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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2012

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗
NASA NTRS2016

Stewardship of NASA's Earth Science Data and Ensuring Long-Term Active Archives

Program, NASA has followed an open data policy, with non-discriminatory access to data with no period of exclusive access. NASA has well-established processes for assigning and or accepting datasets into one of 12 Distributed Active Archive Centers (DAACs) that are parts of EOSDIS. EOSDIS has been evolving through several information technology cycles, adapting to hardware and software changes in the commercial sector. NASA is responsible for maintaining Earth science data as long as users are interested in using them for research and applications, which is well beyond the life of the data gathering missions. For science data to remain useful over long periods of time, steps must be taken to preserve: (1) Data bits with no corruption, (2) Discoverability and access, (3) Readability, (4) Understandability, (5) Usability' and (6). Reproducibility of results. NASAs Earth Science data and Information System (ESDIS) Project, along with the 12 EOSDIS Distributed Active Archive Centers (DAACs), has made significant progress in each of these areas over the last decade, and continues to evolve its active archive capabilities. Particular attention is being paid in recent years to ensure that the datasets are published in an easily accessible and citable manner through a unified metadata model, a common metadata repository (CMR), a coherent view through the earthdata.gov website, and assignment of Digital Object Identifiers (DOI) with well-designed landing product information pages.

Data Management↗
DOE OSTI2018

EGS Collab Experiment 1: Continuous Active-Source Seismic Monitoring (CASSM) Data

The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first experiment was performed at the 4850 ft level of the Sanford Underground Research Facility (SURF), approximately 1.5 km below the surface at Lead, South Dakota. The data reported here were collected by the continuous active-source seismic monitoring (CASSM) system (Ajo-Franklin et al., 2011). This system was permanently installed in the testbed and consisted of 17 piezoelectric sources that were recorded by 2-12 channel hydrophone arrays, 18 3-C accelerometers, and 4 3-C geophones at a Nyquist frequency of 24kHz. The source array was activated in a repeated sequence of shots (each source fired 16 times and stacked into resultant waveforms) for the duration of the experiment (April 25, 2018 - March 7, 2019) with few exceptions. Please see the attached documents describing the source / receiver geometry. The data are available in both seg2 (.dat extension) and segy (.sgy extension) format. Each segy file contains multiple seg2 files.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Thermodynamic modeling of adsorption at the liquid-solid interface

Adsorptive separation techniques are significantly energy efficient in comparison to conventional thermal separation techniques such as distillation. Despite extensive research and development activities undertaken for mixed-gas adsorption, the use of adsorption techniques for the separation of multicomponent liquid mixtures is still limited. A major barrier is the lack of accurate adsorption thermodynamic models, which form the scientific foundation of process simulation of such systems, making the translation to industrial scale challenging. In this work, we have rigorously computed the surface excess of adsorption for six binary liquid mixtures on silica gel at 303 K using the frameworks of the generalized Langmuir isotherm (gL) and the adsorbed solution theory (AST). The six binary liquid mixtures were formed by the pair-wise combinations of four components: benzene, 1,2-dichloroethane, cyclohexane, and n-heptane. We have based our calculations by considering simultaneous equilibria of three phases: saturated vapor phase, bulk liquid phase, and adsorbed phase. Further, the composition of the corresponding saturated vapor phase was estimated by the Nonrandom Two-Liquid activity coefficient model and experimental vapor-liquid equilibria data. The activity coefficients of the adsorbed phase, the central issue of multicomponent adsorption thermodynamics, were calculated using the adsorption Nonrandom Two-Liquid activity coefficient model. Devoid of simplifying assumptions, gL and AST provide rigorous thermodynamic frameworks for adsorption equilibria of multicomponent liquid mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Open Humans: A platform for participant-centered research and personal data exploration

Background: Many aspects of our lives are now digitized and connected to the internet. As a result, individuals are now creating and collecting more personal data than ever before. This offers an unprecedented chance for human-participant research ranging from the social sciences to precision medicine. With this potential wealth of data comes practical problems (e.g., how to merge data streams from various sources), as well as ethical problems (e.g., how best to balance risks and benefits when enabling personal data sharing by individuals). Results: To begin to address these problems in real time, we present Open Humans, a community-based platform that enables personal data collections across data streams, giving individuals more personal data access and control of sharing authorizations, and enabling academic research as well as patient-led projects. We showcase data streams that Open Humans combines (e.g., personal genetic data, wearable activity monitors, GPS location records, and continuous glucose monitor data), along with use cases of how the data facilitate various projects. Conclusions: Open Humans highlights how a community-centric ecosystem can be used to aggregate personal data from various sources, as well as how these data can be used by academic and citizen scientists through practical, iterative approaches to sharing that strive to balance considerations with participant autonomy, inclusion, and privacy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Spectroscopic Evidence of Alfvén Wave Damping in the Off-limb Solar Corona

We investigate the off-limb active-region and quiet-Sun corona using spectroscopic data. The active region is clearly visible in several spectral lines formed in the temperature range of 1.1–2.8 MK. We derive the electron number density using the line ratio method, and the nonthermal velocity in the off-limb region up to the distance of 140 Mm. We compare density scale heights derived from several spectral line pairs with expected scale heights per the hydrostatic equilibrium model. Using several isolated and unblended spectral line profiles, we estimate nonthermal velocities in the active region and quiet Sun. Nonthermal velocities obtained from warm lines in the active region first show an increase and then later either a decrease or remain almost constant with height in the far off-limb region, whereas nonthermal velocities obtained from hot lines show consistent decrease. However, in the quiet-Sun region, nonthermal velocities obtained from various spectral lines show either a gradual decrease or remain almost constant with height. Using these obtained parameters, we further calculate Alfvén wave energy flux in both active and quiet-Sun regions. We find a significant decrease in wave energy fluxes with height, and hence provide evidence of Alfvén wave damping. Furthermore, we derive damping lengths of Alfvén waves in the both regions and find them to be in the range of 25–170 Mm. Different damping lengths obtained at different temperatures may be explained as either possible temperature-dependent damping or by measurements obtained in different coronal structures formed at different temperatures along the line of sight. Temperature-dependent damping may suggest some role of thermal conduction in the damping of Alfvén waves in the lower corona.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1988

Programmable Data Formatter

System adapts data in diverse formats for transmission. Microprocessor controls complex activities of data formatting, error checking, and transmission-priority arbitration. System developed for formatting signals from and to telemetry units on spacecraft for widespread telecommunication network.

Martin, Robert E.↗
NASA NTRS2000

Nitric oxide inhibits calpain-mediated proteolysis of talin in skeletal muscle cells

We tested the hypothesis that nitric oxide can inhibit cytoskeletal breakdown in skeletal muscle cells by inhibiting calpain cleavage of talin. The nitric oxide donor sodium nitroprusside prevented many of the effects of calcium ionophore on C(2)C(12) muscle cells, including preventing talin proteolysis and release into the cytosol and reducing loss of vinculin, cell detachment, and loss of cellular protein. These results indicate that nitric oxide inhibition of calpain protected the cells from ionophore-induced proteolysis. Calpain inhibitor I and a cell-permeable calpastatin peptide also protected the cells from proteolysis, confirming that ionophore-induced proteolysis was primarily calpain mediated. The activity of m-calpain in a casein zymogram was inhibited by sodium nitroprusside, and this inhibition was reversed by dithiothreitol. Previous incubation with the active site-targeted calpain inhibitor I prevented most of the sodium nitroprusside-induced inhibition of m-calpain activity. These data suggest that nitric oxide inhibited m-calpain activity via S-nitrosylation of the active site cysteine. The results of this study indicate that nitric oxide produced endogenously by skeletal muscle and other cell types has the potential to inhibit m-calpain activity and cytoskeletal proteolysis.

NASA Discipline Musculoskeletal↗
DOE OSTI2017

Active Subspace Methods for Data-Intensive Inverse Problems

The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Report on phase 2 of 1990 OSSA data census

The 1990 NASA Office of Space Science and Applications (OSSA) data census contributed significantly to a database intended to identify and briefly describe all archived data and potentially archive-desirable data from active and inactive NASA/OSSA spaceflight investigations. This database is being created at the National Space Science Data Center (NSSDC) and will be more comprehensive than the databases describing data held at individual sites such as NSSDC. Active investigations are defined as those flying on currently operational spacecraft or those that flew on recently operational spacecraft for which project-coordinated data archiving is continuing. Inactive investigations are those that flew on spacecraft that are no longer operational, and for which systematic archiving has ended. The principal purpose of this report is to describe phase two of the 1990 census. The previously reported phase one of this census, as well as a relevant 1981 census, are briefly discussed. The phase two survey instrument is described, those surveyed and respondents/reponses are identified, and data sets from inactive OSSA investigations discovered during the 1990 census (phase two) are briefly discussed individually.

King, Joseph H.↗
NASA NTRS2005

Evaluation of a New Cloud Droplet Activation Parameterization wtih in Situ Data from CRYSTAL-FACE and CSTRIPE

The accuracy of the 2003 prognostic, physically based aerosol activation parameterization of A. Nenes and J. H. Seinfeld (NS) with modification introduced by C. Fountoukis and A. Nenes in 2005 (modified NS) is evaluated against extensive microphysical data sets collected on board the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) Twin Otter aircraft for cumuliform and stratiform clouds of marine and continental origin. The cumuliform cloud data were collected during NASA's Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE, Key West, Florida, July 2002), while the stratiform cloud data were gathered during Coastal Stratocumulus Imposed Perturbation Experiment (CSTRIPE, Monterey, California, July 2003). In situ data sets of aerosol size distribution, chemical composition, and updraft velocities are used as input for the NS parameterization, and the evaluation is carried out by comparing predicted cloud droplet number concentrations (CDNC) with observations. This is the first known study in which a prognostic cloud droplet activation parameterization has been evaluated against a wide range of observations. On average, predicted droplet concentration in adiabatic regions is within -20% of observations at the base of cumuliform clouds and -30% of observations at different altitudes throughout the stratiform clouds, all within experimental uncertainty. Furthermore, CDNC is well parameterized using either a single mean updraft velocity w or by weighting droplet nucleation rates with a Gaussian probability density function of w. This study suggests that for nonprecipitating warm clouds of variable microphysics, aerosol composition, and size distribution the modified NS parameterization can accurately predict cloud droplet activation and can be successfully implemented for describing the aerosol activation process in global climate models.

Meskhidze, Nicholas↗
DOE OSTI2022

Improved evaluation of safeguards parameters from spent fuel measurements with the Differential Die-Away (DDA) instrument

The Differential Die-Away (DDA) technique is a highly sensitive non-destructive assay method for characterizing and detecting the presence of fissile material within an item of interest. DDA utilizes a series of pulses from a neutron generator (NG) to actively interrogate an item of interest. The die-away time of the neutron population induced by this active interrogation and the integral of the total differential die-away signal can be used to characterize items such as nuclear waste drums and spent nuclear fuel assemblies. In this work, Los Alamos National Laboratory (LANL) conceptualized, designed, and fabricated a DDA instrument that was deployed for field test measurements at the Central Interim Storage Facility for Spent Nuclear Fuel (Clab) in Oskarshamn, Sweden. The instrument performed multiple static measurements at fixed locations and dynamic axial scans of 15 pressurized water reactor (PWR) and 10 boiling water reactor (BWR) spent fuel assemblies, collecting both passive and active measurement data. The static assays of the assemblies measured the differential die-away signal, die-away time, and total passive neutron emission rate to create calibration curves for the evaluation of assembly multiplication, burnup, initial enrichment, effective fissile mass, and total elemental plutonium mass. Each calibration curve was optimized by minimizing the relative root mean square error (RRMSE) of assembly assay results compared to declared assembly parameters. The same quantities were also measured with the axial scans, and the resulting data were applied in two ways: (1) in the creation of calibration curves to improve evaluation of the same safeguards parameters as static assays, and (2) for comparison to simulation. In most cases, across both PWR and BWR assemblies, axial scan data improved the estimation of the above parameters, quantified by decreasing the calibration curve RRMSE. These axial scan results demonstrate the ability of the DDA instrument and analysis method to characterize spent PWR and BWR fuel as well as, or better than, a static assay of the same assembly. Furthermore, the DDA instrument’s unique ability to obtain both active and passive data in a single, axial scan of an entire spent fuel assembly represents a more efficient and accurate way of assaying spent fuel for verification purposes. These results represent a significant advancement for characterizing spent nuclear fuel compared to current technologies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Status of LDEF radiation modeling

The current status of model prediction and comparison with LDEF radiation dosimetry measurements is summarized with emphasis on major results obtained in evaluating the uncertainties of present radiation environment model. The consistency of results and conclusions obtained from model comparison with different sets of LDEF radiation data (dose, activation, fluence, LET spectra) is discussed. Examples where LDEF radiation data and modeling results can be utilized to provide improved radiation assessments for planned LEO missions (e.g., Space Station) are given.

Watts, John W.↗
DOE OSTI2016

Low Activity Waste Glass Waste Form Data Package for Hanford's Integrated Disposal Facility Performance Assessment - 16480

A Direct Feed Low Activity Waste (DFLAW) flowsheet has been initiated to begin immobilization of Hanford tank wastes. In the DFLAW configuration, a pretreatment system will segregate the high level and the low activity wastes (LAW). The LAW will be immobilized in the Waste Treatment Plant (WTP) and disposed of in Hanford's Integrated Disposal Facility (IDF). To obtain authorization to dispose of wastes in the IDF, a Performance Assessment (PA) must be completed in accordance with DOE Order 435.1. The PA shall include calculations of potential doses to representative future members of the public and potential releases from the facility to provide a reasonable expectation that performance objectives will not be exceeded as a result of operation and closure of the facility. To support the development of the PA, data from ILAW glass testing are needed to model the long term release of contaminants over the compliance period and verify that impacts to groundwater quality will be within performance objective limits. Washington River Protection Solutions is conducting an ILAW glass testing program to produce the required data. This program is a combined effort involving National Laboratories with known expertise in glass waste form research. The work involves accelerated testing to develop parameters that can be used in computer simulations of glass corrosion and contaminant release in the IDF environment. The results of this work will be compiled in an ILAW glass waste form performance data package for the IDF PA. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Active Subspace Methods for Data-Intensive Inverse Problems

Fostered by advances in computing, simulation and data science have emerged as the third and fourth paradigms enabling scientific discovery. Many mathematical challenges arise when integrating these paradigms to produce new knowledge. One of the most important challenges is the inverse or calibration problem: find the inputs of a simulation such that its outputs agree with a given set of measurements. As both the cost of the complex simulations and the volume of measurement data sets increase, intuition-driven trial-and-error methods for calibration quickly become untenable; modern scientists need more computationally efficient and mathematically rigorous methods. When measurements and simulated predictions contain uncertainty, the Bayesian perspective on statistical inference provides a popular mathematical framework for developing computational methods to solve inverse problems. Markov chain Monte Carlo (MCMC) methods are a mainstay of this framework; they characterize a probability distribution on the space of model inputs that is conditioned on the given measurements. However, despite recent advances, MCMC methods remain impractical for expensive simulations with more than a handful of inputs. At its heart, MCMC searches the space of inputs for corresponding outputs that match measurements, and so it is afflicted with the curse of dimensionality. Additionally, MCMC methods become less efficient as the volume of the measurement data increases, particularly if the measurements are redundant. To make MCMC—and Bayesian methods, in general—amenable to today’s computer models with millions of inputs and terabytes of measurement data, one must devise methods to reduce the dimension of both the simulation inputs and the measurements. For many models used in practice, the outputs vary primarily on a low-dimensional manifold of the nominally high-dimensional input space. Recently developed active subspace methods discover this low-dimensional manifold and exploit it to enable analyses typically suited for low-dimensional settings (e.g., statistical inversion of complex systems). We hypothesize that active subspace methods can provide the necessary dimension reduction, enabling existing Bayesian methods to find solutions for a large class of otherwise intractable statistical inverse problems. We will test the hypothesis with a series of mathematical analyses and computational experiments that will proceed along three research veins: (i) integrating active subspace methods into methods for statistical inversion, (ii) addressing current challenges in active subspace methods, and (iii) incorporating methods for nonlinear dimensionality reduction into active subspace methods. We will apply the methods we develop to real inverse problems in chemical kinetics and turbulent flame modeling. Our team combines expertise in methods for inverse problems, dimension reduction, and reduced order modeling. With a history of active collaboration and thoughtful engagement, we bring enthusiasm and fresh perspectives to a well studied subject. We are excited by the potential opportunity to work together to extend and apply active subspace methods to data-intensive inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Active Subspace Methods for Data-Intensive Inverse Problems (Final Report)

Fostered by advances in computing, simulation and data science have emerged as the third and fourth paradigms enabling scientific discovery. Many mathematical challenges arise when integrating these paradigms to produce new knowledge. One of the most important challenges is the inverse or calibration problem: find the inputs of a simulation such that its outputs agree with a given set of measurements. As both the cost of the complex simulations and the volume of measurement data sets increase, intuition-driven trial-and-error methods for calibration quickly become untenable; modern scientists need more computationally efficient and mathematically rigorous methods. When measurements and simulated predictions contain uncertainty, the Bayesian perspective on statistical inference provides a popular mathematical framework for developing computational methods to solve inverse problems. Markov chain Monte Carlo (MCMC) methods are a mainstay of this framework; they characterize a probability distribution on the space of model inputs that is conditioned on the given measurements. However, despite recent advances, MCMC methods remain impractical for expensive simulations with more than a handful of inputs. At its heart, MCMC searches the space of inputs for corresponding outputs that match measurements, and so it is afflicted with the curse of dimensionality. Additionally, MCMC methods become less efficient as the volume of the measurement data increases, particularly if the measurements are redundant. To make MCMC—and Bayesian methods, in general—amenable to today’s computer models with millions of inputs and terabytes of measurement data, one must devise methods to reduce the dimension of both the simulation inputs and the measurements. For many models used in practice, the outputs vary primarily on a low-dimensional manifold of the nominally high-dimensional input space. Recently developed active subspace methods discover this low-dimensional manifold and exploit it to enable analyses typically suited for low-dimensional settings (e.g., statistical inversion of complex systems). We hypothesize that active subspace methods can provide the necessary dimension reduction, enabling existing Bayesian methods to find solutions for a large class of otherwise intractable statistical inverse problems. We will test the hypothesis with a series of mathematical analyses and computational experiments that will proceed along three research veins: (i) integrating active subspace methods into methods for statistical inversion, (ii) addressing current challenges in active subspace methods, and (iii) incorporating methods for nonlinear dimensionality reduction into active subspace methods. We will apply the methods we develop to real inverse problems in chemical kinetics and turbulent flame modeling. Our team combines expertise in methods for inverse problems, dimension reduction, and reduced order modeling. With a history of active collaboration and thoughtful engagement, we bring enthusiasm and fresh perspectives to a well studied subject. We are excited by the potential opportunity to work together to extend and apply active subspace methods to data-intensive inverse problems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Inter-Calibration of EIS, XRT and AIA using Active Region and Bright Point Data

Certain limitations in our solar instruments have created the need to use several instruments together for long term and/or large field of view studies. We will, therefore, present an intercalibration study of the EIS, XRT and AIA instruments using active region and bright point data. We will use the DEMs calculated from EIS bright point observations to determine the expected AIA and XRT intensities. We will them compare to the observed intensities and calculate a correction factor. We will consider data taken over a year to see if there is a time dependence to the correction factor. We will then determine if the correction factors are valid for active region observations.

Mulu-Moore, Fana M.↗