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At least 757 records · Page 42

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NASA NTRS1997

Improvements for Image Compression Using Adaptive Principal Component Extraction (APEX)

The issues of image compression and pattern classification have been a primary focus of researchers among a variety of fields including signal and image processing, pattern recognition, data classification, etc. These issues depend on finding an efficient representation of the source data. In this paper we collate our earlier results where we introduced the application of the. Hilbe.rt scan to a principal component algorithm (PCA) with Adaptive Principal Component Extraction (APEX) neural network model. We apply these technique to medical imaging, particularly image representation and compression. We apply the Hilbert scan to the APEX algorithm to improve results

Ziyad, Nigel A.↗

NASA NTRS2005

Apparatus Characterizes Transient Voltages in Real Time

The figure shows a prototype of a relatively inexpensive electronic monitoring apparatus that measures and records selected parameters of lightning-induced transient voltages on communication and power cables. The selected parameters, listed below, are those most relevant to the ability of lightning-induced transients to damage electronic equipment. This apparatus bridges a gap between some traditional transient-voltage recorders that record complete waveforms and other traditional transient-voltage recorders that record only peak values: By recording the most relevant parameters and only those parameters this apparatus yields more useful information than does a traditional peak-value (only) recorder while imposing much smaller data-storage and data-transmission burdens than does a traditional complete-waveform recorder. Also, relative to a complete-waveform recorder, this apparatus is more reliable and can be built at lower cost because it contains fewer electronic components. The transients generated by sources other than lightning tend to have frequency components well below 1 MHz. Most commercial transient recorders can detect and record such transients, but cannot respond rapidly enough for recording lightning-induced transient voltage peaks, which can rise from 10 to 90 percent of maximum amplitude in a fraction of a microsecond. Moreover, commercial transient recorders cannot rearm themselves rapidly enough to respond to the multiple transients that occur within milliseconds of each other on some lightning strikes. One transient recorder, designed for Kennedy Space Center earlier [ Fast Transient-Voltage Recorder (KSC- 11991), NASA Tech Briefs, Vol. 23, No. 10, page 6a (October 1999)], is capable of sampling transient voltages at peak values up to 50 V in four channels at a rate of 20 MHz. That recorder contains a trigger circuit that continuously compares the amplitudes of the signals on four channels to a preset triggering threshold. When a trigger signal is received, a volatile memory is filled with data for a total time of 200 ms. After the data are transferred to nonvolatile memory, the recorder rearms itself within 400 ms to enable recording of subsequent transients. Unfortunately, the recorded data must be retrieved through a serial communication link. Depending on the amount of data recorded, the memory can be filled before retrieval is completed. Although large amounts of data are recorded and retrieved, only a small part of the information (the selected parameters) is usually required. The present transient-voltage recorder provides the required information, without incurring the overhead associated with the recording, storage, and retrieval of complete transient-waveform data. In operation, this apparatus processes transient voltage waveforms in real time to extract and record the selected parameters. An analog-to-digital converter that operates at a speed of as much as 100 mega-samples per second is used to sample a transient waveform. A real-time comparator and peak detector are implemented by use of fast field-programmable gate arrays.

Medelius, Pedro↗

NASA NTRS2021

Observation of Low-Energy Proton Direct Ionization in a 72-Layer 3D NAND Flash Memory

Single-event upsets are observed in a 72-layer 3D NAND flash memory operated in single-level cell mode after low-energy proton (500 keV-1.2 MeV) and heavy ion irradiation. The layer-by-layer error count is analyzed to visualize the stopping of low energy protons within the memory stack, and Monte Carlo simulations are correlated with the experimental data. Direct ionization by low-energy protons is identified by three-dimensional data analysis and the energy dependence of device sensitive cross-section. Heavy ion data is also presented for comparison.

Direct ionization↗

DOE OSTI2023

Machine-Learning Assisted Identification of Battery Life Models

Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.

battery↗

NASA NTRS1997

High-Resolution Temperature-Dependent Photoabsorption Cross Section Measurements of S2, with Application to HST UV Spectra of SL9/Jupiter

The Hubble Space Telescope (HST) UV spectra of Jupiter after the collision of Comet SL9 show predominantly molecular features of S2, CS2, NH3, and H2S in the 1800-3200 A region. The HST observations were made under various phases of impact conditions which gave temperatures higher than 1000 K. It is thus clear that temperature-dependent laboratory cross section data are required in order to determine the molecular abundances in Jupiter's atmosphere after the impact of Comet Shoemaker-Levy 9. The required high-resolution temperature dependent S2 absorption cross sections have not been directly measured in the laboratory. To provide the required data for modelers our objective is to accurately measure the high-resolution (FWHM = 0.003 A) and medium resolution (FWHM - 0.08 A) temperature dependent S2 in the 2450-3200 A region. Using the experimental setup we have obtained absorbtion spectra of S2 under various temperature conditions.

Wu, C. Y. Robert↗

DOE OSTI2024

Interpreting test temperature and loading rate effects on the fracture toughness of polymer-metal interfaces via time–temperature superposition

Here, in this letter, we present interfacial fracture toughness data for a polymer-metal interface where tests were conducted at various test temperatures T and loading rates $\dot{δ}$. An adhesively bonded asymmetric double cantilever beam (ADCB) specimen was utilized to measure toughness. ADCB specimens were created by bonding a thinner, upper adherend to a thicker, lower adherend (both 6061 T6 aluminum) using a thin layer of epoxy adhesive, such that the crack propagated along the interface between the thinner adherend and the epoxy layer. The specimens were tested at T from 25 to 65 °C and $\dot{δ}$ from 0.002 to 0.2 mm/s. The measured interfacial toughness Γ increased as both T and $\dot{δ}$ increased. For an ADCB specimen loaded at a constant $\dot{δ}$, the energy release rate G increases as the crack length a increases. For this reason, we defined rate effects in terms of the rate of change in the energy release rate $\dot{G}$. Although not rigorously correct, a formal application of time–temperature superposition (TTS) analysis to the Γ data provided useful insights on the observed dependencies. In the TTS-shifted data, Γ decreased and then increased for monotonically increasing $\dot{G}$. Thus, the TTS analysis suggests that there is a minimum value of Γ. This minimum value could be used to define a lower bound in Γ when designing critical engineering applications that are subjected to T and $\dot{δ}$ excursions.

36 MATERIALS SCIENCE↗

DOE OSTI2026

An ultra-fast method for generating synthetic down-scattered neutron data for inertial confinement fusion implosions

In inertial confinement fusion experiments at the National Ignition Facility, asymmetries are probed by a variety of neutron diagnostics, including neutron imaging systems, real-time neutron activation diagnostics (RTNADs), and neutron spectrometers. It is often useful to generate synthetic data based on these diagnostics to validate and tune models. However, current methods of doing so using Monte Carlo particle tracing are time-consuming. In this paper, an ultra-fast method is presented for generating synthetic neutron images, RTNAD data, and spectrometry data using line integrals and 3D convolutions. While it does not contain as much physics as particle tracing codes, it is thousands of times faster and produces nearly identical data. This enables analysis techniques that depend on generating large amounts of synthetic data, which will prove very useful for the study of asymmetries going forward.

Deuterium↗

DOE OSTI2020

Cybersecurity impact of the growth of data in sports

As the sporting industry continues to increase dependence on new and often massive data sets, they also risk exposing themselves, as well as the leagues, teams, venues, players, and fans, to risks posed by not protecting the confidentiality and integrity of this data. The industry, especially true for professional sports, demands an ever increasing supply of new forms of data to achieve their goals of enticing new fans; enhancing experience; expanding the fan experience from venues and television to the internet and mobile devices; measuring and evaluating the performance and safety of players; and increasing revenue. New methods have emerged to collect data about a variety of aspects of sports ranging from players to fans to teams to venues. Data collected during sporting events is combined with historical data to also help teams analyze and predict performance. To synthesize these predictive analytical and historical memories, sports teams and organizations mix a variety of computer technologies. System integration tends to focus on ensuring the availability of the data and reliability of the technologies but might introduce risks to the confidentiality (privacy) and integrity of the data. Recognizing the potential risks requires review and evaluation. Much of the data is collected for publicly providing information to the fans, so threats to confidentiality pose fewer risks. The greatest risk is violating the privacy of players, such a private performance test, or using technology to gain a competitive advantage.

Jenkins, Stephanie↗

DOE OSTI2025

YbCuBi ARCS + POWGEN data

This dataset contains temperature-dependent powder diffraction patterns collected at POWGEN, SNS (10K - 520K), and inelastic neutron scattering data collected at ARCS, SNS at corresponding temperatures on YbCuBi powder samples.

36 MATERIALS SCIENCE↗

NASA NTRS1981

Low-power portable geophysical data acquisition system and its use in geomagnetic measurements

A low-power portable data acquisition system presently in use for geomagnetic measurements is described. The system is composed of a data-processing system containing a low-power microprocessor, a 9-track digital tape recorder, and a rechargeable battery pack. The magnetometer is a low-power three axis fluxgate design. Under program control the data processing system keeps track of time of day and date, samples three analog magnetometer outputs at intervals of either 0.4 or 2 s, digitizes the data to 15-bit resolution, and, depending upon relative magnetic activity, decides upon data compression to increase the tape storage capacity. It also monitors and records internal voltages and provides self-checking functions which may be monitored through a visual readout on the control panel. The system is mounted in a rugged, weather-tight carrying case suitable for use outdoors with minimal protection. The system, including magnetometer, uses 1.6-W power and can store 5.7 Mbytes of data.

Medford, L. V.↗

NASA NTRS2004

Development of a Low Data Event Timer for Monitoring an Advancing Crack in Fracture

Monitoring the crack position and velocity in a fracture specimen can be difficult and laborious. In addition, the data storage requirements can be considerable depending upon the testing conditions. A low data event timer was developed to alleviate these problems. The test apparatus was applied to cantilever beams bonded with a structural epoxy and tested under different conditions such as stable to unstable transitions and different temperature extremes. The results indicate that the approach eliminates problems associated with other types of crack measurement and greatly simplifies the measuring process.

Macon, D. J.↗

NASA NTRS2021

Conceptualizing the Impact of Dust Contaminated Infrared Radiances on Data Assimilation for Numerical Weather Prediction

Numerical weather prediction systems depend on Hyperspectral Infrared Sounder (HIS) data, yet the impacts of dust-contaminated HIS radiances on weather forecasts has not been quantified. To determine the impact of dust aerosol on HIS radiance assimilation, we use a modified radiance assimilation system employing a one-dimensional variational assimilation system (1DVAR) developed under the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Numerical Weather Prediction–Satellite Application Facility (NWP-SAF) project, which uses the Radiative Transfer for TOVS (RTTOV). Dust aerosol impacts on analyzed temperature and moisture fields are quantified using synthetic HIS observations from rawinsonde, Micropulse Lidar Network (MPLNET), and Aerosol Robotic Network (AERONET). Specifically, a unit dust aerosol optical depth (AOD) contamination at 550 nm can introduce larger than 2.4 and 8.6 K peak biases in analyzed temperature and dewpoint, respectively, over our test domain. We hypothesize that aerosol observations, or even possibly forecasts from aerosol predication models, may be used operationally to mitigate dust induced temperature and moisture analysis biases through forward radiative transfer modeling.

Jared W. Marquis↗

NASA NTRS2021

Conceptualizing the Impact of Dust-Contaminated Infrared Radiances on Data Assimilation for Numerical Weather Prediction

Jared W Marquis↗

DOE OSTI2022

The theory of transport in helical spin-structure crystals

Abstract We study helical structures in spin-spiral single crystals. In the continuum approach for the helicity potential energy the simple electronic band splits into two non-parabolic bands. For low exchange integrals, the lower band is described by a surface with a saddle shape in the direction of the helicity axis. Using the Boltzmann equation with the relaxation due to acoustic phonons, we discover the dependence of the current on the angle between the electric field and helicity axis leading to the both parallel and perpendicular to the electric field components in the electroconductivity. The latter can be interpreted as a planar Hall effect. In addition, we find that the transition rates depend on an electron spin allowing the transition between the bands. The electric conductivities exhibit nonlinear behaviors with respect to chemical potential µ . We explain this effect as the interference of the band anisotropy, spin conservation, and interband transitions. The proposed theory with the spherical model in the effective mass approximation for conduction electrons can elucidate nonlinear dependencies that can be identified in experiments. We find the excellent agreement between the theoretical and experimental data for parallel resistivity depending on temperature at the phase transition from helical to ferromagnetic state in a M n P single crystal. In addition, we predict that the perpendicular resistivity abruptly drops to zero in the ferromagnetic phase.

Physics↗

DOE OSTI2025

Bayesian inference of nuclear incompressibility from collective flow in mid-central Au+Au collisions at 400–1500 MeV/nucleon

The incompressibility K of symmetric nuclear matter (SNM) is determined through a Bayesian analysis of collective flow data from Au + Au collisions at beam energies $E = 400 -1500$ MeV/nucleon. This analysis utilizes a Gaussian process (GP) emulator applied to the isospin-dependent quantum molecular dynamics (IQMD) model for heavy-ion collisions, both with and without incorporating the momentum dependence of the single-nucleon potentials. Specifically, at the 68% confidence level, using rapidity and transverse velocity dependence of proton elliptic flow data with and without consideration of the momentum dependence, the inferred incompressibility values are $K=188.9^{+2.9}_{-4.5}$ MeV and $256.1^{+8.2}_{-8.7}$ MeV at $E = 400$ MeV/nucleon, respectively. When the transverse momentum dependence of proton-like directed flow data is included, the inferred incompressibility values become $K=222.3^{+9.0}_{-9.9}$ MeV and $K=285.5^{+6.7}_{-7.3}$ MeV, respectively. Furthermore, we found that the value of K derived from observables of proton elliptic flow increases with beam energy. Finally, this indicates that the equation of state (EoS) of nuclear matter hardens at higher densities and temperatures in reactions with higher beam energies.

Bayesian inference↗

DOE OSTI2021

Thermal neutron scattering measurements and modeling of yttrium-hydrides for high temperature moderator applications

In this work, thermal neutron scattering measurements of yttrium hydride from 5 to 1,200 K were conducted to determine the change in inelastic scattering as a function of temperature and to probe for anharmonic effects. Additionally, measurements on samples of YH x from x = 1.62 to 1.90 were done to determine the effects of varying hydrogen concentration on the inelastic spectra. Changes in temperature affected the inelastic spectra in unanticipated ways, indicating that there are anharmonic effects, whereas hydrogen concentration did not significantly affect the inelastic spectra. These measurements were compared against the ENDF/B-VIII.0 thermal scattering files of YH 2 , as well as new thermal scattering files created by using the stochastic temperature-dependent effective potential (s-TDEP). Both libraries were found to be in good agreement with the experimental data at lower temperatures. At higher temperatures, the s-TDEP method is better at predicting the experimentally observed softening of phonon modes in acoustic and optical regions.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗

DOE OSTI2024

Multiple magnetic interactions and large inverse magnetocaloric effect in TbSi and TbSi 0.6 Ge 0.4

We present a comprehensive investigation of the electronic structure, magnetization, specific heat, and crystallography of TbSi (FeB structure type) and TbSi 0.6 ⁢Ge 0.4 (CrB structure type) compounds. Both TbSi and TbSi 0.6 ⁢Ge 0.4 exhibit two antiferromagnetic (AFM) transitions at T N⁢1 ≈ 58 and 57 K, and T N⁢2 ≈ 36 and 44 K, respectively, along with an onset of weak metamagneticlike transition around 6 T between T N⁢1 and T N⁢2 . High-resolution specific heat (C P ) measurements show the second- and first-order nature of the magnetic transition at T N⁢1 and T N⁢2 , respectively, for both samples. However, in the case of TbSi, the low-temperature (LT) AFM to high-temperature (HT) AFM transition takes place via an additional AFM phase at the intermediate temperature (IT), where both LT to IT AFM and IT to HT AFM phase transitions exhibit a first-order nature. Both TbSi and TbSi 0.6 ⁢Ge 0.4 manifest significant magnetic entropy changes (Δ⁢S M ) of 9.6 and 11.6 J/kg-K, respectively, for Δ⁢μ 0 ⁢H=7 T, at T N⁢2 . The HT AFM phase of TbSi 0.6 ⁢Ge 0.4 is found to be more susceptible to the external magnetic field, causing a significant broadening in the peaks of Δ⁢S M curves at higher magnetic fields. Temperature- and field-dependent specific-heat data have been utilized to construct the complex HT phase diagram of these compounds. As a result, temperature-dependent x-ray diffraction measurements demonstrate substantial magnetostriction and anisotropic thermal expansion of the unit cell in both samples.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗