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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Computational Study of Variable Fuel-Air Ratio and Hydrogen Doping in a Rotating Detonation Engine

Rotating detonation engines (RDEs) hold great promise as a technology for powering aviation engines. The pressure gain that results from continuously traversing detonation waves enables high theoretical performance compared to deflagration-based combustion. However, the harsh operating conditions inside an RDE restrict the availability of suitable experimental diagnostics to study these systems in detail and the range of spatial and temporal scales render numerical simulations of these systems difficult. In this study, we have combined adaptive mesh refinement and a robust shock-capturing approach to study RDE systems computationally using the compressible, reactive solver PeleC. Multi-species transport along with compressible Navier-Stokes equations are solved in the model along with finite-rate chemistry. Complex geometries are represented using an embedded boundary method with second-order spatial accuracy and the system is evolved in time using a second-order Runge-Kutta method. We present studies of a methane-air RDE system that is doped with varying levels of hydrogen. Our analysis focusses on how fuel mixture and doping levels effect the detonation flame structure and the generation of multiple wave modes.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2020

A buoyancy–shear–drag-based turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing

A phenomenological turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing is developed using a general buoyancy–shear–drag model. Analytic solutions to the simplified model equations corresponding to each instability are derived separately, which are then used to calibrate the model coefficients to predict specific values of the mixing layer growth parameters and exponents. The buoyancy-shear–drag equations for the bubble and spike mixing layer widths are then solved numerically, and a turbulent diffusivity (or viscosity) is constructed dimensionally as the product of the mixing layer width, h, and its time-derivative, dh/dt. Surrogate turbulent fields are then constructed by multiplying a presumed, approximate self-similar spatial profile by appropriate functions of h and dh/dt. Using several simplifying approximations, the turbulent diffusion equations satisfied by the mean mass fraction and mean shear velocity are solved analytically in a reference frame moving with the mean advection velocity, and it is shown that the mean fields evolve in space and time as expected. The explicit modeling and solution of turbulent transport equations (e.g., for the turbulent kinetic energy and its dissipation rate or a lengthscale) are not required. By using separate equations for the bubble and spike evolution, the model naturally captures the asymmetry induced by an increasing density contrast between the heavy and light fluids. The model also includes molecular dissipation and diffusion, and therefore, can describe transition to fully-developed turbulence if the initial turbulent diffusivity/viscosity is much smaller than the molecular diffusivity/viscosity. This model is applied to constant-acceleration Rayleigh–Taylor, impulsively reshocked Richtmyer–Meshkov, and variable-density Kelvin–Helmholtz mixing layers to demonstrate its utility. It is shown that the numerical solutions of the model calibrated using specific values of the instability growth parameters and exponents: (1) produces mixing layer widths in agreement with the expected self-similar growth power laws; (2) gives spatiotemporal profiles of turbulent fields that are expected and consistent with previous results; (3) predicts the expected power-law growths and decays of the spatially-integrated turbulent fields, and; (4) gives spatiotemporal profiles of the mean fields that are expected and consistent with previous results. This relatively simple model can be implemented numerically, and is expected to be useful for fundamental as well as astrophysical and inertial confinement fusion applications.

42 ENGINEERING↗
DOE OSTI2024

Poleward Migration of the Latitude of Maximum Tropical Cyclone Intensity—Forced or Natural?

Abstract Past studies have shown a significant observed poleward trend in the latitude at which tropical cyclones reach their lifetime maximum intensity (LMI), especially in the northwest Pacific basin. Given the brevity of the historical record, it remains difficult to separate the forced trend from internal variability of the climate system. A recently developed tropical cyclone downscaling model is used to downscale the Community Earth System Model, version 2 (CESM2), preindustrial control simulation. It is found that the observed trend in the latitude at which tropical cyclones reach their LMI in the northwest Pacific is very unlikely to be caused by internal variability. The same downscaling model is then used to downscale CESM2 simulations under historical forcing. The resulting trend distribution shows a significant poleward migration of tropical cyclone LMI even after regressing out both natural variability and the part of the forced warming pattern that projects onto natural variability. The results indicate that the observed poleward migration of the latitude at which tropical cyclones reach their LMI in the northwest Pacific basin is likely to be, at least in part, forced. However, the magnitude of the projected poleward trend in climate models can be significantly modulated by the simulated spatial pattern of ocean warming. This highlights how discrepancies between models and observations, with regard to projected changes to the equatorial zonal sea surface temperature gradient under anthropogenic forcing, can lead to large uncertainties in projected changes to the LMI latitude of tropical cyclones. Significance Statement Observations in the northwest Pacific basin show that the latitude at which tropical cyclones are at their most intense has been trending northward in the recent half century. These changes are important since tropical cyclones could bring hazardous weather to coastal areas that are poorly equipped to handle them. Here, we show that natural variations in Earth’s climate are very unlikely to explain the observed poleward trend in the latitude that tropical cyclone reach their maximum intensity. We find that it is much more likely that the observed trend is forced by human-related emissions, though the spatial pattern of warming in response to greenhouse emissions can have significant impacts on the magnitude of the trend.

Lin, Jonathan↗
DOE OSTI2022

Exploring dimethyl sulfide (DMS) oxidation and implications for global aerosol radiative forcing

Abstract. Aerosol indirect radiative forcing (IRF), which characterizes how aerosols alter cloud formation and properties, is very sensitive to the preindustrial (PI) aerosol burden. Dimethyl sulfide (DMS), emitted from the ocean, is a dominant natural precursor of non-sea-salt sulfate in the PI and pristine present-day (PD) atmospheres. Here we revisit the atmospheric oxidation chemistry of DMS, particularly under pristine conditions, and its impact on aerosol IRF. Based on previous laboratory studies, we expand the simplified DMS oxidation scheme used in the Community Atmospheric Model version 6 with chemistry (CAM6-chem) to capture the OH-addition pathway and the H-abstraction pathway and the associated isomerization branch. These additional oxidation channels of DMS produce several stable intermediate compounds, e.g., methanesulfonic acid (MSA) and hydroperoxymethyl thioformate (HPMTF), delay the formation of sulfate, and, hence, alter the spatial distribution of sulfate aerosol and radiative impacts. The expanded scheme improves the agreement between modeled and observed concentrations of DMS, MSA, HPMTF, and sulfate over most marine regions, based on the NASA Atmospheric Tomography (ATom), the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), and the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) measurements. We find that the global HPMTF burden and the burden of sulfate produced from DMS oxidation are relatively insensitive to the assumed isomerization rate, but the burden of HPMTF is very sensitive to a potential additional cloud loss. We find that global sulfate burden under PI and PD emissions increase to 412 Gg S (+29 %) and 582 Gg S (+8.8 %), respectively, compared to the standard simplified DMS oxidation scheme. The resulting annual mean global PD direct radiative effect of DMS-derived sulfate alone is −0.11 W m−2. The enhanced PI sulfate produced via the gas-phase chemistry updates alone dampens the aerosol IRF as anticipated (−2.2 W m−2 in standard versus −1.7 W m−2, with updated gas-phase chemistry). However, high clouds in the tropics and low clouds in the Southern Ocean appear particularly sensitive to the additional aqueous-phase pathways, counteracting this change (−2.3 W m−2). This study confirms the sensitivity of aerosol IRF to the PI aerosol loading and the need to better understand the processes controlling aerosol formation in the PI atmosphere and the cloud response to these changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Analysis of Hydrology and Interim Measure Performance in the Chromium Plume at Los Alamos National Laboratory - 20498

Hexavalent chromium, Cr(VI), is present in the regional aquifer beneath Los Alamos National Laboratory (LANL) at concentrations greater than the New Mexico groundwater standard (50 ppb). The source of the Cr is blowdown from a power plant where potassium dichromate was used as a corrosion inhibitor from 1956 to 1972. Blowdown comingled with effluent from another source and migrated approximately 3 miles down a canyon, primarily as surface flow, until reaching an alluvial infiltration zone. The infiltrating water moved vertically through a thick (approximately 900 ft), complex stratigraphic sequence of unsaturated tuffs, basalt, and unconsolidated alluvial deposits. Horizontal transport also took place within spatially limited perched groundwater horizons in the vadose zone (VZ). Breakthrough at the regional aquifer water table is thought to have occurred in multiple hydraulic windows or 'drip points' located approximately 3 miles from the initial release site at the power plant. The regional aquifer is highly heterogeneous and anisotropic, and displays unconfined behavior in an upper zone and confined behavior at depth. The Cr(VI) contamination has so far remained confined to the upper approximately 25 m of the aquifer. The ambient hydraulic gradient in the regional aquifer is toward the east/southeast, but the water table is extremely flat in the Cr plume area compared to surrounding areas. There is some local variability in flow direction, potentially related to effects of seasonal pumping from nearby Los Alamos county water-supply wells, which draw from the regional aquifer several hundred feet below the water table. An interim measure (IM) is currently operating at the site to achieve hydraulic control of plume migration using a series of extraction wells, ion-exchange treatment, and injection along the downgradient portion of the plume. The migration of Cr contamination in the aquifer has been previously evaluated using a calibrated probabilistic numerical model, which has also been used to design the spatial configuration of extraction and injection wells for the IM, and to identify locations for monitoring wells. The model is built using the Finite Element Heat and Mass (FEHM) transfer code, and the Model Analysis and Decision Support (MADS) software is used for analyses. To date, the portion of the IM system that has operated in a continuous manner has been very effective at hydraulic control. Modifications to the flow field associated with the influence of IM pumping and injection are evaluated here, with modeling constraints to be provided by recent observations of tracers injected into both monitoring wells and IM injection wells, as well as opportunistic observations of geochemical signatures of treated ion-exchange effluent injected into IM injection wells. The tracer and geochemical data provide insights into modified flow directions within the Cr plume area that cannot be otherwise obtained. Results of the modeling work are being used to inform adaptive management of IM operations and will be a valuable tool for development and refinement of long-term remediation strategies. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Simulation of ENSO Teleconnections to Precipitation Extremes over the United States in the High-Resolution Version of E3SM

Abstract We evaluate the simulated teleconnection of El Niño–Southern Oscillation (ENSO) to winter season precipitation extremes over the United States in a long (98 years) 1950 control high-resolution version (HR; 25-km nominal atmosphere model horizontal resolution) of the U.S. Department of Energy’s (DOE) Energy Exascale Earth System Model version 1 (E3SMv1). The model bias and spatial pattern of ENSO teleconnections to mean and extreme precipitation in HR overall are similar to the low-resolution model’s (LR; 110 km) historical simulation (four-member ensemble, 1925–59). However, over the southeastern United States (SE-U.S.), HR produces stronger El Niño–associated extremes, reducing LR’s model bias. Both LR and HR produce weaker than observed increase in storm track activity during El Niño events there, but HR improves the ENSO-associated variability of moisture transport over SE-U.S. During El Niño, stronger vertical velocities in HR produce stronger large-scale precipitation, causing larger latent heating of the troposphere that pulls in more moisture from the Gulf of Mexico into the SE-U.S. This positive feedback also contributes to the stronger mean and extreme precipitation response in HR. Over the Pacific Northwest, LR’s bias of stronger than observed La Niña associated extremes is amplified in HR. Both models simulate stronger than observed moisture transport from the Pacific Ocean into the region during La Niña years. The amplified HR bias there is due to stronger orographically driven vertical updrafts that create stronger large-scale precipitation, despite weaker La Niña–induced storm track activity. Significance Statement New high-resolution Earth system models (ESMs) solve mathematical equations of fluid flow at much smaller spatial scales than prevalent ESMs, and thus are prohibitively expensive to compute. However, they can be useful for simulating accurate details of regional climate extremes that are driven by naturally occurring climate oscillations like El Niño–Southern Oscillation (ENSO). Here, we evaluate the simulation of ENSO-driven precipitation extremes over the United States in the high-resolution version of the U.S. Department of Energy’s new Energy Exascale Earth System Model version 1. We find that the high-resolution model improves upon its low-resolution counterpart over the southeastern United States by producing a better transport of moisture into the region from the Gulf of Mexico during El Niño. Over the U.S. Pacific Northwest, the high-resolution model simulates the atmospheric flow in more detail over the complex mountainous terrain. However, it also brings in more moisture from the Pacific Ocean just like the low-resolution model. This causes it to produce precipitation extremes during La Niña years there that are stronger than that observed in the real world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Discovery of 22 GHz Water Masers in the Serpens South Region

Using the Karl G. Jansky Very Large Array (VLA), we have conducted a survey for 22 GHz, 6{sub 1,6}–5{sub 2,3} H{sub 2}O masers toward the Serpens South region. The masers were also observed with the Very Long Baseline Array following the VLA detections. We detect for the first time H{sub 2}O masers in the Serpens South region that are found to be associated to three Class 0–Class I objects, including the two brightest protostars in the Serpens South cluster, known as CARMA-6 and CARMA-7. We also detect H{sub 2}O masers associated to a source with no outflow or jet features. We suggest that this source is most probably a background asymptotic giant branch star projected in the direction of Serpens South. The spatial distribution of the emission spots suggest that the masers in the three Class 0–Class I objects emerge very close to the protostars and are likely excited in shocks driven by the interaction between a protostellar jet and the circumstellar material. Based on the comparison of the distributions of bolometric luminosity of sources hosting 22 GHz H{sub 2}O masers and 162 young stellar objects covered by our observations, we identify a limit of L {sub Bol} ≈ 10L {sub ⊙} for a source to host water masers. However, the maser emission shows strong variability in both intensity and velocity spread, and therefore masers associated to lower-luminosity sources may have been missed by our observations. We also report 11 new sources with radio continuum emission at 22 GHz.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Observation of spatter-induced stochastic lack-of-fusion in laser powder bed fusion using in situ process monitoring

Material produced via additive manufacturing (AM) continues to exhibit variable mechanical properties despite apparent optimization of processing parameters, inhibiting qualification efforts and limiting use in critical applications. Stochastic lack-of-fusion flaws may help explain this variability, but the origin of these seemingly random defects has to this point remained unclear. In this work, we show that spatter particles, material ejected from the laser melt pool, are directly responsible for generating stochastic lack-of-fusion in laser-based powder bed fusion components through the application of spatial statistics. Herein a statistically significant, causal relationship between spatter particles and stochastic lack-of-fusion is established, and the spatial and morphological relationships between spatter and internal flaws are investigated. The occurrence of spatter-induced lack-of-fusion in relation to the inert gas flow and laser trajectory direction is also investigated, and recommendations for mitigating the occurrence of spatter are evaluated.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Spatiotemporal Evolution of Granular Microslip Precursors to Laboratory Earthquakes

Laboratory earthquake experiments provide important observational constraints for our understanding of earthquake physics. Here we leverage continuous waveform data from a network of piezoceramic sensors to study the spatial and temporal evolution of microslip activity during a shear experiment with synthetic fault gouge. We combine machine learning techniques with ray theoretical seismology to detect, associate, and locate tens of thousands of microslip events within the gouge layer. Microslip activity is concentrated near the center of the system but is highly variable in space and time. While microslip activity rate increases as failure approaches, the spatiotemporal evolution can differ substantially between stick-slip cycles. These results illustrate that even within a single, well-constrained laboratory experiment, the dynamics of earthquake nucleation can be highly complex.

58 GEOSCIENCES↗
DOE OSTI2023

Operator Relaxation and the Optimal Depth of Classical Shadows

Classical shadows are a powerful method for learning many properties of quantum states in a sample-efficient manner, by making use of randomized measurements. Here we study the sample complexity of learning the expectation value of Pauli operators via “shallow shadows,” a recently proposed version of classical shadows in which the randomization step is effected by a local unitary circuit of variable depth t. Here we show that the shadow norm (the quantity controlling the sample complexity) is expressed in terms of properties of the Heisenberg time evolution of operators under the randomizing (“twirling”) circuit—namely the evolution of the weight distribution characterizing the number of sites on which an operator acts nontrivially. For spatially contiguous Pauli operators of weight k, this entails a competition between two processes: operator spreading (whereby the support of an operator grows over time, increasing its weight) and operator relaxation (whereby the bulk of the operator develops an equilibrium density of identity operators, decreasing its weight). From this simple picture we derive (i) an upper bound on the shadow norm which, for depth t~log⁡(k), guarantees an exponential gain in sample complexity over the t=0 protocol in any spatial dimension, and (ii) quantitative results in one dimension within a mean-field approximation, including a universal subleading correction to the optimal depth, found to be in excellent agreement with infinite matrix product state numerical simulations. Our Letter connects fundamental ideas in quantum many-body dynamics to applications in quantum information science, and paves the way to highly optimized protocols for learning different properties of quantum states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Interleaved dual-species arrays of single atoms using a passive optical element and one trapping laser

We demonstrate trapping of individual rubidium (Rb) and cesium (Cs) atoms in an interleaved array of bright tweezers and dark bottle-beam traps, using a microfabricated optical element illuminated by a single-laser beam and a 4f system with spatial filtering. Our approach exploits the opposite-sign dynamic polarizabilities of Rb and Cs, ensuring that each species is exclusively trapped in either bright or dark sites. The passive optical mask creates optimal trap depths for both species using three transmittance levels while minimizing the optical phase difference, implemented using a variable-thickness absorbing layer of amorphous germanium. This trapping architecture achieves atom loading rates close to 50% while reducing system complexity compared to conventional methods using active optoelectronic components and/or multiple-laser wavelengths.

Fang, Chengyu [Univ. of Wisconsin, Madison, WI (Un↗
DOE OSTI2024

Machine Learning Approach for Spatiotemporal Multivariate Optimization of Environmental Monitoring Sensor Locations

Abstract Long-term environmental monitoring is critical for managing the soil and groundwater at contaminated sites. Recent improvements in state-of-the-art sensor technology, communication networks, and artificial intelligence have created opportunities to modernize this monitoring activity for automated, fast, robust, and predictive monitoring. In such modernization, it is required that sensor locations be optimized to capture the spatiotemporal dynamics of all monitoring variables as well as to make it cost-effective. The legacy monitoring datasets of the target area are important to perform this optimization. In this study, we have developed a machine-learning approach to optimize sensor locations for soil and groundwater monitoring based on ensemble supervised learning and majority voting. For spatial optimization, Gaussian process regression (GPR) is used for spatial interpolation, while the majority voting is applied to accommodate the multivariate temporal dimension. Results show that the algorithms significantly outperform the random selection of the sensor locations for predictive spatiotemporal interpolation. While the method has been applied to a four-dimensional dataset (with two-dimensional space, time, and multiple contaminants), we anticipate that it can be generalizable to higher-dimensional datasets for environmental monitoring sensor location optimization.

Siddiquee, Masudur R.↗
DOE OSTI2020

Cloud Atlas: Unraveling the Vertical Cloud Structure with the Time-series Spectrophotometry of an Unusually Red Brown Dwarf

Rotational modulations of emission spectra in brown dwarf and exoplanet atmospheres show that clouds are often distributed non-uniformly in these ultracool atmospheres. The spatial heterogeneity in cloud distribution demonstrates the impact of atmospheric dynamics on cloud formation and evolution. In this study, we update the Hubble Space Telescope (HST) time-series data analysis of the previously reported rotational modulations of WISEP J004701+680352—an unusually red late-L brown dwarf with a spectrum similar to that of the directly imaged planet HR 8799e. We construct a self-consistent spatially heterogeneous cloud model to explain the HST and the Spitzer time-series observations, as well as the time-averaged spectra of WISE 0047. Additionally, in the heterogeneous cloud model, a cloud thickness variation of around one pressure scale height explains the wavelength dependence in the HST near-IR spectral variability. By including disequilibrium CO/CH 4 chemistry, our models also reproduce the redder $J-{K}_{{\rm{s}}}$ color of WISE 0047 compared to that of field brown dwarfs. We discuss the impact of vertical cloud structure on atmospheric profile and estimate the minimum eddy diffusivity coefficient for other objects with redder colors. Our data analysis and forward modeling results demonstrate that time-series spectrophotometry with a broad wavelength coverage is a powerful tool for constraining heterogeneous atmospheric structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Forest aboveground biomass estimation through integration of sentinel-2 and PALSAR-2 time series: assessing models trained on GEDI and field inventory benchmarks

Accurate and spatially explicit forest Aboveground Biomass (AGB) mapping through remote sensing is critical for quantifying terrestrial carbon stocks and informing effective forest management strategies. However, AGB estimation in dense forests with complex terrain remains challenging due to satellite sensor signal saturation problem (saturation issue occurs in high biomass forests), structural complexity, and limited ground truth for calibration. This study presents a novel framework that integrates multi-temporal Sentinel-2 optical imagery, ALOS PALSAR-2 Synthetic Aperture Radar (SAR) data, and topographic variables with explainable Machine Learning to map AGB across mountainous forests within subtropical and temperate oceanic climate zones of Mexico. We evaluate the effects of temporal granularity and sensor synergy by comparing multiple temporal inputs and sensor configurations (Sentinel-2, PALSAR-2, and their fusion), and assess model performance using two reference datasets: NASA GEDI LiDAR-derived biomass and Mexico’s National Forest and Soil Inventory (INFyS). Our results showed that models trained on INFyS consistently outperformed those trained on GEDI, highlighting limitations in GEDI’s reliability in biomass estimates within this study region. Furthermore, the integration of Sentinel-2 and PALSAR-2 provided improved predictions compared to single-sensor models, particularly when combined with temporally explicit yearly statistics. The best-performing model, which was trained on INFyS data, and considered both Sentinel-2 and PALSAR-2 yearly statistics, as well as topographic variables, achieved an R2 of 0.64, RMSE of 51.10 Mg/ha, and relative RMSE (rRMSE) of 58.69%. Explainable ML analysis identified Sentinel-2 spectral indices and topographic features as key predictors, while PALSAR-2 metrics provided complementary information, partially mitigating saturation effects in high-biomass areas. Specifically, integrating both sensors substantially improved AGB estimation in high biomass forest (≥200 Mg/ha), yielding 98% gains over optical-only model, with resulting estimates exceeding GEDI L4B by 29% and ESA-CCI-BIOMASS by 174%. Terrain-stratified analysis indicated close agreement with GEDI in low-slope areas, with increasing divergence as slope steepness increased, while estimates remained consistently higher than ESA-CCI-BIOMASS across all slope classes. The proposed approach advances multi-sensor fusion and temporal feature engineering for AGB mapping using open-access satellite datasets, providing a scalable and reproducible framework for annual biomass monitoring in topographically complex mountainous forests. The resulting 25 m resolution biomass product has the potential to provide spatially detailed information for forest monitoring and may support applications in carbon accounting and forest management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An empirical calibration of the serpentine-water oxygen isotope fractionation at T = 25–100°C

The ability to precisely constrain the physical–chemical conditions of serpentinization, such as temperature and fluid source, is limited by the accuracy of calibrations for oxygen isotope fractionation between serpentine and water – i.e., 1000 lnα( serpentine-water ) – which disagree by up to 20‰ when extrapolated to T<200°C. In this study, we present a new empirical calibration of 1000 lnα( serpentine-water ) aiming to improve applications of oxygen isotope geochemistry to very low-T serpentinization (T<100°C). We used the high-spatial resolution capabilities of Secondary Ion Mass Spectrometry (SIMS) to analyze oxygen isotope ratios in mineral pairs of calcite + serpentine, quartz + serpentine and talc + serpentine co-crystallized at scales≤50μm in six serpentinite samples from the Samail ophiolite (Oman). SIMS analysis shows that the mineral pairs are relatively homogenous in oxygen isotope ratios with variability in δ 18 O values ≤2‰ (2s). Clumped isotope thermometry and petrological constraints indicate crystallization temperatures from 25 to 100°C for the investigated samples. These independent constraints on temperature allowed us to derive 1000 lnα( serpentine-water ) by combining Δ 18 O( quartz-serpentine ), Δ 18 O( talc-serpentine ) and Δ 18 O( calcite-serpentine ) measured by SIMS in the investigated samples with Δ 18 O( quartz-water ), Δ 18 O( talc-water ) and Δ 18 O( calcite-water ) calibrations available in the literature. Our empirical calibration of 1000 lnα( serpentine-water ) = 1.04±0.20 (2SE) × 10 6 /T 2 (T in K), from T = 25 to 100°C, is within uncertainty of former high-temperature empirical calibrations extrapolated to T<100°C and matches experimental calibrations when extrapolated to T=250°C. In conclusion, the new serpentine-water calibration enables more accurate reconstructions of fluid-rock interactions occurring during low-temperature serpentinization processes in various tectonic settings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Experimental study of vorticity-strain interactions in turbulent premixed counterflow flames

Here, the effects of heat release on interactions between vorticity (ω) and strain rate (s) in turbulent premixed CH 4 /O 2 /N 2 counterflow flames are investigated using simultaneous OH laser-induced fluorescence (LIF) and tomographic particle image velocimetry (TPIV) measurements. A comparison between the flames and a corresponding turbulent non-reacting variable density N 2 -vs-products counterflow reveals the impact of heat release on vorticity-strain rate alignment statistics. Vorticity and strain rate statistics in the flames and non-reacting flow are conditioned on distance from the local flame front and gas mixing layer interface (GMLI) contours, respectively. The magnitude, alignment, and spatial distribution of the vorticity and principal strain rates (s 1 , s 2 , s 3 ) are rather different when heat release is present. Density variations without heat release enhance the ω-s 2 alignment while significantly reducing the ω-s 3 alignment and modestly reducing the ω-s 1 alignment. In contrast, heat release at the flame front further reduces the ω-s 1 alignment but increases the ω-s 3 alignment and suppresses the preferential ω-s 2 alignment. Furthermore, increasing turbulence diminishes the effect of heat release on this preferential alignment. In regions with the largest vorticities, both the reacting and non-reacting counterflows show an increase in the probability of ω-s 2 alignment. All counterflow cases have a net positive vortex-stretching contribution to the enstrophy production with a peak production rate at the flame front or GMLI, but the peak values depend on the density variation, heat release, and turbulence level. Elucidation of the complex interplay between these factors contributes to the understanding of the dynamics of turbulence-flame interactions.

42 ENGINEERING↗