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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
NASA NTRS2006

NASA-Langley Web-Based Operational Real-time Cloud Retrieval Products from Geostationary Satellites

At NASA Langley Research Center (LaRC), radiances from multiple satellites are analyzed in near real-time to produce cloud products over many regions on the globe. These data are valuable for many applications such as diagnosing aircraft icing conditions and model validation and assimilation. This paper presents an overview of the multiple products available, summarizes the content of the online database, and details web-based satellite browsers and tools to access satellite imagery and products.

Palikonda, Rabindra↗
DOE OSTI2024

Enhanced Production of Λ b 0 Baryons in High-Multiplicity p p Collisions at s = 13 TeV

The production rate of Λ b 0 baryons relative to B 0 mesons in p p collisions at a center-of-mass energy s = 13 TeV is measured by the LHCb experiment. The ratio of Λ b 0 to B 0 production cross sections shows a significant dependence on both the transverse momentum and the measured charged-particle multiplicity. At low multiplicity, the ratio measured at LHCb is consistent with the value measured in e + e − collisions, and increases by a factor of ∼ 2 with increasing multiplicity. At relatively low transverse momentum, the ratio of Λ b 0 to B 0 cross sections is higher than what is measured in e + e − collisions, but converges with the e + e − ratio as the momentum increases. These results imply that the evolution of heavy b quarks into final-state hadrons is influenced by the density of the hadronic environment produced in the collision. Comparisons with several models and implications for the mechanisms enforcing quark confinement are discussed. © 2024 CERN, for the LHCb Collaboration 2024 CERN

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

SENTRA: A Modular Computational Graph Framework for Critical Mineral and Materials Supply Chains: Part I: Network Construction Latent-Quantity Estimation, and Temporal Graph Forecasting

Global supply chains for critical minerals and materials are complex, evolving networks of countries, products, production stages, and trade relationships. Existing analytical approaches are limited by fragmented data and static network representations that do not capture the dynamic production dependencies linking raw materials, intermediate products, and final goods across multiple countries. Trade and production statistics provide only a partial view of domestic production, inventories, and material flows, making it difficult to identify indirect sourcing pathways, hidden dependencies, and embedded foreign exposures. This paper introduces the Supply Chain Exposure Network Tracking and Risk Assessment (SENTRA) framework, a modular graph-based computational framework for constructing, analyzing, and forecasting dynamic supply chain networks. As the first paper in a three-part methodological series, it establishes the computational foundation of SENTRA by constructing a temporal attributed multi-relational graph whose nodes represent product–country pairs and whose edges encode observed trade and within-country value-chain relationships. Statistical estimation and constrained optimization recover latent production, final demand, and product input dependency coefficients while enforcing economic accounting constraints. Graph-derived exposure measures quantify direct, transshipment, value-chain, and multi-hop supply chain dependencies independently of the forecasting model. A temporal graph forecasting architecture based on a relational graph neural network then forecasts the evolution of the graph under mass-balance constraints with distribution-free conformal uncertainty quantification. Validation on the global aluminum supply chain shows that the learned graph representations recover economically meaningful supply chain structure, accurately forecast out-of-sample trade relationships, and produce well-calibrated prediction intervals. Subsequent papers apply this computational foundation to exposure assessment, disruption analysis, and scenario-based policy analysis, and extend the framework to multimaterial supply chain modeling and decision support.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Navigation and Meteorological Data from Multiple Sensors on Airborne Platform (NAVMET-AIR) Value-Added Product Report

The Navigation and Meteorological Data from Multiple Sensors on Airborne Platform (NAVMET-AIR) value-added product encompasses the aafnaviwg data set in the ARM Data Center (ADC), known as the IWG file, named for the Inter-Agency Working Group for Airborne Data and Telemetry Systems (IWGADTS). Its purpose is to produce a suite of tools to promote standardization of instrument interface, data format, and data processing. This data set’s contents are navigational and meteorological state variables at 1 Hz. It also contains higher-order data flags created by ARM Aerial Facility (AAF) scientists to aid analysis such as periods when the aircraft is flying level, operating in maneuvers, or flying through cloud. Due to the nature of research flights, the payload of the aircraft consists of many duplicate and overlapping instruments to ensure, in case of instrument failure, there is a backup to record the data. Measurements from multiple instruments are consolidated into a single file. Each variable of this data set is carefully chosen from the onboard instrumentation and quality checked by AAF scientists to create this wholistic and most accurate data set for airborne research. This document is intended to be a hub towards the individual “read me” files produced for each campaign. For reference about what instrument was used for calculations on specific days, the read me files are located in the ARM IOP archive at the addresses listed, or access the IOP (intensive operational period) database at https://www.archive.arm.gov/.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Search for pair production of up-type vector-like quarks and for four-top-quark events in final states with multiple b-jets with the ATLAS detector

A search for pair production of up-type vector-like quarks ( T ) with a significant branching ratio into a top quark and either a Standard Model Higgs boson or a Z boson is presented. The same analysis is also used to search for four-top-quark production in several new physics scenarios. The search is based on a dataset of pp collisions at $\sqrt{s}$ =13 TeV recorded in 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider and corresponds to an integrated luminosity of 36.1 fb -1 . Data are analysed in the lepton+jets final state, characterised by an isolated electron or muon with high transverse momentum, large missing transverse momentum and multiple jets, as well as the jets + E T miss final state, characterised by multiple jets and large missing transverse momentum. The search exploits the high multiplicity of jets identified as originating from b -quarks, and the presence of boosted, hadronically decaying top quarks and Higgs bosons reconstructed as large-radius jets, characteristic of signal events. No significant excess above the Standard Model expectation is observed, and 95% CL upper limits are set on the production cross sections for the different signal processes considered. These cross-section limits are used to derive lower limits on the mass of a vector-like T quark under several branching ratio hypotheses assuming contributions from T → W b , Zt , Ht decays. The 95% CL observed lower limits on the T quark mass range between 0 . 99 TeV and 1 . 43 TeV for all possible values of the branching ratios into the three decay modes considered, significantly extending the reach beyond that of previous searches. Additionally, upper limits on anomalous four-top-quark production are set in the context of an effective field theory model, as well as in an universal extra dimensions model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Direct-photon production in inelastic and high-multiplicity proton–proton collisions at $\sqrt{s}$ = 13 TeV

In this letter, we present the first measurement of direct photons at the transverse momentum of 1 < 𝑝 T < 6 GeV/𝑐 at midrapidity 𝜂 < 0.8 in inelastic and high-multiplicity proton–proton collisions at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV. The fraction of virtual direct photons in the inclusive virtual photon spectrum is obtained from a fit to the dielectron invariant mass spectrum. In the limit of zero invariant mass, this fraction is equal to the relative contribution of real direct photons in the inclusive real photon spectrum. Contributions from decays of light- flavour neutral mesons are estimated using independent measurements in proton–proton collisions at the same energy and the same event class. For the first time at the LHC energies, a direct-photon signal is observed at low 𝑝T in both inelastic and high-multiplicity event classes, with a significance of 3.2𝜎 and 1.9𝜎 in terms of standard deviations, correspondingly. The yield of direct photons in inelastic pp collisions is compared to perturbative QCD calculations. The integrated photon yield is studied as a function of charged-particle multiplicity and is compared to the results from other experiments and theoretical calculations. The results show a significant increase of direct- photon yield with charged-particle multiplicity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Fusion of Multiple Models for Improving Gross Primary Production Estimation With Eddy Covariance Data Based on Machine Learning

Abstract Terrestrial gross primary production (GPP) represents the magnitude of CO 2 uptake through vegetation photosynthesis, and is a key variable for carbon cycles between the biosphere and atmosphere. Light use efficiency (LUE) models have been widely used to estimate GPP for its physiological mechanisms and availability of data acquisition and implementation, yet each individual GPP model has exhibited large uncertainties due to input errors and model structure, and further studies of systematic validation, comparison, and fusion of those models with eddy covariance (EC) site data across diverse ecosystem types are still needed in order to further improve GPP estimation. We here compared and fused five GPP models (VPM, EC‐LUE, GOL‐PEM, CHJ, and C‐Fix) across eight ecosystems based on FLUXNET2015 data set using the ensemble methods of Bayesian Model Averaging (BMA), Support Vector Machine (SVM), and Random Forest (RF) separately. Our results showed that for individual models, EC‐LUE gave a better performance to capture interannual variability of GPP than other models, followed by VPM and GLO‐PEM, while CHJ and C‐Fix were more limited in their estimation performance. We found RF and SVM were superior to BMA on merging individual models at various plant functional types (PFTs) and at the scale of individual sites. On the basis of individual models, the fusion methods of BMA, SVM, and RF were examined by a five‐fold cross validation for each ecosystem type, and each method successfully improved the average accuracy of estimation by 8%, 18%, and 19%, respectively.

Environmental Sciences & Ecology↗
DOE OSTI2017

Comparison of methane emission estimates from multiple measurement techniques at natural gas production pads

This study presents the results of a campaign that estimated methane emissions at 268 gas production facilities in the Fayetteville shale gas play using onsite measurements (261 facilities) and two downwind methods - the dual tracer flux ratio method (Tracer Facility Estimate - TFE, 17 facilities) and the EPA Other Test Method 33a (OTM33A Facility Estimate - OFE, 50 facilities). A study onsite estimate (SOE) for each facility was developed by combining direct measurements and simulation of unmeasured emission sources, using operator activity data and emission data from literature. The SOE spans 0-403 kg/h and simulated methane emissions from liquid unloadings account for 88% of total emissions estimated by the SOE, with 76% (95% CI [51%-92%]) contributed by liquid unloading at two facilities. TFE and SOE show overlapping 95% CI between individual estimates at 15 of 16 (94%) facilities where the measurements were paired, while OFE and SOE show overlapping 95% CI between individual estimates at 28 of 43 (65%) facilities. However, variance-weighted least-squares (VWLS) regressions performed on sets of paired estimates indicate statistically significant differences between methods. The SOE represents a lower bound of emissions at facilities where onsite direct measurements of continuously emitting sources are the primary contributor to the SOE, a sub-selection of facilities which minimizes expected inter-method differences for intermittent pneumatic controllers and the impact of episodically-emitting unloadings. At 9 such facilities, VWLS indicates that TFE estimates systematically higher emissions than SOE (TFE-to-SOE ratio = 1.6, 95% CI [1.2 to 2.1]). At 20 such facilities, VWLS indicates that OFE estimates systematically lower emissions than SOE (OFE-to-SOE ratio of 0.41 [0.26 to 0.90]). Given that SOE at these facilities is a lower limit on emissions, these results indicate that OFE is likely a less accurate method than SOE or TFE for this type of facility.

03 NATURAL GAS↗
DOE OSTI2024

Understanding Decision-Relevant Regional Data Products: Workshop Report

A broad community of climate adaptation practitioners, stakeholders and policymakers rely on historical reconstructions and future projections of local to regional climate. To be of value to these users, climate data must be credible, salient, and authoritative (Cash et al. 2002). Namely, data must be consistent with our physical understanding of the global Earth system, must be relevant for informing the decision-making process, and must be backed by expert judgment. As more and more data products have become available, multiple challenges have emerged around the production, evaluation, selection, and use of these data products. Consequently, to ensure crucial decisions leverage the best possible historical and future physical climate data, there is a pressing need to develop a coordinated national climate data strategy that is inclusive of all relevant communities of practice.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Multiplicity dependence of $\pi$, K, and p production in pp collisions at $\sqrt{s}$ = 13 TeV

This paper presents the measurements of π ± , K ± , p and $\bar{p}$ transverse momentum (p T ) spectra as a function of charged-particle multiplicity density in proton–proton (pp) collisions at $\sqrt{s}$ = 13TeV with the ALICE detector at the LHC. Such study allows us to isolate the center-of-mass energy dependence of light-flavour particle production. The measurements reported here cover a p T range from 0.1 to 20 GeV / c and are done in the rapidity interval | y| < 0.5. The p T -differential particle ratios exhibit an evolution with multiplicity, similar to that observed in pp collisions at $\sqrt{s}$ = 7 TeV, which is qualitatively described by some of the hydrodynamical and pQCD-inspired models discussed in this paper. Furthermore, the p T -integrated hadron-to-pion yield ratios measured in pp collisions at two different center-of-mass energies are consistent when compared at similar multiplicities. This also extends to strange and multi-strange hadrons, suggesting that, at LHC energies, particle hadrochemistry scales with particle multiplicity the same way under different collision energies and colliding systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Partitioning Models for Scaling Parallel Sparse Matrix-Matrix Multiplication

We investigate outer-product--parallel, inner-product--parallel, and row-by-row-product--parallel formulations of sparse matrix-matrix multiplication (SpGEMM) on distributed memory architectures. For each of these three formulations, we propose a hypergraph model and a bipartite graph model for distributing SpGEMM computations based on one-dimensional (1D) partitioning of input matrices. Here, we also propose a communication hypergraph model for each formulation for distributing communication operations. The computational graph and hypergraph models adopted in the first phase aim at minimizing the total message volume and balancing the computational loads of processors, whereas the communication hypergraph models adopted in the second phase aim at minimizing the total message count and balancing the message volume loads of processors. That is, the computational partitioning models reduce the bandwidth cost and the communication hypergraph models reduce the latency cost. Our extensive parallel experiments on up to 2048 processors for a wide range of realistic SpGEMM instances show that although the outer-product--parallel formulation scales better, the row-by-row-product--parallel formulation is more viable due to its significantly lower partitioning overhead and competitive scalability. For computational partitioning models, our experimental findings indicate that the proposed bipartite graph models are attractive alternatives to their hypergraph counterparts because of their lower partitioning overhead. Finally, we show that by reducing the latency cost besides the bandwidth cost through using the communication hypergraph models, the parallel SpGEMM time can be further improved up to 32%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Sensor-Enabled Alleviation of Product Inhibition in Chorismate Pyruvate-Lyase

Product inhibition is a frequent bottleneck in industrial enzymes, and testing mutations to alleviate product inhibition via traditional methods remains challenging as many variants need to be tested against multiple substrate and product concentrations. Further, traditional screening methods are conducted in vitro, and resulting enzyme variants may perform differently in vivo in the context of whole-cell metabolism and regulation. In this study, we address these two problems by establishing a high-throughput screening method to alleviate product inhibition in an industrially relevant enzyme, chorismate pyruvate-lyase (UbiC). First, we engineered a highly specific, genetically encoded biosensor for 4-hydroxybenzoate (4HB) in an industrially relevant host, Pseudomonas putida KT2440. We subsequently applied the biosensor to detect the activity of a heterologously expressed UbiC that converts chorismate into 4HB and pyruvate. By using benzoate as a product surrogate that inhibits UbiC without activating the biosensor, we were able to efficiently create and screen a diversified library for UbiC variants with reduced product inhibition. Introduction of the improved UbiC enzyme variant into an experimental production strain for the industrial precursor cis,cis-muconic acid (muconate), enabled a >2-fold yield improvement for glucose to muconate conversion when the new UbiC variant was expressed from a plasmid and a 60% yield increase when the same UbiC variant was genomically integrated into the strain. Overall, this work demonstrates that by coupling a library of enzyme variants to whole-cell catalysis and biosensing, variants with reduced product inhibition can be identified, and that this improved enzyme can result in increased titers of a downstream molecule of interest.

09 BIOMASS FUELS↗
DOE OSTI2017

Concept Overview & Preliminary Analysis

'H2@Scale' is an opportunity for wide-scale use of hydrogen as an intermediate that carries energy from various production options to multiple uses. It is based on identifying and developing opportunities for low-cost hydrogen production and investigating opportunities for using that hydrogen across the electricity, industrial, and transportation sectors. One of the key production opportunities is use of low-cost electricity that may be generated under high penetrations of variable renewable generators such as wind and solar photovoltaics. The technical potential demand for hydrogen across the sectors is 60 million metric tons per year. The U.S. has sufficient domestic renewable resources so that each could meet that demand and could readily meet the demand using a portfolio of generation options. This presentation provides an overview of the concept and the technical potential demand and resources. It also motivates analysis and research on H2@Scale.

30 DIRECT ENERGY CONVERSION↗