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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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116 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques⋆

Modeling large datasets through Multivariate Functional Approximations (MFA) provide an elegant way to handle many visualization and scientific analysis workflows. The process necessitates scalable data partitioning methods to compute MFA representations efficiently without compromising the accuracy or continuity of the reconstructed solution. We propose a domain -decomposed method for computing the MFA with B -spline bases, which reduces the total work per task and uses a restricted Additive Schwarz (RAS) method to converge the control point data degrees -of -freedom along subdomain boundaries. We provide an in-depth analysis of the parallel approach with domain decomposition solvers, aiming to minimize local subdomain error residuals and recover high -order continuity at subdomain interfaces with appropriate choices of knot overlaps. The communication cost, determined by the overlap regions in the RAS implementation, is optimized to recover the numerical error profile of the single subdomain case. Our proposed method stands in contrast to previous methods, which typically only recover either C 0 or at best C 1 continuity for arbitrary B -spline degree expansions, or those that require post -processing to blend discontinuities in the reconstructed data. We demonstrate the effectiveness of our approach using analytical and real -world datasets in 1D, 2D, and 3D through both strong and weak scaling studies. The performance results indicate that the overall cost of computing the approximation is directly proportional to the underlying nearest -neighbor communication implementation, and is only weakly dependent on the overlap region size that determines the size of the messages. This finding underscores the efficiency and scalability of our proposed method, making it a promising solution for handling large datasets in scientific workflows.

additive Schwarz solvers↗
DOE OSTI2024

Influence of Nb alloying on Nb recrystallization and the upper critical field of Nb 3 ⁢Sn

Nb 3 Sn conductors are important candidates for high-field magnets for particle accelerators, and they continue to be widely used for many laboratory and NMR magnets. However, the critical current density, J c , of present Nb 3 Sn conductors declines swiftly above 12-15 T. State-of-the-art Ta- and Ti-doped strands exhibit upper critical field, H c2 , values of ~ 24-26.5 T (4.2 K) and do not reach the FCC target J c , which serves as the present stretch target for Nb 3 Sn development. As recently demonstrated, to meet this goal requires enhanced vortex pinning but an independent and supplementary approach is to significantly enhance H c2 . In this study, we have arc-melted multiple Nb alloys with added Hf, Zr, Ta and Ti and drawn them successfully into monofilament wires to investigate the possibilities of H c2 enhancement through alloying. H c2 (T) was measured for all samples in fields up to 16 T and some up to 31 T. We have found that all alloys show good agreement with the standard Werthamer, Helfand, and Hohenberg (WHH) fitting procedure without the need to adjust the paramagnetic limitation parameter (α) and spin-orbit scattering parameter (λ so ). The evaluation of dH c2 /dT near T c , which is proportional to the electronic specific heat coefficient γ and the normal state resistivity ρn, allows a better understanding of the induced disorder introduced by alloying in the A15 phase. So far, we have observed that Hf alloying of pure Nb can enhance H c2 (0) by 3-4 T to ~28 T, while adding just 1 at. %Hf or Zr into a Nb4Ta base alloy can raise H c2 (0) to ~31 T. Very importantly we find that Hf and Zr raise the alloy recrystallization temperature above the usual A15 reaction temperature range of 650°C – 750°C, thus ensuring denser A15 phase nucleation in the Nb alloy grain boundaries, possibly leading to a more homogeneous A15 phase Sn content and refined A15 grain size. Furthermore, the potential for further advancements in Nb 3 Sn properties is explored in relation to the recrystallization of the Nb alloy and the factors controlling the upper critical field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Forest carbon sequestration on the west coast, USA: Role of species, productivity, and stockability

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, “normal” stands without accounting for the substantial proportion of forests that don’t meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types.

Chisholm, Paul J. (ORCID:0000000238784707)↗
DOE OSTI2025

Data for Stetten et al. (2025), "Biogeochemical controls on iron speciation and cycling across upland to shoreline gradients in freshwater and estuarine coastal soils (Lake Erie and Chesapeake Bay, United States)"

Coastal environments are dynamic interfaces that mediate carbon and nutrient exchanges between terrestrial landscapes and open waters, but it is unclear how biogeochemical reactions, in particular iron (Fe) redox transformations, affect the understanding and prediction of coastal ecosystem functions. This dataset includes measurements from two freshwater sites in the Western and Central basins of Lake Erie (Ohio, United States) and two estuarine sites in the Chesapeake Bay (Maryland, United States); the analytical results were reported by Stetten et al. (2025) in Science of the Total Environment. It was produced as part of the COMPASS-FME project, which seeks to advance a scalable, predictive understanding of the fundamental biogeochemical processes, ecological structure, and ecosystem dynamics that distinguish coastal terrestrial-aquatic interfaces from the purely terrestrial or aquatic systems to which they are coupled. The sites were sampled in November 2022 (CRC), December 2022 (MSM), February 2023 (GCW), and March 2023 (OWC); site codes follow those used by Pennington et al. (2025).The dataset consists of the following soil data:- Solid data (Fe concentration, etc.)- Porewater data (sulfate, sulfide, etc.)- Linear combination fitting results of X-ray absorption near edge structure (XANES) spectra; i.e., quantitative results of the oxidation state of Fe, indicated as a proportion of pure Fe(III) and Fe(II) model compounds- Linear combination fitting results of EXAFS (extended X-ray absorption fine structure) spectra, indicated as proportion of of Fe-model compounds (illite, smectite, etc.)Each data type has a single file in comma-separated value (CSV) format. No special software is required to read it.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large reductions in Permian Basin methane intensity shown in multi-year comparison of aerially-visible methane emissions

Spanning the US states of Texas and New Mexico, the Permian Basin has been a hotspot of methane emissions from oil and natural gas activity 1–4, although studies disagree over the magnitude of these emissions. The most comprehensive measurement campaigns published were conducted in 2019 1–5 .There have been large changes in the energy industry since then, including in the prices of oil and gas, both state and federal regulatory environments, investor and activist pressure over methane emissions, and the adoption of new technologies and policies by energy operators. Understanding how any or all of these might influence methane emissions is important for policy makers, oil and gas operators, and other stakeholders. We characterize the time evolution of Permian Basin methane emissions using a series of comprehensive aerial surveys conducted every year from 2020-2023 and compare them to the 2019 results cited above. To maintain comparability, all the data sets are from surveys using Insight M point source methane sensing technology. The scope of these surveys expanded over time: from 33-46% of wells, oil production, and gas production in 2020 to 60-65% in 2021, to 84% of wells and over 90% of both oil and gas production in 2023. These surveys by Insight M also include hundreds of gas processing plants and compressor stations as well as 1000s of km of gathering and transmission pipelines. Considering only the aerially detected portion of emissions (typically the majority of the total in such surveys 4), we find reductions of more than 70% in methane emissions intensity compared to the 2019 New Mexico-only Insight M survey, with variation depending on the year 3,4. Notably, although sources below 100 kg/hr contributed less than 10% of aerially measured emissions the 2019 New Mexico survey 3, these smaller sources constitute a larger proportion of total aerially measured emissions (although not the majority) in 2020-2023. Production facilities and gathering pipelines are responsible for the larges shares of total emissions, followed by compressor stations and gas processing plants. Permian methane emissions were also measured in a comprehensive 2019 Permian-wide survey by the Carbon Mapper team 2. That analysis led to a lower total emissions estimate at the time 4. These new Insight M-based emission rates are still roughly 30-70% lower than the aerially measured portion of the 2019 Carbon Mapper-based estimates 4. Further work is needed to harmonize these surveys in space and time to create the most intercomparable numbers possible 5. Additional analysis is needed to compare our findings to the more spatially constrained 2020, 2021, and 2023 Carbon Mapper surveys in the Permian 4,6. The evidence is strong from these two survey teams that emissions intensity has declined significantly since 2019. Reasons for this trend are currently unclear but point to possible success of emissions control programs. Future work investigating frequency, source, and operator-specific intensities could provide insights into the causes of this promising trend.

methane, oil and gas, data science, remote sensing↗
DOE OSTI2024

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗
DOE OSTI2024

Comparative study of boron and neon injections on divertor heat fluxes using SOLPS-ITER simulations

Here, based on the EAST equilibrium, the effects of boron (B) and neon (Ne) injected at different locations on the target heat load, and the distributions of B and Ne particles were investigated by transport code SOLPS-ITER. It was found that the B injection was more sensitive to the injection location for heat flux control than impurity Ne. The high electron and ion densities near the inner target in the discharge with impurity B injected from over X-point (R 1 ) led to plasma detachment only at the inner target, and the localized B ions in the cases with injection from outer target location (R 2 ) and upstream location (R 3 ) led to far-SOL detachment at the outer target, but not at the inner target. In contrast, for Ne, the spatial distributions of Ne ions and electrons were found to be similar in all the cases at the three injection locations, and the detached plasma was achieved at the inner target and the electron temperature was reduced at the outer target. For locations R 2 and R 3 , impurity B showed a more pronounced effect on the heat flux at the far-SOL of the outer target. Further analysis indicated that Ne atoms came mainly from the recycling sources, whereas B atoms came mainly from injection, and that their distinct atomic distributions resulted from the difference in the ionization threshold and ionization mean free path. In addition, the radiation proportion of B in the divertor region was larger than that of Ne when the total radiation power was similar, which suggests that B has less influence on the core region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Highly excited electron cyclotron for QCD axion and dark-photon detection

We propose using highly excited cyclotron states of a trapped electron to detect meV axion and dark-photon dark matter, marking a significant improvement over our previous proposal and demonstration [One-electron quantum cyclotron as a milli-ev dark-photon detector, .]. When the axion mass matches the cyclotron frequency ω c , the cyclotron state is resonantly excited, with a transition probability proportional to its initial quantum number, n c . The sensitivity is enhanced by taking n c ∼ 10 6 ( 0.1 meV ω c ) 2 . By optimizing key experimental parameters, we minimize the required averaging time for cyclotron detection to t ave ∼ 10 − 6 s, permitting detection of such a highly excited state before its decay. An open–end-cap trap design enables the external photon signal to be directed into the trap, rendering our background-free detector compatible with large focusing cavities, such as the BREAD proposal, while capitalizing on their strong magnetic fields. Furthermore, the axion conversion rate can be coherently enhanced by incorporating layers of dielectrics with alternating refractive indices within the cavity. Collectively, these optimizations enable us to probe the QCD axion parameter space from 0.1 to 2.3 meV (25–560 GHz), covering a substantial portion of the predicted postinflationary QCD axion mass range. This sensitivity corresponds to probing the kinetic mixing parameter of the dark photon down to ε ≈ 2 × 10 − 16 . Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗