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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Antiproton Production by CR on Air Nuclei

Recent measurements of the cosmic ray (CR) antiproton flux have been shown to challenge existing CR propagation models. In particular, the conventional reacceleration model designed to match secondary/primary nuclei ratios produces too few antiprotons. Recently there appear some indications that the atmospheric contribution to antiproton production is considerably underestimated, which implies that antiproton CR flux might be lower. This may be the primary reason of the discrepancy discovered in CR propagation. We use the Los Alamos version of the Quark-Gluon String Model code LAQGSM together with available data on antiproton production on nuclei to analyse the accuracy of existing parameterizations of antiproton production cross section. The LAQGSM model has been shown to reproduce well nuclear reactions and hadronic data in the range 0.01-800 GeV/nucleon.

Maskalenko, I. V.↗
NASA NTRS2004

Advanced Subsonic Technology (AST) 22-Inch Low Noise Research Fan Rig Preliminary Design of ADP-Type Fan 3

This report presents results of the work completed on the preliminary design of Fan 3 of NASA s 22-inch Fan Low Noise Research project. Fan 3 was intended to build on the experience gained from Fans 1 and 2 by demonstrating noise reduction technology that surpasses 1992 levels by 6 dB. The work was performed as part of NASA s Advanced Subsonic Technology (AST) program. Work on this task was conducted in the areas of CFD code validation, acoustic prediction and validation, rotor parametric studies, and fan exit guide vane (FEGV) studies up to the time when a NASA decision was made to cancel the design, fabrication and testing phases of the work. The scope of the program changed accordingly to concentrate on two subtasks: (1) Rig data analysis and CFD code validation and (2) Fan and FEGV optimization studies. The results of the CFD code validation work showed that this tool predicts 3D flowfield features well from the blade trailing edge to about a chord downstream. The CFD tool loses accuracy as the distance from the trailing edge increases beyond a blade chord. The comparisons of noise predictions to rig test data showed that both the tone noise tool and the broadband noise tool demonstrated reasonable agreement with the data to the degree that these tools can reliably be used for design work. The section on rig airflow and inlet separation analysis describes the method used to determine total fan airflow, shows the good agreement of predicted boundary layer profiles to measured profiles, and shows separation angles of attack ranging from 29.5 to 27deg for the range of airflows tested. The results of the rotor parametric studies were significant in leading to the decision not to pursue a new rotor design for Fan 3 and resulted in recommendations to concentrate efforts on FEGV stator designs. The ensuing parametric study on FEGV designs showed the potential for 8 to 10 EPNdB noise reduction relative to the baseline.

Jeracki, Robert J.↗
NASA NTRS1981

An analysis of LANDSAT MSS scene-to-scene registration accuracy

Measurements were made for 12 registrations done by ERL for 8 registrations done by SRS. The results indicate that the ERL method is significantly more accurate in five of the eight comparison. The difference between the two methods are not significant in the other three cases. There are two possible reasons for the differences. First, the ERL model is a piecewise linear model and the EDITOR model is a cubic polynomial model. Second, the ERL program resamples using bilinear interpolation while the EDITOR software uses a nearest neighbor resampling. This study did not indicate how much of the difference is attributable to each factor. The average of all merged scene error values for ERL was 31.6 meters and the average for the eight common areas was 32.6 meters. The average of the eight merged scene error values for SRS was 40.1 meters.

Seyfarth, B. R.↗
DOE OSTI2022

Accurate core excitation and ionization energies from a state-specific coupled-cluster singles and doubles approach

Here, we investigate the use of orbital-optimized references in conjunction with single-reference coupled-cluster theory with single and double substitutions (CCSD) for the study of core excitations and ionizations of 18 small organic molecules, without the use of response theory or equation-of-motion (EOM) formalisms. Three schemes are employed to successfully address the convergence difficulties associated with the coupled-cluster equations, and the spin contamination resulting from the use of a spin symmetry-broken reference, in the case of excitations. In order to gauge the inherent potential of the methods studied, an effort is made to provide reasonable basis set limit estimates for the transition energies. Overall, we find that the two best-performing schemes studied here for ΔCCSD are capable of predicting excitation and ionization energies with errors comparable to experimental accuracies. The proposed ΔCCSD schemes reduces statistical errors against experimental excitation energies by more than a factor of two when compared to the frozen-core core–valence separated (FC-CVS) EOM-CCSD approach – a successful variant of EOM-CCSD tailored towards core excitations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Global Explainability of A Deep Abstaining Classifier for Cancer Pathology Reports

We present a global explainability method to characterize sources of errors in a real-world multitask deep abstaining classifier (DAC), in the context of cancer histology prediction. Our multitask classifier, currently deployed for automated annotation of cancer pathology reports from NCI-SEER registries, was trained and evaluated on 1.04 million hand-annotated samples and makes simultaneous predictions of cancer site, subsite, histology, laterality, and behavior for each report. The DAC framework enables the model to abstain on ambiguous reports and confusing classes to achieve the target accuracy on the retained (non-abstained) samples, but at the cost of decreased coverage. Requiring 97% accuracy on the histology task caused our model to retain only 22% of all samples, mostly the less ambiguous and common classes. Local explainability with the GradInp technique provided a computationally efficient way of obtaining contextual reasoning for hundreds of thousands of individual predictions. Our method, involving dimensionality reduction of approximately 13000 aggregated local explanations (ALE), offers a tractable path to true global explainability. It enabled identification of sources of errors in histology classification, globally, as hierarchical complexity among classes, label noise, insufficient information, and conflicting evidence. This suggests several strategies for iterative improvement of our DAC, including well-designed exclusion criteria, focused annotation, and reduced penalties for errors involving hierarchically related classes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1982

Earth strain measurements with the transportable laser ranging system: Field techniques and planning

The potential of the transportable laser ranging system for monitoring the ground deformation around satellite ranging stations and other geodetic control points was examined with emphasis on testing the usefulness of the relative alteration technique. The temporal variation of the ratio of the length of each survey line to the mean length of all survey lines in a given area is directly related to the mean shear strain rate for the area. The data from a series of experimental measurements taken over the Los Angeles basin from a TLRS station at Mt. Wilson show that such ratios can be determined to an accuracy of one part in 10 million with a measurement program lasting for three days and without using any corrections for variations in atmospheric conditions. A numerical experiment using a set of hypothetical data indicates that reasonable estimates of the present shear strain rate and the direction of the principal axes in southern California can be deduced from such measurements over an interval of one to two years.

Nakamura, Y.↗
NASA NTRS1987

Determination of Earth rotation by the combination of data from different space geodetic systems

Formerly, Earth Rotation Parameters (ERP), i.e., polar motion and UTI-UTC values, have been determined using data from only one observational system at a time, or by the combination of parameters previously obtained in such determinations. The question arises as to whether a simultaneous solution using data from several sources would provide an improved determination of such parameters. To pursue this reasoning, fifteen days of observations have been simulated using realistic networks of Lunar Laser Ranging (LLR), Satellite Laser Ranging (SLR) to Lageos, and Very Long Baseline Interferometry (VLBI) stations. A comparison has been done of the accuracy and precision of the ERP obtained from: (1) the individual system solutions, (2) the weighted means of those values, (3) all of the data by means of the combination of the normal equations obtained in 1, and (4) a grand solution with all the data. These simulations show that solutions done by the normal equation combination and grand solution methods provide the best or nearly the best ERP for all the periods considered, but that weighted mean solutions provide nearly the same accuracy and precision. VLBI solutions also provide similar accuracies.

Archinal, Brent Allen↗
NASA NTRS2011

New Insights into Prebiotic Chemistry from Old Archived Miller Extracts

Following the discovery of an archived set of samples from Stanley Miller's early experiments, analyses were undertaken to better understand the diversity of compounds produced from electric discharges acting on reducing gas mixtures. The paper chromatography methods that Miller used in the 1950s were only capable of detecting a few amino acids and were unable to provide substantial quantitative data relative to today's techniques. Current analytical techniques are much more sensitive and selective, and are capable of precisely quantifying a much larger range of amino acids and their enantiomeric abundances. In one study, preserved dried samples produced by Miller using a lesser-known volcanic apparatus which differed from Miller's classic apparatus in that it utilized an aspirator that injected steam into the electric discharge chamber, simulating a volcanic eruption. The volcanic apparatus produced a wider variety of amino acids than the classic configuration. Prebiotic compounds synthesized in these environments may have locally accumulated where they could have undergone further processing. An additional preserved set of samples from an experiment conducted in 1958 were also found in Miller's archived collection. These samples which had been generated using a mixture of CH4, NH3, H2S and CO2 were collected, catalogued, and stored by Miller, but for unknown reasons were never studied. In our analyses a total of 23 amino acids and 4 amines, including 7 organosulfur compounds, were detected in these samples. The major amino acids with chiral centers are racemic within the accuracy of the measurements, indicating that they are not contaminants introduced during sample storage. This experiment marks the first synthesis of sulfur amino acids from spark discharge experiments designed to imitate primordial environments. The relative yield of some amino acids, in particular the isomers of amino butyric acid, are the highest ever found in a spark discharge experiment. The simulated primordial conditions used by Miller in these experiments may serve as a model for early volcanic plume chemistry and provide insight to the possible roles such plumes may have played in abiotic organic synthesis. Additionally, the overall abundances of the synthesized amino acids in the presence of H2S are very similar to the abundances found in some carbonaceous meteorites, suggesting that H2S may have played an important role in prebiotic reactions in early solar system environments. Although experiments using a variety of gases as components of the primordial Earth's atmospheric composition and a spark discharge apparatus configured according to Miller's original or volcanic design can be readily carried out, the unique opportunity to investigate samples prepared by the pioneer in abiotic synthesis using state of the art analytical methods is of considerable historic interest.

Parker, Eric T.↗
DOE OSTI2025

NeuroSymbolic Approaches as a Vector for Assured Artificial Intelligence

The deployment of artificial intelligence systems in critical applications requires higher levels of assurance for safety, security, and interpretability. While neurosymbolic (NESY) approaches combining neural networks with symbolic reasoning offer potential advantages for assured AI, existing differentiable neurosymbolic frameworks face significant limitations including computational overhead and performance constraints. This report investigates the ISED (InferSampleEstimateDescend) framework as an alternative approach that enables neurosymbolic learning without requiring endtoend differentiability. We evaluate ISED’s utility for geointelligence applications by comparing neurosymbolic models against standard neural networks on aircraft classification tasks using the RarePlanes and MTARSI imagery datasets. Our results demonstrate that while ISEDbased models achieve slightly lower accuracy (89.7% vs 92.1% on RarePlanes; 91.1% vs 92.5% on MTARSI), they provide critical explainability capabilities that enable tracing incorrect predictions back to specific attribute misclassifications. We also present an automated pipeline that generates both attributeclass mappings and neurosymbolic model architectures from natural language descriptions, significantly reducing the manual effort required for NESY model deployment. These findings suggest that ISED offers a promising direction for developing assured AI systems where interpretability and reasoning transparency are prioritized alongside performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Comparison of Equilibrium and Nonequilibrium Approaches for Relative Binding Free Energy Predictions

Alchemical relative binding free energy calculations have recently found important applications in drug optimization. A series of congeneric compounds are generated from a preidentified lead compound, and their relative binding affinities to a protein are assessed in order to optimize candidate drugs. While methods based on equilibrium thermodynamics have been extensively studied, an approach based on nonequilibrium methods has recently been reported together with claims of its superiority. However, these claims pay insufficient attention to the basis and reliability of both methods. Here we report a comparative study of the two approaches across a large data set, comprising more than 500 ligand transformations spanning in excess of 300 ligands binding to a set of 14 diverse protein targets. Ensemble methods are essential to quantify the uncertainty in these calculations, not only for the reasons already established in the equilibrium approach but also to ensure that the nonequilibrium calculations reside within their domain of validity. If and only if ensemble methods are applied, we find that the nonequilibrium method can achieve accuracy and precision comparable to those of the equilibrium approach. Compared to the equilibrium method, the nonequilibrium approach can reduce computational costs but introduces higher computational complexity and longer wall clock times. There are, however, cases where the standard length of a nonequilibrium transition is not sufficient, necessitating a complete rerun of the entire set of transitions. This significantly increases the computational cost and proves to be highly inconvenient during large-scale applications. Our findings provide a key set of recommendations that should be adopted for the reliable implementation of nonequilibrium approaches to relative binding free energy calculations in ligand-protein systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The ballad of LLM agents: philosophical reasoning for chemistry

Large language models (LLMs) show remarkable potential for scientific reasoning but often produce unreliable or scientifically unactionable outputs when faced with multi-step logic, domain grounding, and interpretability challenges, especially in complex fields like chemistry and materials science. Here, we introduce a framework of philosophical reasoning agents, inspired by canonical thinkers such as Socrates, Descartes, Kant, and Hume, to guide LLM behavior via structured prompt engineering. These agents embody distinct reasoning paradigms (dialectical inquiry, deductive logic, rule-based judgment, and empirical validation) and are evaluated across multiple chemistry subdomains, physical, analytical, general, inorganic, and organic chemistry, using the ChemBench benchmark. Our agentic prompting approach yields substantial accuracy gains on open-ended numerical chemistry questions, with gains of +11.5 percentage points for GPT-4o with Hume, +4.5 percentage points for GPT-5 with Kant, and +21.8 percentage points for GPT-5.1 with Socrates at the strict 1% error threshold, relative to the corresponding base models. Beyond accuracy, we observe benchmark-level model–agent performance patterns, suggesting that different prompting styles interact differently with each base model. These findings demonstrate that embedding philosophy-of-science principles into multi-agent frameworks can improve and produce interpretable, adaptive, and domain-aligned scientific LLMs.

Harb, Hassan [Argonne National Laboratory (ANL), A↗
DOE OSTI2022

Improved Cross Section Generation Capability of Griffin in FY22

The Griffin code is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of deterministic steady-state transport solvers for fixed source, k-eigenvalue, adjoint, and subcritical multiplication as well as transient solvers for spatial dynamics with the improved quasi-static method. Griffin uses cross section data in the ISOXML format generated from external deterministic or Monte Carlo cross section generation codes. In recent years, the MC 2 -3 modules have been added to Griffin for fast reactor cross section generation, and the self-shielding application programming interface (SSAPI) was implemented in the ISOXML module for thermal reactor cross section generation. The on-the-fly slowing down method and double-heterogeneity treatment have been implemented to SSAPI and verified against particulate fuel-bearing graphite-moderated thermal reactor problems with high accuracy. This year, work has been focused on improving the cross section generation capability of ISOXML and streamlining the cross section generation procedures. In addition, the form function data were added to ISOXML in order to support the pin power reconstruction capability that was newly implemented in Griffin in this fiscal year. To facilitate the cross section generation using MC 2 -3 and SSAPI in Griffin, the cross section generation workflows have been set up for both fast and thermal spectrum reactors. The MOOSE action system tool was devised for fast spectrum problems, and the MOOSE stochastic tool was adopted to the branch calculation procedure for thermal spectrum problems. Meanwhile, to ensure the accuracy of group-constants, the thermal up-scattering kernel calculator accounting for resonance scattering was implemented in ISOXML, demonstrating the accurate computation of a Doppler-broadened scattering kernel of any Legendre order within a reasonable timescale. Other aspects of ISOXML, such as deletion solver and data, documentation, ISOXML file management, and the interface for Mixture, were improved as well.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Performance and Reliability Assessment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Data Advisor (ADA)

The Atmospheric Radiation Measurement (ARM) User Facility provides one of the world's largest openly accessible repositories of atmospheric observations through the ARM Data Discovery platform. Although the repository contains more than three decades of measurements collected from permanent observatories, mobile facilities, aircraft campaigns, and field experiments, identifying appropriate datasets can be challenging, particularly for new users unfamiliar with ARM instrumentation and datastream organization. To improve data accessibility, the ARM Data Center developed the ARM Data Advisor (ADA), an artificial intelligence-powered assistant designed to facilitate scientific data discovery, dataset interpretation, and user guidance. This report evaluates ADA's performance as a domain-specific scientific assistant using realistic atmospheric science workflows. The evaluation examines five key capabilities: data retrieval and curation efficiency, hallucination resistance, scientific reasoning, response to ambiguous queries, and content retention and session continuity. Representative prompts were developed to simulate typical interactions between researchers and the ARM Data Discovery platform, and ADA's responses were assessed for retrieval completeness, scientific accuracy, consistency, and practical usefulness. In these representative tests, ADA reduced the complexity of discovering and accessing ARM datasets by recommending appropriate datastreams, explaining instrumentation, interpreting metadata, and assisting with data processing workflows. ADA also exhibits strong domain knowledge of atmospheric science terminology and generally resists hallucination by acknowledging unavailable datasets and requesting clarification when appropriate. Overall, the results indicate that ADA represents a promising advancement in scientific data discovery within the ARM User Facility and has considerable potential to improve researcher productivity, particularly for new users and interdisciplinary scientists seeking efficient access to ARM observations.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗
NASA NTRS2006

Interfacing with USSTRATCOM and UTTR during Stardust Earth Return

The Stardust Sample Return Capsule separated from the main spacecraft four hours prior to atmospheric entry. Between this time and the time at which the SRC touched down at the Utah Test and Training Range, two organizations external to JPL were involved in tracking the Sample Return Capsule. Orbit determination for the Stardust spacecraft during deep space cruise, the encounters of asteroid Annefrank and comet Wild 2, and the final approach to Earth used X-band radio metric Doppler and range data obtained through the Deep Space Network. The SRC lacked the electronics needed for coherently transponded radio metric tracking, so the DSN was not able to track the SRC after it separated from the main spacecraft. Although the expected delivery accuracy at atmospheric entry was well within the capability needed to target the SRC to the desired ground location, it was still desirable to obtain direct knowledge of the SRC trajectory in case of anomalies. For this reason U.S. Strategic Command was engaged to track the SRC between separation and atmospheric entry. Once the SRC entered the atmosphere, ground sensors at UTTR were tasked to acquire the descending SRC and maintain track during the descent in order to determine the landing location, to which the ground recovery team was then directed. This paper discusses organizational interfaces, data products, and delivery schedules, and the actual tracking operations are described.

Utah Test and Training Range (UTTR)↗
NASA NTRS2011

Diagnosing AIRS Sampling with CloudSat Cloud Classes

AIRS yield and sampling vary with cloud state. Careful utilization of collocated multiple satellite sensors is necessary. Profile differences between AIRS and ECMWF model analyses indicate that AIRS has high sampling and excellent accuracy for certain meteorological conditions. Cloud-dependent sampling biases may have large impact on AIRS L2 and L3 data in climate research. MBL clouds / lower tropospheric stability relationship is one example. AIRS and CloudSat reveal a reasonable climatology in the MBL cloud regime despite limited sampling in stratocumulus. Thermodynamic parameters such as EIS derived from AIRS data map these cloud conditions successfully. We are working on characterizing AIRS scenes with mixed cloud types.

model analyses↗
DOE OSTI2024

Applicability of 1D site response analysis to shallow sedimentary basins: A critical evaluation through physics-based 3D ground motion simulations

One-dimensional site response analysis (1D SRA) remains the standard practice in considering the effect of local soil deposits and predicting site-specific ground motions, although its range of applicability to realistic seismic wavefields is still in question. In this 1D approach, horizontal and vertical ground shaking are assumed to be induced by vertically propagating shear and compressional waves, respectively. A recent study based on analytical two-dimensional (2D) plane waves and simple point source earthquake simulations has shown two mechanistic limitations in this 1D modelling technique for general inclined seismic waves, that is, systematic over-prediction of the vertical motion and wave trapping in the 1D soil column. In this article, we evaluate in detail the applicability of this 1D modelling approach to realistic three-dimensional (3D) simulated seismic wavefields in shallow sedimentary basins. Linear-viscoelastic 1D SRA predictions using two types of input motions that are commonly used in practice—rock outcrop and in-column motions, are compared with the reference true site response results from 3D earthquake simulations in terms of various measures in the frequency and time domain. It is shown that the horizontal motion in the 3D seismic wavefield exhibits dominant shear wave propagation phenomenon, while the vertical motion is a combined effect of compressional and shear waves and can be over-predicted by the 1D approach when the incident seismic waves are inclined. Direct evidence of the wave refraction process that leads to the vertical motion over-prediction is provided. 1D SRA with in-column inputs can yield motions that have significantly longer duration compared to the true 3D site response solution due to trapped waves, casting in doubt the frequent need for increased soil damping in existing site studies to compensate for wave attenuation due to scattering alone. Sensitivity investigation on the increase of soil profile damping by a multiplier D mul shows D mul values compatible with those found in the literature for both horizontal and vertical motions. It is shown that the level of D mul optimized for a best match of the spectral acceleration is dependent on the characteristic of the input motion and a larger D mul is typically required for the vertical component. In contrast, 1D SRA with outcrop motions predicts motions with shorter significant duration due to its inability to capture the basin-edge generated surface waves. A suite of ground motion simulations was performed to assess the sensitivity of the observations to the basin geologic structure including the velocity gradient, rock-basin impedance contrast and basin depth. The analysis results show that the accuracy of the simplified 1D procedure is dependent on the wavefield composition of both the input motions and the true 3D site response solution. While the horizontal motions in shallow sedimentary basins can, to the first order, be reasonably captured by the simplified 1D approach, 1D SRA for the vertical component is in general not reliable and contributions from inclined shear waves should be accounted for in site-specific evaluation of the vertical design ground motion.

1D assumption↗
DOE OSTI2021

Machine-Learning-based Algorithms for Automated Image Segmentation Techniques of Transmission X-ray Microscopy (TXM)

Four state-of-the-art Deep Learning-based Convolutional Neural Networks (DCNN) were applied to automate the semantic segmentation of a 3D Transmission x-ray Microscopy (TXM) nanotomography image data. The standard U-Net architecture as baseline along with UNet++, PSPNet, and DeepLab v3+ networks were trained to segment the microstructural features of an AA7075 micropillar. A workflow was established to evaluate and compare the DCNN prediction dataset with the manually segmented features using the Intersection of Union (IoU) scores, time of training, confusion matrix, and visual assessment. Comparing all model segmentation accuracy metrics, it was found that using pre-trained models as a backbone along with appropriate training encoder-decoder architecture of the Unet++ can robustly handle large volumes of x-ray radiographic images in a reasonable amount of time. This opens a new window for handling accurate and efficient image segmentation of in situ time-dependent 4D x-ray microscopy experimental datasets.

36 MATERIALS SCIENCE↗