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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Evaluation of Sentinel-1A Data For Above Ground Biomass Estimation in Different Forests in India

Use of remote sensing data for mapping and monitoring of forest biomass across large spatial scales can aid in addressing uncertainties in carbon cycle. Earlier, several researchers reported on the use of Synthetic Aperture Radar (SAR) data for characterizing forest structural parameters and the above ground biomass estimation. However, these studies cannot be generalized and the algorithms cannot be applied to all types of forests without additional information on the forest physiognomy, stand structure and biomass characteristics. The radar backscatter signal also saturates as forest parameters such as biomass and the tree height increase. It is also not clear how different polarizations (VV versus VH) impact the backscatter retrievals in different forested regions. Thus, it is important to evaluate the potential of SAR data in different landscapes for characterizing forest structural parameters. In this study, the SAR data from Sentinel-1A has been used to characterize forest structural parameters including the above ground biomass from tropical forests of India. Ground based data on tree density, basal area and above ground biomass data from thirty-eight different forested sites has been collected to relate to SAR data. After the pre-processing of Sentinel 1-A data for radiometric calibration, geo-correction, terrain correction and speckle filtering, the variability in the backscatter signal in relation tree density, basal area and above biomass density has been investigated. Results from the curve fitting approach suggested exponential model between the Sentinel-1A backscatter versus tree density and above ground biomass whereas the relationship was almost linear with the basal area in the VV polarization mode. Of the different parameters, tree density could explain most of the variations in backscatter. Both VV and VH backscatter signals could explain only thirty and thirty three percent of variation in above biomass in different forest sites of India. Results also suggested saturation of the Sentinel-1A backscatter signal around hundred tonnes per hectare for VV polarization and one hundred and forty five tonnes per hectare for VH polarization. The presentation will highlight the above results in addition to potentials and limitations of Sentinel-1A data for retrieving forest structural parameters. Also, background information on different forest types of India, biomass variations and forest type mapping efforts in the region will be presented.

Data↗
DOE OSTI2025

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine↗
DOE OSTI2020

Comparison Study of Upper Subcritical Limits Derived Using Sensitivity/Uncertainty Tools Case Studies of Benchmarks and Applications

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP ® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. The initial comparison involves four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been: 1. modeled independently by LANL, IRSN, and ORNL based upon information provided in the ICSBEP Handbook, 2. are common in S/U libraries for LANL, IRSN, and ORNL, 3. span a range of energy spectrum and fissile material, and 4. taken as applications for the purposes of this study and therefore excluded from use as a benchmark for calculating the upper subcritical limit. Results presented in this paper have been computed using covariance data for all isotopes in ENDF/BVII.0 using a 44-group energy structure. Benchmarks in the Whisper library were run in MCNP6.2 using 100,000 neutrons per cycle, skipping 100 cycles for 500 active cycles. Reference 10 also compares the results for baseline USL with an order of magnitude greater neutrons, using the same total number of cycles with 1,000,000 neutrons per cycle. Subsequent to the results presented in Reference 10 changes were made to the benchmark library, as discussed in Reference 11. Newer results using the revised benchmark library are presented herein.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Comparison Study of Upper Subcritical Limits Derived Using Sensitivity/Uncertainty Tools: Case Studies of U233-SOL-THERM-001-001, MIX-COMP-THERM-001-001, IEU-MET-FAST-002-001, LEU-COMP-THERM-001-001, LEU-SOL-THERM-004-001

Neutron transport methods used to establish subcriticality require validation by comparison to critical experiments considered to be benchmarks. Whisper is a sensitivity/uncertainty analysis tool developed to assist with the task of validation in nuclear criticality safety. Details on the Whisper methodology can be found in References 1-3 on the MCNP® reference collection website at https://mcnp.lanl.gov. Whisper-1.0 was originally developed in 2014 and used to assist with nuclear criticality safety validation at Los Alamos National Laboratory. Whisper was upgraded in 2016 to Whisper-1.1 and prepared for release with MCNP6.2 [References 3-5]. Whisper contains a library of over 1100 critical experiment benchmarks and quantifies neutronic similarity of an application to benchmarks in the library. Using highest similarity benchmarks, Whisper computes a calculational margin (CM) encompassing of the worst-case bias and bias uncertainty at a 99% confidence level for each application. In addition, portions of the margin of subcriticality (MOS) for nuclear data uncertainty and potential code errors are computed. The baseline upper subcritical limit (USL) computed by Whisper is comprised of the CM, MOS nuclear data , and MOS code errors . The Whisper baseline USL is absent a portion of the MOS due to the area of application, which is applied based upon judgment by the criticality safety analyst. An objective of this paper is to present the baseline USL, CM and portions of the MOS as computed by Whisper for comparison with similar sensitivity/uncertainty tools, such as those used by IRSN and ORNL. An initial comparison involved four critical experiment benchmarks: HEU-MET-FAST-013-001, HEU-SOLTHERM-001-008, PU-MET-FAST-022-001, AND PU-SOL-THERM-001-001, which have been documented in References 10-13. This study extends the comparison to include cases U233-SOL-THERM-001-001, MIX-COMP-THERM-001-001, IEU-MET-FAST-002-001, LEU-COMP-THERM-001-001, LEU-SOL-THERM- 004-001.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

H2@Scale Hydrogen Economic Potential Supply and Demand Locations

This data release provides estimates of hydrogens economic potential for possible hydrogen applications and production technologies by geographic location for various scenarios, as described in "The Technical and Economic Potential of the H2@Scale Concept within the United States". We define the economic potential as the quantity of hydrogen at an equilibrium price at which suppliers are willing to sell and consumers are willing to buy the same quantity of hydrogen.

alternative energy↗
NASA NTRS2003

Techniques for the Installation of Internal Fiber Optic Instrumentation on an 11-Inch Hybrid Motor Test Bed

The recent developments in Fabry-Perot fiber optic instruments have resulted in accurate transducers with some of the physical characteristics required for use in obtaining internal data from solid rocket motors. These characteristics include small size, non-electrical excitation, and immunity to electro-magnetic interference. These transducers have not been previously utilized in this environment due to the high temperatures typically encountered. A series of tests were conducted using a 1 1-Inch Hybrid test bed to develop installation techniques that will allow the fiber optic instruments to survive and obtain data for a short period of time following the motor ignition. The installation methods developed during this test series have the potential to allow data to be acquired in the motor chamber, propellant bore, and nozzle during the ignition transient. These measurements would prove to be very useful in the characterization of current motor designs and provide insight into the requirements for further refinements. The process of developing these protective methods and the installation techniques used to apply them is summarized.

Cornelius, Michael↗
NASA NTRS2024

Enabling the Assimilation of CrIS Shortwave Infrared Observations in Global NWP at NOAA. Part II: OSEs and Results

The assimilation of data from hyperspectral infrared sounders in global data assimilation systems has historically been focused on observations in the longwave infrared (LWIR) region of the spectrum (650-1100 cm−1), despite the often concurrent availability of measurements from the shortwave infrared (SWIR) region of the spectrum (2150-2550 cm−1), because issues (like solar effects) have generally prevented the assimilation of SWIR observations. Recent advances in radiative transfer models have worked to address some of the previous challenges in simulating SWIR observations, and the assimilation of SWIR data (e.g. from potential future small-satellites) is now a feasible prospect. Still, a better understanding of how these observations perform in a data assimilation system and impact resulting analyses and NWP forecasts is necessary. In this study, the value of SWIR observations in global NWP is assessed by assimilating SWIR observations from the Cross-track Infrared Sounder (CrIS) in NOAA’s Global Data Assimilation System (GDAS). The methodologies used to enable the assimilation of these observations, including the implementation of a scene-dependent observation error and the enhancement of quality control procedures, are discussed, as are the results of Observing System Experiments (OSEs) conducted to evaluate the impact of assimilating SWIR observations on forecast skill. The overall results show that SWIR assimilation produces similar forecast impacts to LWIR assimilation. The ability to demonstrate that the assimilation or SWIR observations in NWP is a realistic prospect may help to shape future constellations of small-satellites to serve as a beneficial complement to the current constellation if hyperspectral IR sounders.

Erin Jones↗
DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗
NASA NTRS1988

A simulator investigation of the use of digital data link for pilot/ATC communications in a single pilot operation

Studies have shown that radio communications between pilots and air traffic control contribute to high pilot workload and are subject to various errors. These errors result from congestion on the voice radio channel, and missed and misunderstood messages. The use of digital data link has been proposed as a means of reducing this workload and error rate. A critical factor, however, in determining the potential benefit of data link will be the interface between future data link systems and the operator of those systems, both in the air and on the ground. The purpose of this effort was to evaluate the pilot interface with various levels of data link capability, in simulated general aviation, single-pilot instrument flight rule operations. Results show that the data link reduced demands on pilots' short-term memory, reduced the number of communication transmissions, and permitted the pilots to more easily allocate time to critical cockpit tasks while receiving air traffic control messages. The pilots who participated unanimously indicated a preference for data link communications over voice-only communications. There were, however, situations in which the pilot preferred the use of voice communications, and the ability for pilots to delay processing the data link messages, during high workload events, caused delays in the acknowledgement of messages to air traffic control.

Hinton, David A.↗
NASA NTRS2021

Single-Turnover Variable Chlorophyll Fluorescence as a Tool for Assessing Phytoplankton Photosynthesis and Primary Productivity: Opportunities, Caveats and Recommendations

Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms.

variable chlorophyll fluorescence↗
NASA NTRS1995

Trend analysis of in-situ spectral reflectance data from the Thermal Control Surfaces Experiment (TCSE)

The Thermal Control Surfaces Experiment (TCSE) on the LDEF was a comprehensive experiment that combined in-space measurements with extensive pre- and post-flight analyses of thermal control surfaces to determine the effects of exposure to the low earth orbit (LEO) space environment. The TCSE is the first space experiment to directly measure in-situ total hemispherical reflectance of thermal control surfaces in the same way they are routinely measured in the laboratory. In-space optical measurements performed by the TCSE provide the unique opportunity for trend analysis of the performance of materials in the space environment. Such trend analysis of flight data offers the potential to develop an empirical life time prediction model for several thermal control surfaces. For material research, trend analysis of the TCSE flight data, particularly the spectral data, can provide insight into the damage mechanisms of space exposure. Trend analysis for the TCSE samples has been limited to those materials that were not significantly eroded by the atomic oxygen (AO) environment. The performance of several materials on the LDEF mission was dominated by AO effects. Trend analysis was performed on both the detailed spectral reflectance measurements (in-space, pre-flight, and post-flight) and on the integrated solar absorptance. Results of this analysis for the five selected TCSE materials are presented along with the spectral flight data. Possible degradation and effects mechanisms will be discussed to better understand and predict the behavior of these materials in the LEO space environment.

Wilkes, Donald R.↗
DOE OSTI2025

"Hidden" hydrothermal technical potential & technoeconomics: Revealing permeability & fluids with more data

Historical hydrothermal estimates have largely relied on temperature or heat flow estimates ignoring the need for natural flowing fluids. More accurate hydrothermal estimates require some indication of permeability and fluids that naturally exist in the subsurface. This paper describes a novel approach that includes proxies of permeability and fluids in hydrothermal estimates by leveraging the relatively data-rich Great Basin. Specifically, nameplate capacities (megawatts) of operating geothermal plants, negative (0 megawatt) locations and 48 geophysical and geologic features are used to used in eXtreme Gradient Boosting (XGBoost) regression to make hydrothermal capacity predictions. Additionally, this work inputs the XGBoost-based hydrothermal predictions into the Renewable Energy Potential (reV) model to quantify technical capacity, its uncertainty and techno-economics. Compared to historical hydrothermal estimates, these predictions adhere to the 37 operating geothermal plants and negative locations. We present a method for subsampling the negative sites to bring the labels into balance that uses the geologic domain knowledge to proportionally represent negatives. Overall, the distributions of the hydrothermal technical capacity and the site levelized cost of energy are respectively much tighter, lower and more accurate than the previous estimates for the Great Basin, as they include geological and geophysical surrogates for permeability and fluids. Percentile (50th and 90th, median and high estimate, respectively) models provide bookends for these metrics.

13 HYDRO ENERGY↗
DOE OSTI2024

Machine learning based reconstruction of intracardiac electrical behavior based on electrocardiograms

A computer-based system and process are disclosed for reconstructing the internal electrical behavior of a patient's heart based partly or wholly on the patient's electrocardiogram (ECG). The output of the process may include, for example, a cardiac activation map, and/or a representation of transmembrane potentials over time. The process advantageously does not require any medical imaging of the patient, and does not require any special medical equipment. For example, the patient's activation map and transmembrane potentials may be reconstructed based solely on a preexisting or newly-obtained 12-lead cardiac ECG of the patient. The process makes use of a machine learning model, such as a neural network based model, trained with actual and/or simulated ECGs and intracardiac electrical data (typically transmembrane potentials) of many thousands of patients. Because an insufficient quantity of such data exists for actual patients, model training may be performed using ECGs and intracardiac electrical data obtained through computer simulations.

Blake, Robert↗
NASA NTRS2019

Cross Kingdom Analysis of Data Within the GeneLab Repository Identifies a Potential Conserved Response of Life to the Stress Associated with Spaceflight

It is important to determine the health risks and potential survival for astronauts associated with long-term space missions. This entails not only understanding the impact the space environment will have on humans, but also how it will affect other organisms needed for humans to survive in space such as plants. In addition, it has been reported in the literature that hundreds of genes seem to be conserved and/or transferred between different organisms from bacteria, archaea, fungi, microorganisms, and plants to animals. Since space travel involves humans in a closed environment over a long period of time, we hypothesize that potential conserved biological factors will occur between the different organisms in that environment possibly due to transfer of genes. Determining the conserved factors that are commonly being regulated in space can shed insight into possible universal master regulators and also determine the symbiotic relationship between the organisms in space. Utilizing NASA's GeneLab Data Repository (a rapidly expanding, curated clustering of spaceflight-related ‘omics-level datasets for all organisms), we were able to uncover a novel pathway and factors that were commonly shared between humans, mice, plants, C. Elegans, and drosophilas. Through ChIP-Seq enrichment analysis techniques utilizing various GeneLab datasets from each species that were flown in space, we found the following factors to be conserved across all species: oxidative stress, DNA damage (through GABPA/NRFs and NFY), SIX5, GTF2B and glutamine synthetase. Such commonalities would likely reflect the effects of factors such as microgravity and the increased radiation exposure inherent in spaceflight on basic physical processes shared by all biological systems at the cellular level. Differences between organismal responses revealed by GeneLab's data should also help understand the unique reactions to life in space that arise from the very different lifestyles of microbes, animals and plants.

Barker, Richard↗
NASA NTRS1988

A model of auroral potential structures based on Dynamics Explorer plasma data

Dynamics Explorer 1 hot plasma data are used to investigate three major features of the mid-altitude auroral electron distribution -- the hole, the bump (at large pitch angles), and the loss cone. The results of a computer simulation show that these features can be approximately reproduced by a model involving an initial plasma sheet electron distribution and two potential drop regions that are widely separated in altitude. The observed distributions could not be reproduced, even qualitatively, by any of a wide range of distributed potential drops involving parallel electric fields at the point of observation.

Burch, J. L.↗
DOE OSTI2024

Assessment of uranium nitride interatomic potentials

Uranium mononitride (UN) is a promising nuclear fuel due to its high fissile density, high thermal conductivity, and suitability for reprocessing. In this study, two uranium nitride interatomic potentials are assessed: Tseplyaev and Starikov's angular-dependent potential and Kocevski et al.'s embedded atom model potential. Predictions of the thermophysical and elastic properties of UN, UN 2 , and α- and β-U 2 N 3 computed using both potentials are assessed and compared to available experimental data. Notably, the Tseplyaev potential performs better with the energetic aspects of UN, e.g., specific heat capacity and point defect formation energies, whereas the Kocevski potential performs better with the structural aspects of UN, e.g., thermal expansion as well as with the elastic properties. The reasons why the Kocevski potential underestimates the UN specific heat are explained by examining the UN phonon properties modeled using both potentials. The Kocevski potential shows better identification of the mechanical stability ranges of UN, UN 2 , and α- and β-U 2 N 3 , reasonably predicting the melting point of UN and predicting stable structures for UN 2 and α- and β-U 2 N 3 . On the other hand, the Tseplyaev potential predicts a premature phase change of both UN and UN 2 and cannot stabilize α- nor β-U 2 N 3 . However, the Kocevski potential cannot predict a stable α-U phase and is thus not suitable for the calculation of formation energies for non-stoichiometric point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Photoionisation study of Xe.CF{sub 4} and Kr.CF{sub 4} van-der-Waals molecules

We report on photoionization studies of Xe.CF{sub 4} and Kr.CF{sub 4} van-der-Waals complexes produced in a supersonic expansion and detected using synchrotron radiation and photoelectron-photoion coincidence techniques. The ionization potential of CF{sub 4} is larger than those of the Xe and Kr atoms and the ground state of the Rg.CF{sub 4}{sup +} ion correlates with Rg{sup +} ({sup 2}P{sub 3/2}) + CF{sub 4}. The onset of the Rg.CF{sub 4}{sup +} signals was found to be only ∼0.2 eV below the Rg ionization potential. In agreement with experiment, complementary ab initio calculations show that vertical transitions originating from the potential minimum of the ground state of Rg.CF{sub 4} terminate at a part of the potential energy surfaces of Rg.CF{sub 4}{sup +}, which are approximately 0.05 eV below the Rg{sup +} ({sup 2}P{sub 3/2}) + CF{sub 4} dissociation limit. In contrast to the neutral complexes, which are most stable in the face geometry, for the Rg.CF{sub 4}{sup +} ions, the calculations show that the minimum of the potential energy surface is in the vertex geometry. Experiments which have been performed only with Xe.CF{sub 4} revealed no Xe.CF{sub 4}{sup +} signal above the first ionization threshold of Xe, suggesting that the Rg.CF{sub 4}{sup +} ions are not stable above the first dissociation limit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗