life Cycle Greenhouse Gas Emissions of Coal-Fired Electricity Generation: Systematic Review and Harmonization

This systematic review and harmonization of life cycle assessments (LCAs) of utility-scale coal-fired electricity generation systems focuses on reducing variability and clarifying central tendencies in estimates of life cycle greenhouse gas (GHG) emissions. Screening 270 references for quality LCA methods, transparency, and completeness yielded 53 that reported 164 estimates of life cycle GHG emissions. These estimates for subcritical pulverized, integrated gasification combined cycle, fluidized bed, and supercritical pulverized coal combustion technologies vary from 675 to 1,689 grams CO{sub 2}-equivalent per kilowatt-hour (g CO{sub 2}-eq/kWh) (interquartile range [IQR]= 890-1,130 g CO{sub 2}-eq/kWh; median = 1,001) leading to confusion over reasonable estimates of life cycle GHG emissions from coal-fired electricity generation. By adjusting published estimates to common gross system boundaries and consistent values for key operational input parameters (most importantly, combustion carbon dioxide emission factor [CEF]), the meta-analytical process called harmonization clarifies the existing literature in ways useful for decision makers and analysts by significantly reducing the variability of estimates ({approx}53% in IQR magnitude) while maintaining a nearly constant central tendency ({approx}2.2% in median). Life cycle GHG emissions of a specific power plant depend on many factors and can differ from the generic estimates generated by the harmonization approach, but the tightness of distribution of harmonized estimates across several key coal combustion technologies implies, for some purposes, first-order estimates of life cycle GHG emissions could be based on knowledge of the technology type, coal mine emissions, thermal efficiency, and CEF alone without requiring full LCAs. Areas where new research is necessary to ensure accuracy are also discussed.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2015

Late Holocene fire and vegetation reconstruction from the western Klamath Mountains, California, USA: A multi-disciplinary approach for examining potential human land-use impacts

The influence of Native American land-use practices on vegetation composition and structure has long been a subject of significant debate. This is particularly true in portions of the western United States where tribal hunter-gatherers did not use agriculture to meet subsistence and other cultural needs. Climate has been viewed as the dominant determinant of vegetation structure and composition change over time, but ethnographic and anthropological evidence suggests that Native American land-use practices (particularly through the use of fire) had significant landscape effects on vegetation. However, it is difficult to distinguish climatically driven vegetation change from human-caused vegetation change using traditional paleoecological methods. To address this problem, we use a multidisciplinary methodology that incorporates paleoecology with local ethnographic and archaeological information at two lake sites in northwestern California. We show that anthropogenic impacts can be distinguished at our Fish Lake site during the cool and wet ‘Little Ice Age’, when we have evidence for open-forest or shade-intolerant vegetation, fostered for subsistence and cultural purposes, rather than the closed-forest or shade-tolerant vegetation expected due to the climatic shift. We also see a strong anthropogenic influence on modern vegetation at both sites following European settlement, decline in tribal use, and subsequent fire exclusion. These results demonstrate that Native American influences on vegetation structure and composition can be distinguished using methods that take into account both physical and cultural aspects of the landscape. Furthermore, they also begin to determine the scale at which western forests were influenced by Native American land-use practices and how modern forests of northwestern California are not solely products of climate alone.

58 GEOSCIENCES↗

DOE OSTI2025

Levoglucosan data from five coastal streams impacted by the 2020 CZU Lightning Complex Fires, California, United States

This dataset includes levoglucosan data for five coastal California (United States) streams impacted by the 2020 CZU Lightning Complex Fires which burned from August 16th through September 22nd. Levoglucosan is a highly soluble and biolabile fraction of pyrogenic carbon. The five watersheds (San Lorenzo River, Pescadero Creek, Majors Creek, Laguna Creek, and Scott Creek) were impacted by the fires with watersheds experiencing a range of burn severity and extents. Grab samples were collected from each stream between October 2020 and May 2021, targeting both baseflow and event flow hydrologic conditions. Additional biogeochemistry data (i.e., organic and black carbon concentrations) can be found in a separate data package (https://doi.org/10.4211/hs.421c0226bb38460c8393d67fe0c4f802). This data package consists of one main data folder that contains (1) readme; (2) file-level metadata; (3) data dictionary; (4) field metadata with international generic sample numbers (IGSN); (5) methods codes; and (6) levoglucosan data. All files are .csv or .pdf.

2020 CZU Lightning Complex Fires↗

DOE OSTI2016

Fire Intensity Data for Validation of the Radiative Transfer Equation

A set of experiments and test data are outlined in this report that provides radiation intensity data for the validation of models for the radiative transfer equation. The experiments were performed with lightly-sooting liquid hydrocarbon fuels that yielded fully turbulent fires 2 m diameter). In addition, supplemental measurements of air flow and temperature, fuel temperature and burn rate, and flame surface emissive power, wall heat, and flame height and width provide a complete set of boundary condition data needed for validation of models used in fire simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Soil Screening Concentrations for Airborne Exposure to Radionuclides Released from Wildland Fires and Fugitive Dust Sources

This document calculates soil screening concentrations for two release scenarios: 1) radionuclides suspended in fugitive dust, and 2) radionuclides on plant surfaces and in plant tissue that are released during a wildland fire on INL Site lands. Soil screening concentrations are based on a dose of 10 mrem effective dose (ED) to a firefighter, INL Site worker, or member of the public. Soil screening concentrations that would result in an effective dose of 10 mrem to an individual (firefighter, INL Site worker, or member of the public) exposed to releases from a wildland fire or fugitive dust emissions were calculated for key radionuclides at the INL. These concentrations are intended to be compared with radionuclide soil measurements to determine whether soil contamination may need to be monitored for or remediated.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Report

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of subcritical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

An Integrated Approach to Predicting Ash Deposition and Heat Transfer in Coal-Fired Boilers

The overall goal of this project is to develop via measurements and simulations an advanced online technology to predict, monitor and manage fireside ash deposition in a coal-fired boiler allowing for more efficient operations under a range of load conditions and fuel property variability. With this in place fuel sorting and blending can be done upstream and operations can be optimized to compensate for load and fuel properties. In support of this objective, three experimental campaigns were undertaken during the course of the project to measure ash deposition rates within the boiler at different fuel flow rates and its ash composition variability. Simulations of the experimental conditions representing actual geometry, operational scenarios in terms of air flow rates, coal flow rates as well as coal compositions, heating values, and particle size distributions were also carried out. Deposition rates were predicted using a unique particle kinetic energy and viscosity based ash deposition methodology whose validity was ascertained by comparing against deposition rate measurements for widely varying operating conditions and ash compositions in a lab-scale furnace. With a unique end-to-end combustion modeling methodology established and different simulation scenarios carried out, the results from our computational fluid dynamic (CFD) simulations in conjunction with the plant data summarized in this report were used to refine Microbeam Technology Incorporated’s MTI CSPI-CT Tool to predict and monitor fire-side ash deposition under a range of load conditions and fuel property variability in real time.

01 COAL, LIGNITE, AND PEAT↗