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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Retrieval of Atmospheric and Surface Parameters from AIRS/AMSU/HSB Data Under Cloudy Conditions

New state of the art methodology is described to analyze AIRS/AMSU/HSB data in the presence of multiple cloud formations. The methodology forms the basis for the AIRS Science Team algorithm which will be used to analyze AIRS/AMSU/HSB data on EOS Aqua. The cloud clearing methodology requires no knowledge of the spectral properties of the clouds. The basic retrieval methodology is general and extracts the maximum information from the radiances, consistent with the channel noise covariance matrix. The retrieval methodology minimizes the dependence of the solution on the first guess field and the first guess error characteristics. Results are shown for AIRS Science Team simulation studies with multiple cloud formations. These simulation studies imply that clear column radiances can be reconstructed under partial cloud cover with an accuracy comparable to single spot channel noise in the temperature and water vapor sounding regions, temperature soundings can be produced under partial cloud cover with RMS errors on the order of, or better than, 1deg K in 1 km thick layers from the surface to 700 mb, 1 km layers from 700 mb to 300 mb, 3 km layers from 300 mb to 30 mb, and 5 km layers from 30 mb to 1 mb, and moisture profiles can be obtained with an accuracy better than 20% absolute errors in 1 km layers from the surface to nearly 200 mb.

Susskind, Joel↗
DOE OSTI2017

Metabolic Reconstruction and Modeling Microbial Electrosynthesis

Microbial electrosynthesis is a renewable energy and chemical production platform that relies on microbial cells to capture electrons from a cathode and fix carbon. Yet despite the promise of this technology, the metabolic capacity of the microbes that inhabit the electrode surface and catalyze electron transfer in these systems remains largely unknown. Here, we assembled thirteen draft genomes from a microbial electrosynthesis system producing primarily acetate from carbon dioxide, and their transcriptional activity was mapped to genomes from cells on the electrode surface and in the supernatant. This allowed us to create a metabolic model of the predominant community members belonging to Acetobacterium, Sulfurospirillum, and Desulfovibrio. According to the model, the Acetobacterium was the primary carbon fixer, and a keystone member of the community. Transcripts of soluble hydrogenases and ferredoxins from Acetobacterium and hydrogenases, formate dehydrogenase, and cytochromes of Desulfovibrio were found in high abundance near the electrode surface. Cytochrome c oxidases of facultative members of the community were highly expressed in the supernatant despite completely sealed reactors and constant flushing with anaerobic gases. The resulting molecular discoveries and metabolic modeling now serve as a foundation for future examination and development of electrosynthetic microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Measurement of space charge effects in the MicroBooNE LArTPC using cosmic muons

Large liquid argon time projection chambers (LArTPCs), especially those operating near the surface, are susceptible to space charge effects. In the context of LArTPCs, the space charge effect is the build-up of slow-moving positive ions in the detector primarily due to ionization from cosmic rays, leading to a distortion of the electric field within the detector. This effect leads to a displacement in the reconstructed position of signal ionization electrons in LArTPC detectors ("spatial distortions"), as well as to variations in the amount of electron-ion recombination experienced by ionization throughout the volume of the TPC. We present techniques that can be used to measure and correct for space charge effects in large LArTPCs by making use of cosmic muons, including the use of track pairs to unambiguously pin down spatial distortions in three dimensions. Finally, the performance of these calibration techniques are studied using both Monte Carlo simulation and MicroBooNE data, utilizing a UV laser system as a means to estimate the systematic bias associated with the calibration methodology.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2021

Tree-ring cellulose δ(18)O records similar large-scale climate influences as precipitation δ(18)O in the Northwest Territories of Canada

Stable oxygen isotopes measured in tree rings are useful for reconstructing climate variability and explaining changes in physiological processes occurring in forests, complementing other tree-ring parameters such as ring width. Here, we analyzed the relationships between different climate parameters and annually resolved tree-ring δ(18)O records (δ(18)O(TR)) from white spruce (Picea glauca [Moench]Voss) trees located near Tungsten (Northwest Territories, Canada) and used the NASA GISS ModelE2 isotopically-equipped general circulation model (GCM) to better interpret the observed relationships. We found that the δ(18)O(TR) series were primarily related to temperature variations in spring and summer, likely through temperature effects on the precipitation δ(18)O in spring, and evaporative enrichment at leaf level in summer. The GCM simulations showed significant positive relationships between modelled precipitation δ(18)O over the study region and surface temperature and geopotential height over northwestern North America, but of stronger magnitudes during fall-winter than during spring–summer. The modelled precipitation δ(18)O was only significantly associated with moisture transport during the fall-winter season. The δ(18)O(TR) showed similar correlation patterns to modelled precipitation δ(18)O only during spring–summer when water matters more for trees, with significant positive correlations with surface temperature and geopotential height, but no correlations with moisture transport. Overall, the δ(18)O(TR) records for northwestern Canada reflect the same significant large-scale climate patterns as precipitation δ(18)O for spring–summer, and therefore have potential for reconstructing past atmospheric dynamics in addition to temperature variability in the region.

paleoclimate↗
DOE OSTI2024

Modular flow in JT gravity and entanglement wedge reconstruction

It has been shown in recent works that JT gravity with matter with two boundaries has a type II ∞ algebra on each side. As the bulk spacetime between the two boundaries fluctuates in quantum nature, we can only define the entanglement wedge for each side in a pure algebraic sense. As we take the semiclassical limit, we will have a fixed long wormhole spacetime for a generic partially entangled thermal state (PETS), which is prepared by inserting heavy operators on the Euclidean path integral. Under this limit, with appropriate assumptions of the matter theory, geometric notions of the causal wedge and entanglement wedge emerge in this background. In particular, the causal wedge is manifestly nested in the entanglement wedge. Different PETS are orthogonal to each other, and thus the Hilbert space has a direct sum structure over sub-Hilbert spaces labeled by different Euclidean geometries. The full algebra for both sides is decomposed accordingly. From the algebra viewpoint, the causal wedge is dual to an emergent type III 1 subalgebra, which is generated by boundary light operators. To reconstruct the entanglement wedge, we consider the modular flow in a generic PETS for each boundary. We show that the modular flow acts locally and is the boost transformation around the global RT surface in the semiclassical limit. It follows that we can extend the causal wedge algebra to a larger type III 1 algebra corresponding to the entanglement wedge. Within each sub-Hilbert space, the original type II ∞ reduces to type III 1 .

2D Gravity↗
DOE OSTI2017

Simulation of gas flow in micro-porous media with the regularized lattice Boltzmann method

One primary challenge for prediction of gas flow in the unconventional gas reservoir at the pore-scale such as shale and tight gas reservoirs is the geometric complexity of the micro-porous media. In this paper, a regularized multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is applied to analyze gas flow in 2-dimensional micro-porous medium reconstructed by quartet structure generation set (QSGS) on pore-scale. In this paper, the velocity distribution inside the porous structure is presented and analyzed, and the effects of the porosity and specific surface area on the rarefied gas flow and apparent permeability are examined and investigated. The simulation results indicate that the gas exhibits different flow behaviours at various pressure conditions and the gas permeability is strongly related to the pressure. Finally, the increased porosity or the decreased specific surface area leads to the increase of the gas apparent permeability, and the gas flow is more sensitive to the pore morphological properties at low-pressure conditions.

02 PETROLEUM↗
DOE OSTI2021

Exploring Causal Physical Mechanisms via Non-Gaussian Linear Models and Deep Kernel Learning: Applications for Ferroelectric Domain Structures

Rapid emergence of multimodal imaging in scanning probe, electron, and optical microscopies has brought forth the challenge of understanding the information contained in these complex data sets, targeting the intrinsic correlations between different channels, and further exploring the underpinning causal physical mechanisms. Here, we develop such an analysis framework for Piezoresponse Force Microscopy. We argue that under certain conditions, we can bootstrap experimental observations with the prior knowledge of materials structure to get information on certain nonobserved properties, and demonstrate linear causal analysis for PFM observables. We further demonstrate that the strength of individual causal links between complex descriptors can be ascertained using the deep kernel learning (DKL) model. In this DKL analysis, we use the prior information on domain structure within the image to predict the physical properties. This analysis demonstrates the correlative relationships between morphology, piezoresponse, elastic property, etc., at nanoscale. The prediction of morphology and other physical parameters illustrates a mutual interaction between surface condition and physical properties in ferroelectric materials. Overall, this analysis is universal and can be extended to explore the correlative relationships of other multichannel data sets, and allow for high-fidelity reconstruction of underpinning functionalities and physical mechanisms.

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

PTT System Performance Evaluation in 3-D Imaging of Calibrated Defects: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Research activity in this project is aimed at developing pulsed thermal tomography (PTT) architecture and algorithms for in-service non-destructive examination (NDE) of additively manufactured (AM) reactor components and materials. Recent advances in AM technology could allow cost-efficient fabrication of parts for operating reactors. However, because of stringent safety requirements, long-term performance of AM reactor components needs to be investigated before AM is widely accepted. Because of the complex shapes and significant surface roughness of components due to layer-by-layer welding process in AM, conventional methods might not be useful for in-service NDE of AM components. PTT is ideally suited for in-service NDE of AM metallic components because the method is non-contact, and offers high resolution #-D imaging of material flaws. The objective of this report is to provide initial evaluate of PTT performance sin detecting calibrated flaws in reactor structural materials. Preliminary COMSOL models were developed to conduct super computing simulations of PTT. In the experimental studies, high strength Stainless Steel 316 and Inconel 718 alloys were considered, as well as lower grade Stainless Steel 304, Nickel 200, and Hastelloy C276. Specimens investigated in this report consisted of approximately 1/4in-thick plates made out of these alloys using conventional manufacturing methods. The calibrated defects were created in the form of flat bottom holes (FBH) drilled in metallic plates. The diameters of FBH's varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. The size of the smallest FBH was limited to 1mm because conventional mechanic drills were used for creating the holes. PTT imaging results have shown that 1mm-diameter FBH located 1mm and 2mm below the surface were detectable. Larger size FBH were detectable at greater depth. For example, 6mm-diameter FBH could be detected at 8mm depth. Image contrast varied slightly between the specimens, with the best reconstructions obtained in SS316 and C276 plates. In addition, a 2/3in-thick Inconel 718 nozzle plate produced with additive manufacturing method was imaged with PTT. It was shown that PTT can scan through the plate in approximately 20s. Several modes of 3-D data visualization were explored, including using ImageJ and MATLAB software packages.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1981

Radiographic evidence of disuse osteoporosis in the monkey /M. nemestrina/

Radiological techniques were utilized for monitoring progressive changes in compact bone in the tibia of monkeys during experimentally induced osteopenia. Bone mass loss in the tibia during restraint was evaluated from radiographs, from bone mineral analysis, and from images reconstructed from gamma ray computerized tomography. The losses during 6 months of restraint tended to occur predominantly in the proximal tibia and were characterized by subperiosteal bone loss, intracortical striations, and scalloped endosteal surfaces. Bone mineral content in the cross section of the tibia declined 17-21%. In 6 months of recovery, the mineral content of the proximal tibia remained depressed.

Young, D. R.↗
NASA NTRS2003

Records of our Early Biosphere Illuminate our Origins and Guide our Search for Life Beyond Earth

A scientific "mission of exploration to early Earth" will help us chart the distribution of life elsewhere. We must discriminate between attributes of biospheres that are universal versus those attributes that represent principally the outcomes of long-term survival specifically on Earth. In addition to the basic physics and chemistry of matter, the geologic evolution of rocky habitable planets and their climates might be similar elsewhere in the Universe. Certain key agents that drive long-term environmental change (e.g., stellar evolution, impacts, geothermal heat flow, tectonics, etc.) can help us to reconstruct ancient climates and to compare their evolution among populations of Earth- like planets. Early Earth was tectonically more active than today and therefore it exhaled reduced chemical species into the more oxidized surface environment at greater rates. This tectonic activity thus sustained oxidation-reduction reactions that provided the basis for the development of biochemical pathways that harvest chemical energy ("bioenergetics"). Most examples of bioenergetics today that extract energy by reacting oxidized and reduced chemicals in the environment were likely more pervasive among our microbial ancestors than are the presently known examples of photosynthesis. The geologic rock record indicates that, as early as 3.5 billion years ago (3.5 Ga), microbial biofilms were widespread within the coastal environments of small continents and tectonically unstable volcanic islands. Non oxygen-producing (non-oxygenic) photosynthesis preceded oxygenic photosynthesis, but all types of photosynthesis contributed substantially to the long-term increase in global primary biological productivity. Evidence of photosynthesis is tentative by 3.5 Ga and compelling by 2.7 Ga. Evidence of oxygenic photosynthesis is strong by 2.7 Ga and compelling by 2.3 Ga. These successive innovations transformed life from local communities that survived principally by catalyzing chemical equilibration to a globally dominant agent that created and sustained widespread chemical disequilibria in the environment and shallow crust. Major biogeochemical perturbations ca. 2.3 to 2.0 Ga, 1.3 Ga, and also 0.8 to 0.6 Ga, contributed to the irreversible oxidation of the global environment and perhaps also triggered evolutionary innovations (e.g., the development of multi-cellular biota) that became the foundations of our modern biosphere. Understanding the nature and timing of this ascent of life is crucial for discerning our o m beginnings. This understanding also empowers OUT search for the origins, evolution and distribution of life elsewhere in our solar system and beyond.

DesMarais, David J.↗
NASA NTRS1995

Possible role of oceanic heat transport in early Eocene climate

Increased oceanic heat transport has often been cited as a means of maintaining warm high-latitude surface temperatures in many intervals of the geologic past, including the early Eocene. Although the excess amount of oceanic heat transport required by warm high latitude sea surface temperatures can be calculated empirically, determining how additional oceanic heat transport would take place has yet to be accomplished. That the mechanisms of enhanced poleward oceanic heat transport remain undefined in paleoclimate reconstructions is an important point that is often overlooked. Using early Eocene climate as an example, we consider various ways to produce enhanced poleward heat transport and latitudinal energy redistribution of the sign and magnitude required by interpreted early Eocene conditions. Our interpolation of early Eocene paleotemperature data indicate that an approximately 30% increase in poleward heat transport would be required to maintain Eocene high-latitude temperatures. This increased heat transport appears difficult to accomplish by any means of ocean circulation if we use present ocean circulation characteristics to evaluate early Eocene rates. Either oceanic processes were very different from those of the present to produce the early Eocene climate conditions or oceanic heat transport was not the primary cause of that climate. We believe that atmospheric processes, with contributions from other factors, such as clouds, were the most likely primary cause of early Eocene climate.

NASA Discipline Number 52-30↗
NASA NTRS2005

Two Successive Martian Years on the Orbit: Similarities and Differences of CO2 Seasonal Cycle from HEND/ODYSSEY Data

The three years of Mars Odyssey successful work on the martian orbit provide a lot of new information about peculiarities of long term variations of CO2 seasonal cycle. To start such analysis we have used observations of neutron albedo of Mars obtained by High Energy Neutron detector (HEND) mounted onboard Mars Odyssey spacecraft. The high latitude northern and southern regions of Mars are affected by global redistribution of atmospheric CO2 which resulted in 25% of atmospheric mass condensed on martian surface of these regions during winter period of time. The seasonal deposit is formed starting from 60N/60S latitudes and achieve its maximal thickness about 1 m at latitudes close to martian poles. Changes of CO2 deposit thickness is the reason for significant variations of neutron flux above martian poles from summer to winter seasons because CO2 frost effectively hides upper water rich surface layers from the orbit observations in neutrons and gamma-rays. This effect was used to estimate column density of CO2 deposit at different latitudes on North and South of Mars and reconstruct multidimensional model of CO2 deposit showing how snow depth varies as function of latitude, longitude and time. In this presentation we tried to make a next step in our study of martian seasonal CO2 cycle and look for similarities and differences between two successive martian years.

Litvak, M. L.↗
DOE OSTI2022

Hybrid Curve Fitting For Reducing Motion Commands In Object Construction

Existing slicing software for additive manufacturing typically requires a triangulated mesh as its input. Triangulated meshes are approximate representations of exact CAD models. Despite the loss in dimensional accuracy, triangulated meshes are used because they are computationally easier to cross-section and offset than the exact geometry in CAD format. When a triangulated object is prepared, the resulting machine instructions include only linear motion commands. Numerous modern motion controllers can move in arc and spline motions; however, the absence of slicing software that supports curvature prevents these commands from being leveraged. To address this limitation, this paper presents a method for the hybrid reconstruction of arcs and splines as a post-processing step to traditional slicing. This method can greatly reduce the number of motion commands required to construct an object by printing smooth curved surfaces. This concise representation of tool-pathing allows for more even extrusion and is computed without a major impact on slicing time.

Wade, Charles↗
DOE OSTI2023

Calibration of the ProtoDUNE Horizontal-Drift position reconstruction using a laser system

Forthcoming in the next decade of neutrino physics advancements is the construction of the Deep Underground Neutrino Experiment (DUNE), a long baseline neutrino oscillation experiment which has the potential to answer fundamental questions such as why there is more matter than antimatter in the universe, and ultimately why we exist at all. A prototype of this experiment, ProtoDUNE, sits in a charged particle test beam at the European Organization for Nuclear Research (CERN) and uses Liquid Argon time projection chambers to image interactions of these particles. ProtoDUNE Single-Phase (ProtoDUNESP) had positively charged hadrons as well as positrons in its initial 2018 beam data run. Because ProtoDUNE is a surface-based time projection chamber, it experiences a constant influx of cosmic rays. These cosmic rays ionize the liquid argon within the detector, resulting in an accumulation of slow moving positive ions towards the cathode. This local charge distribution results in electric field non uniformities, which can have a significant effect on the accuracy of the event reconstruction. This paper outlines a monte carlo simulation study which adapts methodology from the MicroBooNE experiment, another neutrino oscillation experiment, to derive electric field correction maps which can correct for distortions of the electric field within the detector. These correction maps accurately estimate the electric field throughout the detector volume and correct for uncertainties in reconstructed event data enabling for physics discoveries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗
NASA NTRS2011

Orthographic Stereo Correlator on the Terrain Model for Apollo Metric Images

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.

Terrain Model↗
DOE OSTI2021

Buried Interfaces in Halide Perovskite Photovoltaics

Understanding the fundamental properties of buried interfaces in perovskite photovoltaics is of paramount importance to the enhancement of device efficiency and stability. Nevertheless, accessing buried interfaces poses a sizeable challenge because of their non-exposed feature. In this paper, the mystery of the buried interface in full device stacks is deciphered by combining advanced in situ spectroscopy techniques with a facile lift-off strategy. By establishing the microstructure-property relations, the basic losses at the contact interfaces are systematically presented, and it is found that the buried interface losses induced by both the sub-microscale extended imperfections and lead-halide inhomogeneities are major roadblocks toward improvement of device performance. The losses can be considerably mitigated by the use of a passivation-molecule-assisted microstructural reconstruction, which unlocks the full potential for improving device performance. The findings open a new avenue to understanding performance losses and thus the design of new passivation strategies to remove imperfections at the top surfaces and buried interfaces of perovskite photovoltaics, resulting in substantial enhancement in device performance.

36 MATERIALS SCIENCE↗