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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Estimating Lithium Fluxes from Produced Water: Marcellus Shale and Beyond

This talk summarizes the potential for critical minerals extraction from produced water and the current data constraints on making these evaluations. First, we present results from production simulations carried out using data from the Marcellus shale showing the lithium resource potential from this formation. Second, we broaden our estimations to show the critical mineral resource estimates from U.S. domestic shale operations. Lastly, we conclude with an overview of the NEWTS database and dashboard where we host the data used in our assessments.

Mackey, Justin↗
NASA NTRS2022

Trace Element Partitioning Between Olivine and Melt in Lunar Basalts

Mineral/melt partition coefficients have been widely used to provide insights into magmatic processes. Olivine is one of the most abundant and important minerals in the lunar mantle and mare basalts. Yet, no systematic olivine/melt partitioning data are available for lunar conditions. We report trace element partition data between host mineral olivine and its melt inclusions in lunar basalts. Equilibrium is evaluated using the Fe-Mg exchange coefficient, leading to the choice of melt inclusion-host olivine pairs in lunar basalts 12040, 12009, 15016, 15647, and 74235. Partition coefficients of 21 elements (Li, Mg, Al, Ca, Ti, V, Cr, Mn, Fe, Co, Y, Zr, Nb, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) were measured. Except for Li, V, and Cr, these elements show no significant difference in olivine-melt partitioning compared to the data for terrestrial samples. The partition coefficient of Li between olivine and melt in some lunar basalts with low Mg# (Mg# < 0.75 in olivine, or < ~0.5 in melt) is higher than published data for terrestrial * Corresponding author. Email address: youxue@umich.edu 2 samples, which is attributed to the dependence of DLi on Mg# and the lack of literature DLi data with low Mg#. The partition coefficient of V in lunar basalts is measured to be 0.17 to 0.74, significantly higher than that in terrestrial basalts (0.003 to 0.21), which can be explained by the lower oxygen fugacity in lunar basalts. The significantly higher DV can explain why V is less enriched in evolved lunar basalts than terrestrial basalts. The partition coefficient of Cr between olivine and basalt melt in the Moon is 0.11 to 0.62, which is lower than those in terrestrial settings by a factor of approximately 2. This is surprising because previous authors showed that Cr partition coefficient is independent of fO2. A quasi-thermodynamically based model is developed to correlate Cr partition coefficient to olivine and melt composition and fO2. The lower Cr partition coefficient between olivine and basalt in the Moon can lead to more Cr enrichment in the lunar magma ocean, as well as more Cr enrichment in mantle-derived basalts in the Moon. Hence, even though Cr is typically a compatible element in terrestrial basalts, it is moderately incompatible in primitive lunar basalts, with a similar degree of incompatibility as V based on partition coefficients in this work, as also evidenced by the relatively constant V/Cr ratio of 0.039 ± 0.011 in lunar basalts. The confirmation of constant V/Cr ratio is important for constraining concentrations of Cr (slightly volatile and siderophile) and V (slightly siderophile) in the bulk silicate Moon.

partition coefficients↗
DOE OSTI2025

IRIS-MEMFLOW: Data Flow-Enabled Portable Memory Orchestration in IRIS Runtime for Diverse Heterogeneity

Task-based programming models and execution paradigms provide a means to decompose a computation by expressing it as a graph in which each node represents a specific computation operating on memory objects and the edges define the dependencies in the execution flow. In this execution model, independent nodes in the graph can be executed concurrently in different computing devices, making it suitable for heterogeneous systems in which computing devices with different architectures coexist. However, careful memory orchestration across heterogeneous devices is needed because copies of the same memory object may reside in multiple devices during execution. Manually ensuring such an orchestration is quite challenging. Not only must an application developer guard against race conditions, but they must also optimize data movement between the host and devices because unnecessary data movement significantly impacts performance. To mitigate these challenges, we enhance the IRIS heterogeneous runtime and introduce IRIS-MEMFLOW–a data flow–enabled portable memory abstraction for seamlessly orchestrating memory in diverse heterogeneous computing environments. By using data-flow analysis, IRIS-MEMFLOW guards against race conditions while multiple heterogeneous devices access memory objects. IRIS-MEMFLOW also optimizes data movement between the host and devices without manual intervention. As a result, IRIS provides improved programming productivity, performance, and portability for multidevice heterogeneous executions in high-performance computing and cloud systems that run diverse architectures from different vendors. The efficacy of IRIS-MEMFLOW is evaluated through experiments that show its capability in terms of programming productivity, multidevice heterogeneity, portability, and low overhead versus the state of the art.

Monil, M. A. H. [ORNL] (ORCID:0000000334194037)↗
NASA NTRSDate not supplied

Transcriptomics Processing Pipelines for Space Biology: An Open Source and Consensus-Driven Approach

Transcriptomics holds significant value in elucidating the relationship between gene expression, experimental factors, biological factors, and various types of omics data. Enhancing our understanding of these connections is paramount for foundational biology, which plays a pivotal role in devising solutions for challenges pertinent to both space travel and terrestrial life. The NASA GeneLab project, part of the Open Science Data Repository (OSDR.nasa.gov), seeks to accelerate space biology research through cataloging and democratizing ‘omics data, including transcriptomics. Since raw omics data are largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community via the Open Science Analysis Working Groups (AWGs) to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data have greater immediate value to diverse users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. As of June 2023, transcriptomics studies comprise over half of GeneLab datasets hosted on the OSDR, including data from bulk RNA-seq and Affymetrix or Agilent 1-Channel DNA microarray assays. In collaboration with the AWGs, GeneLab developed consensus processing pipelines for these transcriptomics data types that includes quality control, background correction (microarray only), data normalization and quantification, culminating in the detection and annotation of differentially expressed genes. The work presented here describes Nextflow implementations of GeneLab’s consensus transcriptomics pipelines that automates and accelerates processing of these datasets. In addition to the core data processing, these workflows also include raw data staging and a robust verification and validation program to identify errors in real-time, stop additional downstream computation, and preserve computational resources. These workflows are used to generate GeneLab processed data hosted on the OSDR, and are publicly available as open source software for others to use at: https://github.com/nasa/GeneLab_Data_Processing.

Jonathan Oribello↗
NASA NTRS1995

Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems

Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.

Menasce, Daniel A.↗
DOE OSTI2022

The Dark Energy Survey Supernova Program results: type Ia supernova brightness correlates with host galaxy dust

ABSTRACT Cosmological analyses with type Ia supernovae (SNe Ia) often assume a single empirical relation between colour and luminosity (β) and do not account for varying host-galaxy dust properties. However, from studies of dust in large samples of galaxies, it is known that dust attenuation can vary significantly. Here, we take advantage of state-of-the-art modelling of galaxy properties to characterize dust parameters (dust attenuation AV, and a parameter describing the dust law slope RV) for 1100 Dark Energy Survey (DES) SN host galaxies. Utilizing optical and infrared data of the hosts alone, we find three key aspects of host dust that impact SN cosmology: (1) there exists a large range (∼1–6) of host RV; (2) high-stellar mass hosts have RV on average ∼0.7 lower than that of low-mass hosts; (3) for a subsample of 81 spectroscopically classified SNe there is a significant (>3σ) correlation between the Hubble diagram residuals of red SNe Ia and the host RV that when corrected for reduces scatter by $\sim 13{{\ \rm per\ cent}}$ and the significance of the ‘mass step’ to ∼1σ. These represent independent confirmations of recent predictions based on dust that attempted to explain the puzzling ‘mass step’ and intrinsic scatter (σint) in SN Ia analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Optical evolution of AT 2024wpp: the high-velocity outflows in Cow-like transients are consistent with high spherical symmetry

ABSTRACT We present the analysis of optical/near-infrared (NIR) data and host galaxy properties of a bright, extremely rapidly evolving transient, AT 2024wpp, which resembles the enigmatic AT 2018cow. AT 2024wpp rose to a peak brightness of $c=-21.9$ mag in 4.3 d and remained above the half-maximum brightness for only 6.7 d. The blackbody fits to the photometry show that the event remained persistently hot ($T\gtrsim 20\, 000$ K) with a rapidly receding photosphere ($v\sim 11\, 500$ km s$^{-1}$), similarly to AT 2018cow albeit with a several times larger photosphere. $JH$ photometry reveals an NIR excess over the thermal emission at $\sim +20$ d, indicating a presence of an additional component. The spectra are consistent with blackbody emission throughout our spectral sequence ending at $+21.9$ d, showing a tentative, very broad emission feature at $\sim 5500$ Å – implying that the optical photosphere is likely within a near-relativistic outflow. Furthermore, reports of strong X-ray and radio emission cement the nature of AT 2024wpp as a likely Cow-like transient. AT 2024wpp is the second event of the class with optical polarimetry. Our $BVRI$ observations obtained from $+6.1$ to $+14.4$ d show a low polarization of $P\lesssim 0.5$ per cent across all bands, similar to AT 2018cow that was consistent with $P\sim 0$ per cent during the same outflow-driven phase. In the absence of evidence for a preferential viewing angle, it is unlikely that both events would have shown low polarization in the case that their photospheres were aspherical. As such, we conclude that the near-relativistic outflows launched in these events are likely highly spherical, but polarimetric observations of further events are crucial to constrain their ejecta geometry and stratification in detail.

Pursiainen, M.↗
DOE OSTI2026

ML–Enabled FPGA Framework for Fast Quantum State Discrimination in Mid-Circuit Measurement Regimes

Accurate and low-latency quantum state discrimination is essential for protocols involving mid-circuit measurement (MCM) and conditional feed-forward. In superconducting quantum systems, conventional readout pipelines transfer measurement data to host processors for post-processing, introducing millisecond-scale delays that far exceed qubit coherence times. To overcome this bottleneck, we present an in-situ machine learning (ML) inference engine implemented on an FPGA for real-time quantum state discrimination. Our design performs inference directly on digitized readout signals with 40 ns latency, supports both qubit and qutrit readout, and enables conditional operations without host-side intervention. This capability is critical for MCM and for feedback-driven protocols such as quantum error correction. We validate the system on superconducting transmon hardware, demonstrating robust discrimination fidelity across multiple qubit and qutrit channels. We further demonstrate conditional qutrit logic driven by FPGA-resident classification, highlighting the potential of low-latency ML-on-FPGA control for NISQ applications and scalable fault-tolerant quantum computing.

Vora, Neel [Lawrence Berkeley National Laboratory ↗
DOE OSTI2022

Wintap

Wintap is an extensible, general purpose agent framework for the Windows operating system. It provides an easy-to-use plugin architecture, an integrated streaming analytics engine, and real-time event subscriptions for host-based data. Wintap can support a wide variety of applications across production operations, cyber security operations, and cyber security research.

Frye, DavidJ↗
DOE OSTI2022

A Systematic Exploration of Kilonova Candidates from Neutron Star Mergers during the Third Gravitational-wave Observing Run

We present a comprehensive analysis of 653 optical candidate counterparts reported during the third gravitational-wave (GW) observing run. Our sample concentrates on candidates from the 15 events (published in GWTC-2, GWTC-3, or not retracted on GraceDB) that had a >1% chance of including a neutron star in order to assess their viability as true kilonovae. In particular, we leverage tools available in real time, including pre-merger detections and cross-matching with catalogs (i.e., point-source, variable-star, quasar and host-galaxy redshift data sets), to eliminate 65% of candidates in our sample. We further employ spectroscopic classifications, late-time detections, and light-curve behavior analyses and conclude that 66 candidates remain viable kilonovae. These candidates lack sufficient information to determine their classifications, and the majority would require luminosities greater than that of AT 2017gfo. Pre-merger detections in public photometric survey data and comparison of cataloged host-galaxy redshifts with the GW event distances are critical to incorporate into vetting procedures, as these tools eliminated >20% and >30% of candidates, respectively. We expect that such tools that leverage archival information will significantly reduce the strain on spectroscopic and photometric follow-up resources in future observing runs. Finally, we discuss the critical role prompt updates from GW astronomers to the EM community play in reducing the number of candidates requiring vetting.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

The strong equivalence principle and its violation

Theoretical and observational aspects of an SEP violation are discussed. A two-times theory is presented as a possible framework to handle an SEP violation, and tests performed to check the compatibility of such violation with a host of data ranging from nucleosynthesis to geophysics are summarized. Also discussed are the dynamical equations needed to analyze radar ranging data to reveal an SEP violation and in particular the method employed by Shapiro and Reasenberg (1976).

Canuto, V. M.↗
NASA NTRS1990

Improved "Smart" Robot Hand

Improved version of developmental "smart" robot hand equipped with bidirectional, wide-band optical-fiber link for transmission of digitized strain-gauge force- and torque-sensor signals from hand and for transmission of command signals to motor drive unit on hand. Collection of sensor data speeded hundredfold. Higher data-collection speed makes possible to perform advanced processing of sensor data in host processor.

Szakaly, Zoltan F.↗
NASA NTRS1989

AdaNET phase 0 support for the AdaNET Dynamic Software Inventory (DSI) management system prototype. Catalog of available reusable software components

The Ada Software Repository is a public-domain collection of Ada software and information. The Ada Software Repository is one of several repositories located on the SIMTEL20 Defense Data Network host computer at White Sands Missile Range, and available to any host computer on the network since 26 November 1984. This repository provides a free source for Ada programs and information. The Ada Software Repository is divided into several subdirectories. These directories are organized by topic, and their names and a brief overview of their topics are contained. The Ada Software Repository on SIMTEL20 serves two basic roles: to promote the exchange and use (reusability) of Ada programs and tools (including components) and to promote Ada education.

Hanley, Lionel↗
NASA NTRS1991

Sensor data validation and reconstruction. Phase 1: System architecture study

The sensor validation and data reconstruction task reviewed relevant literature and selected applicable validation and reconstruction techniques for further study; analyzed the selected techniques and emphasized those which could be used for both validation and reconstruction; analyzed Space Shuttle Main Engine (SSME) hot fire test data to determine statistical and physical relationships between various parameters; developed statistical and empirical correlations between parameters to perform validation and reconstruction tasks, using a computer aided engineering (CAE) package; and conceptually designed an expert system based knowledge fusion tool, which allows the user to relate diverse types of information when validating sensor data. The host hardware for the system is intended to be a Sun SPARCstation, but could be any RISC workstation with a UNIX operating system and a windowing/graphics system such as Motif or Dataviews. The information fusion tool is intended to be developed using the NEXPERT Object expert system shell, and the C programming language.

Source record↗
NASA NTRS1992

Computer systems

In addition to the discussions, Ocean Climate Data Workshop hosts gave participants an opportunity to hear about, see, and test for themselves some of the latest computer tools now available for those studying climate change and the oceans. Six speakers described computer systems and their functions. The introductory talks were followed by demonstrations to small groups of participants and some opportunities for participants to get hands-on experience. After this familiarization period, attendees were invited to return during the course of the Workshop and have one-on-one discussions and further hands-on experience with these systems. Brief summaries or abstracts of introductory presentations are addressed.

Olsen, Lola↗
NASA NTRS2010

Kepler Science Operations Center Architecture

We give an overview of the operational concepts and architecture of the Kepler Science Data Pipeline. Designed, developed, operated, and maintained by the Science Operations Center (SOC) at NASA Ames Research Center, the Kepler Science Data Pipeline is central element of the Kepler Ground Data System. The SOC charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Data Pipeline, including the hardware infrastructure, scientific algorithms, and operational procedures. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center that hosts the computers required to perform data analysis. We discuss the high-performance, parallel computing software modules of the Kepler Science Data Pipeline that perform transit photometry, pixel-level calibration, systematic error-correction, attitude determination, stellar target management, and instrument characterization. We explain how data processing environments are divided to support operational processing and test needs. We explain the operational timelines for data processing and the data constructs that flow into the Kepler Science Data Pipeline.

Middour, Christopher↗
NASA NTRS2016

The Kepler Science Data Processing Pipeline Source Code Road Map

We give an overview of the operational concepts and architecture of the Kepler Science Processing Pipeline. Designed, developed, operated, and maintained by the Kepler Science Operations Center (SOC) at NASA Ames Research Center, the Science Processing Pipeline is a central element of the Kepler Ground Data System. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center which hosts the computers required to perform data analysis. The SOC's charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Processing Pipeline, including, the software algorithms. We present the high-performance, parallel computing software modules of the pipeline that perform transit photometry, pixel-level calibration, systematic error correction, attitude determination, stellar target management, and instrument characterization.

Kepler pipeline software↗
NASA NTRSDate not supplied

NASA Briefing to Unidata

The NASA report to Unidata for October, 2021 covers several topics of mutual interest to Unidata. These include plans for hosting NASA data in the cloud, data analysis-in-place, and NASA plans for Open Source Science. Major collaborations with other organizations are also discussed.

NetCDF↗