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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Foundational Performance Analyses of Pressure Gain Combustion Thermodynamic Benefits for Gas Turbines

A methodology is described whereby the work extracted by a turbine exposed to the fundamentally nonuniform flowfield from a representative pressure gain combustor (PGC) may be assessed. The method uses an idealized constant volume cycle, often referred to as an Atkinson or Humphrey cycle, to model the PGC. Output from this model is used as input to a scalable turbine efficiency function (i.e., a map), which in turn allows for the calculation of useful work throughout the cycle. Integration over the entire cycle yields mass-averaged work extraction. The unsteady turbine work extraction is compared to steady work extraction calculations based on various averaging techniques for characterizing the combustor exit pressure and temperature. It is found that averages associated with momentum flux (as opposed to entropy or kinetic energy) provide the best match. This result suggests that momentum-based averaging is the most appropriate figure-of-merit to use as a PGC performance metric. Using the mass-averaged work extraction methodology, it is also found that the design turbine pressure ratio for maximum work extraction is significantly higher than that for a turbine fed by a constant pressure combustor with similar inlet conditions and equivalence ratio. Limited results are presented whereby the constant volume cycle is replaced by output from a detonation-based PGC simulation. The results in terms of averaging techniques and design pressure ratio are similar.

Paxson, Daniel E.↗
NASA NTRS2013

Bulk Insolation Models as Predictors for Locations for High Lunar Hydrogen Concentrations

In this study we consider the bulk effects of surface illumination on topography (insolation) and the possible thermodynamic effects on the Moon's hydrogen budget. Insolation is important as one of the dominant loss processes governing distributions of hydrogen volatiles on the Earth, Mars and most recently Mercury. We evaluated three types of high latitude > 65 deg., illumination models that were derived from the Lunar Observing Laser Altimetry (LOLA) digital elevation models (DEM)'s. These models reflect varying accounts of solar flux interactions with the Moon's near-surface. We correlate these models with orbital collimated epithermal neutron measurements made by the Lunar Exploration Neutron Detector (LEND). LEND's measurements derive the Moon's spatial distributions of hydrogen concentration. To perform this analysis we transformed the topographic model into an insolation model described by two variables as each pixels 1) slope and 2) slope angular orientation with respect to the pole. We then decomposed the illumination models and epithermal maps as a function of the insolation model and correlate the datasets.

Hydrogen Concentrations↗
NASA NTRS2015

Epithermal Neutron Evidence for a Diurnal Surface Hydration Process in the Moon's High Latitudes

We report evidence from epithermal neutron flux observations that show that the Moon's high latitude surfaces are being actively hydrated, dehydrated and rehydrated in a diurnal cycle. The near-surface hydration is indicated by an enhanced suppression of the lunar epithermal neutron leakage flux on the dayside of the dawn terminator on poleward-facing slopes (PFS). At 0600 to 0800 local-time, hydrogen concentrations within the upper 1 meter of PFS are observed to be maximized relative to equivalent equator-facing slopes (EFS). During the lunar day surface hydrogen concentrations diminish towards dusk and then rebuild overnight. Surface hydration is determined by differential comparison of the averaged EFS to PFS epithermal neutron count rates above +/- 75 deg latitude. At dawn the contrast bias towards PFS is consistent with at least 15 to 25 parts-per-million (ppm) hydrogen that dissipates by dusk. We review several lines of evidence derived from temperature and epithermal neutron data by a correlated analysis of observations from the Lunar Reconnaissance Orbiter's (LRO) Lunar Exploration Neutron Detector (LEND) that were mapped as a function of lunar local-time, Lunar Observing Laser Altimeter (LOLA) topography and Diviner (DLRE) surface temperature.

diurnal cycles↗
NASA NTRS2015

NASA's Meteoroid Environments Office's Response to Three Significant Bolide Events Over North America

Being the only U.S. Government entity charged with monitoring the meteor environment, the Meteoroid Environment Office has deployed a network of all sky and wide field meteor cameras, along with the appropriate software tools to quickly analyze data from these systems. However, the coverage of this network is still quite limited, forcing the incorporation of data from other cameras posted to the internet in analyzing many of the fireballs reported by the public and media. A procedure has been developed that determines the analysis process for a given fireball event based on the types and amount of data available. The differences between these analysis process will be explained and outlined by looking at three bolide events, all of which were large enough to produce meteorites. The first example is an ideal event - a bright meteor that occurred over NASA's All Sky Camera Network on August 2, 2014. With clear video of the event from various angles, a high-accuracy trajectory, beginning and end heights, orbit and approximate brightness/size of the event are able to be found very quickly using custom software. The bolide had the potential to have dropped meteorites, so dark flight analysis and modeling was performed, allowing potential fall locations to be mapped as a function of meteorite mass. The second case study was a bright bolide that occurred November 3, 2014 over West Virginia. This was just north of the NASA southeastern all-sky network, and just south of the Ohio-Pennsylvania network. This case study showcases the MEO's ability to use social media and various internet sources to locate videos of the event from obscure sources (including the Washington Monument) for anything that will permit a determination of a basic trajectory and fireball light curve The third case study will highlight the ability to use doppler weather radar in helping locate meteorites, which enable a definitive classification of the impactor. The input data and analysis steps differ for each case study, but the goals remain the same - a trajectory, orbit, and mass estimate for the bolide within hours of the event, and, for events with a high probability of producing meteorites, a location of the strewn field within a day.

Blaauw, Rhiannon C.↗
NASA NTRS2015

The Rapid Response Radiation Survey (R3S) Mission Using the HiSat Conformal Satellite Architecture

The Rapid Response Radiation Survey (R3S) experiment, designed as a quick turnaround mission to make radiation measurements in Low Earth Orbit (LEO), will fly as a hosted payload in partnership with NovaWurks using their Hyper-integrated Satlet (HISat) architecture. The need for the mission arises as the Nowcast of Atmospheric Ionization Radiation for Aviation Safety (NAIRAS) model moves from a research effort into an operational radiation assessment tool. Currently, airline professionals are the second largest demographic of radiation workers and to date their radiation exposure is undocumented in the USA. The NAIRAS model seeks to fill this information gap. The data collected by R3S, in addition to the complementary data from a NASA Langley Research Center (LaRC) atmospheric balloon mission entitled Radiation Dosimetry Experiment (RaD-X), will validate exposure prediction capabilities of NAIRAS. The R3S mission collects total dose and radiation spectrum measurements using a Teledyne μDosimeter and a Liulin-6SA2 LED spectrometer. These two radiation sensors provide a cross correlated radiometric measurement in combination with the Honeywell HMR2300 Smart Digital Magnetometer. The magnetometer assesses the Earth's magnetic field in the LEO environment and allows radiation dose to be mapped as a function of the Earth's magnetic shielding. R3S is also unique in that the radiation sensors will be exposed on the outer surface of the spacecraft, possibly making this the first measurements of the LEO radiation environment with bare sensors. Viability of R3S as an extremely fast turnaround mission is due, in part, to the nature of the robust, well-defined interfaces of the conformal satellite HiSat Architecture. The HiSat architecture, which was developed with the support of the Defense Advanced Research Projects Agency's (DARPA's) Phoenix Program, enabled the R3S system to advance from the first concept to delivery of preliminary design review (PDR) level documents in 29 calendar days. The architecture allows for interface complexities between the specific devices and the satellite bus to be resolved in a standardized interface control document (ICD). The ICD provided a readymade framework to interface to the modular satellite bus. This modularity allowed for approximately 90% of the R3S system to be designed and fabricated in two months without constraint of the hosting satellite's development cycle. This paper discusses the development of the R3S experiment as made possible by use of the HiSat architecture. The system design and operational modes of the experiment are described, as well as the experiment interfaces to the HiSat satellite via the user defined adapter (UDA) provided by NovaWurks. This paper outlines the steps taken by the project to execute the R3S mission in the 4 months of design, build, and test. Additionally portrayed is the ground work done at LaRC to posture the organization for a fast response and the process by which the opportunity was identified as aligning with key strategic goals. Finally, a description of the engineering process is provided, including the use of facilitated rapid/concurrent engineering sessions, the associated documentation, and the review process employed.

Miller, Nathanael A.↗
NASA NTRS2019

Consistency Between NASS Surveyed Soil Moisture Conditions and SMAP Soil Moisture Observations

The USDA National Agricultural Statistics Survey (NASS) collects and publishes crop growth status and soil moisture conditions in major US agricultural regions. The operationally-produced weekly reports are based on survey information. The surveys are based on visual assessments and ? in the case of soil moisture ? report soil moisture levels in one of four categories (Very Short, Short, Adequate and Surplus). In this study, we show that these reports have remarkable correspondence with the NASA Soil Moisture Active Passive (SMAP) Level-4 Soil Moisture (L4SM) product. This consistency allows the combining the two distinct types of data to produce a value-added combination, which is mapped fields rather than State-by-State tables and it is refreshed daily rather than weekly. In this study classification thresholds are derived for L4SM by mapping cumulative distribution functions of L4SM surface and root-zone SM to the categorical NASS SM conditions. The results show that, year-over-year, the SMAP cumulative SM distributions are consistent with the NASS SM conditions and, furthermore, that the temporal evolution of the SMAP-derived thresholds is consistent with the seasonal crop growth cycles from year to year. The results signify that the SMAP SM retrievals are relatable to SM estimation conducted in agriculture by land managers and farmers, which underlines the general applicability of the SMAP data.

Andreas Colliander↗
NASA NTRSDate not supplied

"Giovanni at 20: Consistency and Persistency in Making Earth Remote Sensing Data Available (and Useful) to the Earth Science Community"

Since its creation in the year 2000, the NASA Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) has been an exemplar of how to provide remotely-sensed satellite data and related Earth science datasets to a broad and globally diverse researcher community. One of the hallmarks of Giovanni system usage is that it is common to see practitioners of many branches of science – particularly those in fields not traditionally associated with remote-sensing data, such as animal behavior and paleooceanography – both accessing and employing datasets which the system provides. This usage pattern is attested to by the diversity of published science citing Giovanni. Giovanni has evolved through several versions, each of which increased analytical and visualization options while also enhancing ease-of-use. Information resources supporting Giovanni from the Goddard Earth Sciences Data and Information Services Center (GES DISC), which hosts the system, start with basic mapping and plotting functions and extend to “How-to” recipes demonstrating interusability with other data analysis systems and software. Giovanni is now being developed for use in a cloud environment, potentially expanding datasets the system can be applied to, and also improving performance for data having high spatial and temporal resolution. This presentation covers the system’s historical success with interesting examples of Giovanni-citing research, and will apply its current capabilities to a multi-dataset examination of derecho events associated with mesoscale convective phenomena in the summer of 2020, indicating how Giovanni is prepared for ongoing support of Earth science in a changing world.

Giovanni Derecho visualization↗
NASA NTRS2021

Landsat Derived Bathymetry of Lakes on the Arctic Coastal Plan of Northern Alaska

The Pleistocene sand sea on the Arctic Coastal Plain (ACP) of northern Alaska is underlain by anancient sand dune field, a geological feature that affects regional lake characteristics. Many of these lakes, whichcover approximately 20 % of the Pleistocene sand sea, are relatively deep (up to 25 m). In addition to the nat-ural importance of ACP sand sea lakes for water storage, energy balance, and ecological habitat, the need forwinter water for industrial development and exploration activities makes lakes in this region a valuable resource.However, ACP sand sea lakes have received little prior study. Here, we collect in situ bathymetric data to test12 model variants for predicting sand sea lake depth based on analysis of Landsat-8 Operational Land Imager(OLI) images. Lake depth gradients were measured at 17 lakes in midsummer 2017 using a Humminbird 798ciHD SI Combo automatic sonar system. The field-measured data points were compared to red–green–blue (RGB)bands of a Landsat-8 OLI image acquired on 8 August 2016 to select and calibrate the most accurate spectral-depth model for each study lake and map bathymetry. Exponential functions using a simple band ratio (withbands selected based on lake turbidity and bed substrate) yielded the most successful model variants. For eachlake, the most accurate model explained 81.8 % of the variation in depth, on average. Modeled lake bathymetrieswere integrated with remotely sensed lake surface area to quantify lake water storage volumes, which rangedfrom 1.056×10−3to 57.416×10−3km3. Due to variations in depth maxima, substrate, and turbidity betweenlakes, a regional model is currently infeasible, rendering necessary the acquisition of additional in situ datawith which to develop a regional model solution. Estimating lake water volumes using remote sensing will fa-cilitate better management of expanding development activities and serve as a baseline by which to evaluatefuture responses to ongoing and rapid climate change in the Arctic. All sonar depth data and modeled lakebathymetry rasters can be freely accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) andhttps://doi.org/10.18739/A2HT2GC6G (Simpson, 2019), respectively.

Claire E Simpson↗
NASA NTRS2025

On the Stability Analysis of Astrophysical Cooling Functions

To model the temperature evolution of optically thin astrophysical environments at MHD scales, radiative and collisional cooling rates are typically either pretabulated or fit into a functional form and then input into MHD codes as a radiative loss function. Thermal balance requires estimates of the analogous heating rates, which are harder to calculate, and due to uncertainties in the underlying dissipative heating processes these rates are often simply parameterized. The resulting net cooling function defines an equilibrium curve that varies with density and temperature. Such cooling functions can make the gas prone to thermal instability (TI), which will cause departures from equilibrium. There has been no systematic study of thermally unstable parameter space for nonequilibrium states. Motivated by our recent finding that there is a related linear instability, catastrophic cooling instability, that can dominate over TI, here we carry out such a study. We show that Balbus instability criteria for TI can be used to define a critical cooling rate, Λc, that permits a nonequilibrium analysis of cooling functions through the mapping of TI zones. We furthermore illustrate how thermal conduction modifies the shape of TI zones. Upon applying a Λc-based stability analysis to coronal loop simulations, we find that loops undergoing periodic episodes of coronal rain formation are linearly unstable to catastrophic cooling instability, while TI is stabilized by thermal conduction.

Amanda Stricklan↗
DOE OSTI2023

Control of matrix converters using machine learning

A method of controlling a matrix converter system is provided. The method includes receiving an operating condition and consulting a trained Q-data structure for reward values associated with respective switching states of the switching matrix for an operating state that corresponds to the operating condition. The Q-data structure is trained using Q-learning to map a reward value predicted for respective switching states to respective discrete operating states. The method further includes sorting the reward values predicted for the respective switching states mapped to the operating state that corresponds to the operating condition, selecting a subset of the set of the mappings as a function of a result of sorting the reward values associated with the switching states of the operating state, evaluating each switching state included in the subset, and selecting an optimal switching state for the operating condition based on a result of evaluating the switching states of the subset.

Chamie, Mahmoud El↗
DOE OSTI2025

Curiosity driven exploration to optimize structure–property learning in microscopy

Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Mappings and accuracy for Chebyshev pseudo-spectral approximations

The effect of mappings on the approximation, by Chebyshev collocation, of functions which exhibit localized regions of rapid variation is studied. A general strategy is introduced whereby mappings are adaptively constructed which map specified classes of rapidly varying functions into low order polynomials which can be accurately approximated by Chebyshev polynomial expansions. A particular family of mappings constructed in this way is tested on a variety of rapidly varying functions similar to those occurring in approximations. It is shown that the mapped function can be approximated much more accurately by Chebyshev polynomial approximations than in physical space or where mappings constructed from other strategies are employed.

Bayliss, Alvin↗
NASA NTRS1992

Mappings and accuracy for Chebyshev pseudo-spectral approximations

The effect of mappings on the approximation, by Chebyshev collocation, of functions which exhibit localized regions of rapid variation is studied. A general strategy is introduced whereby mappings are adaptively constructed which map specified classes of rapidly varying functions into low order polynomials which can be accurately approximated by Chebyshev polynomial expansions. A particular family of mappings constructed in this way is tested on a variety of rapidly varying functions similar to those occurring in approximations. It is shown that the mapped function can be approximated much more accurately by Chebyshev polynomial approximations than in physical space or where mappings constructed from other strategies are employed.

Bayliss, Alvin↗
NASA NTRS1984

A model function for ocean radar cross sections at 14.6 GHz

The relationship between the ocean's normalized radar cross section (NRCS) at 14.6 GHz and the surface wind vector is derived using the 3 months of Seasat microwave scatterometer (SASS) measurements. The derivation is based on the statistics of the SASS observations, and no in situ measurements are required, other than a mean global wind speed, which comes from climatology. The frequency distribution of the global wind vectors observed by SASS is assumed to be a bivariate normal probability function. A NRCS model function is found that maps the assumed wind vector statistics into the observed SASS NRCS statistics. This function is compared with a NRCS model coming from the Joint Air Sea Interaction Experiment (JASIN) and with aircraft scatterometer measurements. The results indicate that the statistically derived NRCS model is an improvement over the JASIN model, which was based on a limited number of in situ anemometer measurements.

Wentz, F. J.↗
DOE OSTI2023

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Comparative mapping of Pluto's sub-Charon hemisphere - Three least squares models based on mutual event lightcurves

Observations of Charon transits are used here to derive preliminary maps of Pluto's sub-Charon hemisphere. Three models are used to describe the brightness of Pluto's surface as functions of latitude and longitude. Mapping results are presented using spherical harmonic functions, polynomial functions, and finite elements. A smoothing algorithm applied to the maps is described and the validity and resolution of the maps is tested by reconstruction from synthetic data. A preliminary finding from the maps is that the south polar region has the highest albedo of any location on the planet.

Young, Eliot F.↗
DOE OSTI2020

Integration of Soft Data Into Geostatistical Simulation of Categorical Variables

Uncertain or indirect “soft” data, such as geologic interpretation, driller’s logs, geophysical logs or imaging, offer potential constraints or “soft conditioning” to stochastic models of discrete categorical subsurface variables in hydrogeology such as hydrofacies. Previous bivariate geostatistical simulation algorithms have not fully addressed the impact of data uncertainty in formulation of the (co) kriging equations and the objective function in simulated annealing (or quenching). This paper introduces the geostatistical simulation code tsim-s, which accounts for categorical data uncertainty through a data “hardness” parameter. In generating geostatistical realizations with tsim-s, the uncertainty inherent to soft conditioning is factored into both 1) the data declustering and spatial correlation functions in cokriging and 2) the acceptance probability for change of category in simulated quenching. The degree or sensitivity to which soft data conditions a realization as a function of hardness can be quantified by mapping category probabilities derived from multiple realizations. In addition to point or borehole data, arrays of data (e.g., as derived from a depth-dependency function, probability map, or “prior realization”) can be used as soft conditioning. The tsim-s algorithm provides a theoretically sound and general framework for integrating datasets of variable location, resolution, and uncertainty into geostatistical simulation of categorical variables. A practical example shows how tsim-s is capable of generating a large-scale three-dimensional simulation including curvilinear features.

54 ENVIRONMENTAL SCIENCES↗