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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

"Smart" Sensor Module

An assembly that contains a sensor, sensor-signal-conditioning circuitry, a sensor-readout analog-to-digital converter (ADC), data-storage circuitry, and a microprocessor that runs special-purpose software and communicates with one or more external computer(s) has been developed as a prototype of "smart" sensor modules for monitoring the integrity and functionality (the "health") of engineering systems. Although these modules are now being designed specifically for use on rocket-engine test stands, it is anticipated that they could also readily be designed to be incorporated into health-monitoring subsystems of such diverse engineering systems as spacecraft, aircraft, land vehicles, bridges, buildings, power plants, oilrigs, and defense installations. The figure is a simplified block diagram of the "smart" sensor module. The analog sensor readout signal is processed by the ADC, the digital output of which is fed to the microprocessor. By means of a standard RS-232 cable, the microprocessor is connected to a local personal computer (PC), from which software is downloaded into a randomaccess memory in the microprocessor. The local PC is also used to debug the software. Once the software is running, the local PC is disconnected and the module is controlled by, and all output data from the module are collected by, a remote PC via an Ethernet bus. Several smart sensor modules like this one could be connected to the same Ethernet bus and controlled by the single remote PC. The software running in the microprocessor includes driver programs for operation of the sensor, programs that implement self-assessment algorithms, programs that implement protocols for communication with the external computer( s), and programs that implement evolutionary methodologies to enable the module to improve its performance over time. The design of the module and of the health-monitoring system of which it is a part reflects the understanding that the main purpose of a health-monitoring system is to detect damage and, therefore, the health-monitoring system must be able to function effectively in the presence of damage and should be capable of distinguishing between damage to itself and damage to the system being monitored. A major benefit afforded by the self-assessment algorithms is that in the output of the module, the sensor data indicative of the health of the engineering system being monitored are coupled with a confidence factor that quantifies the degree of reliability of the data. Hence, the output includes information on the health of the sensor module itself in addition to information on the health of the engineering system being monitored.

Mahajan, Ajay↗
NASA NTRS2010

Shorebird Migration Patterns in Response to Climate Change: A Modeling Approach

The availability of satellite remote sensing observations at multiple spatial and temporal scales, coupled with advances in climate modeling and information technologies offer new opportunities for the application of mechanistic models to predict how continental scale bird migration patterns may change in response to environmental change. In earlier studies, we explored the phenotypic plasticity of a migratory population of Pectoral sandpipers by simulating the movement patterns of an ensemble of 10,000 individual birds in response to changes in stopover locations as an indicator of the impacts of wetland loss and inter-annual variability on the fitness of migratory shorebirds. We used an individual based, biophysical migration model, driven by remotely sensed land surface data, climate data, and biological field data. Mean stop-over durations and stop-over frequency with latitude predicted from our model for nominal cases were consistent with results reported in the literature and available field data. In this study, we take advantage of new computing capabilities enabled by recent GP-GPU computing paradigms and commodity hardware (general purchase computing on graphics processing units). Several aspects of our individual based (agent modeling) approach lend themselves well to GP-GPU computing. We have been able to allocate compute-intensive tasks to the graphics processing units, and now simulate ensembles of 400,000 birds at varying spatial resolutions along the central North American flyway. We are incorporating additional, species specific, mechanistic processes to better reflect the processes underlying bird phenotypic plasticity responses to different climate change scenarios in the central U.S.

Smith, James A.↗
DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learningmethods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with uniform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10 Gbps connections with 0–366 ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss ratesbut become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Rao, Nageswara S.↗
DOE OSTI2016

Principles of proteome allocation are revealed using proteomic data and genome-scale models

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

Geonex: A NASA-NOAA Collaboration for Producing Land Surface Products from Geostationary Sensors Using Cloud Computing

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement.Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. We estimate the cost of deploying GEONEX to be $400 - 750 a month for processing data (every 30 minutes) and producing products over the conterminous US. For products such as Fire, latency can be as little as 10 minutes from the time of data acquisition.

Geostationary↗
DOE OSTI2020

2018 LDRD Annual Report (Argonne National Laboratory)

Argonne National Laboratory’s Laboratory Directed Research and Development (LDRD) program encourages the development of novel technical concepts, enhances the Laboratory’s research and development (R&D) capabilities, and enables pursuit of strategic laboratory goals. Argonne’s LDRD projects are proposal based and peer reviewed, supporting ideas that require advanced exploration so they can be sufficiently developed to pursue support through normal programmatic channels. Among the aims of the projects supported by the LDRD program are the establishment of engineering proofs of principle, assessment of design feasibility for prospective facilities, development of instrumentation or computational methods or systems, and discoveries in fundamental science and exploratory development. All LDRD projects have demonstrable ties to one or more of the science, energy, environment, and national security missions of the U.S. Department of Energy (DOE) and its National Nuclear Security Administration (NNSA), and many are also relevant to the missions of other federal agencies that sponsor work at Argonne. A natural consequence of the more “applied” type projects is their concurrent relevance to industry. The LDRD program is managed in overarching portfolios, each containing multiple projects each fiscal year. The LDRD Prime portfolio is further divided into strategic focus areas aligned with Argonne’s strategic plan. The largest component of Argonne’s program is LDRD Prime, which emphasizes R&D explicitly aligned with Laboratory major initiatives in support of Argonne’s strategic plan. The choice of Focus Areas under the LDRD Prime component reflects the major initiatives; the state of development of relevant technical fields; the potential value of advancing those fields to DOE/NNSA and the nation; and the compatibility of the fields with existing facilities, capabilities, and staff expertise at Argonne. Focus Areas with projects that ended in FY18 are: Advanced Computing, Biological and Environmental Science Capability Development, Energy Manufacturing Science and Engineering, Hard X-ray Sciences, Materials and Chemistry, Securing Energy and Critical Resources, and The Universe as Our Laboratory (ULab).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Future Trends in Nuclear Physics Computing

In nuclear physics (NP) today the study of quarks, gluons and their strong interactions extends across a broad research program at a varied range of collaborative scales, from a few collaborators up to large experiments at scales comparable to those typical of high energy physics (HEP). Overall, the software and computing efforts vary accordingly, from pragmatic do-it-yourself approaches among a few, to substantial organized software and computing activities within large experiments. With new experiments starting up and on the horizon [1], and rapidly increasing data volumes [2, 3] and processing demands even at small experiments, the NP community has in recent years been thinking about the next generation of data processing and analysis workflows that will maximize the science output. One context for this discussion has been a series of workshops, “Future Trends in Nuclear Physics Computing” [4]. The most recent in this series took place in Fall 2020, organized by the authors together with colleagues. The workshop focused on identifying the unique aspects of software and computing in NP, and discussing how the NP community could strengthen common efforts and chart a path forward for the next decade, sure to be an exciting one with rich ongoing scientific programs at Brookhaven National Laboratory (BNL), Jefferson Lab (JLab), and other NP facilities, and culminating in datataking at the Electron-Ion Collider (EIC) [5,6,7] in the early 2030s. Without claiming to present a collective view from the workshop and discussions since—fortunately this is not expected of us in this opinion editorial—we offer here our reflections on the topic, informed by the workshop and the summary we authored with our colleagues [8], as well as discussions and developments in the eventful time since.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Multihierarchy Gaussian Process Models for Probabilistic Aerodynamic Databases using Uncertain Nominal and Off-Nominal Configuration Data

Probabilistic aerodynamic databases are a crucial component of the development lifecycle for aerospace vehicles. A key challenge when building aerodynamic databases is that most data used to construct them represent various simplifications of the real flight vehicle. For example, wind tunnel models often simplify the vehicle geometry and surface roughness characteristics, while CFD computations often make simplifications to the physics being modeled, such as fully laminar or turbulent calculations. Multifidelity data fusion models rely on a user being able to define a hierarchy of fidelity levels anchored to some "truth" data. This approach is unsatisfactory when no data can be considered to accurately reflect real flight conditions. In this work, we provide an alternative approach by presenting a consistent mathematical framework for building probabilistic aerodynamic databases in the form of a conditional probability distribution described by an ensemble of multifidelity Gaussian Processes. Instead of relying on a single hierarchy of data fidelity levels, the presented framework identifies a "nominal" configuration and potential corrections to the nominal which represent specific physical phenomena not represented in the nominal data. The nominal and correction functions themselves are constructed as multifidelity Gaussian Processes and linearly combined to form an ensemble model which fuses the uncertainties associated nominal and correction models. Results obtained using the proposed framework on a simplified Orion Crew Module wind tunnel dataset demonstrate the predictive capability of the multihierarchy framework. We further demonstrate the benefits of such a probabilistic aerodynamic database approach through function sampling and computing the conditional distributions of derived quantities, such as the trim angle of attack and aerodynamic coefficients at trim.

Gaussian Processes↗
DOE OSTI2021

Tailoring Interfaces in Solid-State Batteries Using Interfacial Thermochemistry and Band Alignment

Solid-state lithium ion batteries have enhanced thermal stability compared to batteries using liquid electrolytes. Although their practical implementation is limited by undesired side reactions between the electrode and electrolyte, different modification strategies have been proposed to stabilize these reactive interfaces. These approaches have been primarily based upon bulk materials properties, however, which may not necessarily be representative of the chemistry at the solid/solid interface. In this work, first principles calculations and X-ray scattering experiments are used to elucidate molecular-level reactivity and develop design principles for tailored interfaces based on surface and interfacial properties. Because of its well-known instability, the interface between the Li metal anode and the lithium lanthanum titanate (LLTO) solid electrolyte is applied as a model system. Density functional theory calculations are used to describe bulk, surface, and interfacial thermochemistry of the Li/LLTO system, and interfacial reconstruction is probed using ab initio molecular dynamics. These simulations of the Li/LLTO interface demonstrate facile decomposition concomitant with reduction of Ti 4+ ions. Based on further insights from computational analysis of the surface band edge positions, La 2 O 3 is proposed as an interlayer coating and is shown to provide an energetic barrier for interfacial charge transfer and decomposition reactions from X-ray reflectivity measurements and theoretical calculations. The findings in this work suggest that design strategies based on surface and interfacial properties can be used to kinetically stabilize electrode/electrolyte interfaces in solid-state batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Metal-to-Ligand Charge-Transfer Spectrum of a Ru-Bipyridine-Sensitized TiO 2 Cluster from Embedded Multiconfigurational Excited-State Theory

Understanding optical properties of the dye molecule in dye-sensitized solar cells (DSSCs) from first-principles quantum mechanics can contribute to improving the efficiency of such devices. While density functional theory (DFT) and time-dependent DFT have been pivotal in simulating optoelectronic properties of photoanodes used in DSSCs at the atomic scale, questions remain regarding DFT’s adequacy and accuracy to furnish critical information needed to understand the various excited-state processes involved. In this work, we simulate the absorption spectra of a dye-sensitized solar cell analogue, comprised of a Ru-bipyridine (Ru-bpy) dye molecule and a small TiO2 cluster via DFT and via an accurate embedded correlated wavefunction (CW) theory. We generated CW spectra for the adsorbed Ru-bpy dye via a recently introduced capped density functional embedding theory or capped-DFET (to generate the embedding potential that accounts for the interaction of the molecule and the TiO 2 cluster). We then combined capped-DFET with the accurate but expensive multiconfigurational complete active space second-order perturbation theory (CASPT2)—embedded CASPT2. Because the CW theory is conducted on only a portion of the total system in the presence of an embedding potential that describes that portion’s interaction with its environment, we efficiently obtain CW-quality predictions that reflect local properties of the entire system. Specifically, for example, with capped-DFET and embedded CW theory, we can simulate accurately a plethora of metal-to-ligand charge-transfer excited properties at a manageable computational cost. Here, we predict detailed electronic spectra within the visible region, featuring the lowest three singlet and triplet excited states, along with predictions of the singlets’ lifetimes. We illustrated these results using a Jablonski diagram that show the relative energy position of the singlet and longer-lived triplet excited states and analyzed and proposed relaxation paths for the excited state corresponding to the most intense but short-lived absorption (interconversion, intersystem crossing, fluorescence, and phosphorescence) that may lead to longer-lived excited states necessary for efficient charge separation required to generate current in solar cells.

14 SOLAR ENERGY↗
DOE OSTI2025

Evaluating the Structural Response of Amphiphilic Monolayers to Environmental Stimuli

Amphiphilic monolayers composed of end groups with distinct polar and nonpolar functional groups offer rapid and reversible interfacial adaptation in response to environmental stimuli such as a change in interfacial medium polarity. We have synthesized and characterized a suite of monolayers with functional groups of competing polarity designed to reconfigure their interfacial chemical composition in response to solvent polarity. In these films, the end group is designed to be able to reorient and expose the functional groups that minimize the interfacial free energy between the film and the environment. Using a combination of spectroscopic, computational, and wettability studies, we have investigated the responsive interfacial behavior of different end groups upon exposure to environments with varying polarities. Contact angle measurements across a series of polar and dispersive probe liquids reveal trends that reflect the underlying molecular flexibility and composition. Vibrational sum frequency generation (SFG) spectroscopy and atomistic molecular dynamics (MD) simulations confirm solvent-driven reorientation of the end groups, with restructuring observed at the interface. To quantify these effects, we have developed a surface energy calculation model that incorporates solvent-induced surface rearrangements into the estimations. Our findings reveal a strong dependence of surface energy and switching behavior on the length and flexibility of the functionalities in the end group, which affects the exposure of certain interfacial compositions under different solvents. These results offer new insights into the design of adaptive monolayers and provide a framework for evaluating solvent-responsive surfaces.

functional groups↗
DOE OSTI2015

Understanding the Electronic Structure of 4d Metal Complexes: From Molecular Spinors to L-Edge Spectra of a di-Ru Catalyst

L{sub 2,3}-edge X-ray absorption spectroscopy (XAS) has demonstrated unique capabilities for the analysis of the electronic structure of di-Ru complexes such as the blue dimer cis,cis-[Ru{sub 2}{sup III}O(H{sub 2}O){sub 2}(bpy){sub 4}]{sup 4+} water oxidation catalyst. Spectra of the blue dimer and the monomeric [Ru(NH{sub 3}){sub 6}]{sup 3+} model complex show considerably different splitting of the Ru L{sub 2,3} absorption edge, which reflects changes in the relative energies of the Ru 4d orbitals caused by hybridization with a bridging ligand and spin-orbit coupling effects. To aid the interpretation of spectroscopic data, we developed a new approach, which computes L{sub 2,3}-edges XAS spectra as dipole transitions between molecular spinors of 4d transition metal complexes. This allows for careful inclusion of the spin-orbit coupling effects and the hybridization of the Ru 4d and ligand orbitals. The obtained theoretical Ru L{sub 2,3}-edge spectra are in close agreement with experiment. Critically, existing single-electron methods (FEFF, FDMNES) broadly used to simulate XAS could not reproduce the experimental Ru L-edge spectra for the [Ru(NH{sub 3}){sub 6}]{sup 3+} model complex nor for the blue dimer, while charge transfer multiplet (CTM) calculations were not applicable due to the complexity and low symmetry of the blue dimer water oxidation catalyst. We demonstrated that L-edge spectroscopy is informative for analysis of bridging metal complexes. The developed computational approach enhances L-edge spectroscopy as a tool for analysis of the electronic structures of complexes, materials, catalysts, and reactive intermediates with 4d transition metals.

Alperovich, Igor↗
DOE OSTI2018

Comparative study of perovskite-type scintillator materials CsCaI 3 and KCaI 3 via first-principles calculations

Several members of a large family of perovskite-like halides with a common chemical formula, ABX3 (A = monovalent, B = divalent, and X = halogen ion), are being investigated for their interesting properties and potential technological applications. CsCaI3 and KCaI3 are two such ionic compounds who are of interest in the quest for superior and cost-effective alternatives to NaI or CsI based scintillators. They are the subject of this first-principles based computational study. Both are wide-gap materials having primarily I 5p and Ca 3d characters near the valence and conduction band edges, respectively. Although built from [CaI6] octahedral motifs, structural differences between the two compounds is reflected in anisotropic electron effective mass and distinctive formation and migration of self-trapped holes. We discuss these properties as they relate to scintillation decay and proportional light yield.

Kang, Byungkyun↗
DOE OSTI2022

Benchmark evaluation of one dimensional array of HEU moderated and reflected by Lucite

The evaluation of two HEU-Lucite experiments is presented. The critical experiments were performed using the Planet Universal Critical Assembly Machine at Los Alamos National Laboratory in 2019. In these experiments, HEU foils were interleaved with Lucite in a column stack and were moderated and reflected from the square Lucite plates. The neutron data produced were used to approximate the multiplication of each measured configuration. The evaluation of the experiments using calculational techniques is presented in the paper. A Monte-Carlo computational model to be used with MCNP6 was developed for the determination of uncertainties and the effects of various uncertainties on the multiplication factor were studied. The evaluation of the benchmark was performed for comparison of calculation results with the experimental data and validation of calculation techniques in particular the newly available thermal scattering data for the Lucite material. The sensitivity studies include parametric variations of material composition and geometry. Experimental uncertainties were low, with the overall height of the HEU/Lucite stack being the largest contributor to the overall uncertainty in k{sub eff}. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1971

Fast Mars communication geometry program

Computer program calculates trajectories of orbiting spacecraft and lander vehicles simultaneously. Using data from both vehicles, program calculates communications geometry which consists of orbiting spacecraft cone/clock angle, lander cone/clock angle, range, range rate and acceleration, and fade, reflective, and system margins.

Garner, W. R.↗
NASA NTRS1973

Net radiation method for transmission through partially transparent plates

It is shown that the net radiation method for enclosures with opaque surfaces described by Siegel and Howell (1972) can, in an appropriately adapted version, provide a computation procedure suitable for situations with semitransparent regions. This procedure involves simple equations at each interface and can be readily applied to complicated systems such as those consisting of absorbing and nonabsorbing layers, and layers with different reflectivities at each interface. The equations can also be readily incorporated in a computerized design procedure.

Siegel, R.↗
NASA NTRS1975

Application of ERTS images and image processing to regional geologic problems and geologic mapping in northern Arizona

The author has identified the following significant results. Computer image processing was shown to be both valuable and necessary in the extraction of the proper subset of the 200 million bits of information in an ERTS image to be applied to a specific problem. Spectral reflectivity information obtained from the four MSS bands can be correlated with in situ spectral reflectance measurements after path radiance effects have been removed and a proper normalization has been made. A detailed map of the major fault systems in a 90,000 sq km area in northern Arizona was compiled from high altitude photographs and pre-existing published and unpublished map data. With the use of ERTS images, three major fault systems, the Sinyala, Bright Angel, and Mesa Butte, were identified and their full extent measured. A byproduct of the regional studies was the identification of possible sources of shallow ground water, a scarce commodity in these regions.

Goetz, A. F. H.↗
NASA NTRS1977

Remote sensing of vegetation and soil using microwave ellipsometry

A method is described of determining vegetation height and water content of vegetation from the intensity and state of elliptical polarization of a reflected train of microwaves. The method comprises the steps of reflecting a circularly polarized train of microwaves from vegetation at a predetermined angle of incidence and detecting the reflected train of microwaves. The ratio of the intensities of the electric field vector components is determined, the phase difference of the components is measured, and the refractive index and thickness of the layer of vegetation are computed from a formula. The refractive index is given essentially by the water content of the vegetation.

Auer, S. O.↗