Search NASA⌕ Search

SEARCH · Search NASA

Results for “Data article”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54

Computer simulation results for PCM/PM/NRZ receivers in nonideal channels

This article studies, by computer simulations, the performance of deep-space telemetry signals that employ the pulse code modulation/phase modulation (PCM/PM) technique, using nonreturn-to-zero data, under the separate and combined effects of unbalanced data, data asymmetry, and a band-limited channel. The study is based on measuring the symbol error rate performance and comparing the results to the theoretical results presented in previous articles. Only the effects of imperfect carrier tracking due to an imperfect data stream are considered. The presence of an imperfect data stream (unbalanced and/or asymmetric) produces undesirable spectral components at the carrier frequency, creating an imperfect carrier reference that will degrade the performance of the telemetry system. Further disturbance to the carrier reference is caused by the intersymbol interference created by the band-limited channel.

Anabtawi, A.↗

Machine Learning Benchmarks for the Classification of Equivalent Circuit Models from Electrochemical Impedance Spectra

Analysis of Electrochemical Impedance Spectroscopy (EIS) data for electrochemical systems often consists of defining an Equivalent Circuit Model (ECM) using expert knowledge and then optimizing the model parameters to deconvolute various resistance, capacitive, inductive, or diffusion responses. For small data sets, this procedure can be conducted manually; however, it is not feasible to manually define a proper ECM for extensive data sets with a wide range of EIS responses. Automatic identification of an ECM would substantially accelerate the analysis of large sets of EIS data. We showcase machine learning methods to classify the ECMs of 9,300 impedance spectra provided by QuantumScape for the BatteryDEV hackathon. The best-performing approach is a gradient-boosted tree model utilizing a library to automatically generate features, followed by a random forest model using the raw spectral data. A convolutional neural network using boolean images of Nyquist representations is presented as an alternative, although it achieves a lower accuracy. We publish the data and open source the associated code. The approaches described in this article can serve as benchmarks for further studies. A key remaining challenge is the identifiability of the labels, underlined by the model performances and the comparison of misclassified spectra.

25 ENERGY STORAGE↗

Visualizing Diurnal Population Change in Urban Areas for Emergency Management

There is an increasing need for a quick, simple method to represent diurnal population change in metropolitan areas for effective emergency management and risk analysis. Many geographic studies rely on decennial U.S. Census data that assume that urban populations are static in space and time. This has obvious limitations in the context of dynamic geographic problems. The U.S. Department of Transportation publishes population data at the transportation analysis zone level in fifteen-minute increments. This level of spatial and temporal detail allows for improved dynamic population modeling. This article presents a methodology for visualizing and analyzing diurnal population change for metropolitan areas based on this readily available data. Areal interpolation within a geographic information system is used to create twenty-four (one per hour) population surfaces for the larger metropolitan area of Salt Lake County, Utah. The resulting surfaces represent diurnal population change for an average workday and are easily combined to produce an animation that illustrates population dynamics throughout the day. A case study of using the method to visualize population distributions in an emergency management context is provided using two scenarios: a chemical release and a dirty bomb in Salt Lake County. This methodology can be used to address a wide variety of problems in emergency management.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Inlet↗

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Data Acquisition↗

Orographic enhancement of rainfall over the Congo Basin

Abstract The Congo rainforest located in central equatorial Africa is an important, yet understudied part of the globe surrounded by complex orographic features. A primitive understanding of precipitation processes such as mesoscale convective dynamics magnifies uncertainties in the future climate projections of the hydrological cycle over the Congo. Furthermore, the effects of orography, which is an important forcing for convection and precipitation, are poorly resolved by climate models, and ill‐conceptualized over the Congo. To address this knowledge gap, perturbed orographic forcing experiments are conducted using the Weather Research and Forecasting (WRF) mesoscale numerical model in a high‐resolution convection‐permitting model setup. The model simulated selected dates in November 2014. The thunderstorms and rainfall simulated in the control run for the case study analyzed in this article compared reasonably well to satellite‐derived brightness temperature and rainfall data. The results from this case study show that the dynamical impact of increasing the height of the East African Highlands is the blocking of the lower‐tropospheric tropical easterlies. This weakening of the lower‐tropospheric zonal winds increases the windshear over the Congo Basin resulting in slower propagating, more intense mesoscale convective systems with enhanced rainfall.

54 ENVIRONMENTAL SCIENCES↗

Advancing our predictive understanding of river corridor exchange

Despite decades of research, we lack an accurate framework to predict and manage hydrologic exchange in the river corridor and the associated ecosystem services and functions at the scales of stream reaches and entire networks. While many individual studies have been conducted to investigate specific mechanisms, they have not been synthesized to account for heterogeneity in space, nonstationarity, and multiscale feedbacks that typify the river corridor. As a result, contradictory predictions of exchange flux, geometry, and timescale are prevalent in the literature. We attribute these contradictions to (a) failure to account for multiscale feedbacks and (b) uncertainty in the information content of common measurement methods. Here, we apply the concept of interacting multiscale spatial and time‐variable domains to the river corridor to demonstrate why more complete multiscale characterization is necessary to achieve predictive understanding. Next, we highlight uncertainties and inconsistencies in measurement methods which may obfuscate our understanding of river corridor exchange. Finally, we briefly outline four necessary advances to achieve predictive understanding of river corridor exchange: standardization of metadata, critical evaluation of the information content and support volumes for measurement techniques, multiscale model‐data integration, and advancing theoretical models of river corridor exchange. This article is categorized under: Science of Water > Hydrological Processes Water and Life > Nature of Freshwater Ecosystems Science of Water > Methods

Ward, Adam S.↗

Measuring Distribution Performance? Benchmarking Warrants Your Attention

Identifying, designing, and measuring performance metrics is critical to securing customer value, but can be a difficult task. This article examines the use of benchmarks based on publicly available performance data to set challenging, yet fair, metrics and targets.

2017 customer value ranking↗

The CAM assay in the study of the metastatic process

Among the in vivo experimental models, the chick embryo chorioallantoic membrane (CAM) has been routinely used to implant several malignant cell lines or tumor tissues to study their angiogenic and metastatic capability. Since the chick embryo is naturally immunodeficient, the CAM can support the engraftment of tumor cells, and their growth therein can faithfully recapitulate most of the characteristics of the carcinogenic process including: growth, invasion, angiogenesis and colonization of distant tissues. This review article is focused on the discussion of the more recent literature data concerning the use of the CAM to investigate the metastatic process.

60 APPLIED LIFE SCIENCES↗

Erratum: Electrokinetic detection for x-ray spectra of weakly interacting liquids: n-decane and n-nonane [J. Chem. Phys. 140, 234202 (2014)]

Here, the peak centered at 287.8 eV was incorrectly assigned to a C(1s) → σ* (C–C) transition. This peak corresponds to a second C(1s) → σ* (C–H) transition orthogonal to the peak at 287.2 eV as can be seen with the revisualized isosurfaces for the two states. The revisualized isosurfaces use the same calculated volumetric data for the core-excited electron density from the original article. This erroneous assignment appears in the last paragraph on page 4 and in Fig. 4. An updated Fig. 4 with the revisualized isosurfaces is presented here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The sea of quarks and antiquarks in the nucleon

The quark and gluon structure of the proton has been under intense experimental and theoretical investigation for five decades. Even for the distributions of the well-studied valence quarks, challenges such as the value of the down quark to up quark ratio at high fractional momenta remain. Much of the sea of quark-antiquark pairs emerges from the splitting of gluons and is well described by perturbative evolution in quantum chromodynamics. However, experiments confirm that there is a non-perturbative component to the sea that is not well understood and hitherto has been difficult to calculate with ab initio non-perturbative methods. This non-perturbative structure shows up, perhaps most directly, in the flavor dependence of the sea antiquark distributions. Even though some of the general trends can be reproduced by models, there are features of the data that do not seem to be well described. Conclusively, this article discusses the experimental situation, the status of calculations and models, and the directions where these studies will progress in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Consistency relations for sharp inflationary non-Gaussian features

If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗

Cohort organized learning: clustering through agreement

In this article we describe cohort organized learning (CoOL), a method for clustering data without explicit distance or similarity computations. Herein, we will describe CoOL, derive the gradients determined by expectation maximization to train the networks, show how to monitor convergence during training and evaluate the clusters after training, and discuss a series of examples and use cases. We also discuss CoOL’s limitations and future prospects on related tasks. Because CoOL uses neural networks to estimate the clusters, it can be used to cluster any data that can be made compatible and we illustrate this on vector data and images.

clustering↗

Polarization transfer observables in elastic electron-proton scattering at Q 2 = 2.5 , 5.2, 6.8, and 8.5 GeV 2

In this paper, interest in the behavior of nucleon electromagnetic form factors at large momentum transfers has steadily increased since the discovery, using polarization observables, of the rapid decrease of the ratio G p E /G p M of the proton's electric and magnetic form factors for momentum transfers Q 2 ≳ 1 GeV 2 , in strong disagreement with previous extractions of this ratio using the traditional Rosenbluth separation technique. The GEp-III and GEp-2$\gamma$ experiments were carried out in Jefferson Lab's (JLab's) Hall C from 2007-2008, to extend the knowledge of $G_E^p/G_M^p$ to the highest practically achievable $Q^2$ and to search for effects beyond the Born approximation in polarization transfer observables of elastic $\vec{e}p$ scattering. This article reports an expanded description of the common experimental apparatus and data analysis procedure, and the results of a final reanalysis of the data from both experiments, including the previously unpublished results of the full-acceptance data of the GEp-2$\gamma$ experiment. The Hall C High Momentum Spectrometer detected and measured the polarization of protons recoiling elastically from collisions of JLab's polarized electron beam with a liquid hydrogen target. A large-acceptance electromagnetic calorimeter detected the elastically scattered electrons in coincidence to suppress inelastic backgrounds. The final GEp-III data are largely unchanged relative to the originally published results. The statistical uncertainties of the final GEp-2$\gamma$ data are significantly reduced at $\epsilon = 0.632$ and $0.783$ relative to the original publication. The decrease with $Q^2$ of $G_E^p/G_M^p$ continues to $Q^2 = 8.5$ GeV$^2$, but at a slowing rate relative to the approximately linear decrease observed in earlier Hall A measurements. At $Q^2 = 2.5$ GeV$^2$, the proton form factor ratio $G_E^p/G_M^p$ shows no statistically significant $\epsilon$-dependence, as expected in the Born approximation. The ratio $P_\ell/P_\ell^{Born}$ of the longitudinal polarization transfer component to its Born value shows an enhancement of roughly 1.7\% at $\epsilon = 0.783$ relative to $\epsilon = 0.149$, with $\approx 2.2\sigma$ significance based on the total uncertainty, implying a similar effect in the transverse component $P_t$ that cancels in the ratio $R$.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Rapid detection of rare events from in situ X-ray diffraction data using machine learning

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics ( e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

Zheng, Weijian↗

ColorMoves: Real-time Interactive Colormap Construction for Scientific Visualization

This article presents ColorMoves, an interactive tool that promotes exploration of scientific data through artist-driven color methods in a unique and transformative way. Here, we discuss the power of contrast in scientific visualization, the design of the ColorMoves tool, and the tools application in several science domains.

97 MATHEMATICS AND COMPUTING↗

Challenges and Lessons Learned From Fabrication, Testing, and Analysis of Eight MQXFA Low Beta Quadrupole Magnets for HL-LHC

By the end of October 2022, the US HL-LHC Accelerator Upgrade Project (AUP) had completed fabrication of ten MQXFA magnets and tested eight of them. The MQXFA magnets are the low-beta quadrupole magnets to be used in the Q1 and Q3 Inner Triplet elements of the High Luminosity LHC. This AUP effort is shared by BNL, Fermilab, and LBNL, with strand verification tests at NHMFL. An important step of the AUP QA plan is the testing of MQXFA magnets in a vertical cryostat at BNL. The acceptance criteria that could be tested at BNL were all met by the first four production magnets (MQXFA03-MQXFA06). Subsequently, two magnets (MQXFA07 and MQXFA08) did not meet some of the criteria and were disassembled. Furthermore, lessons learned during the disassembly of MQXFA07 caused a revision to the assembly specifications that were used for MQXFA10 and subsequent magnets. In this article, we present a summary of 1) the fabrication and test data for all the MQXFA magnets; 2) the analysis of MQXFA07/A08 test results with characterization of the limiting mechanism; 3) the outcome of the investigation, including the lessons learned during MQXFA07 disassembly; and 4) the finite element analysis correlating observations with test performance.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

CERES MODIS Cloud Product Retrievals for Edition 4--Part I: Algorithm Changes

The Edition 2 (Ed2) cloud property retrieval algorithm system was upgraded and applied to the MODerate-resolution Imaging Spectroradiometer (MODIS) data for the Clouds and the Earth's Radiant Energy System (CERES) Edition 4 (Ed4) products. New calibrations for solar channels and the use of the 1.24-μm channel for cloud optical depth (COD) over snow improve the daytime consistency between Terra and Aqua MODIS retrievals. Use of additional spectral channels and revised logic enhanced the cloud-top phase retrieval accuracy. A new ice crystal reflectance model and a CO₂-channel algorithm retrieved higher ice clouds, while a new regional lapse rate technique produced more accurate water cloud heights than in Ed2. Ice cloud base heights are more accurate due to a new cloud thickness parameterization. Overall, CODs increased, especially over the polar (PO) regions. The mean particle sizes increased slightly for water clouds, but more so for ice clouds in the PO areas. New experimental parameters introduced in Ed4 are limited in utility, but will be revised for the next CERES edition. As part of the Ed4 retrieval evaluation, the average properties are compared with those from other algorithms and the differences between individual reference data and matched Ed4 retrievals are explored. Part II of this article provides a comprehensive, objective evaluation of selected parameters. More accurate interpretation of the CERES radiation measurements has resulted from the use of the Ed4 cloud properties.

54 ENVIRONMENTAL SCIENCES↗