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At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Design and analysis of dudded fuel experiments at the National Ignition Facility

Recent experiments conducted at the National Ignition Facility (NIF) within the past 2 years have achieved the burning plasma state and exceeded the Lawson criterion for the first time in the laboratory. Here, we report on a set of experiments where the deuterium and tritium (DT) ice layers were replaced with dudded tritium, hydrogen, and deuterium (THD) fuel mixtures to remove the influence of alpha-heating on hot spot dynamics. The hot spot compression and yield in the absence of alpha particle self-heating were measured to assess the proximity of NIF implosions toward the ignition cliff. We find that the “burn-off” Lawson parameters χnoα inferred from the THD experiments are in good agreement with the inferences from postshot simulations of the DT-layered implosions. The THD for burning plasma shot N210307 yielded χnoα≈0.88±0.03 while the THD for ignition shot N210808 yielded χnoα≈1.04±0.04. These results also provide important context for the observed variability in the repeat attempts of ignition shot N210808 since implosions on the ignition cliff are expected to exhibit very large variations in the fusion yield from small changes in the initial conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Comparison of Irradiated TRISO Fuel Radioactivity from Multiple Advanced Reactor Designs

The SCALE code system was used to model, deplete, and compare several different TRISO-fueled reactor designs: a helium-cooled prismatic reactor, a helium-cooled pebble-bed reactor (PBR), and a Fluoride-Lithium-Beryllium (FLIBE) molten-salt-cooled PBR. The purpose of this comparison was to understand how differences in the reactor designs affect the radioactivity of the fuel after discharge and whether those differences are significant. First, the various reactor designs were build and depleted in the TRITON module for each design and fuel enrichment. Then, the TRITON outputs were used to create burn-up dependent reactor libraries. These libraries were then used by ORIGEN to determine the activities of discharged fuel for each reactor, which were compared to generic Westinghouse 17x17 fuel. Overall, the results showed that short term decays are dominated by reactors with higher operating powers, and the reactor type, initial fuel enrichment, and maximum burn-up are of only secondary importance. Although this analysis only focuses on activities in becquerels, these dependencies are consistent with the expected behavior of decay heat. However, analysis of long- term time periods post-irradiation shows that the reactor type and maximum burn-up have strong impacts on the activities; initial fuel enrichment has a secondary impact while operating power is inconsequential. These results would be useful for analyses, such as dose assessment and modeling in post- release scenarios; normal fuel handling operations; and spent fuel transport, storage and disposal. Of particular interest, the results in this report show that analyses that focus on spent nuclear fuel of advanced reactors need to consider each parameter carefully. Unsurprisingly, if the correct operating power is not used in short term analyses, the results will not be correct. Perhaps unexpectedly, however, if the correct reactor type is not used, then the long term results will also be incorrect, especially for areas such as permanent disposal. Even though this report focuses on the total activity of nuclear fuel, it provides initial results on the effects of various input parameters and also provides a framework to extend the work into other analyses of spent fuel from advanced reactors, especially those employing TRISO fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Spectro-Microscopic Analysis of Soot Particle Composition and Source Attribution

Ambient soot particles significantly impact Earth’s radiative balance, human health, and atmospheric visibility. Their microstructural properties depend on formation and aging mechanisms, which vary by emission source and atmospheric processes. Hence, accurately identifying sources of soot enhances our understanding of their physicochemical properties and atmospheric implications. This study used a multi-modal approach to characterize and attribute sources of submicron soot particles collected in Israel during new particle formation events, biomass burning episodes, and background atmospheric conditions. Synchrotron-based X-ray microscopy was used to map soot (elemental carbon), organic carbon, and inorganic species. Implemented atomic force microscopy showed highly diverse phase states, with soot consistently exhibiting a solid-like phase. Automated µ-Raman analysis was subsequently performed on ~690 particles, identifying three soot classes based on spectral features corresponding to the "Defect" (D) and "Graphite" (G) bands of soot. We applied two-peak and five-peak fitting approaches to deconvolute the “Defect” peaks (D1, D2, D3, and D4) and G band from average Raman, revealing varying degrees of graphitic order. The degree of graphitic order was determined from metrics such as the D3 peak area, often observed when soot was internally mixed with organic material. Raman spectral features, along with temporal variations in particle classes contributions, suggest that Particle Type 1 corresponds to traffic related soot and Particle Type 2 to less graphitic soot from biomass burning, while Particle Type 3 is associated with more heterogeneous particulate representative of soot-OC mixtures emitted during new particle formation and biomass burning episodes.

Rivera-Adorno, Felipe (ORCID:0000000273557999)↗
DOE OSTI2024

Observation of alpha-particles in recent D–T experiments on JET

The fusion reaction between deuterium and tritium, D(T,n) 4 He is the main source of energy in future thermonuclear reactors. Alpha-particles ( 4 He-ions) born with an average energy of 3.5 MeV transferring energy to the thermal plasma during their slowing down, should provide the self-sustained D–T plasma burn. The adequate confinement of α-particles is essential to provide efficient heating of the bulk plasma and steady burning of a reactor plasma. That is why the fusion-born α-particle studies have been a priority task in the second D–T experiments (DTE2) on the Joint European Torus (JET) to understand the main mechanisms of their slowing down, redistribution and losses and to develop optimal plasma scenarios. JET with Be-wall and W-divertor, enhanced auxiliary heating systems and improved energetic-particle diagnostic capabilities, producing significant population of α-particles, provided the possibility for comprehensive studying of the α-particle behaviour. Selected results of the confined and lost α-particle measurements, evidence of α-particle self-heating and assessments of the fusion performance are presented in this paper giving an opportunity for further modelling and extrapolation to the International Thermonuclear Experimental Reactor and burning plasma reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Smoke from 2020 United States wildfires responsible for substantial solar energy forecast errors

Abstract The 2020 wildfire season (May through December) in the United States was exceptionally active, with the National Interagency Fire Center reporting over 10 million acres ( > 40 000 km 2 ) burned. During the September 2020 wildfire events, large concentrations of smoke particulates were emitted into the atmosphere. As a result, smoke was responsible for ∼10%–30% reduction in solar power production during peak hours as recorded by the California Independent System Operator (CAISO) sites. In this study, we focus on a 9 d period in September when wildfire smoke had a profound impact on solar energy production. During the smoke episodes, hour-ahead forecasts utilized by CAISO did not include the effects of smoke and therefore overestimated the expected power production by ∼10%–50%. Here we use multiple observational networks and a numerical weather prediction (NWP) model to show that the wildfire events of 2020 had a significantly detrimental influence on solar energy production due to high aerosol loading. We find that including the contribution of biomass burning particles greatly improves the day-ahead solar energy bias forecast of both global horizontal irradiance and direct normal irradiance by nearly ∼50%. Our results suggest that a more comprehensive treatment of aerosols, including biomass burning aerosols, in NWP models may be an important consideration for energy grid balancing, in addition to solar resource assessment, as solar power reliance increases.

14 SOLAR ENERGY↗
DOE OSTI2023

Climate and air pollution impacts of generating biopower from forest management residues in California

California faces crisis conditions on its forested landscapes. A century of aggressive logging and fire suppression in combination with conditions exacerbated by climate change have created an ongoing ecological, economic, and public health emergency. Between commercial harvests on California’s working forestlands and the increasing number of acres the state treats each year for fire risk reduction and carbon sequestration, California forests generate millions of tons of woody residues annually—residues that are typically left or burned in the field. State policymakers have turned to biomass electricity generation as a key market for woody biomass in the hope that it can support sustainable forest management activities while also providing low-carbon renewable electricity. However, open questions surrounding the climate and air pollution performance of electricity generation from woody biomass have made it difficult to determine how best to manage the risks and opportunities posed by forest residues. The California Biomass Residue Emissions Characterization (C-BREC) model offers a spatially-explicit life cycle assessment framework to rigorously and transparently establish the climate and air pollution impacts of biopower from forest residues in California under current conditions. The C-BREC model characterizes the variable emissions from different biomass supply chains as well as the counterfactual emissions from prescribed burn, wildfire, and decay avoided by residue mobilization. We find that the life cycle ‘carbon footprint’ of biopower from woody residues generated by recent forest treatments in California ranges widely—from comparable with solar photovoltaic on the low end to comparable with natural gas on the high end. This variation stems largely from the heterogeneity in the fire and decay conditions these residues would encounter if left in the field, with utilization of residue that would otherwise have been burned in place offering the best climate and air quality performance. California’s energy and forest management policies should account for this variation to ensure desired climate benefits are achieved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of short-interval reburns in the boreal forest on soil bacterial communities compared to long-interval reburns

Abstract Increasing fire frequency in some biomes is leading to fires burning in close succession, triggering rapid vegetation change and altering soil properties. We studied the effects of short-interval (SI) reburns on soil bacterial communities of the boreal forest of northwestern Canada using paired sites (n = 44). Both sites in each pair had burned in a recent fire; one site had burned within the previous 20 years before the recent fire (SI reburn) and the other had not. Paired sites were closely matched in prefire ecosite characteristics, prefire tree species composition, and stand structure. We hypothesized that there would be a significant effect of short vs. long fire-free intervals on community composition and that richness would not be consistently different between paired sites. We found that Blastococcus sp. was consistently enriched in SI reburns, indicating its role as a strongly ‘pyrophilous’ bacterium. Caballeronia sordidicola was consistently depleted in SI reburns. The depletion of this endophytic diazotroph raises questions about whether this is contributing to—or merely reflects—poor conifer seedling recolonization post-fire at SI reburns. While SI reburns had no significant effect on richness, dissimilarity between short- and long-interval pairs was significantly correlated with difference in soil pH, and there were small significant changes in overall community composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A Continuous Galactic Line Source of Axions: The Remarkable Case of 23 Na

Here, we argue that $^{23}$Na is a potentially significant source of galactic axions. For temperatures $\gtrsim 7 \times 10^8$K -- characteristic of carbon burning in the massive progenitors of supernovae and ONeMg white dwarfs -- the 440 keV first excited state of $^{23}$Na is thermally populated, with its repeated decays pumping stellar energy into escaping axions. Odd-A nuclear abundances are typically very low in high-temperature stellar environments (or absent entirely due to burn-up). $^{23}$Na is an exception: $\approx 0.1 M_\odot$ of the isotope is synthesized during carbon burning then maintained at $\approx 10^9$K for times ranging up to $6 \times 10^4$y. Using MESA simulations, a galactic model, and sampling over progenitor masses, locations, and evolutionary stages, we find a continuous flux at earth of $\langle ϕ_a \rangle \approx 22$/cm$^2$s for $g^\mathrm{eff}_{aNN} = 10^{-9}$. Some fraction of these axions convert to photons as they propagate through the galactic magnetic field, producing a distinctive 440 keV line $γ$ ray detectable by all-sky detectors like the Compton Spectrometer and Imager (COSI). Assuming a 1$μ$G galactic magnetic field and a sufficiently light axion mass, we find that COSI will be able to probe $| g_{aNN}^\mathrm{eff} g_{a γγ} | \gtrsim1.8 \times 10^{-22}$ GeV$^{-1}$ at $3σ$ after two years of surveying.

Dark matter↗
DOE OSTI2026

Utilizing the deuterium-tritium fusion resonance to diagnose thermal runaway in igniting plasmas

For high-efficiency inertial confinement fusion implosions, it is predicted that a burning hot spot will successfully encompass all surrounding fuel and then transition into a thermal runaway where the internal energy increase from fusion occurs on a timescale faster than the expansion of the fuel is able to quench the fusion chain reaction after ignition occurs. Observation of this dynamic phase transition would indicate distinct burn properties and indicate an implosion's robustness. A technique for diagnosing the presence of thermal runaway from measurements of nuclear reaction history is presented. The technique is based on taking the logarithmic derivative of the nuclear reaction history, called the 𝛼 curve, and allowing a mathematical decoupling of the mass, volume, and thermal reactivity in the fusion reaction rate equation. During thermal runaway, where the thermal temperature dominates the burn dynamics, a maximum in the 𝛼 curve is found where there is a maximum in the first derivative of the thermal fusion reactivity, an effect to the deuterium-tritium (DT) fusion cross-section resonance. This provides a distinct signature related to the fundamental nature of the DT fusion nuclear resonance and signifies the transition into the fusion thermal instability. Impacts of charged particle transport on the effect are also assessed and the analytical formulas are compared and found to be in agreement with radiation hydrodynamic codes.

high-energy-density plasmas↗
DOE OSTI2026

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗
DOE OSTI2023

Prescribed fire selects for a pyrophilous soil sub‐community in a northern California mixed conifer forest

Abstract Prescribed fire is a critical strategy for mitigating the effects of catastrophic wildfires. While the above‐ground response to fire has been well‐documented, fewer studies have addressed the effect of prescribed fire on soil microorganisms. To understand how soil microbial communities respond to prescribed fire, we sampled four plots at a high temporal resolution (two burned, two controls), for 17 months, in a mixed conifer forest in northern California, USA. Using amplicon sequencing, we found that prescribed fire significantly altered both fungal and bacterial community structure. We found that most differentially abundant fungal taxa had a positive fold‐change, while differentially abundant bacterial taxa generally had a negative fold‐change. We tested the null hypothesis that these communities assembled due to neutral processes (i.e., drift and/or dispersal), finding that >90% of taxa fit this neutral prediction. However, a dynamic sub‐community composed of burn‐associated indicator taxa that were positively differentially abundant was enriched for non‐neutral amplicon sequence variants, suggesting assembly via deterministic processes. In synthesizing these results, we identified 15 pyrophilous taxa with a significant and positive response to prescribed burns. Together, these results lay the foundation for building a process‐driven understanding of microbial community assembly in the context of the classical disturbance regime of fire.

Microbiology↗
DOE OSTI2021

Large Eddy Simulation of Lean Mixed-Mode Combustion Assisted by Partial Fuel Stratification in a Spark-Ignition Engine

Partial fuel stratification (PFS) is a promising fuel injection strategy to improve the stability of lean combustion by applying a small amount of pilot injection right before spark timing. Mixed-mode combustion, which makes use of end-gas autoignition following conventional deflagration-based combustion, can be further utilized to speed up the overall combustion. In this study, PFS-assisted mixed-mode combustion in a lean-burn direct injection spark-ignition (DISI) engine is numerically investigated using multi-cycle large eddy simulation (LES). A previously developed hybrid G-equation/well-stirred reactor combustion model for the well-mixed operation is extended to the PFS-assisted operation. The experimental spray morphology is employed to derive spray model parameters for the pilot injection. The LES-based model is validated against experimental data and is further compared with the Reynolds-averaged Navier–Stokes (RANS)-based model. Overall, both RANS and LES predict the mean pressure and heat release rate traces well, while LES outperforms RANS in capturing the cycle-to-cycle variation (CCV) and the combustion phasing in the mass burned space. Liquid and vapor penetrations obtained from the simulations agree reasonably well with the experiment. Detailed flame structures predicted from the simulations reveal the transition from a sooting diffusion flame to a lean premixed flame, which is consistent with experimental findings. LES captures more wrinkled and stretched flames than RANS. Finally, the LES model is employed to investigate the impacts of fuel properties, including heat of vaporization (HoV) and laminar burning speed (SL). Combustion phasing is found more sensitive to SL than to HoV, with a larger fuel property sensitivity of the heat release rate from autoignition than that from deflagration. Moreover, the combustion phasing in the PFS-assisted operation is shown to be less sensitive to SL compared with the well-mixed operation.

fuel property sensitivity↗
DOE OSTI2022

Path to Increasing p-B11 Reactivity via ps and ns Lasers

The Lawson criterion for proton-boron (p-11B) thermonuclear fusion is substantially higher than that for deuterium-tritium (DT) because the fusion cross section is lower and peaks at higher ion energies. The Maxwellian averaged p-11B reactivity peaks at several hundred keV, where bremsstrahlung radiation emission may dominate over fusion reactions if electrons and ions are in thermal equilibrium and the losses are unrestricted. Nonequilibrium burn has often been suggested to realize the benefits of this aneutronic reaction, but the predominance of elastic scattering over fusion reactivity makes this difficult to achieve. The development of ultrashort pulse lasers (USPL) has opened new possibilities for initiating nonequilibrium thermonuclear burns and significant numbers of p-11B alpha particles have been reported from several experiments. We present an analysis that shows that these significant alpha yields are the result of beam fusion reactions that do not scale to net energy gain. We further find that the yields can be explained by experimental parameters and recently updated cross sections such that a postulated avalanche mechanism is not required. We use this analysis to understand the underlying physics of USPL-driven nonequilibrium fusion reactions and whether they can be used to initiate fusion burns. We conclude by outlining a path to increasing the p-11B reactivity towards the goal of achieving ignition and describing the design principles that we will use to develop a computational point design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The Influence of Anomalous Biomass Emissions on ENSO in CESM2

Abstract The influence of biomass burning (BB) aerosols arising from wildfires and agricultural fires on the transient coupled evolution of El Niño–Southern Oscillation (ENSO) is explored in Community Earth System Model, version 2 (CESM2). For both El Niño and La Niña, two 20-member ensembles are generated from initial states that are predisposed to evolve into ENSO events. For each ENSO phase, one ensemble is forced with the observed BB emissions during satellite-era ENSO events while the other is forced with a climatological annual cycle, with the responses to anomalous BB emissions estimated from interensemble differences. It is found that the regional responses to anomalous BB emissions occur mainly during boreal fall, which is also the time of the climatological seasonal maximum in emissions. Transient responses are identified in precipitation, clouds, and radiation in both the tropics and extratropics. At the onset of El Niño, these include increased precipitation in the northern branch of the intertropical convergence zone (ITCZ) and an enhancement of cloud albedo and amount across the Maritime Continent and eastern subtropical Pacific Ocean. Additional responses are identified through the course of El Niño and successive La Niña events, the net effect of which is to strengthen sea surface temperature (SST) anomalies in the eastern Pacific Ocean during El Niño and warm the tropical Pacific Ocean during La Niña. These responses improve the simulation of ENSO power, diversity, and asymmetry in CESM2. Significance Statement Biomass burning emissions from both wildfires and agricultural fires during ENSO act as a climate feedback, as they are both driven by fire weather anomalies tied to ENSO and influence clouds, radiation, and precipitation on a global scale. While the largest biomass burning (BB) emissions emanate mainly from Indonesia, other regions also exhibit systematic responses. When simulated in CESM2, the emissions collectively impact the flows of energy across the tropical Pacific Ocean in a spatially and temporally complex fashion, with the net effect of improving CESM2’s simulation of ENSO events.

Fasullo, John T. [National Center for Atmospheric ↗
DOE OSTI2022

Flammability and thermal stability of thermoplastic-based composites filled with natural carbon

This investigation characterized flammability and thermal stability for a novel sustainable composite engineered for use in building applications. Flammability and thermal stability of coal plastic composites composed of coal (40–60 wt.%) and high-density polyethylene were compared to commercial wood–plastic composites. Pyrolysis thermogravimetric analysis results indicated that coal plastic composites possessed a single-step decomposition and higher char residue, while wood–plastic composites had two-step decomposition, with the first peak occurring at much lower temperatures. Thermogravimetric analyses in air suggest coal plastic composites, compared to wood–plastic composites and neat high-density polyethylene, were more thermally stable. Flash ignition temperatures for coal plastic composites were higher than high-density polyethylene and wood–plastic composites, while self-ignition temperatures were in the same range as wood–plastic composites. Rate of burning data indicated coal plastic composites were slower burning than wood–plastic composites, with increasing coal content slowing burning rate by 19.9%–27.6%. Cone calorimeter testing showed 27% and 59% reduction in total heat release and total smoke release as coal content increased while coal plastic composite with 60 wt.% coal possessed lower overall flammability in comparison with predominant commercially available wood–plastic composite products. Coal improved composite overall thermal stability and flammability by acting as char former and foaming agent.

Engineering↗
DOE OSTI2021

Evaluation of residual gas fraction estimation methods for cycle-to-cycle combustion variability analysis and modeling

Cycle-to-cycle combustion variability in spark-ignition engines during normal operation is mainly caused by random perturbations of the in-cylinder conditions such as the flow velocity field, homogeneity of the air-fuel distribution, spark energy discharge, and turbulence intensity of the flame front. Such perturbations translate into the variability of the energy released observed at the end of the combustion process. During normal operating conditions, the cycle-to-cycle variability (CCV) of the energy release behaves as random uncorrelated noise. However, during diluted combustion, in either the form of exhaust gas recirculation (EGR) or excess air (lean operation), the CCV tends to increase as dilution increases. Moreover, when the ignition limit is reached at high dilution levels, the combustion CCV is exacerbated by sporadic occurrences of incomplete combustion events, and the uncorrelation assumption no longer holds. The low or null energy released by partial burns and misfires has an impact on the following combustion event due to the residual gas that carries burned and unburned gases, which contributes to the deterministic coupling between engine cycles. Many residual gas fraction estimation methods, however, only address the nominal case where complete combustion occurs and combustion events are uncorrelated. Here we evaluate the efficacy of such methods on capturing the effects of partial burns and misfires on the residual gas estimate for high-EGR operation. The advantages and disadvantages of each method are discussed based on their ability to generate cycle-to-cycle estimates. Finally, a comparison between the different estimation techniques is presented based on their usefulness for control-oriented modeling.

42 ENGINEERING↗
DOE OSTI2026

Machine learning enables reconstruction of past fire regimes from charcoal-derived fire intensity and fuel composition

Background Fire is a foundational ecological process that shapes ecosystem structure, diversity, and resilience. Quantifying paleofire regime attributes such as frequency, severity, and intensity is essential for understanding the historical range of variability in fire behavior and its ecological effects. While frequency and severity are often reconstructed in paleofire studies, quantitative reconstructions of fire intensity remain limited. Recent work has shown that maximum pyrolysis temperature—a proxy for fire intensity—and plant species type can be inferred from charcoal using transmission Fourier-transform infrared (FTIR) spectroscopy. However, the sample preparation for transmission FTIR is destructive and time-consuming, limiting application and reuse of materials for other analyses. We evaluated reflectance FTIR spectroscopy as a non-destructive alternative for reconstructing combustion temperature and plant species from laboratory-generated charcoal. We also examined the influence of contrasting airflow environments (ambient air versus nitrogen-rich) on pyrolysis temperature and plant species reconstruction prediction accuracies and compared predictive performance between a novel, neural network–based deep learning model with the traditional modern analogue technique (MAT) using k-nearest neighbor functions. As proof of concept, we apply our enhanced methodology to ancient charcoal to demonstrate applicability at improving long-term fire regime reconstructions and the ability to link paleofire records with contemporary fire ecology. Results Our analysis shows that transmission and reflectance FTIR spectra yield comparable spectral profiles. However, sample preparation for reflectance FTIR is minimal and non-destructive, unlike transmission FTIR which is destructive. We demonstrate that oxygen environments improved reconstruction accuracy relative to nitrogen-rich conditions. Finally, our deep learning neural network (DL) achieved testing accuracies of 98.7% for temperature and 96.2% for species identification, outperforming MAT’s k-NN approach (89.8% and 65.9%, respectively). A Shapley importance analysis identified 5 key spectral regions that greatly influenced the model’s temperature or species categorization. When applied to ancient charcoal, our results show historic fires from the most recent past primarily burned at low intensities (400–500 °C), reflective of natural fire regimes in ponderosa pine forests. Our results corroborate charcoal morphology data that suggests all ancient charcoal originated from burned woody plant types. Conclusions By combining reflectance FTIR spectroscopy with a deep learning approach, we provide the first accuracies high enough to confidently identify both species and temperature from laboratory-produced charcoal, improving quantitative reconstructions of fire intensity and fuel composition from paleofire records. This opens a wide range of research into the link between fire and larger drivers (i.e., climate or human) and greater ecological understanding of fire regimes beyond that of burn scars or recent observations. These methodological improvements have direct relevance for fire management by improving interpretation of historical fire behavior, informing fuel–fire relationships, and providing a scalable analytical framework applicable to both long-term ecological studies and contemporary fire science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-KS2 Kennedy Space Center (scrub oak)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-KS2 Kennedy Space Center (scrub oak). This is the FLUXNET version of the carbon flux data for the site US-KS2 Kennedy Space Center (scrub oak) produced by applying the standard ONEFlux (1F) software. Site Description - The Kennedy Space Center Scrub Oak site is located within the Merritt Island National Wildlife Refuge at the Kennedy Space Center (KSC) on the east coast of central Florida. Situated in a 10 ha scrub oak ecosystem, the surrounding stand was completely burned by a prescribed fire in 1996. The purpose of the burn was to control understory fuel load, which has been a common practice since 1969. Within a few weeks of the 1996 burn, the stand began to naturally regenerate from roots and rhizomes. Most scrub oak stands in the region undergo a 7 to 10 year disturbance cycle, mostly related to fire or hurricane activity. A severe drought gripped most of Florida beginning in 1998 until the later half of 2001 resulting in four years of relatively low amount of annual rainfall. Exceptionally high annual rainfall amount in 2004 was the result of a pair of hurricanes that hit the area in August and September of 2004. Prevaling wind directions for the site are as follows: W to NW in the winter, afternoon E sea breeze in the summer.

Drake, Bert↗