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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Utah FORGE: Fiber Optic Cumulative Strain Change and Strain Change Rate Data From Well 16A Stimulation at Well 16B

This dataset includes Rayleigh Frequency Shift (RFS) Distributed Strain Sensing (DSS) cumulative strain change and change rate data. The data was acquired during the stimulation of Utah FORGE Well 16A(78)-32 in April 2024 via fiber installed in Well 16B(78)-32. The fiber optic data was acquired using Neubrex SR7000 RFS DSS Distributed Strain sensing instruments and is saved here in the format of HDF5 files (.h5 extension). The spatial sampling on the full wellbore profiles is 0.20 centimeters. The data is the far field strain change response from a baseline profile made down the 16B well on April 3, 2024, so each strain value represents the strain change or strain change rate at each depth relative to the baseline reference profile. The data arrays for each type share the same dimensions (number of channels and time stamps).

15 GEOTHERMAL ENERGY↗

NASA NTRS1987

Flight experience of solar mesosphere explorer's power system over high temperatures ranges

The performance of the power system on the Solar Mesosphere Explorer (SME) satellite for the life of the mission and the techniques used to ensure power system health are summarized. Early in the mission high cell imbalances in one of the batteries resulted in a loading scheme which attempted to minimize the cell imbalances without causing an undervoltage condition. A short term model of the power system allowed planners to predict depth of discharge using the latest available data. Due to expected orbital shifts the solar arrays experience extended periods of no eclipse. This has required special conditioning schemes to keep the batteries healthy when the eclipses return. Analysis of the SME data indicates long term health of the SME power system as long as the conditioning scheme is continued.

Faber, Jack↗

NASA NTRS1994

Object recognition and pose estimation of planar objects from range data

The Extravehicular Activity Helper/Retriever (EVAHR) is a robotic device currently under development at the NASA Johnson Space Center that is designed to fetch objects or to assist in retrieving an astronaut who may have become inadvertently de-tethered. The EVAHR will be required to exhibit a high degree of intelligent autonomous operation and will base much of its reasoning upon information obtained from one or more three-dimensional sensors that it will carry and control. At the highest level of visual cognition and reasoning, the EVAHR will be required to detect objects, recognize them, and estimate their spatial orientation and location. The recognition phase and estimation of spatial pose will depend on the ability of the vision system to reliably extract geometric features of the objects such as whether the surface topologies observed are planar or curved and the spatial relationships between the component surfaces. In order to achieve these tasks, three-dimensional sensing of the operational environment and objects in the environment will therefore be essential. One of the sensors being considered to provide image data for object recognition and pose estimation is a phase-shift laser scanner. The characteristics of the data provided by this scanner have been studied and algorithms have been developed for segmenting range images into planar surfaces, extracting basic features such as surface area, and recognizing the object based on the characteristics of extracted features. Also, an approach has been developed for estimating the spatial orientation and location of the recognized object based on orientations of extracted planes and their intersection points. This paper presents some of the algorithms that have been developed for the purpose of recognizing and estimating the pose of objects as viewed by the laser scanner, and characterizes the desirability and utility of these algorithms within the context of the scanner itself, considering data quality and noise.

Pendleton, Thomas W.↗

DOE OSTI2024

Understanding electric vehicle ownership using data fusion and spatial modeling

The global shift toward electric vehicles (EVs) for climate sustainability lacks comprehensive insights into the impact of the built environment on EV ownership, especially in varying spatial contexts. This study, focusing on New York State, integrates data fusion techniques across diverse datasets to examine the influence of socioeconomic and built environmental factors on EV ownership. The utilization of spatial regression models reveals consistent coefficient values, highlighting the robustness of the results, with the Spatial Lag model better at capturing spatial autocorrelation. Further, results underscore the significance of charging stations within a 10-mile radius, indicative of a preference for convenient charging options influencing EV ownership decisions. Factors like higher education levels, lower rental populations, and concentrations of older population align with increased EV ownership. Utilizing publicly available data offers a more accessible avenue for understanding EV ownership across regions, complementing traditional survey approaches.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1999

Self-organizing map (SOM) of space acceleration measurement system (SAMS) data

In this paper, space acceleration measurement system (SAMS) data have been classified using self-organizing map (SOM) networks without any supervision; i.e., no a priori knowledge is assumed regarding input patterns belonging to a certain class. Input patterns are created on the basis of power spectral densities of SAMS data. Results for SAMS data from STS-50 and STS-57 missions are presented. Following issues are discussed in details: impact of number of neurons, global ordering of SOM weight vectors, effectiveness of a SOM in data classification, and effects of shifting time windows in the generation of input patterns. The concept of 'cascade of SOM networks' is also developed and tested. It has been found that a SOM network can successfully classify SAMS data obtained during STS-50 and STS-57 missions.

STS-57 Shuttle Project↗

NASA NTRS1979

Data reformatting with less hardware

Dual-function integrated circuits use one shift register array instead of two to feed video data to seven tape channels thereby making system more reliable and less expensive than predecessor. Basic principle of reformatter is also applicable to multiplexing and frequency conversion circuits.

Engel, A.↗

NASA NTRS1975

Zero-G experiments in two-phase fluids flow regimes

The two-phase flows studied were liquid and gas mixtures in a straight flow channel of circular cross-section. Boundaries between flow regimes have been defined for normogravity on coordinates of gas quality and total mass velocity; and, when combined with boundary expressions having a Froude number term, an analytical model was derived predicting boundary shifts with changes in gravity level. Experiments with air and water were performed, first in the normogravity environment of a ground laboratory and then in 'zero gravity' aboard a KC-135 aircraft flying parabolic trajectories. Data reduction confirmed regime boundary shifts in the direction predicted, although the magnitude was a little less than predicted. Pressure drop measurements showed significant increases for the low gravity condition.

Heppner, D. B.↗

NASA NTRS1993

X-ray spectra of 12 distant clusters of galaxies

An X-ray spectral analysis of 12 distant clusters of galaxies observed on-axis with the Einstein Observatory imaging proportional counter is presented. Statistically, X-ray spectral data of the highest red shift clusters in the sample are inconsistent with an optically thin plasma emission model plus absorptions only in the Milky Way. Inclusions of excess absorptions in the clusters significantly improve the spectral fits to the data, indicating the possible presence of large amounts of X-ray absorbing cool gas in some of the distant clusters. By using X-ray luminosities determined from observed fluxes only in the 0.8-3.5 keV band and the temperature-to-luminosity correlation for nearby clusters, the estimated temperatures of the hot intracluster medium in these distant clusters constrain the absorption columns in the clusters. The data also show possible positive temperature evolution of the hot ICM with time which, if present, would further increase the absorptions required in fitting the spectra.

Wang, Qingde↗

DOE OSTI2023

Time-temperature-stress superposition of PBX 9502 compressive creep data for lifetime predictions

The plastic-bonded explosive (PBX) 9502 is a viscoelastic, high-solids loaded polymer bound composite comprised of 95 weight% (wt%) TATB explosive crystals and 5 wt% FK-800 polymer binder. The uniaxial quasi-static mechanical properties have been studied and characterized extensively over 25+ years, including creep. Creep is the strain evolution over time as a result of an asymmetric load typically at temperatures above ambient. Creep measurements to failure can take excessively long periods of time depending on various factors including applied stress, temperature, and loading rate that render a single test to failure impossible. Using the principles of time-temperature-stress superposition (TTSSP), short-term creep tests at various applied stresses and temperatures can be used for long-term creep predictions. The TTSSP model shifts short-term test data using two factors, one for temperature and stress, creating a master curve at a reference test condition. The master curve can be shifted to predict the creep response at any desired test condition. PBX 9502 compression specimens were tested at three temperatures and various applied stresses. This work discusses the TTSSP analysis of PBX 9502 compressive creep data to create a single comprehensive master curve.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Time-Temperature-Stress Superposition of PBX 9502 Compressive Creep Data for Lifetime Predictions

36 MATERIALS SCIENCE↗

NASA NTRS1993

Water Surface Currents, Short Gravity-Capillary Waves and Radar Backscatter

Despite their importance for air-sea interaction and microwave remote sensing of the ocean surface, intrinsic properties of short gravity-capillary waves are not well established. This is largely due to water surface currents and their effects on the direct measurements of wave parameters conducted at a fixed point. Frequencies of small scale waves propagating on a surface which itself is in motion, are subject to Doppler shifts. Hence, the high frequency tail of the wave spectra obtained from such temporal observations is smeared. Conversion of this smeared measured-frequency spectra to intrinsic-frequency (or wavenumber) spectra requires corrections for the Doppler shifts. Such attempts in the past have not been very successful in particular when field data were used. This becomes evident if the amplitude modulation of short waves by underlying long waves is considered. Microwave radar studies show that the amplitude of a short wave component attains its maximum value near the crests and its minimum in the troughs of the long waves. Doppler-shifted wave data yield similar results but much larger in modulation magnitude, as expected. In general, Doppler shift corrections reduce the modulation magnitude. Overcorrection may result in a negligible modulation or even in a strong modulation with the maximum amplitude in the wave troughs. The latter situation is clearly contradictory to our visual observations as well as the radar results and imply that the advection by currents is overestimated. In this study, a differential-advection approach is used in which small scale waves are advected by the currents evaluated not at the free surface, but at a depth proportional to their wavelengths. Applicability of this approach is verified by the excellent agreement in phase and magnitude of short-wave modulation between results based on radar and on wave-gauge measurements conducted on a lake.

Atakturk, Serhad S.↗

DOE OSTI2025

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗

NASA NTRS1985

Signal Processor for Multirate PSK Signals

Any of six different data formats at any of five different data rates from phase-shift-key (PSK) modulated input signal extracted by digital radio receiver. Subcarrier Demodulator is Costas loop with hard limiter in inphase arm. There are six low-pass filters, each selectable for rate and format of data to be processed.

Helgesen, R. J.↗

DOE OSTI2021

Preventing Failures By Dataset Shift Detection in Safety-Critical Graph Applications

Dataset shift refers to the problem where the input data distribution may change over time (e.g., between training and test stages). Since this can be a critical bottleneck in several safety-critical applications such as healthcare, drug-discovery, etc., dataset shift detection has become an important research issue in machine learning. Though several existing efforts have focused on image/video data, applications with graph-structured data have not received sufficient attention. Therefore, in this paper, we investigate the problem of detecting shifts in graph structured data through the lens of statistical hypothesis testing. Specifically, we propose a practical two-sample test based approach for shift detection in large-scale graph structured data. Our approach is very flexible in that it is suitable for both undirected and directed graphs, and eliminates the need for equal sample sizes. Using empirical studies, we demonstrate the effectiveness of the proposed test in detecting dataset shifts. We also corroborate these findings using real-world datasets, characterized by directed graphs and a large number of nodes.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1963

Analysis of proton-alpha scattering

Phase shift values from polarization and elastic scattering data analysis

DATA ANALYSIS↗

DOE OSTI2021

Determination of oxidation rates and volatile oxidation products for HTGR graphite matrix material exposed to steam atmospheres

High-temperature gas-cooled reactors (HTGRs) in operation use tristructural isotropic (TRISO) particles embedded in graphite and carbonized resin matrix to form the fuel element. This graphite matrix material serves as a supportive structural element, heat transfer medium, and neutron moderator. In HTGR designs, fuel compacts are exposed to helium coolant, which facilitates high outlet temperatures (750°C 2 O, 800°C 2 , and H 2 , are quantified in varied oxidant atmospheres using a coupled thermogravimetric analyzer and mass spectrometer. Furthermore, oxidation rates reported here for varied steam (H 2 O [g]) atmospheres are predominantly linear and comparable with literature values in the range of tested temperatures (800–1200°C). Changes in dominant matrix oxidation products from primarily CO to a mixture of CO, CO 2 , and H 2 were observed at higher temperatures (≥1000°C) and steam atmospheres (≥5 kPa pH 2 O). Kinetic data indicates that there was no shift in oxidation regime with chemical oxidation occurring at all temperatures and H2O (g) atmospheres tested. These data provide insight into the oxidation behavior of graphite matrix material and will inform future testing conditions, notably mixed atmospheric conditions, of HTGR fuel elements.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Real-time Multi-granular Analytics Framework for HIT Systems

Streaming analytics is the process of ingesting and digesting live data from multiple data sources. In the healthcare domain, as the importance of extracting immediate insights while data are streaming into the system grows, the focus is shifting from batch processing to streaming analytics. With data increasing dramatically at high speeds, many informatics designs have been proposed to adapt healthcare domain into this new environment. In our previous work, we introduced a prototype of health informatics technology (HIT) framework that aims to address challenges in adopting state-of-the-art technologies to enable advanced healthcare analytic tasks in new streaming environments. We recently made major updates to the framework so that anomaly from multiple streaming data sources at different granularity levels can be detected in near real-time. In this paper, we detail the implementation and deployment of the framework in Kubernetes clusters and report its performances when tested on electronic health record (EHR) data of Veterans Affairs.

Park, Byung↗

NASA NTRS1990

Stress Dependence of Ultrasonic Velocity in Unidirectional Graphite/Epoxy Composites for Longitudinal Waves Propagating Along the Direction of Stress

The first measurements of the stress induced velocity changes for propagation directions along the direction of applied stress in gr/ep composites have been presented. For propagation and stress direction perpendicular to the fiber direction, the data demonstrated a linear relation between normalized velocity shift and stress. After corrections for the delay line were made, the slope or SAC was determined and compared favorably with the expected value calculated from the previously determined nonlinear coefficients of this material. The ratio of the SAC to the elastic compliance for this direction of loading was evaluated and found to have a value similar to numerous other materials which have very different linear elastic properties. Measurements with stress and propagation along the fibers yielded unusual behavior. The curves were very nonlinear and even shifted direction at higher loads. The large scatter in the data due to bond variations made separation of material effects from bond induced artifacts impossible. Thus the SAC, R, and the remaining two unknown TOEC's could not be determined for this direction of propagation. These measurements further expand the basis of determining nonlinear elastic properties of composite materials. These properties may be useful in developing much needed NDE techniques to determine such important parameters as residual stress after cure and residual strength after impact damage. Additional study is needed to measure the nonlinear behavior in other composite materials including angle ply laminates. Also, other techniques to measure elastic nonlinearity such as harmonic generation should be applied to composites to improve the understanding of these properties and their importance.

Prosser, William H.↗