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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 NTRS1973

Determination of aerosol content in the atmosphere

This investigation is designed to demonstrate the feasibility of determining the aerosol content in the atmosphere from contrast measurements of ground features, and from radiance measurements. Theoretical relationships between aerosol content and contrast reduction and radiance have been derived for ideal model atmospheres. The preliminary data analysis of the MSS transparencies has shown promising results for the contrast-aerosol content relationship in the Salton Sea/desert region.

Griggs, M.↗

NASA NTRS1992

Venus gravity: Summary and coming events

The first significant dataset to provide local measures of venusian gravity field variations was that acquired from the Pioneer Venus Orbiter (PVO) during the 1979-1981 period. These observations were S-band Doppler radio signals from the orbiting spacecraft received at Earth-based tracking stations. Early reductions of these data were performed using two quite different techniques. Estimates of the classical spherical harmonics were made to various degrees and orders up to 10. At that time, solutions of much higher degree and order were very difficult due to computer limitations. These reductions, because of low degree and order, revealed only the most prominent features with poor spatial resolution and very reduced peak amplitudes.

Sjogren, W. L.↗

NASA NTRS1993

Discrimination of poorly exposed lithologies in AVIRIS data

One of the advantages afforded by imaging spectrometers such as AVIRIS is the capability to detect target materials at a sub-pixel scale. This paper presents several examples of the identification of poorly exposed geologic materials - materials which are either subpixel in scale or which, while having some surface expression over several pixels, are partially covered by vegetation or other materials. Sabol et al. (1992) noted that a primary factor in the ability to distinguish sub-pixel targets is the spectral contrast between the target and its surroundings. In most cases, this contrast is best expressed as an absorption feature or features present in the target but absent in the surroundings. Under such circumstances, techniques such as band depth mapping (Clark et al., 1992) are feasible. However, the only difference between a target material and its surroundings is often expressed solely in the continuum. We define the 'continuum' as the reflectance or radiance spanning spectral space between spectral features. Differences in continuum slope and shape can only be determined by reduction techniques which considers the entire spectral range; i.e., techniques such as spectral mixture analysis (Adams et al., 1989) and recently developed techniques which utilize an orthogonal subspace projection operator (Harsanyi, 1993). Two of the three examples considered herein deal with cases where the target material differs from its surroundings only by such a subtle continuum change.

Farrand, William H.↗

NASA NTRS1994

K'-band observations of the evil eye galaxy: Are the optical and near-infrared dust albedos identical?

New measurements of the reduction of the V-band surface brightness across the prominent dust feature in the galaxy NGC 4826 are compared with corresponding increases in the V-K' color within the context of radiative transfer models invoking both absorption and scattering. The K'-band surface brightness is found to be higher than expected from standard dust models. We interpret the difference as resulting from a high effective dust albedo at K', with a likely value in excess of 0.8, provided the near-IR extinction curve in NGC 4826 is identical to the Galactic one. The high effective albedo may result from scattering by dust with a maximum grain size at least twice as large as assumed by standard models, a conclusion already indirectly hinted at by recent studies of dust star-forming regions and reflection nebulae. At least part of the high effective albedo at K' may result from near-IR nonequilibrium continuum emission attributable to very small grains.

Witt, Adolf N.↗

DOE OSTI2020

Classification of Dissolution Events Using Fusion of Effluents Measurements and Classifiers

Classifiers for dissolution events at a radiochemical processing facility are studied using gamma spectra measurements of effluents collected by a high purity germanium detector located at its off-gas stack. Data sets collected at the Oak Ridge National Laboratory’s Radiochemical Engineering Development Center under a Pu dissolution campaign spanning a three months period are utilized. Features corresponding to the activity levels of 15 radionuclides, including isotopes of iodine, krypton, and xenon, that are indicated by the target decay chains, are computed from the spectra at 1 hour intervals. A conceptualization diagram is developed to reflect the steps from the source to measurement to feature computation that depend on fission products indicated by decay chains, chemical processing, and effluents transport to the off-gas stack. A diverse set of eight classifiers based on different design principles are trained using the ground truth data for this campaign, and the outputs of top three classifiers, namely, classification trees, Ensemble of Trees (EOT), and k-nearest neighbor, are combined using EOT classifier-fuser. Our results show that for 5-fold cross validation, features associated with isotopes of xenon provide the lowest classification error among the different elements across the classifiers; the classification error is furthered improved when all 15 isotope features are used by each classifier, and it is again improved by the fusion of three classifiers. Further reduction in classification error is achieved by using a measurement window of 1-2 days which is identified based on half-life time estimates of the isotopes; it is long enough for the stabilization of feature estimates while being short enough not to be affected by the follow on dissolution events. As a net result of feature and classifier fusion, combined with the incorporation of decay chain and isotope half-life information, this approach achieves 98% detection rate while maintaining a false alarm rate under 2% for this data set.

Rao, Nageswara↗

DOE OSTI2025

MARIE: A Python-Based Framework for Comprehensive Fuel Recycling Modeling

One of the most pressing challenges to the continued deployment of nuclear energy systems is in the ultimate management and disposition of discharged fuel assemblies. While reprocessing and recovery of valuable materials from UNF assemblies has been considered as part of an overall strategy for minimization of the volume of reactor-based wastes to be managed, the deployment of commercial-scale reprocessing facilities presents an enormous economic challenge. The MARIE software package has been developed as a means of confronting this challenge. Representing components of a generic fuel reprocessing operation as individual physical processes, MARIE is designed as a modular framework intended to allow for analysis and cost-optimization for a hypothetical reprocessing facility while realistically accounting for the physical characteristics of the used fuel source term, such as decay heat, activity, and radiation dose (informing corresponding shielding requirements). Capabilities supported by MARIE include head-end operations such as fuel shearing, voloxidation, and dissolution; generic solvent extraction operations informed by available open-literature data; a suite of unit operations intended to represent electrochemical processing of used fuel assemblies (i.e., oxide reduction, electrorefining, and electrowinning); and finally, accounting for both costs and physical features of discharged waste streams, which can be used to inform follow-on analyses such as the feasibility of deep-borehole disposal of HLW. This paper presents an overview of the MARIE software capabilities, including how individual unit operations are implemented to enable a larger-scale optimization of a hypothetical reprocessing operation on aspects such as cost and recovery of valuable materials.

Skutnik, Steve [ORNL] (ORCID:000000016441135X)↗

NASA NTRS1995

An Example of Unsupervised Networks Kohonen's Self-Organizing Feature Map

Kohonen's self-organizing feature map belongs to a class of unsupervised artificial neural network commonly referred to as topographic maps. It serves two purposes, the quantization and dimensionality reduction of date. A short description of its history and its biological context is given. We show that the inherent classification properties of the feature map make it a suitable candidate for solving the classification task in power system areas like load forecasting, fault diagnosis and security assessment.

Kohonen Feature Map↗

DOE OSTI2023

Deep Vadose Zone Monitoring Test Bed (FY23 Status Report)

A subsurface air injection at the Hanford Site’s Deep Vadose Zone Monitoring Test Bed was completed to realize a change in subsurface hydrologic conditions in accordance with a soil desiccation remedy. The injection mimicked a previous injection at the site that was performed in accordance with a vadose zone treatability study. Unlike the previous test which relied on electrical methods only, the change in hydrologic conditions during the recent test was also monitored using cross-hole seismic sensing methods to assess the ability of the seismic methods to evaluate changes in moisture conditions of desiccated sediment at the field scale. Data from in situ neutron probes indicates a reduction of soil moisture in the vicinity of the injection well due to the air injection. Similar changes were observed in the time-lapse electrical resistivity and seismic data, which indicates a loss of soil moisture over time. Tomographic inversions of the time-lapse geophysical data illustrate the 2D and 3D features of the soil moisture distribution over time. Time-lapse electrical resistivity tomography (ERT) results show a reduction in the electrical conductivity of the subsurface in the vicinity of the injection well, with most changes occurring within the screened interval. Similar patterns are observed in the seismic tomography results, with both methods illustrating two lobe-shaped features of reduced soil moisture. Use of seismic and ERT technologies in tandem takes advantage of two complementary geophysical monitoring technologies, providing increased sensitivity to specific hydrologic conditions. The multiphysics approach, therefore, has the potential to improve the ability to estimate subsurface moisture conditions from sensor-based and remotely sensed geophysical data that will ultimately improve the ability of remediation contractors to evaluate remedy performance.

58 GEOSCIENCES↗

NASA NTRS1974

A data reduction technique and associated computer program for obtaining vehicle attitudes with a single onboard camera

A detailed discussion of the application of a previously method to determine vehicle flight attitude using a single camera onboard the vehicle is presented with emphasis on the digital computer program format and data reduction techniques. Application requirements include film and earth-related coordinates of at least two landmarks (or features), location of the flight vehicle with respect to the earth, and camera characteristics. Included in this report are a detailed discussion of the program input and output format, a computer program listing, a discussion of modifications made to the initial method, a step-by-step basic data reduction procedure, and several example applications. The computer program is written in FORTRAN 4 language for the Control Data 6000 series digital computer.

Bendura, R. J.↗

DOE OSTI2020

Reactor Power Level Estimation by Fusing Multi-Modal Sensor Measurements

Estimates of the power level of a nuclear reactor based on measurements from an independent monitoring sensor system can help in the compliance verification of its declared operations. We present a three-level fusion method to estimate the power level of a nuclear reactor using features derived from infrared, electromagnetic, and acoustic sensor measurements collected in proximity to the reactor. Based on a simplified analytical model of the secondary coolant system of the reactor, we identify partial regression functions of the power level in terms of the temperature difference between inlet and outlet of coolant pipes, and the activity levels of four fans and four pumps, which are estimated as features from the sensor measurements. The power level estimator employs a combination of aggregate and complementary fusion steps at three levels to incorporate the multi-modal features in a structure that reflects the secondary cooling system and its partial regression functions. Using the measurements from a test campaign at an operational reactor, we show that this estimator achieves 3.47% or lower root mean square error under 5-fold cross validation. More generally, these results illustrate a progressive reduction in estimation error as additional modalities are appropriately incorporated, and that the fuser outperforms single modality features and their sub-combinations.

Rao, Nageswara↗

DOE OSTI2021

Oxidative Catalytic Fractionation of Lignocellulosic Biomass under Non-alkaline Conditions

Biomass pretreatment methods are commonly used to isolate carbohydrates from biomass, but they often lead to modification, degradation, and/or low yields of lignin. Catalytic fractionation approaches provide a possible solution to these challenges by separating the polymeric sugar and lignin fractions in the presence of a catalyst that promotes cleavage of the lignin into aromatic monomers. In this work, we demonstrate an oxidative fractionation method conducted in the presence of a heterogeneous non-precious-metal Co-N-C catalyst and O 2 in acetone as the solvent. The process affords a 15 wt% yield of phenolic products bearing aldehydes (vanillin, syringaldehyde) and carboxylic acids (p-hydroxybenzoic acid, vanillic acid, syringic acid), complementing the alkylated phenols obtained from existing reductive catalytic fractionation methods. The oxygenated aromatics derived from this process have appealing features for use in polymer synthesis and/or biological funneling to value-added products, and the non-alkaline conditions associated with this process support preservation of the cellulose, which remains insoluble at reaction conditions and is recovered as a solid.

09 BIOMASS FUELS↗

DOE OSTI2023

Selective Methane Oxidation by Heterogenized Iridium Catalysts

Oxidative methane (CH 4 ) carbonylation promises a direct route to the synthesis of value-added oxygenates such as acetic acid (CH 3 COOH). Here, in this paper, we report a strategy to realize oxidative CH 4 carbonylation through immobilized Ir complexes on an oxide support. Our immobilization approach not only enables direct CH 4 activation but also allows for easy separation and reutilization of the catalyst. Furthermore, we show that a key step, methyl migration, that forms a C–C bond, is sensitive to the electrophilicity of carbonyl, which can be tuned by a gentle reduction to the Ir centers. While the as-prepared catalyst that mainly featured Ir(IV) preferred CH 3 COOH production, a reduced catalyst featuring predominantly Ir(III) led to a significant increase of CH 3 OH production at the expense of the reduced yield of CH 3 COOH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Parameterizing Convective Organization Effects With a Moisture-PDF Approach in Climate Models: Concept and a Regional Case Simulation

We propose a parameterization scheme of convective organization effects based on a moisture-distribution approach, which can reflect aggregation of convective cells within a model grid as well as the interaction between convection and spatial heterogeneity in free-troposphere moisture. With this concept, convective cells in an aggregated state are surrounded by air that is moister than the grid-mean condition, which provides a “shielding” effect favorable for deeper convective updrafts. Such effects are represented quantitatively via utilizing a schematic diagram about the geometric interpretation of convective cluster, dry area, and their contact area, in which both the convective cluster size and dry area fraction increase during the development of convection. Our sensitivity analyses indicate that the new scheme performs well in capturing the mean precipitation features. Excluding the convective organization effects in the model leads to a considerable reduction in the simulated precipitation magnitude. Notably, there exists an inverse relationship between background mean moisture condition and sub-grid moisture variability for a given rain rate, suggesting that with a high spatial heterogeneity in free-troposphere moisture, convection can still develop and maintain its strength under relatively dry background conditions, consistent with the convection-permitting model simulation. Overall, our new parameterization of convective organization effects can successfully reproduce the relationship between precipitation and sub-grid moisture variability, which is a missing element in traditional convection parameterization schemes but important for the simulations of precipitation variability at various scales in climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Thermo-Hydro-Chemical Simulation of Mid-Ocean Ridge Hydrothermal Systems: Static 2D Models and Effects of Paleo-Seawater Chemistry

Decades of research have resulted in characterization of the ocean floor manifestations of mid-ocean ridge (MOR) hydrothermal systems, yet numerical models accounting for the connections between heat transfer, hydrology and geochemistry have been slow to develop. The Thermo-hydro-chemical code ToughReact can be used to describe the coupled effects of fluid flow, heat transfer, and fluid-rock chemical interactions that occur in MOR systems. We describe the results of 2-dimensional simulations of steady state flow in fractured diabase with mineral-fluid chemical reactions. Basal heating and specified permeability yield maximum temperature of 400°C. Total fluid flux and high fracture flow velocities are in accord with observations. Fluid chemistry, mineralogical changes and 87 Sr/ 86 Sr ratios can be compared to observations to assess and calibrate models. Simulated high temperature fracture fluids have Mg and SO 4 near zero, elevated Ca and 87 Sr/ 86 Sr of about 0.7040. Total alteration is 10%–50% for simple models of spreading. Anhydrite forms mainly near the base of the upwelling zone and results in substantial local fracture porosity reduction. A calibrated model is used to predict how Sr isotopes and other features of altered oceanic crust would be different in the Cretaceous (95 Ma) early Proterozoic (1,800 Ma) and Archean (3,800 Ma), when seawater may have had high Ca and Sr concentrations, lower pH, higher temperature, and lower Na, Mg, and SO 4 . The simulations are offered as a start on what ultimately may require a longer-term community effort to better understand the role of MOR thermo-hydro-chemical systems in Earth evolution.

58 GEOSCIENCES↗

DOE OSTI2022

Prediction of grain structure after thermomechanical processing of U-10Mo alloy using sensitivity analysis and machine learning surrogate model

Abstract Hot rolling and annealing are critical intermediate steps for controlling microstructures and thickness variations when fabricating uranium alloyed with 10% molybdenum (U-10Mo), which is highly relevant to worldwide nuclear non-proliferation efforts. This work proposes a machine-learning surrogate model combined with sensitivity analysis to identify and predict U-10Mo microstructure development during thermomechanical processing. Over 200 simulations were collected using physics-based microstructure models covering a wide range of thermomechanical processing routes and initial alloy grain features. Based on the sensitivity analysis, we determined that an increase in rolling reduction percentage at each processing pass has the strongest effect in reducing the grain size. Multi-pass rolling and annealing can significantly improve recrystallization regardless of the reduction percentage. With a volume fraction below 2%, uranium carbide particles were found to have marginal effects on the average grain size and distribution. The proposed stratified stacking ensemble surrogate predicts the U-10Mo grain size with a mean square error four times smaller than a standard single deep neural network. At the same time, with a significant speedup (1000×) compared to the physics-based model, the machine learning surrogate shows good potential for U-10Mo fabrication process optimization.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Electronically-coupled redox centers in trimetallic cobalt complexes

Synthesis and isolation of molecular building blocks of metal–organic frameworks (MOFs) can provide unique opportunities for characterization that would otherwise be inaccessible due to the heterogeneous nature of MOFs. Herein, we report a series of trinuclear cobalt complexes incorporating dithiolene ligands, triphenylene-2,3,6,7,10,11-hexathiolate (THT) (1 3+ ), and benzene hexathiolate (BHT) (2 3+ ), with 1,1,1,-tris(diphenylphosphinomethyl)ethane (triphos) employed as the capping ligand. Single crystal X-ray analyses of 1 3+ and 2 3+ display three five-coordinate cobalt centers bound to the triphos and dithiolene ligands in a distorted square pyramidal geometry. Cyclic voltammetry studies of 1 3+ and 2 3+ reveal three redox features associated with the formation of mixed valence states due to the sequential reduction of the redox-active metal centers (Co III/II ). Using this electrochemical data, the comproportionality values were determined for 1 and 2 (log K c = 1.4 and 1.5 for 1, and 4.7 and 5.8 for 2), suggesting strong resonance-stabilized coupling of the metal centers, with stronger electronic coupling observed for complex 2 compared to that for complex 1. Cyclic voltammetry studies were also performed in solvents of varying polarity, whereupon the difference in the standard potentials (ΔE 1/2 ) for 1 and 2 was found to shift as a function of the polarity of the solvent, indicating a negative correlation between the dielectric constant of the electrochemical medium and the stability of the mixed valence species. Spectroelectrochemical studies of in situ generated multi-valent (MV) states of complexes 1 and 2 display characteristic NIR intervalence charge transfer (IVCT) bands, and analysis of the IVCT transitions for complex 2 suggests a weakly coupled class II multi-valent species and relatively large electronic coupling factors (1700 cm –1 for the first multi-valent state of 2 2+ , and 1400 and 4000 cm –1 for the second multi-valent state of 2 + ). Here, density functional theory (DFT) calculations indicate a significant deviation in relative energies of the frontier orbitals of complexes 1 3+ , 2 3+ , and 3 + that contrasts those calculated for the analogous trinuclear cobalt dithiolene complexes employing pentamethylcyclopentadienyl (Cp*) as the capping ligand (Co 3 Cp* 3 THT and Co 3 Cp* 3 BHT, respectively), and may be a result of the cationic nature of complexes 1 3+ , 2 3+ , and 3 + .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Dicarbonyl[10,10-dimethyl-5,15-bis(pentafluorophenyl)biladiene]ruthenium(II): discovery of the first ruthenium tetrapyrrole cis -dicarbonyl complex by X-ray and electron diffraction

Dicarbonyl[10,10-dimethyl-5,15-bis(pentafluorophenyl)biladiene]ruthenium(II), [Ru(C 33 H 16 F 10 N 4 )(CO) 2 ] or Ru(CO) 2 [DMBil1], is the first reported ruthenium(II) cis-dicarbonyl tetrapyrrole complex. The neutral complex sports two carbonyls and an oligotetrapyrrolic biladiene ligand. Notably, the biladiene adopts a coordination geometry that is well distorted from square planar and much more closely approximates a seesaw arrangement. Accordingly, Ru(CO) 2 [DMBil1] is not only the first ruthenium cis-dicarbonyl with a tetrapyrrole ligand, but also the first metal biladiene complex in which the tetrapyrrole does not adopt a (pseudo-)square-planar coordination geometry. Ru(CO) 2 [DMBil1] is weakly luminescent, displaying λ em = 552 nm upon excitation at λ ex = 500 nm, supports two reversible 1 e – reductions at –1.45 and –1.73 V (versus Fc + /Fc), and has significant absorption features at 481 and 531 nm, suggesting suitability for photocatalytic and photosensitization applications. While the structure of Ru(CO) 2 [DMBil1] was initially determined by X-ray diffraction, a traditionally acceptable quality structure could not be obtained (despite multiple attempts) because of consistently poor crystal quality. Furthermore, an independent structure obtained from electron diffraction experiments corroborates the structure of this unusual biladiene complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts

This article proposes a generalizable, data-driven framework for qualifying laser powder bed fusion additively manufactured parts using part-specific in situ data, including powder bed imaging, machine health sensors, and laser scan paths. To achieve part qualification without relying solely on statistical processes or feedstock control, a sequence of machine learning models was trained on 6299 tensile specimens to locally predict the tensile properties of stainless-steel parts based on fused multi-modal in situ sensor data and a priori information. A cyberphysical infrastructure enabled the robust spatial tracking of individual specimens, and computer vision techniques registered the ground truth tensile measurements to the in situ data. The co-registered 230 GB dataset used in this work has been publicly released and is available as a set of HDF5 files. The extensive training data requirements and wide range of size scales were addressed by combining deep learning, machine learning, and feature engineering algorithms in a relay. The trained models demonstrated a 61% error reduction in ultimate tensile strength predictions relative to estimates made without any in situ information. Lessons learned and potential improvements to the sensors and mechanical testing procedure are discussed.

36 MATERIALS SCIENCE↗