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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

THE NUCLEAR ACTIVITIES OF NEARBY S0 GALAXIES

We present a study of nuclear activities in nearby S0 galaxies. After cross-matching the Sloan Digital Sky Survey Data Release 7 with the Third Reference Catalog of Bright Galaxies (RC3) and visually checking the SDSS images, we derive a sample of 583 S0 galaxies with the central spectrophotometric information. In order to separate nebular emission lines from the underlying stellar contribution, we fit the stellar population model to the SDSS spectra of these S0 galaxies. According to the BPT diagram, we find that 8% of S0 galaxies show central star-forming activity, while the fractions of Seyfert, Composite, and low-ionization nuclear emission-line regions (LINERs) are 2%, 8%, and 21.4%, respectively. We also find that star-forming S0s have the lowest stellar masses, over one magnitude lower than the others, and that the active S0s are mainly located in the sparse environment, while the normal S0s are located in the dense environment, which might suggest that the environment plays an important role in quenching star formation and/or AGN activity in S0 galaxies. By performing bulge-disk decomposition of 45 star-forming S0s in g - and r -bands with the 2D fitting software Galfit, as well as exploiting the catalog of 2D photometric decompositions of Meert et al., we find that the bulges of approximately one-third of star-forming S0 galaxies (16/45) are bluer than their disks, while for other types of S0s the bulge and disk components show similar color distributions. Besides, the Sérsic index of most star-forming S0s bulges is less than two, while for normal S0s, it is between two and six.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

BSEC flux towers: CSAT3B and TRH

The data were collected as part of the BSEC project, during the period from June 2025 to May 2026. Directory "broadway" contains data collected on a multi-level flux tower (US-BWf) in the Broadway East neighborhood (1808 North Patterson Park Ave., Baltimore City, MD 21213; LAT: 39o18'40.31'' N; LONG: 76o35'12.43'' W). At each of the four measurement heights (8.5 m, 11.1 m, 13.4 m, 15.9 m), a Campbell Scientific CSAT3B sonic anemometer was operated at 50 Hz to measure virtual temperature (tc) and three velocity components (u: 270 degrees; v: 180 degrees; w: vertical), and a RM Young temperature sensor (model 41382VC) was operated at 1 Hz inside a compact aspirated radiation shield (model 43502) to measure absolute temperature (T) and relative humidity (RH). Inside directory "broadway", directory "netcdf" contains data collected each day in 5-minute chunks that have been converted to NetCDF format (before quality checking), while "4hr" contains data arranged into 4-hour chunks (also in NetCDF format) that have been through basic quality checking steps (treating data points with nonzero diagnostic codes as missing data; fixing six or fewer consecutive missing data points using linear interpolation). Users are recommended to start with data in directory "4hr", while data in directory "netcdf" can be used for reference purposes.

Baltimore↗
NASA NTRS1987

The KATE shell: An implementation of model-based control, monitor and diagnosis

The conventional control and monitor software currently used by the Space Center for Space Shuttle processing has many limitations such as high maintenance costs, limited diagnostic capabilities and simulation support. These limitations have caused the development of a knowledge based (or model based) shell to generically control and monitor electro-mechanical systems. The knowledge base describes the system's structure and function and is used by a software shell to do real time constraints checking, low level control of components, diagnosis of detected faults, sensor validation, automatic generation of schematic diagrams and automatic recovery from failures. This approach is more versatile and more powerful than the conventional hard coded approach and offers many advantages over it, although, for systems which require high speed reaction times or aren't well understood, knowledge based control and monitor systems may not be appropriate.

Cornell, Matthew↗
NASA NTRS1991

Assessing damping uncertainty in space structures with fuzzy sets

NASA has been interested in the development of methods for evaluating the predictive accuracy of structural dynamic models. This interest stems from the use of mathematical models in evaluating the structural integrity of all spacecraft prior to flight. Space structures are often too large and too weak to be tested fully assembled in a ground test lab. The predictive accuracy of a model depends on the nature and extent of its experimental verification. The further the test conditions depart from in-service conditions, the less accurate the model will be. Structural damping is known to be one source of uncertainty in models. The uncertainty in damping is explored in order to evaluate the accuracy of dynamic models. A simple mass-spring-dashpot system is used to illustrate a comparison among three methods for propagating uncertainty in structural dynamics models: the First Order Method, the Numerical Simulation Method, and the Fuzzy Set Method. The Fuzzy Set Method is shown to bound the range of possible responses and thus to provide a valuable limiting check on the First Order Method near resonant conditions. Fuzzy Methods are a relative inexpensive alternative to numerical simulation.

Ross, Timothy J.↗
DOE OSTI2024

Towards in-situ certification of additively manufactured parts: the vital roles of physics-based and data-driven models

Certifying additively manufactured (AM) parts in-situ at the completion of a build is an enticing prospect, as it can help reduce the high costs associated with post-build testing and evaluation. However, achieving this goal presents significant challenges that may keep it aspirational for the foreseeable future. Nonetheless, incremental progress can pave the way forward. A critical aspect of in-situ certification involves continuous quality checking due to the random nature of the AM process and the difficulties in detecting defects or anomalies once layers are built over. While real-time in-situ monitoring strategies assisted by machine learning (ML) play a pivotal role in auditing part quality, they must ideally be supported by real-time (or near real-time) adaptive process control enabled by ML-assisted decision-making. By analyzing in-situ monitoring data in real-time (or near real- time) to dynamically adjust manufacturing parameters, such intervention can ensure AM parts are built to meet stringent certification standards. This can be achieved virtually by using high-fidelity performance models for the physical testing and evaluation tasks. In this short editorial, we discuss the key contributions made by data-driven and physics-based models in providing intelligence to the monitoring and process control tasks underpinning in-situ certification and in the simulation of the build’s performance under test and service conditions. While our focus lies in metal AM, the concepts discussed here are also relevant to other AM processes.

: In-situ monitoring↗
NASA NTRS2005

Matlab GUI for a Fluid Mixer

The Test and Engineering Directorate at NASA John C. Stennis Space Center developed an interest to study the modeling, evaluation, and control of a liquid hydrogen (LH2) and gas hydrogen (GH2) mixer subsystem of a ground test facility. This facility carries out comprehensive ground-based testing and certification of liquid rocket engines including the Space Shuttle Main engine. A software simulation environment developed in MATLAB/SIMULINK (M/S) will allow NASA engineers to test rocket engine systems at relatively no cost. In the progress report submitted in February 2004, we described the development of two foundation programs, a reverse look-up application using various interpolation algorithms, a variety of search and return methods, and self-checking methods to reduce the error in returned search results to increase the functionality of the program. The results showed that these efforts were successful. To transfer this technology to engineers who are not familiar with the M/S environment, a four-module GUI was implemented allowing the user to evaluate the mixer model under open-loop and closed-loop conditions. The progress report was based on an udergraduate Honors Thesis by Ms. Jamie Granger Austin in the Department of Electrical Engineering and Computer Science at Tulane University, during January-May 2003, and her continued efforts during August-December 2003. In collaboration with Dr. Hanz Richter and Dr. Fernando Figueroa we published these results in a NASA Tech Brief due to appear this year. Although the original proposal in 2003 did not address other components of the test facility, we decided in the last few months to extend our research and consider a related pressurization tank component as well. This report summarizes the results obtained towards a Graphical User Interface (GUI) for the evaluation and control of the hydrogen mixer subsystem model and for the pressurization tank each taken individually. Further research would combine the two components - mixer and tank, for a more realistic simulation tool.

Barbieri, Enrique↗
DOE OSTI2023

Soft syndrome iterative decoding of quantum LDPC codes and hardware architectures

In practical quantum error correction implementations, the measurement of syndrome information is an unreliable step—typically modeled as a binary measurement outcome flipped with some probability. However, the measured syndrome is in fact a discretized value of the continuous voltage or current values obtained in the physical implementation of the syndrome extraction. In this paper, we use this “soft” or analog information to benefit iterative decoders for decoding quantum low-density parity-check (QLDPC) codes. Syndrome-based iterative belief propagation decoders are modified to utilize the soft syndrome to correct both data and syndrome errors simultaneously. We demonstrate the advantages of the proposed scheme not only in terms of comparison of thresholds and logical error rates for quasi-cyclic lifted-product QLDPC code families but also with faster convergence of iterative decoders. Additionally, we derive hardware (FPGA) architectures of these soft syndrome decoders and obtain similar performance in terms of error correction to the ideal models even with reduced precision in the soft information. The total latency of the hardware architectures is about 600 ns (for the QLDPC codes considered) in a 20 nm CMOS process FPGA device, and the area overhead is almost constant—less than 50% compared to min-sum decoders with noisy syndromes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Sequence modeling of higher-order wave modes of quasi-circular, spinning, non-precessing binary black hole mergers

Higher-order gravitational wave modes from quasi-circular, spinning, non-precessing binary-black-hole (BBH) mergers encode rich information about the nonlinear dynamics of strong-field gravity. We present a transformer-based sequence-completion surrogate that, given an early-inspiral segment, forecasts the subsequent late inspiral, merger, and ringdown. The intended applications are (i) patching or completing expensive or interrupted numerical-relativity (NR) simulations and (ii) providing late-time cross-checks and rapid hybridization studies. The training set is built from the NRHybSur3dq8 surrogate, which provides spherical-harmonic modes up to $\ell$ ≤ 4 (excluding (4, 0) and (4,±1), and including (5, 5)) for mass ratios q ≤ 8, dimensionless spin components s$^{z}_{1,2}$ ϵ[–0.8, 0.8], and inclination angles θ ϵ [0, π]. Waveforms are supplied on the interval t ϵ [–5000M, –100 M) and the model autoregressively generates the plus and cross polarizations (h + , h x ) on t ϵ [–100 M, 130M]. Training on the Delta supercomputer with 16 NVIDIA A100 GPUs required ~15 h on more than 14 million hybrid waveforms. Evaluation on a held-out test set of 840,000 samples yields mean and median overlaps of 0.996 and 0.997, respectively, with respect to the surrogate ground truth.

black-hole merger↗
DOE OSTI2018

OSIRIS-REx, bringing back a bit of an asteroid

The OSIRIS-REx mission will provide invaluable ground-truth validation for the computer models in a case study that set out to determine the timeframe within which we must launch either a kinetic impactor or a nuclear explosive carrier and develop a conceptual design for that spacecraft. From the on-asteroid data gathered when the spacecraft touches down and, eventually, from hands-on research here on Earth, we will get a reality check for what we think we know about Bennu’s material composition (boulders, chunks, and dust), shape, mass, density, and so on. Gravimetric data could reveal whether the asteroid is hollow. Back on Earth, researchers will run various tests on the material. We may have enough information to develop a theoretical equation of state. We could then compare it to its closest match in SESAME, the Los Alamos database of equations of state. Armed with that data, we will rerun the models to see how much each scenario changes. Comparing data from the touchdown and sample return to the earlier, remotely observed data from Bennu will help us calibrate remote observations of other objects in the future. Then we can more precisely model the effects of our deflection and disruption strategies and refine the spacecraft design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

GRUMDN: A Multi-Task Model for Predicting Human Patterns-of-Life from Stay Transition Data

Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.

Gunaratne, Chathika [ORNL] (ORCID:0000000225088745↗
DOE OSTI2023

Generating Co-expression Networks for Three Cyanobacteria: Synechococcus sp. PCC 7942, Synechococcus sp. PCC 7002, Synechocystis sp. PCC 6803

Cyanobacteria are photosynthetic organisms capable of high growth rate and represent a promising bioplatform for harnessing the sun’s energy to make biofuel. Additionally, the process of photosynthesis absorbs CO2 from the environment. Understanding the metabolic processes involved in photosynthesis could lead to solutions to the recent rise of CO2 concentration in Earth’s atmosphere and the associated climate change. More research on the transcriptional regulation of these cells is needed to learn how to harness the untapped potential of cyanobacteria for these applications. Transcriptional analysis via RNA-seq provides an understanding of how gene expression changes at the mRNA level under diverse growing conditions. I systematically collected and analyzed RNA-Seq data obtained under a variety of conditions and available on the NCBI database for three cyanobacteria model organisms: Synechococcus elongatus sp. PCC 7942, Synechococcus sp. PCC 7002, and Synechocystis sp. PCC 6803. For each organism, the data was mapped to a reference genome to characterize the RNA expression profile. Samples were checked for quality based on the number of reads and the correlation of the expression profile between labeled replicates. All samples were transformed into transcripts per million reads, followed by a log transformation to account for the wide range of sample sizes. Gene co-expression networks were generated and analyzed for each species using Cytoscape. These networks provide a base level of gene expression for each species. The network topology and high-betweeness nodes of these networks need to be analyzed further to provide insight on potential ways to harness cyanobacteria genetics. Additionally, these datasets can be used together to form a core genome network analysis- one that includes only the genes that are homologous between the three species. This project has prepared the way for a more in-depth study on photosynthetic microbes on a genetic level.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

Aerospace Ground Equipment for model 4080 sequence programmer. A standard computer terminal is adapted to provide convenient operator to device interface

The Aerospace Ground Equipment (AGE) provides an interface between a human operator and a complete spaceborne sequence timing device with a memory storage program. The AGE provides a means for composing, editing, syntax checking, and storing timing device programs. The AGE is implemented with a standard Hewlett-Packard 2649A terminal system and a minimum of special hardware. The terminal's dual tape interface is used to store timing device programs and to read in special AGE operating system software. To compose a new program for the timing device the keyboard is used to fill in a form displayed on the screen.

Nissley, L. E.↗
NASA NTRS1980

Magnetic Field Satellite (Magsat) data processing system specifications

The software specifications for the MAGSAT data processing system (MDPS) are presented. The MDPS is divided functionally into preprocessing of primary input data, data management, chronicle processing, and postprocessing. Data organization and validity, and checks of spacecraft and instrumentation are dicussed. Output products of the MDPS, including various plots and data tapes, are described. Formats for important tapes are presented. Dicussions and mathematical formulations for coordinate transformations and field model coefficients are included.

Berman, D.↗
NASA NTRS1987

Evaluating cockpit resource management training

The determinants of effective or ineffective cockpit resurce management and the difficulties these multiple factors pose for validation of the effectiveness of cockpit resource management (CRM) training are discussed. A model of an evaluation design that may be applied to this type of training is presented. Concept validation is discussed as well as criteria for judging crew proficiency. Attention is given to accidents and proficiency checks, incidents and repeated maneuvers, attitude measuremet, and self-report evauation of training.

Helmreich, Robert L.↗
NASA NTRS1990

Aerodynamic parameters of High-Angle-of attack Research Vehicle (HARV) estimated from flight data

Aerodynamic parameters of the High-Angle-of-Attack Research Aircraft (HARV) were estimated from flight data at different values of the angle of attack between 10 degrees and 50 degrees. The main part of the data was obtained from small amplitude longitudinal and lateral maneuvers. A small number of large amplitude maneuvers was also used in the estimation. The measured data were first checked for their compatibility. It was found that the accuracy of air data was degraded by unexplained bias errors. Then, the data were analyzed by a stepwise regression method for obtaining a structure of aerodynamic model equations and least squares parameter estimates. Because of high data collinearity in several maneuvers, some of the longitudinal and all lateral maneuvers were reanalyzed by using two biased estimation techniques, the principal components regression and mixed estimation. The estimated parameters in the form of stability and control derivatives, and aerodynamic coefficients were plotted against the angle of attack and compared with the wind tunnel measurements. The influential parameters are, in general, estimated with acceptable accuracy and most of them are in agreement with wind tunnel results. The simulated responses of the aircraft showed good prediction capabilities of the resulting model.

Klein, Vladislav↗