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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

The TSO Logic and G2 Software Product

This internship assignment for spring 2014 was at John F. Kennedy Space Center (KSC), in NASAs Engineering and Technology (NE) group in support of the Control and Data Systems Division (NE-C) within the Systems Hardware Engineering Branch. (NEC-4) The primary focus was in system integration and benchmarking utilizing two separate computer software products. The first half of this 2014 internship is spent in assisting NE-C4s Electronics and Embedded Systems Engineer, Kelvin Ruiz and fellow intern Scott Ditto with the evaluation of a newly piece of software, called G2. Its developed by the Gensym Corporation and introduced to the group as a tool used in monitoring launch environments. All fellow interns and employees of the G2 group have been working together in order to better understand the significance of the G2 application and how KSC can benefit from its capabilities. The second stage of this Spring project is to assist with an ongoing integration of a benchmarking tool, developed by a group of engineers from a Canadian based organization known as TSO Logic. Guided by NE-C4s Computer Engineer, Allen Villorin, NASA 2014 interns put forth great effort in helping to integrate TSOs software into the Spaceport Processing Systems Development Laboratory (SPSDL) for further testing and evaluating. The TSO Logic group claims that their software is designed for, monitoring and reducing energy consumption at in-house server farms and large data centers, allows data centers to control the power state of servers, without impacting availability or performance and without changes to infrastructure and the focus of the assignment is to test this theory. TSOs Aaron Rallo Founder and CEO, and Chris Tivel CTO, both came to KSC to assist with the installation of their software in the SPSDL laboratory. TSOs software is installed onto 24 individual workstations running three different operating systems. The workstations were divided into three groups of 8 with each group having its own operating system. The first group is comprised of Ubuntus Debian -based Linux the second group is windows 7 Professional and the third group ran Red Hat Linux. The highlight of this portion of the assignment is to compose documentation expressing the overall impression of the software and its capabilities.

TSO Logic↗
NASA NTRS2024

Future of the Search for Life: Workshop Report

The 2-week, virtual Future of the Search for Life science and engineering workshop brought together more than 100 scientists, engineers, and technologists in March and April 2022 to provide their expert opinion on the interconnections between life-detection science and technology. Participants identified the advances in measurement and sampling technologies they believed to be necessary to perform in situ searches for life elsewhere in our Solar System, 20 years or more in the future. Among suggested measurements for these searches, those pertaining to three potential indicators of life termed “dynamic disequilibrium,” “catalysis,” and “informational polymers” were identified as particularly promising avenues for further exploration. For these three indicators, small breakout groups of participants identified measurement needs and knowledge gaps, along with corresponding constraints on sample handling (acquisition and processing) approaches for a variety of environments on Enceladus, Europa, Mars, and Titan. Despite the diversity of these environments, sample processing approaches all tend to be more complex than those that have been implemented on missions or envisioned for mission concepts to date. The approaches considered by workshop breakout groups progress from nondestructive to destructive measurement techniques, and most involve the need for fluid (especially liquid) sample processing. Sample processing needs were identified as technology gaps. These gaps include technology and associated sampling strategies that allow the preservation of the thermal, mechanical, and chemical integrity of the samples upon acquisition; and to optimize the sample information obtained by operating suites of instruments on common samples. Crucially, the interplay between science-driven life-detection strategies and their technological implementation highlights the need for an unprecedented level of payload integration and extensive collaboration between scientists and engineers, starting from concept formulation through mission deployment of life-detection instruments and sample processing systems.

Marc Neveu↗
DOE OSTI2018

Principles of Design for Substrate-Supported Molecular Switches Based on Physisorbed and Chemisorbed States

The physisorbed (precursor) and chemisorbed states of a molecule on metal surfaces can be utilized to build a logic switch at the single-molecule level, enabling further microminiaturization of electronic devices beyond the silicon limits. However, a serious drawback of this design is easy lateral diffusion of the molecule in the physisorbed state, which may destroy the normal switch operation. Here, we demonstrate that anchoring engineering can be an effective way to enhance the stability of molecular switches without degrading switching functionality. As exemplified by trans -ADT on Cu(111), we show that the lateral diffusion of such molecular switch can be obstructed by the anchoring of the ending thiophene groups, along with a rotation of the adsorbate during the switching process. More general, our results also suggest that when searching for molecular switches with reversible physisorbed and chemisorbed states with excellent bistability and lateral stability, the focus should be on finding molecules with a moderate HOMO–LUMO energy gap and anchoring atoms with positive charge that can then be deposited on substrates with which they interact moderately. Furthermore, this allows further improvement of the lateral and vertical stability of such a molecular switch by substituting the thiophene groups with selenophene, thus establishing trans -ADS on Cu(111) as a promising switch.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗
DOE OSTI2015

COUPLING OF RELAP5-SCDAP MOD4.0 AND NEUTRONIC CODES

High-fidelity and accurate nuclear system codes play a key role in the design and analysis of complex nuclear power plants, which consist of multiple subsystems, such as the reactor core (and its fuel, burnable poisons, control elements, etc.), the reactor internal structures, the vessel, and the energy conversion subsystem and beyond to grid demand. Most commonly the interplay between these various subsystems is modeled using coupled codes, each of which represents one of the subsystems. And the most common direct coupling is that of thermal-hydraulics and neutronics codes. The subject of this paper is the coupling of codes that model not only thermal-hydraulics and neutronics, but also structural components damage. Furthermore, the neutronic component is not limited to the sole core solver. The coupled code system encompasses thermal-hydraulics, material performance of the fuel, neutronic solver, and neutronic data preparation. Thus, this paper presents a framework for coupling RELAP5/SCDAPSIM/MOD4.0 with a suite of neutron kinetics codes that includes NESTLE, DRAGON and a version of the ENDF library. The version of the RELAP5/SCDAPSIM/MOD4.0 code used in this work is one developed by Innovate System Software (ISS) as part of the international SCDAP Development and Training Program (SDTP) for best-estimate analysis to model reactor transients including severe accident phenomena. This RELAP5/SCDAPSIM/MOD4.0 code version is also capable of predicting nuclear fuel performance. It uses nodal power distributions to calculate mechanical and thermal parameters such as heat-up, oxidation and meltdown of fuel rods and control rods, the ballooning and rupture of fuel rod cladding, the release of fission products from fuel rods, and the disintegration of fuel rods into porous debris and molten material. On the neutronics side, this work uses the NESTLE and DRAGON codes. NESTLE is a multi-dimensional static and kinetic neutronic code developed at North Carolina State University. It solves up to four energy groups neutron diffusion equations utilizing the Nodal Expansion Method (NEM) in Cartesian or hexagonal geometry. The DRAGON code, developed at Ecole Polytechnique de Montreal, performs lattice physics calculations based on the neutron transport equation and is capable of using very fine energy group structures. In this work, we have developed a coupling approach to exchange data among the various modules. In the coupling process, the generated nuclear data (in fine multigroup energy structure) are collapsed down into two- or four-group energy structures for use in NESTLE. The neutron kinetics and thermal-hydraulics modules are coupled at each time step by using the cross-section data. The power distribution results of the neutronic calculations are transmitted to the thermal-hydraulics code. The spatial distribution of coolant density and the fuel-moderator temperature, which result from the thermal-hydraulic calculations, are transmitted back to the neutron kinetics codes and then the loop is closed using new neutronics results. Details of the actual data transfers will be described in the full length paper.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Experimental study and discrete element method simulation of Geldart Group A particles in a small-scale fluidized bed

Geldart Group A particles are of great importance in various chemical processes because of advantages such as ease of fluidization, large surface area, and many other unique properties. It is very challenging to model the fluidization behavior of such particles as widely reported in the literature. In this study, a pseudo-2D experimental column with a width of 5 cm, a height of 45 cm, and a depth of 0.32 cm was developed for detailed measurements of fluidized bed hydrodynamics of fine particles to facilitate the validation of computational fluid dynamic (CFD) modeling. The hydrodynamics of sieved FCC particles (Sauter mean diameter of 148 µm and density of 1300 kg/m3) and NETL-32D sorbents (Sauter mean diameter of 100 µm and density of 480 kg/m3) were investigated mainly through the visualization by a high-speed camera. Numerical simulations were then conducted by using NETL’s open source code MFIX-DEM. Both qualitative and quantitative information including bed expansion, bubble characteristics, and solid movement were compared between the numerical simulations and the experimental measurement. Furthermore, the cohesive van der Waals force was incorporated in the MFIX-DEM simulations and its influences on the flow hydrodynamics were studied.

42 ENGINEERING↗
NASA NTRS1973

Comparison of Lidar Methods for Remote Measurement of Air Pollutants

This paper presents quantitative comparisons of several single-ended lidar techniques for the remote measurement of gaseous pollutants. These techniques are divided into two groups. The first group is based on the measurement of energy scattered directly by the gas of interest. The gaseous scattering processes considered are ordinary fluorescence, resonance fluorescence (also called resonance scattering), Raman scattering, and resonant (or nearly resonant) Raman scattering. The second group is based on the measurement of a characteristic differential absorption produced by the gas of interest at two discrete wavelengths, using energy scattered back toward the receiver by a remote reflector other than the gas of interest. The remote reflector may be intermixed with the gas of interest, as is the case with aerosols and atmospheric gases (principally nitrogen), or they may be fixed reflectors such as terrestrial objects or retroflectors. The detectability of a given material will depend on the magnitude and characteristics of the optical interaction with that material. The main characteristics of interest are the cross section, the response time, and the spectral response of the material relative to both the transmit and receive functions of the lidar. These characteristics and their implications for remote sensing will be reviewed for the four direct scatter processes and for the differential absorption technique. The characteristic behavior of the direct backscatter technique is different from the differential absorption technique with respect to sensitivity, concentration of material, and the effect of range. For these reasons, the direct backscatter processes cannot be compared directly to the differential absorption technique. The two techniques can be compared for specific material and system configurations, however. This paper describes specific lidar system configurations and gives the calculated performance level for these systems in both the direct backscatter and differential absorption modes for a wide variety of pollutant monitoring situations. The results of this comparison of techniques indicate that the differential- absorption lidar technique can provide adequate range and sensitivity for a wide variety of pollution monitoring applications involving a number of interesting pollutant materials. No other single technique appears to provide these capabilities for such a wide range of materials.

Wright, M. L.↗
DOE OSTI2023

Investigation of process history and underlying phenomena associated with the synthesis of plutonium oxides using Vector Quantizing Variational Autoencoder

Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. Among other candidates, a neural network called a Vector Quantizing Variational Autoencoder (VQ-VAE) has shown the ability to quantitatively describe particle morphology to attain >85% accuracy in identifying uranium oxide processing routes. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO 2 ) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO 2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO 2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE, then further reduce the dimensionality of the feature space using a bottlenecking neural network fit to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO 2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Group Additivity Determination for Enthalpies of Formation of Carbenium Ions

Modeling of acid-catalyzed hydrocarbon conversion processes at the mechanistic level requires rate coefficients for a large number of reactions. The computational demand of finding activation energy barriers for each reaction is substantially reduced by employing structure–reactivity correlations such as the Evans–Polanyi relationship that correlates activation energy with the enthalpy of reaction. However, there are many species for which the enthalpies of formation are unknown. Therefore, group additivity methods to specify enthalpies of formation for each species involved in the reaction network are valuable. Quantum mechanical (QM) calculations and isodesmic reactions were used to calculate enthalpies of formation for a number of acyclic and cyclic carbenium ions, including allylic carbenium ions. These values compare favorably with experimental values, establishing Gaussian-4 as an accurate QM method for these calculations. Using these values, Benson-type group additivity values for enthalpies of formation were then derived through multiple linear regression. Enthalpies of formation values calculated from the group additivity scheme capture experimental and QM enthalpies of formation well and enhance the range of species that can be described by the group additivity approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-J-107: Supervised Learning Model of Aligned Collagen for Human Breast Carcinoma Prognosis

Purpose: Our goal is to develop and apply a set of optical and computational tools to enable large-scale investigations of the interaction between collagen and tumor cells. Methods: We have built a novel imaging system for automating the capture of whole-slide second harmonic generation (SHG) images of collagen in registry with bright field (BF) images of hematoxylin and eosin stained tissue. To analyze our images, we have integrated a suite of supervised learning tools that semi-automatically model and score collagen interactions with tumor cells via a variety of metrics, a method we call Electronic Tumor Associated Collagen Signatures (eTACS). This group of tools first segments regions of epithelial cells and collagen fibers from BF and SHG images respectively. We then associate fibers with groups of epithelial cells and finally compute features based on the angle of interaction and density of the collagen surrounding the epithelial cell clusters. These features are then processed with a support vector machine to separate cancer patients into high and low risk groups. Results: We validated our model by showing that eTACS produces classifications that have statistically significant correlation with manual classifications. In addition, our system generated classification scores that accurately predicted breast cancer patient survival in a cohort of 196 patients. Feature rank analysis revealed that TACS positive fibers are more well aligned with each other, generally lower density, and terminate within or near groups of epithelial cells. Conclusion: We are working to apply our model to predict survival in larger cohorts of breast cancer patients with a diversity of breast cancer types, predict response to treatments such as COX2 inhibitors, and to study collagen architecture changes in other cancer types. In the future, our system may be used to provide metastatic potential information to cancer patients to augment existing clinical assays.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Digital mammography, cancer screening: Factors important for image compression

The use of digital mammography for breast cancer screening poses several novel problems such as development of digital sensors, computer assisted diagnosis (CAD) methods for image noise suppression, enhancement, and pattern recognition, compression algorithms for image storage, transmission, and remote diagnosis. X-ray digital mammography using novel direct digital detection schemes or film digitizers results in large data sets and, therefore, image compression methods will play a significant role in the image processing and analysis by CAD techniques. In view of the extensive compression required, the relative merit of 'virtually lossless' versus lossy methods should be determined. A brief overview is presented here of the developments of digital sensors, CAD, and compression methods currently proposed and tested for mammography. The objective of the NCI/NASA Working Group on Digital Mammography is to stimulate the interest of the image processing and compression scientific community for this medical application and identify possible dual use technologies within the NASA centers.

Clarke, Laurence P.↗
NASA NTRS1993

Carbonate compositions in CM and CI chondrites, and implications for aqueous alteration

Carbonate minerals in fourteen CM chondrites and two CI chondrites have been analyzed by electron microprobe to provide a better understanding of the aqueous processes that affected carbonaceous chondrite parent bodies. Calcites in CM chondrites and dolomites and magnesites in CI chondrites display the compositions expected of stable phases formed at low temperatures. Dolomites in CM chondrites, identified here for the first time in five members of the group, have small amounts of excess Ca which may reflect metastable growth. The distribution of Fe between dolomite and coexisting serpentine differs in the two chondrite groups. If the distributions reflect an approach to chemical equilibrium, then the difference implies higher alteration temperatures for the CI group than the CM group in agreement with the results of previously published oxygen isotope thermometry and mineral solubility modeling of the alteration process. Dolomite Fe contents are relatively uniform in the two chondrite groups. Dolomite Mn contents, by contrast, vary widely. The variations may reflect transport-controlled coprecipitation of Mn resulting from a heterogeneous distribution of the element in the anhydrous precursor material. If this interpretation is correct, then the altering fluids were essentially immobile white hydration reactions proceeded on the meteorite parent bodies. The near closed-system character of the alteration process, long known from bulk chemical analyses of the meteorites, is a direct consequence of the limited mobility of dissolved species.

Johnson, Craig A.↗
DOE OSTI2015

Synthesis and characterization of bulk Cu{sub 2}ZnSnX{sub 4} (X: S, Se) via thermodynamically supported mechano-chemical process

Materials with the general formula, Cu{sub 2}ZnSnX{sub 4} (CZTX; X: Group 16 elements), with X being S/Se, have been receiving considerable attention due to their utility as an absorber layer in solar photovoltaics (PV). This paper reports on the synthesis of CZTSe and CZTS nanocrystalline powders at low temperatures, starting from elemental metal and chalcogen powders, via the low cost, scalable technique of ball milling. The prepared samples were well characterized using the different characterization tools. XRD, Raman, SEM and TEM studies confirm the formation of single-phase, stoichiometric, nano-crystalline kesterite CZTS and CZTSe powders. The low temperature phase selection of the complex quaternary compound in this system is seen as a direct consequence of the thermodynamic facilitation, coupled with the capability of mechano-chemical synthesis to aid in overcoming kinetic constraints. The optical bandgap of the various samples of CZTS was observed in the range of 1.4–1.6 eV and corresponding values for CZTSe was observed to be in the range of 1.08–1.18 eV. Our work provides a pathway for developing cheap, scalable, and ink-based techniques for low cost solar PV. - Graphical abstract: Display Omitted - Highlights: • A scalable route for synthesis of near phase pure CZTS/Se nano-crystals has been demonstrated. • Stoichiometric CZTS and CZTSe were synthesized via mechano-chemical synthesis route. • Synthesis at near room temperature is supported by thermodynamic calculations.

36 MATERIALS SCIENCE↗
NASA NTRS1970

The effects of work-related values on communication between R and D groups, part 1

The research concerned with the liaison, interface, coupling, and technology transfer processes that occur in research and development is reported. Overviews of the functions of communication and coupling in the R and D processes, and the theoretical considerations of coupling, communication, and values are presented along with descriptions of the field research program and the instrumentation.

Douds, C. F.↗
NASA NTRS1999

Physical Processes Governing Atmospheric Trace Constituents Measured from Aircraft in Pem-Tropics

The MIT group participated in seven publications in the 1999 issues of JGR with sections devoted in PEM-Tropics A, and had two papers which may be considered offshoots of these studies combined with commercial aircraft trace constituents data, one in Nature and one in EOS. In the meteorological overview we contributed a set of 1000 hPa divergent wind maps which we calculated from ECMWF data, meridional wind cross-sections, velocity potential and divergent wind maps, maps of stream function and rotational wind components, and vertical velocity profiles computed from mass balance, these all constituting part of the overall climatology. We also contributed material for the "stalactite" case observed from the DC-8 on September 3, 1996. This included a map of potential vorticity on 350 K, a cross-section of lidaro O3 a cross-section of potential vorticity along 140 deg W, and a map of specific humidity showing extreme dryness accompanying the high potential vorticity values and the high ozone values, all suggesting subsidence from the local stratosphere. In the paper on chemical characteristics we contributed 12 hour values of the 1000 hPa divergent wind component for the full period of PEM Tropics A; these were used by David Westberg to establish the air mass boundaries and in turn used by Gerry Gregory to set up a table of quantitative values of trace constituents and their ratios both sides of the boundaries.

Newell, Reginald E.↗
DOE OSTI2015

Selecting a Classification Ensemble and Detecting Process Drift in an Evolving Data Stream

We characterize the commercial behavior of a group of companies in a common line of business using a small ensemble of classifiers on a stream of records containing commercial activity information. This approach is able to effectively find a subset of classifiers that can be used to predict company labels with reasonable accuracy. Performance of the ensemble, its error rate under stable conditions, can be characterized using an exponentially weighted moving average (EWMA) statistic. The behavior of the EWMA statistic can be used to monitor a record stream from the commercial network and determine when significant changes have occurred. Results indicate that larger classification ensembles may not necessarily be optimal, pointing to the need to search the combinatorial classifier space in a systematic way. Results also show that current and past performance of an ensemble can be used to detect when statistically significant changes in the activity of the network have occurred. The dataset used in this work contains tens of thousands of high level commercial activity records with continuous and categorical variables and hundreds of labels, making classification challenging.

Ensemble classifiers↗
DOE OSTI2026

Simultaneous global and local clustering in multiplex networks with covariate information

Understanding both global and layer-specific group structures is useful for uncovering complex patterns in networks with multiple interaction types. In this work, we introduce a new model, the hierarchical multiplex stochastic blockmodel, which simultaneously detects communities within individual layers of a multiplex network while inferring a global node clustering across the layers. A stochastic blockmodel is assumed in each layer, with probabilities of layer-level group memberships determined by a node’s global group assignment. Our model uses a Bayesian framework, employing a probit stick-breaking process to construct node-specific mixing proportions over a set of shared Griffiths–Engen–McCloseky distributions. These proportions determine layer-level community assignment, allowing for an unknown and varying number of groups across layers, while incorporating nodal covariate information to inform the global clustering. We propose a scalable variational inference procedure with parallelisable updates for application to large networks. Extensive simulation studies demonstrate our model’s ability to accurately recover both global and layer-level clusters in complicated settings, and applications to real data showcase the model’s effectiveness in uncovering interesting latent network structure.

community detection↗