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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

A Data Set of Monthly Freshwater Fluxes From the Greenland Ice Sheet’s Marine-Terminating Glaciers on A Glacier–Basin Scale 2010–2020

The loss of mass from the Greenland ice sheet causes an increasing influx of freshwater to the Greenlandic fjords and the oceans. Freshwater fluxes from marine-terminating glaciers are important to understand fjord circulation and ecosystem dynamics. Here, we present a data set constructed by reformulating existing products into a shared temporal and spatial framework. We combine three publicly available data sets of solid-ice discharge (iceberg), liquid-surface runoff (runoff) and basal melt to present a cohesive overview of the flow of freshwater from marine-terminating glaciers to the Greenlandic fjords. We also calculate glacier drainage basins and compare our findings to previous studies showing that drainage-basin sizes may vary considerably depending on how they were reconstructed. The data set will be a valuable asset to oceanographic, glaciological and marine biological research activities.

Ice mass loss↗
DOE OSTI2023

Correction of the baseline fluctuations in the GEM-based ALICE TPC

To operate the ALICE Time Projection Chamber in continuous mode during the Run 3 and Run 4 data-taking periods of the Large Hadron Collider, the multi-wire proportional chamber-based readout was replaced with gas-electron multipliers. As expected, the detector performance is affected by the so-called common-mode effect, which leads to significant baseline fluctuations. A detailed study of the pulse shape with the new readout has revealed that it is also affected by ion tails. Since reconstruction and data compression are performed fully online, these effects must be corrected at the hardware level in the FPGA-based common readout units. The characteristics of the common-mode effect and of the ion tail, as well as the algorithms developed for their online correction, are described in this paper. The common-mode dependencies are studied using machine-learning techniques. Toy Monte Carlo simulations are performed to illustrate the importance of online corrections and to investigate the performance of the developed algorithms.

47 OTHER INSTRUMENTATION↗
NASA NTRS1988

Using data tagging to improve the performance of Kanerva's sparse distributed memory

The standard formulation of Kanerva's sparse distributed memory (SDM) involves the selection of a large number of data storage locations, followed by averaging the data contained in those locations to reconstruct the stored data. A variant of this model is discussed, in which the predominant pattern is the focus of reconstruction. First, one architecture is proposed which returns the predominant pattern rather than the average pattern. However, this model will require too much storage for most uses. Next, a hybrid model is proposed, called tagged SDM, which approximates the results of the predominant pattern machine, but is nearly as efficient as Kanerva's original formulation. Finally, some experimental results are shown which confirm that significant improvements in the recall capability of SDM can be achieved using the tagged architecture.

Rogers, David↗
DOE OSTI2025

Large Language Model Integration for Knowledge Retrieval and Interaction for the DUNE Experiment

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment that will generate an unprecedented volume of heterogeneous information-from documentation and technical notes to experimental data and reconstruction pipelines. Efficient knowledge retrieval and contextual understanding are increasingly critical for collaboration-wide productivity and onboarding. In this work, we present DUNE-GPT, a prototype framework that leverages large language models (LLMs) and retrieval-augmented generation (RAG) to enable natural-language querying of DUNE's internal documentation and technical resources. The system provides an intelligent interface for DUNE collaborators to interact with experiment-specific knowledge while maintaining data privacy and infrastructure compliance within Fermilab computing resources.

Rafique, A. [Argonne (main)]↗
NASA NTRS2013

The Paradox of a Wet (High H2O) and Dry (Low H2O/Ce) Mantle: High Water Concentrations in Mantle Garnet Pyroxenites from Hawaii

Water dissolved as trace amounts in anhydrous minerals has a large influence on the melting behavior and physical properties of the mantle. The water concentration of the oceanic mantle is inferred from the analyses of Mid-Ocean Ridge Basalt (MORB) and Oceanic Island Basalt (OIB). but there is little data from actual mantle samples. Moreover, enriched mineralogies (pyroxenites, eclogites) are thought as important sources of heterogeneity in the mantle, but their water concentrations and their effect on the water budget and cycling in the mantle are virtually unknown. Here, we analyzed by FTIR water in garnet clinopyroxenite xenoliths from Salt Lake Crater, Oahu, Hawaii. These pyroxenites are high-pressure (>20kb) crystal fractionates from alkalic melts. The clinopyroxenes (cpx) have 260 to 576 ppm wt H2O, with the least differentiated samples (Mg#>0.8) in the 400-500 ppm range. Orthopyroxene (opx) contain 117-265 ppm H2O, about half of that of cpx, consistent with other natural sample studies, but lower than cpx/opx equilibrium from experimental data. The pyroxenite cpx and opx H2O concentrations are at the high-end of on-and off-craton peridotite xenolith concentrations and those of Hawaiian spinel peridotites. In contrast, garnet has extremely low water contents (<5ppm H2O). There is no correlation between H2O in cpx and lithophile element concentrations. Phlogopite is present in some samples, and its modal abundance shows a positive correlation in Mg# with cpx, implying equilibrium. However, there is no correlation between H2O concentrations and or the presence of phlogopite. These data imply that cpx and opx may be at water saturation, far lower than experimental data suggest. Reconstructed bulk rock pyroxenite H2O ranges from 200-460 ppm (average 331 +/- 75 ppm), 2 to 8 times higher than H2O estimates for the MORB source (50-200 ppm), but in the range of E-MORB, OIB and the source of rejuvenated Hawaiian magmas. The average bulk rock pyroxenite H2O/Ce is 69 +/-35, lower than estimates of the MORB source (approx 150) or FOZO, C (200-250) mantle component, but consistent with "dry" EM sources (<100). These data suggest that a metasomatized, refertilized oceanic lithosphere that contains pyroxenitic veins (e.g. the lower part of an oceanic plate, where ascending melts can become trapped and crystallize), will have both higher water concentrations and low H2O/Ce, and may contribute to EM-type OIB sources, like that of Samoa basalts. Therefore, a low H2O/Ce mantle source may not necessarily be "dry".

Peslier, Anne H.↗
DOE OSTI2024

Dark Matter Reconstruction in LBAI Experiments with Imperfect Data

Long-baseline atom interferometer (LBAI) experiments offer unprecedented sensitivity to ultralight scalar dark matter (DM) [1], however reconstruction of a putative DM signal with traditional frequency-domain analysis requires ``perfect data (i.e., regularly-sampled with no missing samples). In a real LBAI experiment, there will undoubtedly be imperfections in the data leading to downtime. This downtime can arise from operational considerations (e.g., maintenance), the operational environment (motion of people and animals [2] or elevators), and robustness of the experimental apparatus (e.g., bad atom launches). In this work, we investigate the impact of various downtime models on the overall DM sensitivity of such an experiment. We compare the sensitivity for each downtime model as determined by a ``compound FFT analysis to a baseline no-downtime case. We also show how much sensitivity can be regained by moving to a Lomb-Scargle frequency analysis, as in [2]. Furthermore, we demonstrate reconstruction of the DM wave s phase as well as its frequency. [1] D. Antypas, et al, ``New Horizons: Scalar and Vector Ultralight Dark Matter (2022). arXiv:2203.14915 [2] J. Carlton and C. McCabe, ``From RATs to riches: mitigating anthropogenic and synanthropic noise in atom interferometer searches for ultra-light dark matter (2023). arXiv:2308.101731

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Deep learning enables nanoscale X-ray 3D imaging with limited data

Deep neural network can greatly improve tomography reconstruction with limited data. A recent effort of combining ptycho-tomography model with the 3D U-net demonstrated a significant reduction in both the number of projections and computation time, and showed its potential for integrated circuit imaging that requires high-resolution and fast measurement speed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Reconstructing gravity on cosmological scales

We present the data-driven late-time reconstruction of gravitational theories and dark energy models on cosmological scales. We showcase the power of present cosmological probes at constraining these models and quantify the knowledge of their properties that can be acquired through state of the art data. This reconstruction exploits the power of the effective field theory approach to dark energy and modified gravity phenomenology, which compresses the freedom in defining such models into a finite set of functions that can be reconstructed across cosmic times using cosmological data. We consider several model classes described within this framework and thoroughly discuss their phenomenology and data implications. In this work, we find that some models can alleviate the present discrepancy in the determination of the Hubble constant as inferred from the cosmic microwave background and as directly measured. This results in a statistically significant preference for the reconstructed theories over the standard cosmological model.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

Reconstruction of the Mars Science Laboratory Parachute Performance and Comparison to the Descent Simulation

The Mars Science Laboratory used a single mortar-deployed disk-gap-band parachute of 21.35 m nominal diameter to assist in the landing of the Curiosity rover on the surface of Mars. The parachute system s performance on Mars has been reconstructed using data from the on-board inertial measurement unit, atmospheric models, and terrestrial measurements of the parachute system. In addition, the parachute performance results were compared against the end-to-end entry, descent, and landing (EDL) simulation created to design, develop, and operate the EDL system. Mortar performance was nominal. The time from mortar fire to suspension lines stretch (deployment) was 1.135 s, and the time from suspension lines stretch to first peak force (inflation) was 0.635 s. These times were slightly shorter than those used in the simulation. The reconstructed aerodynamic portion of the first peak force was 153.8 kN; the median value for this parameter from an 8,000-trial Monte Carlo simulation yielded a value of 175.4 kN - 14% higher than the reconstructed value. Aeroshell dynamics during the parachute phase of EDL were evaluated by examining the aeroshell rotation rate and rotational acceleration. The peak values of these parameters were 69.4 deg/s and 625 deg/sq s, respectively, which were well within the acceptable range. The EDL simulation was successful in predicting the aeroshell dynamics within reasonable bounds. The average total parachute force coefficient for Mach numbers below 0.6 was 0.624, which is close to the pre-flight model nominal drag coefficient of 0.615.

Cruz, Juan R.↗
NASA NTRS2016

Orion Exploration Flight Test Reaction Control System Jet Interaction Heating Environment from Flight Data

The Orion Multi-Purpose Crew Vehicle (MPCV) Reaction Control System (RCS) is critical to guide the vehicle along the desired trajectory during re-­‐entry. However, this system has a significant impact on the convective heating environment to the spacecraft. Heating augmentation from the jet interaction (JI) drives thermal protection system (TPS) material selection and thickness requirements for the spacecraft. This paper describes the heating environment from the RCS on the afterbody of the Orion MPCV during Orion's first flight test, Exploration Flight Test 1 (EFT-1). These jet plumes interact with the wake of the crew capsule and cause an increase in the convective heating environment. Not only is there widespread influence from the jet banks, there may also be very localized effects. The firing history during EFT-1 will be summarized to assess which jet bank interaction was measured during flight. Heating augmentation factors derived from the reconstructed flight data will be presented. Furthermore, flight instrumentation across the afterbody provides the highest spatial resolution of the region of influence of the individual jet banks of any spacecraft yet flown. This distribution of heating augmentation across the afterbody will be derived from the flight data. Additionally, trends with possible correlating parameters will be investigated to assist future designs and ground testing programs. Finally, the challenges of measuring JI, applying this data to future flights and lessons learned will be discussed.

White, Molly E.↗
DOE OSTI2024

AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

molecular replacement↗
NASA NTRS2011

Binary-Signal Recovery

Binary communication through long cables, opto-isolators, isolating transformers, or repeaters can become distorted in characteristic ways. The usual solution is to slow the communication rate, change to a different method, or improve the communication media. It would help if the characteristic distortions could be accommodated at the receiving end to ease the communication problem. The distortions come from loss of the high-frequency content, which adds slopes to the transitions from ones to zeroes and zeroes to ones. This weakens the definition of the ones and zeroes in the time domain. The other major distortion is the reduction of low frequency, which causes the voltage that defines the ones or zeroes to drift out of recognizable range. This development describes a method for recovering a binary data stream from a signal that has been subjected to a loss of both higher-frequency content and low-frequency content that is essential to define the difference between ones and zeroes. The method makes use of the frequency structure of the waveform created by the data stream, and then enhances the characteristics related to the data to reconstruct the binary switching pattern. A major issue is simplicity. The approach taken here is to take the first derivative of the signal and then feed it to a hysteresis switch. This is equivalent in practice to using a non-resonant band pass filter feeding a Schmitt trigger. Obviously, the derivative signal needs to be offset to halfway between the thresholds of the hysteresis switch, and amplified so that the derivatives reliably exceed the thresholds. A transition from a zero to a one is the most substantial, fastest plus movement of voltage, and therefore will create the largest plus first derivative pulse. Since the quiet state of the derivative is sitting between the hysteresis thresholds, the plus pulse exceeds the plus threshold, switching the hysteresis switch plus, which re-establishes the data zero to one transition, except now at the logic levels of the receiving circuit. Similarly, a transition from a one to a zero will be the most substantial and fastest minus movement of voltage and therefore will create the largest minus first derivative pulse. The minus pulse exceeds the minus threshold, switching the hysteresis switch minus, which re-establishes the data one to zero transition. This innovation has a large increase in tolerance for the degradation of the binary pattern of ones and zeroes, and can reject the introduction of noise in the form of low frequencies that can cause the voltage pattern to drift up or down, and also higher frequencies that are beyond the recognizable content in the binary transitions.

Griebeler, Elmer L.↗
DOE OSTI2022

Real-time streaming tomographic reconstruction with on-demand data capturing and 3D zooming to regions of interest

Complex dynamic tomographic experiments at brilliant X-ray light sources require real-time feedback on the sample changes with respect to environmental conditions, selecting representative regions of interest for high-resolution scanning, and on-demand data saving mechanisms for storing only relevant projections acquired by fast area detectors and reducing data volumes. Here the implementation details of a 3D real-time imaging monitoring instrument, with zooming to a volume of interest with easy-to-use visualization via ImageJ , a tool familiar to most beamline users, is presented. The instrument relies on optimized data flow between the detector and processing machines and is implemented on commodity computers. The instrument has been developed at beamline 2-BM of the Advanced Photon Source, where the automatic lens changing mechanism for zooming is implemented with an Optique Peter microscope. Performance tests demonstrate the ability to process more than 3 GB of projection data per second and generate real-time 3D zooming with different magnification. These new capabilities are essential for new APS Upgrade instruments such as the projection microscope under development at beamline 32-ID. The efficacy of the proposed instrument was demonstrated during an in situ tomographic experiment on ice and gas hydrate formation in porous samples.

3D zooming↗
NASA NTRS1991

Chaos in the sunspot cycle - Analysis and prediction

The variability of solar activity over long time scales, given semiquantitatively by measurements of sunspot numbers, is examined as a nonlinear dynamical system. First, a discussion of the data set used and the techniques utilized to reduce the noise and capture the long-term dynamics inherent in the data is presented. Subsequently, an attractor is reconstructed from the data set using the method of time delays. The reconstructed attractor is then used to determine both the dimension of the underlying system and also the largest Lyapunov exponent, which together indicate that the sunspot cycle is indeed chaotic and also low dimensional. In addition, recent techniques of exploiting chaotic dynamics to provide accurate, short-term predictions are utilized in order to improve upon current forecasting methods and also to place theoretical limits on predictability extent. The results are compared to chaotic solar-dynamo models as a possible physically motivated source of this chaotic behavior.

Mundt, Michael D.↗
DOE OSTI2026

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗
DOE OSTI2024

Correction to: Imaging Light–Induced Migration of Dislocations in Halide Perovskites with 3D Nanoscale Strain Mapping

Owing to an error in properly normalizing the reconstruction phase data into atomic displacements, the strain values that we used to calculate the root mean squared local strain, ε rms , and to calculate the fraction of the crystals more strain than 1%, f, quoted in the original paper, are roughly one order of magnitude too large. This error was only discovered recently whilst performing further analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulation-driven optimization of high-order meshes in ALE hydrodynamics

Here we propose tools for high-order mesh optimization and demonstrate their benefits in the context of multi-material Arbitrary Lagrangian-Eulerian (ALE) compressible shock hydrodynamic applications. The mesh optimization process is driven by information provided by the simulation which uses the optimized mesh, such as shock positions, material regions, known error estimates, etc. These simulation features are usually represented discretely, for instance, as finite element functions on the Lagrangian mesh. The discrete nature of the input is critical for the practical applicability of the algorithms we propose and distinguishes this work from approaches that strictly require analytical information. Our methods are based on node movement through a high-order extension of the Target-Matrix Optimization Paradigm (TMOP). The proposed formulation is fully algebraic and relies only on local Jacobian matrices, so it is applicable to all types of mesh elements, in 2D and 3D, and any order of the mesh. We discuss the notions of constructing adaptive target matrices and obtaining their derivatives, reconstructing discrete data in intermediate meshes, node limiting that enables improvement of global mesh quality while preserving space-dependent local mesh features, and appropriate normalization of the objective function. The adaptivity methods are combined with automatic ALE triggers that can provide robustness of the mesh evolution and avoid excessive remap procedures. The benefits of the new high-order TMOP technology are illustrated on several simulations performed in the high-order ALE application BLAST.

97 MATHEMATICS AND COMPUTING↗