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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

The Aravalli sequence of Rajasthan, India: A Precambrian continental margin?

The extent to which plate tectonics in its present form operated during the Precambrian is unknown, but is a subject of considerable current interest. A remarkable succession of Precambrian rocks in Rajasthan, Northwestern India, which may help to shed more light on this question are discussed. Data indicates that the Aravalli sequence has a number of characteristics generally ascribed to active continental margins. Although much more work is required to bear this out, the evidence suggests that the processes operating in such an environment in the early Proterozoic or late Archean were not vastly different from today.

Macdougall, J. D.↗
NASA NTRS1971

Nonsystematic convolutional codes for sequential decoding in space applications.

Description of a class of rate 1/2 nonsystematic convolutional codes with the following desirable properties: (1) an undetected decoding error probability verified by simulation to be much smaller than for the best systematic codes of the same constraint length; (2) computation behavior with sequential decoding verified by simulation to be virtually identical to that of the best systematic codes; (3) a ?quick-look-in' feature that permits recovery of the information sequence from the hard-decisioned received data without decoding simply by modulo-two addition of the received sequences; and (4) suitability for encoding by simple circuitry requiring less hardware than encoders for the best systematic codes of the same constraint length. Theoretical analyses are given. These codes have been adopted for use in several forthcoming space missions.

Massey, J. L.↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗
NASA NTRS1974

Liquid rocket combustion computer model with distributed energy release. DER computer program documentation and user's guide, volume 1

A computer program for analyzing rocket engine performance was developed. The program is concerned with the formation, distribution, flow, and combustion of liquid sprays and combustion product gases in conventional rocket combustion chambers. The capabilities of the program to determine the combustion characteristics of the rocket engine are described. Sample data code sheets show the correct sequence and formats for variable values and include notes concerning options to bypass the input of certain data. A seperate list defines the variables and indicates their required dimensions.

Combs, L. P.↗
DOE OSTI2024

Recent Progress on Surface Water Quality Models Utilizing Machine Learning Techniques

Surface waterbodies are heavily exposed to pollutants caused by natural disasters and human activities. Empowering sensor technologies in water quality monitoring, sufficient measurements have become available to develop machine learning (ML) models. Numerous ML models have quickly been adopted to predict water quality indicators in various surface waterbodies. This paper reviews 78 recent articles from 2022 to October 2024, categorizing water quality models utilizing ML into three groups: Point-to-Point (P2P), which estimates the current target value based on other measurements at the same time point; Sequence-to-Point (S2P), which utilizes previous time series data to predict the target value at one time point ahead; and Sequence-to-Sequence (S2S), which uses previous time series data to forecast sequential target values in the future. The ML models used in each group are classified and compared according to water quality indicators, data availability, and model performance. Widely used strategies for improving performance, including feature engineering, hyperparameter tuning, and transfer learning, are recognized and described to enhance model effectiveness. The interpretability limitations of ML applications are discussed. This review provides a perspective on emerging ML for surface water quality models.

machine learning (ML)↗
NASA NTRS1995

Partial gene sequences for the A subunit of methyl-coenzyme M reductase (mcrI) as a phylogenetic tool for the family Methanosarcinaceae

Representatives of the family Methanosarcinaceae were analyzed phylogenetically by comparing partial sequences of their methyl-coenzyme M reductase (mcrI) genes. A 490-bp fragment from the A subunit of the gene was selected, amplified by the PCR, cloned, and sequenced for each of 25 strains belonging to the Methanosarcinaceae. The sequences obtained were aligned with the corresponding portions of five previously published sequences, and all of the sequences were compared to determine phylogenetic distances by Fitch distance matrix methods. We prepared analogous trees based on 16S rRNA sequences; these trees corresponded closely to the mcrI trees, although the mcrI sequences of pairs of organisms had 3.01 +/- 0.541 times more changes than the respective pairs of 16S rRNA sequences, suggesting that the mcrI fragment evolved about three times more rapidly than the 16S rRNA gene. The qualitative similarity of the mcrI and 16S rRNA trees suggests that transfer of genetic information between dissimilar organisms has not significantly affected these sequences, although we found inconsistencies between some mcrI distances that we measured and and previously published DNA reassociation data. It is unlikely that multiple mcrI isogenes were present in the organisms that we examined, because we found no major discrepancies in multiple determinations of mcrI sequences from the same organism. Our primers for the PCR also match analogous sites in the previously published mcrII sequences, but all of the sequences that we obtained from members of the Methanosarcinaceae were more closely related to mcrI sequences than to mcrII sequences, suggesting that members of the Methanosarcinaceae do not have distinct mcrII genes.

NASA Discipline Number 52-30↗
NASA NTRS1997

Determining divergence times with a protein clock: update and reevaluation

A recent study of the divergence times of the major groups of organisms as gauged by amino acid sequence comparison has been expanded and the data have been reanalyzed with a distance measure that corrects for both constraints on amino acid interchange and variation in substitution rate at different sites. Beyond that, the availability of complete genome sequences for several eubacteria and an archaebacterium has had a great impact on the interpretation of certain aspects of the data. Thus, the majority of the archaebacterial sequences are not consistent with currently accepted views of the Tree of Life which cluster the archaebacteria with eukaryotes. Instead, they are either outliers or mixed in with eubacterial orthologs. The simplest resolution of the problem is to postulate that many of these sequences were carried into eukaryotes by early eubacterial endosymbionts about 2 billion years ago, only very shortly after or even coincident with the divergence of eukaryotes and archaebacteria. The strong resemblances of these same enzymes among the major eubacterial groups suggest that the cyanobacteria and Gram-positive and Gram-negative eubacteria also diverged at about this same time, whereas the much greater differences between archaebacterial and eubacterial sequences indicate these two groups may have diverged between 3 and 4 billion years ago.

NASA Discipline Exobiology↗
DOE OSTI2026

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space

Background Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens is often confounded by extreme sequence homology. This homology leads to “data leakage” in standard random validation splits, yielding inflated performance metrics that fail to translate into real-world biosurveillance utility. Results We present Protein Representation Inference for Mutation Evaluation (PRIME), a framework that integrates domain-specific fine-tuning with a rigorous position-stratified validation protocol to evaluate viral threats. Using a dataset of 347,432 SARS-CoV-2 receptor binding domain (RBD) sequences, we demonstrate that while random training data split yields deceptive R 2 values (> 0.90), they fail to generalize to novel mutational sites. By benchmarking models up to 650 M parameters, we show that domain-specific fine-tuning of the ESM-C 600 M model with correctly stratified data provides an initial demonstration of predictive signal for binding affinity and expression at unseen mutational sites of binding affinity and expression on unseen sites (R 2 ~0.23), a significant advancement over base foundation models which exhibit no predictive power (R 2 <0). PRIME’s embedding-based clustering identified 3.03% of bat coronavirus sequences as candidates for further experimental prioritization based on their functional similarity to human-infective strains in embedding space, offering a perspective complementary to traditional phylogenetic methods. Conclusion PRIME establishes a new benchmark for the application of PLMs in pathogen surveillance. Our findings demonstrate that state-of-the-art models and fine-tuning, when paired with stratified validation, provide biologically meaningful insights into pathogen evolution and zoonotic risk.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Assessment of Accelerated Stress Testing Data for Silicon Photovoltaics Using Tensor Decomposition Methods

In this work, we examine the use of high-order tensor decompositions to analyze degradation pathways emerging from accelerated stress testing of silicon photovoltaic (PV) modules. Matrix-based decompositions are powerful tools for studying two-dimensional data arrays and form the foundation of a host of classical data analysis techniques. Tensors are high-order extrapolations of matrices that are able to account for more parameter dimensions, and a variety of tensor decomposition methods have been developed that similarly seek to extend insights from matrix decompositions to higher dimensions. Applying and interpreting tensor decomposition methods to sequences of PV module image data, we seek to uncover and isolate different degradation modes occurring from accelerated stress testing procedures. Further, we consider the contributions of different modes to PV module performance degradations.

data analysis↗
NASA NTRS1986

Word and frame synchronization with verification for PPM optical communications

A method for obtaining word and frame synchronization in pulse position modulated optical communication systems is described. The method uses a short sync sequence inserted at the beginning of each data frame and a verification procedure to distinguish between inserted and randomly occurring sequences at the receiver. This results in an easy to implement sync system which provides reliable synchronization even at high symbol error rates. Results are given for the application of this approach to a highly energy efficient 256-ary PPM test system.

Marshall, William K.↗
NASA NTRS1971

Image coding by adaptive block quantization.

A new source encoder called the adaptive block quantizer is proposed for coding data sources that emit a sequence of correlated real numbers with known first- and second-order statistics. Blocks of source output symbols are first classified and then block quantized in a manner that depends on their classification. The system is optimized relative to both the mean square error and the subjective quality of the reconstructed data for a certain class of pictorial data, and the resulting system performance demonstrated. Some interesting relationships between mean square error and subjective picture quality are presented.

Tasto, M.↗
DOE OSTI2024

Short-period post-common envelope binaries with Balmer emission from SDSS and LAMOST based on ZTF photometric data

ABSTRACT We present here 55 short-period post-common envelope binaries (PCEBs) containing a hot white dwarf (WD) and a low-mass main sequence (MS). Based on the photometric data from Zwicky Transient Facility survey data Release 19 (ZTF DR19), the light curves are analysed for about 200 WDMS binaries with emission line(s) identified from the Sloan Digital Sky Survey (SDSS) or the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) spectra, in which 55 WDMS binaries are found to exhibit variability in their luminosities with a short period and are thus short-period binaries (i.e. PCEBs). In addition, it is found that the orbital periods of these PCEBs locate in a range from 2.2643 to 81.1526 h. However, only six short-period PCEBs are newly discovered and the orbital periods of 19 PCEBs are improved in this work. Meanwhile, it is found that three objects are newly discovered eclipsing PCEBs, and a object (i.e. SDSS J1541) might be the short-period PCEB with a late M-type star or a brown dwarf companion based on the analysis of its spectral energy distribution. At last, the mechanism(s) being responsible for the emission features in the spectra of these PCEBs are discussed, the emission features arising in their optical spectra might be caused by the stellar activity or an irradiated component owing to a hot WD companion because most of them contain a WD with an effective temperature higher than $\sim$10 000 K.

Li, Lifang↗
NASA NTRS1992

A knowledge based system for scientific data visualization

A knowledge-based system, called visualization tool assistant (VISTA), which was developed to assist scientists in the design of scientific data visualization techniques, is described. The system derives its knowledge from several sources which provide information about data characteristics, visualization primitives, and effective visual perception. The design methodology employed by the system is based on a sequence of transformations which decomposes a data set into a set of data partitions, maps this set of partitions to visualization primitives, and combines these primitives into a composite visualization technique design. Although the primary function of the system is to generate an effective visualization technique design for a given data set by using principles of visual perception the system also allows users to interactively modify the design, and renders the resulting image using a variety of rendering algorithms. The current version of the system primarily supports visualization techniques having applicability in earth and space sciences, although it may easily be extended to include other techniques useful in other disciplines such as computational fluid dynamics, finite-element analysis and medical imaging.

Senay, Hikmet↗
DOE OSTI2026

Integration of ultra-low coverage whole-genome sequences for reconstructing the evolutionary history of Galapagos giant tortoises

Genomic data from contemporary and historical samples often need to be coupled for evolutionary reconstructions of multitaxon complexes. However, the genetic data recovered from historical samples may result only in ultra-low coverage whole-genome sequences (ulcWGS; <0.15× depth), leading to inaccurate evolutionary inferences given a preponderance of missing data. Using the Galapagos giant tortoise radiation as a study system (Chelonoidis spp., composed of 13 extant and four extinct lineages), we assembled a novel methodological pipeline that removes potential noise introduced by the missing data and enhances the evolutionary signal from ulcWGS samples. We leveraged existing tools for phylogenomic placement (EPA-ng), population genomic structure (smartsnp) and admixture (Admixfrog, NGSadmix) to demonstrate that the evolutionary history of samples can be uncovered with sequencing depths as low as 0.008–0.139×. Importantly, these approaches do not use genotype imputation of the ulcWGS samples, which would require extensive reference datasets. Our application to two cases of extinct lineages of Galapagos giant tortoises, with and without references from the same lineage, demonstrates the general value of the approach. We confirm where the extinct lineages from San Cristóbal and Santa Fe islands fit into the Galapagos giant tortoise radiation, and that these lineages were evolutionarily distinct entities.

ancient DNA↗
DOE OSTI2026

Untargeted, tandem mass spectrometry (LC/MS-MS) metaproteomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization. This package contains soil metaproteomics data in the context of site specific metagenomes from soil depth profiles in three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. These metaproteomes were collected in 2018 after 4.5 years of warming from five depth intervals (0-10 cm, 10-30 cm, 30-45 cm, 45-60 cm, 60-80 cm). For protein identification, the collected spectra were searched following a target-decoy search strategy against a database of metagenome predicted proteins (covering 96 samples from 2014 to 2021) representing the complete sequence diversity at the site. Data was searched with mass spectrometry database search tool (MS-GF+) using Pacific Northwest National Laboratory (PNNL)'s Data Management System (DMS) Processing pipeline. The metagenomes are published as part of another data package. Raw metaproteomic data and the data products from MS-GF+ are deposited in the Mass Spectrometry Interactive Virtual Environment (MassIVE) database under accession no. MSV000097826. Here we present a dataset that includes spectral counts for the detected proteins across samples (EMSL50964_BrodieAllMAGs_Globals_SC.txt), the sequences of the detected proteins, and sample metadata file that contains site information for the soil metaproteome samples.

Belowground Biogeochemistry Science Focus Area↗
NASA NTRS1975

Acquisition and description of Mariner 10 television science data at Mercury

The Mariner 10 television science subsystem was an improved version of the Mariner 9 system, using 1500-mm-focal-length optics. An elaborate picture-taking sequence resulted in transmission of over 4000 frames back to earth during two flyby encounters with Mercury. These sequences utilized a real-time data rate of 117.6 kbit/s, resulting in coverage of about 75% of the lighted portion of Mercury's surface at a resolution of better than 2 km. The complete set of useful images, which amounted to about 3000 frames, was processed with three different types of digital image-processing enhancements.

Danielson, G. E., Jr.↗
NASA NTRS1990

Fabry-Perot observations of comet Austin

Preliminary results of a program to observe Comet Austin (1990c1) from 16 April to 4 May and from 11 May to 27 May 1990 using the West Auxiliary of the McMath Solar Telescope on Kitt Peak, Arizona were presetned. The observations were made with a 15 cm duel-etalon Fabry-Perot scanning and imaging spectrometer with two modes of operation: a high resolution mode with a velocity resolution of 1.2 km/s and a medium resolution mode with a velocity resolution 10 km/s. Scanning data was obtained with an RCA C31034A photomultiplier tube and imaging data was obtained with a Photometrics LN2 cooled CCD camera with a 516 by 516 Ford chip. The results include: (1) information on the coma outflow velocity from high resolution spectral profiles of (OI)6300 and NH2 emissions, (2) gaseous water production rates from medium resolution observation of (OI)6300, (3) spectra of H2O(+) emissions in order to study the ionized component of the coma, (4) spatial distribution of H2O(+) emission features from sequences of velocity resolved images (data cubes), and (5) spatial distribution of (OI)6300 and NH2 emissions from medium resolution images. The field of view on the sky was 10.5 arcminutes in diameter. In the imaging mode the CCD was binned 4 by 4 resulting in 7.6 sec power pixel and a subarray readout for a field of view of 10.5 min.

Schultz, David↗
NASA NTRS1976

Improved data display for milling machine

Axis position and sequence number indicator system is designed to work in conjunction with numerical tape controller. Visual display of coordinate-axis position to nearest 0.0001 inch and sequential blocks of input data up to maximum of 999 are provided.

Surrency, W. M.↗