Atmospheric OH Response to the 11-Year Solar Cycle: Could the Gap Between Model and Observations Be Filled by SORCE Data
No abstract available
ground based measurements↗
SEARCH · Engineering Papers
Results for “Data gaps”
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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A Network-Based Algorithm for Clustering Multivariate Repeated Measures Data
The National Aeronautics and Space Administration (NASA) Astronaut Corps is a unique occupational cohort for which vast amounts of measures data have been collected repeatedly in research or operational studies pre-, in-, and post-flight, as well as during multiple clinical care visits. In exploratory analyses aimed at generating hypotheses regarding physiological changes associated with spaceflight exposure, such as impaired vision, it is of interest to identify anomalies and trends across these expansive datasets. Multivariate clustering algorithms for repeated measures data may help parse the data to identify homogeneous groups of astronauts that have higher risks for a particular physiological change. However, available clustering methods may not be able to accommodate the complex data structures found in NASA data, since the methods often rely on strict model assumptions, require equally-spaced and balanced assessment times, cannot accommodate missing data or differing time scales across variables, and cannot process continuous and discrete data simultaneously. To fill this gap, we propose a network-based, multivariate clustering algorithm for repeated measures data that can be tailored to fit various research settings. Using simulated data, we demonstrate how our method can be used to identify patterns in complex data structures found in practice.
Koslovsky, Matthew↗
Transition Induced by Fence Geometrics on Shuttle Orbiter at Mach 10
Fence-induced transition data simulating a raised gap filler have been acquired on the wing lower surface of a Shuttle Orbiter model in the Langley 31-Inch Mach 10 Tunnel to compare with the Shuttle Boundary Layer Transition Flight and HYTHIRM Experiments, and to provide additional correlation data for the Boundary Layer Transition Tool. In a qualitative assessment, the data exhibit the expected response to all parameter variations; however, it is unclear whether fully effective tripping at the fence was ever realized at any test condition with the present model hardware. A preliminary, qualitative comparison of the ground-based transition measurements with those obtained from the STS-128 HYTHIRM imagery at Mach 15 reveal similar transition-wake response characteristics in terms of the spreading and the path along the vehicle surface.
Everhart, Joel L.↗
Comparison of Orbiter STS-2 development flight instrumentation data with thermal math model predictions
Thermal performance verification of Reusable Surface Insulation (RSI) has been accomplished by comparisons of STS-2 Orbiter Flight Test (OFT) data with Thermal Math Model (TMM) predictions. The OFT data was obtained from Development Flight Instrumentation RSI plug and gap thermocouples. Quartertile RSI TMMs were developed using measured flight data for surface temperature and pressure environments. Reference surface heating rates, derived from surface temperature data, were multiplied by gap heating ratios to obtain tile sidewall heating rates. This TMM analysis resulted in good agreement of predicted temperatures with flight data for thermocouples located in the RSI, Strain Isolation Pad, filler bar and structure.
Norman, I.↗
ORNL_AISD_DL-HLgap
This dataset provides supplementary molecular dataset of Deep Learning Workflow for the Inverse Design of Molecules with Specific Optoelectronic Properties. The dataset comprises three main directories such as GDB-9_dataset, Low_HL_Gap_dataset, and High_HL_Gap_dataset which individually has csv files, smiles_txt files, pdb files and xyz files containing information of molecular structures, properties and coordinates generated from deep learning workflow using generative model, surrogate model and DFTB calculation results. GDB-9_dataset contains the molecular data extracted from the original GDB-9 dataset with additional data of DFTB HL gap, surrogate HL gap and molecular property analysis. (the number of atoms, aromaticity and double bond equivalent) Low_HL_Gap_dataset and High_HL_Gap_dataset contains series of dataset for different generations with further split to train and test dataset that were obtained from the iterative workflow described in the manuscript. Additional directory Chemiscope_visualization in Low_HL_Gap_dataset directory contains compressed json files to visualize molecules using chemiscope.org page or application to help readers examine generated molecules.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Increasing Data Discovery and Re-Use: The Space Life Sciences Ontology
Two of the most important goals of the adoption of the FAIR principles are increasing the ability of agents to find and re-use research data. Achieving these goals for space life sciences research is even more pressing, given the relatively expensive and scarce nature of these data. We have reported in the past on the progress made by exemplar life sciences data systems towards implementing FAIR, showing gaps particularly in the “interoperability area” of the principles; the lack of common conceptual models for space life science research is one reason for this gap. There were few available resources that define, annotate, categorize or otherwise relate various kinds of metadata describing the acquisition, nature, and intent of investigational space life sciences data. To address this gap, NASA is working with the Open Biological and Biomedical Ontology Foundry (https://obofoundry.org/) to develop the Space Life Science Ontology (SLSO) that is intended to support archival and other kinds of systems that operate using these data. The scope of the ontology includes concepts regarding those aspects of investigation design and execution specific or unique to space environments, such as types of specialized equipment, operating organizations, and documentation. The ontology is continually being developed and published to the life science community (https://github.com/nasa/LSDAO/); at the time of this publication, the SLSO newly and uniquely defines 30 types (classes), 90 properties, and 14 relations specific to space life sciences metadata. In addition, the SLSO reuses (imports) some 2,360 types (classes), 49 properties, and 393 relations from other ontologies that are relevant to these kinds of metadata. In addition to its role as a common conceptualization for space biomedical research activities, the SLSO can also be used to provide automated support for traditionally difficult and expensive activities such as data curation and cross-system data integration and analysis.
fair↗
Long-term missing value imputation for time series data using deep neural networks
We present an approach that uses a deep learning model, in particular, a MultiLayer Perceptron, for estimating the missing values of a variable in multivariate time series data. We focus on filling a long continuous gap (e.g., multiple months of missing daily observations) rather than on individual randomly missing observations. Our proposed gap filling algorithm uses an automated method for determining the optimal MLP model architecture, thus allowing for optimal prediction performance for the given time series. We tested our approach by filling gaps of various lengths (three months to three years) in three environmental datasets with different time series characteristics, namely daily groundwater levels, daily soil moisture, and hourly Net Ecosystem Exchange. We compared the accuracy of the gap-filled values obtained with our approach to the widely used R-based time series gap filling methods ImputeTS and mtsdi. The results indicate that using an MLP for filling a large gap leads to better results, especially when the data behave nonlinearly. Thus, our approach enables the use of datasets that have a large gap in one variable, which is common in many long-term environmental monitoring observations.
97 MATHEMATICS AND COMPUTING↗
Prediction of orbiter RSI tile gap heating ratios from NASA/Ames double wedge model test
In-depth gap heating ratios for Orbiter RSI tile sidewalls were predicted based on near steady state temperature measurements obtained from double wedge model tests. An analysis was performed to derive gap heating ratios which would result in the best fit of test data; provide an assessment of open gap response, and supply the definition of gap filler requirements on the Orbiter. A comparison was made of these heating ratios with previously derived ratios in order to verify the extrapolation of the wing glove data to Orbiter flight conditions. The analysis was performed with the Rockwell TPS Multidimensional Heat Conduction Program for a 3-D, 2.0-inch thick flat RSI tile with 255 nodal points. The data from 14 tests was used to correlate with the analysis. The results show that the best-fit heating ratios at the station farthest upstream on the model for most gap depths were less than the extrapolated values of the wing glove model heating ratios. For the station farthest downstream on the model, the baseline heating ratios adequately predicted or over-predicted the test data.
Source record↗
High-throughput and data-driven search for stable optoelectronic AMSe 3 materials
The rapid advancement in emerging optoelectronic technologies demands highly efficient, affordable, and ecofriendly materials. In this context, ternary chalcogenides, especially ternary selenides, show early promise as a material class due to their stability and remarkable electronic, optical, and transport properties. In this work, we integrate first-principles-based high-throughput computations with machine learning (ML) techniques to predict the thermodynamic stability and optoelectronic properties of 920 valency-satisfied selenide compounds. Through investigating polymorphism, our study reveals the edge-sharing orthorhombic Pnma phase (NH 4 CdCl 3 -type) as the most stable structure for most ternary selenides. High-fidelity supervised ML models are trained and tested to accelerate stability and band gap predictions. These data-driven models pin down the most influential features that dominantly control key material characteristics. The multistep high-throughput computations identify the ternary selenides with optimal direct band gaps, light carrier masses, and strong optical absorption edges. The extensive materials screening considering phase stability, toxicity, and defect tolerance, finally identifies the seven most suitable candidates for photovoltaic applications. Two of these final compounds, SrZrSe 3 and SrHfSe 3 , have already been synthesized in a single-phase form, with the latter showing an optically suitable band gap, aligning well with our findings. The non-adiabatic molecular dynamics reveal sufficiently long photoexcited charge carrier lifetimes (on the order of nanoseconds) in some of these selected selenide materials, indicating their exciting characteristics. Overall, our study suggests a robust in silico framework that can be extended to screen large datasets of various material classes for identifying promising photoactive candidates.
36 MATERIALS SCIENCE↗
Pretest Simulations of a Supersonic Mixing and Combustion Validation Experiment to Assess Sensitivities
The reliance on CFD simulations to develop, design, and optimize scramjet systems (or components) has become commonplace. This reliance inevitably hinges on the ability of the computational analyst to quantify the level of confidence in their computational results. Unfortunately, nearly all the measured data available for this assessment comes from antiquated experimental datasets, or from tests that focused on the extraction of scramjet system (or component) performance. The objective of a CFD validation experiment is to quantify the predictive accuracy of one or more of the CFD physics submodels, implying that other uncertainties related to replicating the facility flow environment (e.g., knowledge of boundary conditions) must be minimized to the extent possible. This inevitably places stringent requirements on the quality and quantity of measurements taken to accurately specify inflow, outflow, and surface conditions for the CFD simulations; in addition to the measurements taken for the validation of physics submodels. This places additional demands on the experimental process above and beyond those for test article performance assessment. A recent high speed code credibility workshop series sponsored by AFRL identified a gap in existing validation data for fundamental assessments of turbulent mixing and combustion CFD closure models at scramjet engine relevant conditions. To address this gap, engineers at AFRL have designed a coaxial jet flame configuration that will be tested at two facilities (Research Cell 19 at the Air Force Research Lab, and at Purdue University). The effort described here documents pretest simulations of this validation experiment with the goal of fleshing out the extent of the facility flowpath that must be included to adequately reproduce the facility test section flow environment. The findings indicate that the flow around the support structure for the fuel injection centerbody upstream of the facility nozzle generates disturbances that persist throughout the nozzle expansion process; corrupting the azimuthal symmetry that was desired in the fuel/air mixing region of the test section. Simulations without this support structure maintained a high degree of azimuthal symmetry up until the fuel injection plane. However, even in this scenario the azimuthal symmetry was not maintained once the centerbody boundary layer transitioned to a wake flow downstream of the fuel injection plane.
CFD↗
Pretest Simulations of a Supersonic Mixing and Combustion Validation Experiment to Assess Sensitivities
The reliance on CFD simulations to develop, design, and optimize scramjet systems (or components) has become commonplace. This reliance inevitably hinges on the ability of the computational analyst to quantify the level of confidence in their computational results. Unfortunately, nearly all the measured data available for this assessment comes from antiquated experimental datasets, or from tests that focused on the extraction of scramjet system (or component) performance. The objective of a CFD validation experiment is to quantify the predictive accuracy of one or more of the CFD physics submodels, implying that other uncertainties related to replicating the facility flow environment (e.g., knowledge of boundary conditions) must be minimized to the extent possible. This inevitably places stringent requirements on the quality and quantity of measurements taken to accurately specify inflow, outflow, and surface conditions for the CFD simulations; in addition to the measurements taken for the validation of physics submodels. This places additional demands on the experimental process above and beyond those for test article performance assessment. A recent high speed code credibility workshop series sponsored by AFRL identified a gap in existing validation data for fundamental assessments of turbulent mixing and combustion CFD closure models at scramjet engine relevant conditions. To address this gap, engineers at AFRL have designed a coaxial jet flame configuration that will be tested at two facilities (Research Cell 19 at the Air Force Research Lab, and at Purdue University). The effort described here documents pretest simulations of this validation experiment with the goal of fleshing out the extent of the facility flowpath that must be included to adequately reproduce the facility test section flow environment. The findings indicate that the flow around the support structure for the fuel injection centerbody upstream of the facility nozzle generates disturbances that persist throughout the nozzle expansion process; corrupting the azimuthal symmetry that was desired in the fuel/air mixing region of the test section. Simulations without this support structure maintained a high degree of azimuthal symmetry up until the fuel injection plane. However, even in this scenario the azimuthal symmetry was not maintained once the centerbody boundary layer transitioned to a wake flow downstream of the fuel injection plane.
CFD↗
Aerosol, Cloud and Trace Gas Observations Derived from Airborne Hyperspectral Radiance and Direct Beam Measurements in Recent Field Campaigns
The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions. The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. Dunagan et al. [2013] present results establishing the performance of the instrument, along with calibration, engineering flight test, and preliminary scientific field data. The 4STAR instrument operated successfully in the SEAC4RS [Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys] experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE [Department of Energy]-sponsored TCAP [Two Column Aerosol Project, July 2012 & Feb. 2013] experiment aboard the DoE G-1 aircraft (Shinozuka et al., 2013), and acquired a wealth of data in support of mission objectives on all SEAC4RS and TCAP research flights. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2; Segal-Rosenheimer et al., 2014), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In addition, 4STAR measured zenith radiances underneath cloud decks for retrievals of cloud optical depth and effective diameter. In this presentation, we provide an overview of the new 4STAR capabilities for airborne field campaigns, with an emphasis on comparisons between 4STAR and AERONET sky radiances, and retrievals of aerosol microphysical properties based on sky radiance measurements, column trace gas amounts from spectral direct beam measurements and cloud property retrievals from zenith mode observations for a few select case studies in the SEAC4RS and TCAP experiments. We summarize the aerosol, trace gas, cloud and airmass characterization studies made possible by the combined 4STAR direct beam, and sky/zenith radiance observations.
Aerosol-Climate↗
Cinema:Snap: Real-time tools for analysis of dynamic diamond anvil cell experiment data
We report we developed tools and a workflow for real-time analysis of data from dynamic diamond anvil cell experiments performed at user light sources. These tools allow users to determine the phases of matter observed during the compression of materials in order to make decisions during an experiment to improve the quality of experimental results and maximize the use of scarce experimental facility time. The tools fill a gap in dynamic compression data analysis tools that are real-time, are flexible to the needs of high-pressure scientists, connect to automated processing of results, can be easily incorporated into workflows with existing tools and data formats, and support remote experimental data analysis workflows. Specific analytics developed include novel automated two-peak analysis for overlapping peaks and multiple phases, coordinated views of pressure and temperature values, full-compression contour plots, and configurable views of integrated x-ray diffraction. We present an experimental use case to show how the tools produce real-time analytics that help the scientists revise parameters for the next compression
47 OTHER INSTRUMENTATION↗
Aerosol Properties Derived from Airborne Sky Radiance and Direct Beam Measurements in Recent NASA and DoE Field Campaigns
The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions.The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL (Pacific Northwest National Laboratory) with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. The 4STAR instrument operated successfully in the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE (Department of Energy)-sponsored TCAP (Two Column Aerosol Project, July 2012 & Feb. 2013) experiment aboard the DoE G-1 aircraft. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In this presentation, we provide an overview of the new 4STAR capabilities, with an emphasis on 26 high-quality sky radiance measurements carried out by 4STAR in SEAC4RS. We compare collocated 4STAR and AERONET sky radiances, as well as their retrievals of aerosol microphysical properties for a subset of the available case studies. We summarize the particle property and air-mass characterization studies made possible by the combined 4STAR direct beam and sky radiance observations.
DoE↗
Behavior of Spinning Space Vehicles with Onboard Liquids, 2nd Edition, Technical Report B8030
Although the fundamental principles of spin stabilization are well established, uncertainty regarding the potential for rapid nutation growth caused by onboard liquids is a continuing concern. NASA and other organizations regularly encounter the issue of rapid nutation growth due to energy dissipation by liquids on spinning vehicles. Of concern is the stability of spinning upper stages and of spacecraft that spin for part or all of their missions. Several missions have required last-minute hardware or operational changes to deal with rapid nutation divergences that were identified late in the program. In some instances, major schedule slips were barely averted. In at least two cases, it was determined that a spinning upper stage was not a viable option. Historically, the "slosh" issue has been addressed by each space vehicle project individually, if it has been addressed at all. Due to budgetary and programmatic constraints, individual projects are unable to address the problem globally. Hence, there has been little effort to collect available test and flight data and use that data to make a coherent, unified picture of the "slosh" effect and how to deal with it. To some extent, each project has had to "reinvent the wheel", which can be both costly and risky. This study is a step toward correcting the situation. Specifically, the goal was to identify and collect available flight and test data for spinning vehicles with onboard liquid propellants. A total of 149 flight data points and 1,692 test points were collected as part of this study. This data was analyzed, correlated, and is presented here in a normalized form. In most cases, the normalization involves a dimensionless nutation time constant that can be used to predict performance of other vehicles with the same type of tank. For some configurations, it was also possible to identify conditions that can lead to resonance between nutational motion and liquid modes. Gaps in the knowledge base are identified and approaches to filling those gaps are outlined. The data presented here has two different but related uses. First, it can be applied directly to current and future spacecraft programs. Second, it can provide truth models for testing analytical techniques. Experience has shown that purely analytical models of the liquid "slosh" effect on spinning vehicles are unreliable unless they are validated against flight or test data. To the author's knowledge, this report contains the most extensive and varied data set available. As such, it should be a good resource for anyone seeking to develop and validate improved analytical techniques. All of the original digital data sets have been archived on disk, with copies provided to NASA/KSC. With some restrictions, many of these data sets can be made available to researchers within the United States. Whenever possible, spacecraft are identified by name in this report. However, several organizations provided access to data with the explicit proviso that their programs not be identified and that parameters be presented only in normalized form. These constraints have been respected.
Hubert, Carl↗
GMSK Modulation for Deep Space Applications
Due to scarcity of spectrum at 8.42 GHz deep space Xband allocation, many deep space missions are now considering the use of higher order modulation schemes instead of the traditional binary phase shift keying (BPSK). One such scheme is pre-coded Gaussian minimum shift keying (GMSK). GMSK is an excellent candidate for deep space missions. GMSK is a constant envelope, bandwidth efficien modulation whose frame error rate (FER) performance with perfect carrier tracking and proper receiver structure is nearly identical to that of BPSK. There are several issues that need to be addressed with GMSK however. Specificall, we are interested in the combined effects of spectrum limitations and receiver structure on the coded performance of the X-band link using GMSK. The receivers that are typically used for GMSK demodulations are variations on offset quadrature phase shift keying (OQPSK) receivers. In this paper we consider three receivers: the standard DSN OQPSK receiver, DSN OQPSK receiver with filte ed input, and an optimum OQPSK receiver with filte ed input. For the DSN OQPSK receiver we show experimental results with (8920, 1/2), (8920, 1/3) and (8920, 1/6) turbo codes in terms of their error rate performance. We also consider the tracking performance of this receiver as a function of data rate, channel code and the carrier loop signal-to-noise ratio (SNR). For the other two receivers we derive theoretical results that will show that for a given loop bandwidth, a receiver structure, and a channel code, there is a lower data rate limit on the GMSK below which a higher SNR than what is required to achieve the required FER on the link is needed. These limits stem from the minimum loop signal-to-noise ratio requirements on the receivers for achieving lock. As a result of this, for a given channel code and a given FER, there could be a gap between the maximum data rate that BPSK can support without violating the spectrum limits and the minimum data rate that GMSK can support with the required FER depending on the type of GMSK receiver that is used.
Communications↗
Local observation of linear-T superfluid density and anomalous vortex dynamics in URu2Si2
The heavy fermion superconductor URu2Si2 is a candidate for chiral, time-reversal symmetry-breaking superconductivity with a nodal gap structure. Here, we microscopically visualized superconductivity and spatially inhomogeneous ferromagnetism in URu2Si2. We observed linear-T superfluid density, consistent with d-wave pairing symmetries including chiral d wave, but did not observe the spontaneous magnetization expected for chiral d wave. Local vortex pinning potentials had either four- or twofold rotational symmetries with various orientations at different locations. Taken together, these data support a nodal gap structure in URu2Si2 and suggest that chirality either is not present or does not lead to detectable spontaneous magnetization.
36 MATERIALS SCIENCE↗
Quantitative Mineralogical Analysis of Mars Analogues Using CHEMIN Data and Rietveld Refinement
Mineralogical analysis is a critical component of planetary surface exploration. Chemical data alone leave serious gaps in our understanding of the surfaces of planets where complex minerals may form in combination with H, S, and halogens. On such planets (e.g., Mars) a single chemical composition may represent a range of mineral assemblages. For example, Viking chemical analyses of excavated duricrust indicate that Mg and S are correlated and ~10% MgSO4 (anhydrous weight) is a likely cementing agent. Pathfinder chemical data support a similar abundance of MgSO4 in the most altered materials. However, there are many possible Mg-sulfates with widely varying hydration states (including dehydrated and 1-, 2-, 3-, 4-, 5-, 6-, and 7-hydrates). In addition, other sulfate minerals such as gypsum (CaSO4 .2H2O) and other salts containing Cl may also exist. X-ray diffraction (XRD) has the ability to decipher mixtures of these phases that would be difficult, if not impossible to unravel using only chemical or spectral data.
Bish, D. L.↗