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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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At least 19 records

Geochemistry and Multiomics Data Differentiate Streams in Pennsylvania Based on Unconventional Oil and Gas Activity

Unconventional oil and gas (UOG) extraction is increasing exponentially around the world, as new technological advances have provided cost-effective methods to extract hard-to-reach hydrocarbons. While UOG has increased the energy output of some countries, past research indicates potential impacts in nearby stream ecosystems as measured by geochemical and microbial markers. Here, we utilized a robust data set that combines 16S rRNA gene amplicon sequencing (DNA), metatranscriptomics (RNA), geochemistry, and trace element analyses to establish the impact of UOG activity in 21 sites in northern Pennsylvania. These data were also used to design predictive machine learning models to determine the UOG impact on streams. We identified multiple biomarkers of UOG activity and contributors of antimicrobial resistance within the order Burkholderiales. Furthermore, we identified expressed antimicrobial resistance genes, land coverage, geochemistry, and specific microbes as strong predictors of UOG status. Of the predictive models constructed (n = 30), 15 had accuracies higher than expected by chance and area under the curve values above 0.70. The supervised random forest models with the highest accuracy were constructed with 16S rRNA gene profiles, metatranscriptomics active microbial composition, metatranscriptomics active antimicrobial resistance genes, land coverage, and geochemistry (n = 23). The models identified the most important features within those data sets for classifying UOG status. These findings identified specific shifts in gene presence and expression, as well as geochemical measures, that can be used to build robust models to identify impacts of UOG development.

16S rRNA↗

Wave Energy Prize - 1/20th Testing - M3 Wave Submerged Mid-Column Pressure Differential

Data from the 1/20th scale testing data completed on the Wave Energy Prize for the M3 Wave team, including the 1/20th scale test plan, raw test data, video, photos, and data analysis results. The top level objective of the 1/20th scale device testing is to obtain the necessary measurements required for determining Average Climate Capture Width per Characteristic Capital Expenditure (ACE) and the Hydrodynamic Performance Quality (HPQ), key metrics for determining the Wave Energy Prize (WEP) winners.

1/20th scale↗

IAEA CIELO Evaluation of Neutron-induced Reactions on 235 U and 238 U Targets

Evaluations of nuclear reaction data for the major uranium isotopes 238 U and 235 U were performed within the scope of the CIELO Project on the initiative of the OECD/NEA Data Bank under Working Party on Evaluation Co-operation (WPEC) Subgroup 40 coordinated by the IAEA Nuclear Data Section. Both the mean values and covariances are evaluated from 10 -5 eV up to 30 MeV. The resonance parameters of 238 U and 235 U were re-evaluated with the addition of newly available data to the existing experimental database. The evaluations in the fast neutron range are based on nuclear model calculations with the code EMPIRE–3.2 Malta above the resonance range up to 30 MeV. 235 U(n,f), 238 U(n,f), and 238 U(n,γ) cross sections and 235 U(n th ,f) prompt fission neutron spectrum (PFNS) were evaluated within the Neutron Standards project and are representative of the experimental state-of-the-art measurements. The Standards cross sections were matched in model calculations as closely as possible to guarantee a good predictive power for cross sections of competing neutron scattering channels. 235 U(n,γ) cross section includes fluctuations observed in recent experiments. 235 U(n,f) PFNS for incident neutron energies from 500 keV to 20 MeV were measured at Los Alamos Chi-Nu facility and re-evaluated using all available experimental data. While respecting the measured differential data, several compensating errors in previous evaluations were identified and removed so that the performance in integral benchmarks was restored or improved. Covariance matrices for 235 U and 238 U cross sections, angular distributions, spectra and neutron multiplicities were evaluated using the GANDR system that combines experimental data with model uncertainties. Unrecognized systematic uncertainties were considered in the uncertainty quantification for fission and capture cross sections above the thermal range, and for neutron multiplicities. Evaluated files were extensively benchmarked to ensure good performance in reactor calculations and fusion-related systems. New comprehensive evaluations show excellent agreement with available differential data and integral performance better than current evaluated data libraries, and represent a step forward in a quest for better nuclear data for applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Comparative Study of Differentially Private Data Synthesis Methods

When sharing data among researchers or releasing data for public use, there is a risk of exposing sensitive information of individuals in the data set. Data synthesis is a statistical disclosure limitation technique for releasing synthetic data sets with pseudo individual records. Traditional data synthesis techniques often rely on strong assumptions of a data intruder’s behaviors and background knowledge to assess disclosure risk. Differential privacy (DP) formulates a theoretical approach for a strong and robust privacy guarantee in data release without having to model intruders’ behaviors. Efforts have been made aiming to incorporate the DP concept in the data synthesis process. Here, we examine current DIfferentially Private Data Synthesis (DIPS) techniques for releasing individual-level surrogate data for the original data, compare the techniques conceptually and evaluate the statistical utility and inferential properties of the synthetic data via each DIPS technique through extensive simulation studies. Our work sheds light on the practical feasibility and utility of the various DIPS approaches, and suggests future research directions for DIPS.

97 MATHEMATICS AND COMPUTING↗

Theoretical interpretation of thermal arrest data from differential thermal analysis measurements

A theory was developed to interpret the thermal arrest data of HgCdTe system from differential thermal analysis measurements. A nonlinear regression program is used to model fit the data. The purpose is to obtain a set of parameters which will give the information about average radiation coefficient, latent heat of fussion, and specific heat of the HgCdTe system at various compositions. The liquidus and solidus at various compositions are also obtained. The heat radiation from the furnace, heat radiation from the system, heat capacity from both the system and the quartz tube and the heat of fusion of the system are considered, however, it neglects heat transfer through conduction and convection.

Wang, J. C.↗

Differential tracking data types for accurate and efficient Mars planetary navigation

Ways in which high-accuracy differential observations of two or more deep space vehicles can dramatically extend the power of earth-based tracking over conventional range and Doppler tracking are discussed. Two techniques - spacecraft-spacecraft differential very long baseline interferometry (S/C-S/C Delta(VLBI)) and same-beam interferometry (SBI) - are discussed. The tracking and navigation capabilities of conventional range, Doppler, and quasar-relative Delta(VLBI) are reviewed, and the S/C-S/C Delta (VLBI) and SBI types are introduced. For each data type, the formation of the observable is discussed, an error budget describing how physical error sources manifest themselves in the observable is presented, and potential applications of the technique for Space Exploration Initiative scenarios are examined. Requirements for spacecraft and ground systems needed to enable and optimize these types of observations are discussed.

Edwards, C. D., Jr.↗

Dataset_for_Molecular_Motion_Below_the_Glass_Transition_A_Solid-State_NMR_Study_of_Siloxane_Polymer_Dynamics Study

This dataset contains solid-state 1H and 13C NMR relaxometry data, differential scanning calorimetry (DSC) data, and size exclusion chromatography (SEC/GPC) data supporting the study of sub-glass-transition (sub-Tg) molecular dynamics in a composition- and sequence-controlled series of diphenyl-substituted polysiloxanes (PDMS, 14Ph, 33Ph, 50Ph, 67Ph, and 100Ph; 0–100% diphenylsiloxane content by mole).All solid-state NMR data were acquired on a 200 MHz Bruker Avance III HD spectrometer using a static 7 mm HX probe or a 4 mm HX probe under 4 kHz magic-angle spinning. Raw Bruker TopSpin experiment folders are included for: (1) variable-temperature 1H lineshape measurements used to determine linewidth (FWHM) as a function of temperature across the glass transition; (2) 1H T1 (saturation recovery with solid-echo detection), probing nanosecond-scale dynamics near the 1H Larmor frequency; (3) 1H T1rho (direct spin-lock, 62.5 kHz), probing microsecond-scale segmental dynamics; (4) 13C-detected Lee–Goldburg cross-polarization 1H T1rho (LGCPH T1rho) for 33Ph and 50Ph, resolving aromatic and aliphatic proton environments; and (5) 13C T1 relaxation for 33Ph and 50Ph. Differential scanning calorimetry data (TA Instruments DSC 25, −150 to +120 °C, up to +300 °C for 100Ph, 10 °C/min) are included for all six compositions and support the glass-transition temperatures in Table 1 and Figure 1. Size exclusion chromatography data (Agilent 1200 Series, PL-Gel 300 mixed-C column, THF mobile phase, polystyrene calibration standards) are included for the three synthesized copolymers (33Ph, 50Ph, 67Ph) and support the number-average molecular weights in Table 1. Processed data include per-composition relaxation-time summaries (Excel), curve-fitting and Bloembergen-Purcell-Pound (BPP) model analysis notebooks (Jupyter/Python), and Igor Pro (.pxp) master files used to generate the manuscript's figures.

Bloembergen-Purcell-Pound theory↗

Analysis of differential scanning calorimetry data for aged plutonium

Differential scanning calorimetry data for samples of a 52 year old plutonium alloy with 3.3 at. % Ga that were heated beyond the melting point is analyzed using transition state theory to find activation energies for the δ to ε and ε to liquid phase transitions. A Bayesian statistical method involving a Gaussian process model is used to find mean values and confidence intervals for the activation energies. The activation energy for the δ to ε phase transition increases by 3.3 ± 3.8% per decade, relative to the case when all age related plutonium lattice point defects have been removed through annealing. The corresponding increase in activation energy for the ε to liquid transition is shown to be 7.1 ± 1.8% per decade. It is postulated that the change in activation energy with age for both phase transitions is caused, in part, by the accumulation of the same type of lattice point defects associated with the observed increase in elastic bulk modulus over time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The use of Airborne Imaging Spectrometer (AIS) data to differentiate marsh vegetation

The Airborne Imaging Spectrometer (AIS) is a high spectral resolution (9.6-nm-wide bands between 0.9 and 2.4 microns) instrument. Analysis of AIS data revealed significant differences in characteristics of the spectral radiance curves of four types of wetland vegetation canopies (trees, broadleaf herbaceous, Spartina alterniflora, and S. patens/Distichlis spicata) in Delaware, enabling them to be distinguished. The single most useful spectral region was that between 1.40 and 1.90 microns. Differences in radiance values at various wavelengths between samples of the same vegetation type could potentially be used to estimate biomass. Thus, high spectral resolution spectrometry appears to have significant value for remote sensing studies of wetland vegetation.

Gross, M. F.↗

Nuclear Data Testing Of Pu{sup 239} CIELO Evaluation With NDaST

Within the Collaborative International Evaluated Library Organisation (CIELO) project a coordinated effort is being made amongst the different nuclear data evaluation projects, ENDF, JEFF, JENDL etc. to improve the cross sections of six of the most important isotopes, Pu{sup 239}, U{sup 235}, U{sup 238}, Fe{sup 56}, O{sup 16} and H{sup 1}. Recently developed, the Nuclear Data and Sensitivity Tool (NDaST) is an online tool (http://www.oecd-nea.org/ndast/) that allows nuclear data evaluators to get rapid feedback about the consequences of changes to nuclear data on integral experiment benchmarks that exist within the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and International Reactor Physics Evaluation (IRPhE) Project handbooks. NDaST links the thousands of nuclear data sensitivity profiles in the Database for ICSBEP (DICE) and the IRPhE Database and Analysis Tool (IDAT), with the nuclear data viewing tool JANIS. NDaST can be used to provide timely feedback to CIELO participants. Normally an evaluator changes the ENDF/B files based on differential data, and subsequently hands the new evaluation to testers who give feedback on the performance of the new evaluation in terms of accurately predicting the integral benchmark results. This process is often slow. With accurate sensitivity coefficients it is feasible to predict the results of changes to differential data without performing the direct substitution, by simply multiplying the change in cross section with the sensitivity. Furthermore, when multiple aspects of the file are changed simultaneously, the impact of each individual change can be muddled in the substitution testing. NDaST when used in conjunction with direct perturbation testing can help provide feedback as to which cross section changes are driving changes in the benchmarks. In this paper we focus on Pu{sup 239}, and comparing the NDaST predictions of CIELO files to direct substitution. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

The ENDF/B Nuclear Data Library and Its Impact on Reactor Simulations

The ENDF/B library, which is developed, maintained, and distributed by the Cross Section Evaluation Working Group, is the main source of nuclear data for analyses and computational simulations in nuclear applications, like different nuclear reactors concepts, radiation shielding, medical applications, astrophysics, etc. The library is constantly being improved and updated, with each release bringing an optimal representation of nuclear interactions as they are understood in their time. The most recent release, ENDF/B-VIII.1, represents a significant improvement in terms of the performance and consistency of the measured differential data relative to previous versions, as it combines the most recent experimental differential data and advanced theoretical nuclear models. As one of the many highlights, ENDF/B-VIII.1 restores a high-burnup depletion performance, comparable to ENDF/B-VII.1, that had been degraded in ENDF/B-VIII.0, while further improving the performance in criticality benchmarks, such as those in the Mosteller’s suite. Additionally noteworthy is the improved performance of ENDF/B-VIII.1 in radiation shielding and thick-target leakage spectrum integral experiments, which are also important for fusion and reactor applications. In this work we present in a very summarized way the main updates implemented in the ENDF/B-VIII.1 release and its main impacts, and also begin to delineate the path forward as to what to expect in the future for the next ENDF/B release, which, based on the timeline of the past few releases, is estimated to happen around 5 years from now. We emphasize that the ENDF/B-VIII.1 release was the product of an enormous collaborative effort among many authors and that for a complete detailed picture, the reader is strongly encouraged to refer to the article accompanying the release, which is currently in the publication process, but available as preprint [G. P. A. Nobre et al. arXiv Preprint arXiv: 2511.03564 (2025)].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Thermal scattering law for ice based on neutron time-of-flight experiments carried out at the SEQUOIA spectrometer at the Oak Ridge National Laboratory

Precise estimation of neutron thermalization in moderators relies on high-fidelity thermal scattering cross-section data governed by the thermal scattering law (TSL). The Institut de Radioprotection et de Sûreté Nucléaire (IRSN) has been working on the development of improved TSL for light water ice. Many polymorphic phases of light water ice exist depending on the thermodynamic conditions. The most common type of ice at standard pressure and temperature below water freezing point (273.15 K) is ice-Ih. It is essential to have high-resolution experimental double differential data for developing and/or validating TSL for moderator materials.Existing experimental double-differential scattering data for ice-Ih are extremely sparse and of limited quality. New high-quality double-differential measurements for ice-Ih over multiple temperatures and incident neutron energies would directly support the validation and improvement of ice-Ih TSL models for criticality safety applications.Series of time-of-flight (TOF) inelastic neutron scattering experiments on ice-Ih at temperatures starting at 271 K and down to 6 K, have been carried out at the SEQUOIA spectrometer at the Spallation Neutron Source (SNS) at the Oak Ridge National Laboratory (ORNL), United States. The experiments have been performed for incident neutron energies, Ei= 11, 55, 160, 250, and 600 meV, to explore different excitation energies in the vibrational phonon spectrum. This paper presents the thermodynamic conditions and the details of the TOF measurements on ice-Ih and the derived phonon spectrum from the experimentally measured double differential data. A study of the variation of the phonon spectrum of ice-Ih as a function of temperature is highlighted, and a preliminary TSL evaluation is developed based on the experimental phonon spectrum.

Jaiswal, V↗

Investigation of traveling ionospheric disturbances using the differential Doppler data from the Apollo-Soyuz mission

The ASTP Doppler data were recalibrated, analyzed and related to geophysical phenomena and found consistent. Spectra were computed for data intervals covering each hemisphere. As many as 14 such intervals were analyzed. Wave structure is seen in much of the data. The spectra for all those intervals are very similar in a number of respects. They all decrease with frequency, or with decreasing wavelength. Power law fits are reasonable and spectral indices are found to range from about -2.0 to about -3.5. Both large scale (thousands of kilometers) and medium scale (hundreds of kilometers) waves are evident. These spectra are very similar to spectra of in situ measurements of neutrals and ionization measured by Atmosphere Explorer C.

Gross, S. H.↗

Querying databases of trajectories of differential equations: Data structures for trajectories

One approach to qualitative reasoning about dynamical systems is to extract qualitative information by searching or making queries on databases containing very large numbers of trajectories. The efficiency of such queries depends crucially upon finding an appropriate data structure for trajectories of dynamical systems. Suppose that a large number of parameterized trajectories gamma of a dynamical system evolving in R sup N are stored in a database. Let Eta is contained in set R sup N denote a parameterized path in Euclidean Space, and let the Euclidean Norm denote a norm on the space of paths. A data structure is defined to represent trajectories of dynamical systems, and an algorithm is sketched which answers queries.

Grossman, Robert↗

Computing Orbits Around Planets From Differential Doppler Data

Report presents analysis of information content of interferometric measurements of rates of change of propagation delay of radio signals transmitted to and from spacecraft in orbit around distant planet. "Information content" used here defined, somewhat loosely, as contribution of given measurement or series of measurements to accurate knowledge of orbit.

Thurman, Sam W.↗

SubTSBR to tackle high noise and outliers for data-driven discovery of differential equations

Data-driven discovery of differential equations has been an emerging research topic. We propose a novel algorithm subsampling-based threshold sparse Bayesian regression (SubTSBR) to tackle high noise and outliers. The subsampling technique is used for improving the accuracy of the Bayesian learning algorithm. It has two parameters: subsampling size and the number of subsamples. When the subsampling size increases with fixed total sample size, the accuracy of our algorithm goes up and then down. When the number of subsamples increases, the accuracy of our algorithm keeps going up. We demonstrate how to use our algorithm step by step and compare our algorithm with threshold sparse Bayesian regression (TSBR) for the discovery of differential equations. We show that our algorithm produces better results. We also discuss the merits of discovering differential equations from data and demonstrate how to discover models with random initial and boundary condition as well as models with bifurcations. The numerical examples are: (1) predator-prey model with noise, (2) shallow water equations with outliers, (3) heat diffusion with random initial and boundary condition, and (4) fish-harvesting problem with bifurcations.

97 MATHEMATICS AND COMPUTING↗