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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Partial Least Squares and Neural Networks for Quantitative Calibration of Laser-induced Breakdown Spectroscopy (LIBs) of Geologic Samples

The ChemCam instrument [1] on the Mars Science Laboratory (MSL) rover will be used to obtain the chemical composition of surface targets within 7 m of the rover using Laser Induced Breakdown Spectroscopy (LIBS). ChemCam analyzes atomic emission spectra (240-800 nm) from a plasma created by a pulsed Nd:KGW 1067 nm laser. The LIBS spectra can be used in a semiquantitative way to rapidly classify targets (e.g., basalt, andesite, carbonate, sulfate, etc.) and in a quantitative way to estimate their major and minor element chemical compositions. Quantitative chemical analysis from LIBS spectra is complicated by a number of factors, including chemical matrix effects [2]. Recent work has shown promising results using multivariate techniques such as partial least squares (PLS) regression and artificial neural networks (ANN) to predict elemental abundances in samples [e.g. 2-6]. To develop, refine, and evaluate analysis schemes for LIBS spectra of geologic materials, we collected spectra of a diverse set of well-characterized natural geologic samples and are comparing the predictive abilities of PLS, cascade correlation ANN (CC-ANN) and multilayer perceptron ANN (MLP-ANN) analysis procedures.

Anderson, R. B.↗
DOE OSTI2020

Automated Vehicle Detection in a Nuclear Facility Using Low-Frequency Acoustic Sensors

This article presents an analysis of the method of construction and results for a classifier intended to identify vehicles using low-frequency acoustic data collected by a dis-tributed sensor network. This data is collected as part of a venture intended to explore data analytics and multisensor fusion techniques for the monitoring of activities at a test bed nuclear facility located at Oak Ridge National Laboratory in Oak Ridge, Tennessee. We describe the associated target signature and design a classifier based on a multilayer perceptron, followed by an analysis of its results. We discuss how overall accuracy is not the only consideration in constructing this classifier, and how for this application, it is actually desirable to operate at a lower level of accuracy in exchange for a reduction in the false alarm rate, as well as how this relates to the actual deployment of the classifier in practical use.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2020

Permanently Magnetized Insulating Thin-Film Devices by Reduction

A reduction-based manufacturing process for creating technologically important multilayer structures from lattice-matched ferromagnetic insulators and ferromagnetic conductors is reported. The process is demonstrated by growing a permanently magnetized double-layer structure, consisting of lattice-matched conducting (Ni,Co) and insulating (Ni 0.4 Co 0.6 ) 3 O 3 layers, through a single deposition cycle. The orientation of the metal cation network is preserved after reduction. Close-packing displacements of Ni and Co take place in such a manner that the in-plane hexagonal arrangement is preserved. This is critical for ensuring high-quality interfaces joining the layers. At room temperature the hysteresis loop is centered. At low temperature the oxide layer becomes ferrimagnetically ordered, accompanied by a shift of the hysteresis loop along the magnetic field axis. The shift is assigned to exchange bias phenomenon. Biaxial compressive strain is responsible for the required ferrimagnetic ordering. Finally, spin valves and closely related magnetoresistance random access memory and spin-transfer-torque magnetic random access memory devices are addressed as potential applications.

42 ENGINEERING↗
NASA NTRS2003

Compact Interconnection Networks Based on Quantum Dots

Architectures that would exploit the distinct characteristics of quantum-dot cellular automata (QCA) have been proposed for digital communication networks that connect advanced digital computing circuits. In comparison with networks of wires in conventional very-large-scale integrated (VLSI) circuitry, the networks according to the proposed architectures would be more compact. The proposed architectures would make it possible to implement complex interconnection schemes that are required for some advanced parallel-computing algorithms and that are difficult (and in many cases impractical) to implement in VLSI circuitry. The difficulty of implementation in VLSI and the major potential advantage afforded by QCA were described previously in Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 42. To recapitulate: Wherever two wires in a conventional VLSI circuit cross each other and are required not to be in electrical contact with each other, there must be a layer of electrical insulation between them. This, in turn, makes it necessary to resort to a noncoplanar and possibly a multilayer design, which can be complex, expensive, and even impractical. As a result, much of the cost of designing VLSI circuits is associated with minimization of data routing and assignment of layers to minimize crossing of wires. Heretofore, these considerations have impeded the development of VLSI circuitry to implement complex, advanced interconnection schemes. On the other hand, with suitable design and under suitable operating conditions, QCA-based signal paths can be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes. The proposed architectures require two advances in QCA-based circuitry beyond basic QCA-based binary-signal wires described in the cited prior article. One of these advances would be the development of QCA-based wires capable of bidirectional transmission of signals. The other advance would be the development of QCA circuits capable of high-impedance state outputs. The high-impedance states would be utilized along with the 0- and 1-state outputs of QCA.

Fijany, Amir↗
DOE OSTI2025

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗
NASA NTRS1998

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

Chepfer, H.↗
NASA NTRS1987

NASA plans for observations of SN1987A

The scientific aims and technological implementation of NASA observations of SN 1987A are outlined in a status report. Key questions to be answered involve nucleosynthesis and the light curves of type II SN; the multilayer structure of the progenitor and the SNR; circumstellar gas, shock-wave, and dust formation; and the evolution of the core remnant. Consideration is given to continued SMM, IUE, Voyager UVS, and DSN observations; future space missions such as GRO, AXAF, and Rosat; balloon-borne gamma-ray, rocket-borne X-ray, and airborne IR observations; and the Science Communications Network and Data Archive.

Riegler, Guenter R.↗
NASA NTRS1993

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗
NASA NTRS1988

Surface emitting lasers for optical circuitry - Optical interconnect technology

Surface emitting (SE) lasers and their application in VLSI optical interconnect networks are considered. In particular, the advantages provided by SE lasers in optical interconnect circuits and monolithic integration are discussed. Some of the requirements, such as wavelength stability, power dissipation, emission angle, size, etc., are compared with respect to conventional laser diodes. It is noted that the operation of SE lasers will be critically dependent on the properties of the feedback reflectors. Experimental measurements of reflection spectra on AlGaAs/GaAs multilayer reflectors and InAlAs/InGaAs etalons formed with molecular beam epitaxy (MBE) are presented.

Yu, P. K. L.↗
DOE OSTI2024

Regulating the Third Metal to Design and Engineer Multilayered NiFeM (M: Co, Mn, and Cu) Nanofoam Anode Catalysts for Anion-Exchange Membrane Water Electrolyzers

In this study, alkaline anion-exchange membrane water electrolyzers (AEMWEs) for green hydrogen production have received intensive attention due to their feasibility of using earth-abundant platinum group metal (PGM)-free catalysts. Herein, the third metal is incorporated into NiFe-based catalysts to regulate their electronic structures and morphologies, aiming to achieve sufficient oxygen evolution reaction (OER) activity and performance in AEMWEs. The ternary NiFeM (M: Cu, Co, or Mn) catalysts are featured with multiple layered structures and nanofoam network morphologies, consisting of highly OER-active amorphous Ni-rich oxide shells and electrically conductive metallic alloy cores. The physical and electronic perturbations to the NiFe induced by a third element lead to a fine-tuning of the redox ability of the metal sites at the reaction centers, which breaks the scaling relationship between OH* and O* intermediates at the reaction centers. Thus, the unique structural configuration and electronic regulation simultaneously benefit catalytic activity and performance improvements. These NiFeM nanofoam catalysts demonstrated promising anode performance in actual AEMWEs, comparable to the IrO 2 reference, especially at high current densities. Notably, using various electrolytes (e.g., KOH solution or pure water) for AEMWEs exhibited a different performance trend among studied NiFeM catalysts, likely due to dynamic changes of catalysts under various OER environments.

25 ENERGY STORAGE↗
DOE OSTI2023

Chapter 32 - Power Grid Resilience

The new energy paradigm is altering the current power grid trend from synchronous generator reliant system toward power-electronics-based distributed energy resources (DERs). The resilient operation of modern power grid is highly dependent upon cyber and physical reliable operation of DERs. Power grid resilience broadly refers to the ability of the grid to be robust to eventualities and singularities that may disrupt the continuity of reliable power flow. This could involve resilience related to the physical system but more recently, the focus on cyber resilience has been evolving rapidly especially given the burgeoning growth of distributed generation and power-electronics-based DERs under smart grid and given that such threats to reliable operation do not have to evolve localized to where the physical asset is. Commonly, in power grids dominated by DERS, control and energy management are structured at a multitime scale multilayer fashion: (i) primary control layer at microseconds time scale, (ii) secondary control layer at millisecond time scale, and (iii) tertiary control layer at seconds to minutes time scale. The cyber-related issues that may affect the power grid resilience can be introduced in through primary, secondary, and tertiary control layers. The failure of each of these control layers may impact the reliable and resilient operation of the overall network and cause widespread failures which leads to unintended blackouts. As such, this chapter focuses on cyber-related resilience issues in primary control layer, secondary control layer, tertiary control layer, wide area/utility control, and anomaly detection and resilient communication.

anomaly detection↗
DOE OSTI2023

Emulating aerosol optics with randomly generated neural networks

Abstract. Atmospheric aerosols have a substantial impact on climate and remain one of the largest sources of uncertainty in climate prediction. Accurate representation of their direct radiative effects is a crucial component of modern climate models. However, direct computation of the radiative properties of aerosol populations is far too computationally expensive to perform in a climate model, so optical properties are typically approximated using a parameterization. This work develops artificial neural networks (ANNs) capable of replacing the current aerosol optics parameterization used in the Energy Exascale Earth System Model (E3SM). A large training dataset is generated by using Mie code to directly compute the optical properties of a range of atmospheric aerosol populations given a large variety of particle sizes, wavelengths, and refractive indices. Optimal neural architectures for shortwave and longwave bands are identified by evaluating ANNs with randomly generated wirings. Randomly generated deep ANNs are able to outperform conventional multilayer-perceptron-style architectures with comparable parameter counts. Finally, the ANN-based parameterization produces significantly more accurate bulk aerosol optical properties than the current parameterization when compared with direct Mie calculations using mean absolute error. The success of this approach makes possible the future inclusion of much more sophisticated representations of aerosol optics in climate models that cannot be captured by extension of the existing parameterization scheme and also demonstrates the potential of random-wiring-based neural architecture search in future applications in the Earth sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Tempering kinetics during multilayer laser additive manufacturing of a ferritic steel

Grade 91 steel forms martensite during additive manufacturing and the extent of tempering of martensite significantly affects the mechanical properties of parts. Currently, there is a lack of quantitative understanding of the tempering kinetics for Grade 91 steel, and as a result, the effects of repeated thermal cycles on properties for different processing conditions cannot be determined. Here we evaluate the tempering kinetics by determining the constant terms in the Johnson Mehl Avrami kinetic equation from the tempering data available in the literature and the thermal cycles computed using a rigorously-tested heat and fluid flow model of multi-layer additive manufacturing. The raw tempering data are cleaned using a neural network to enhance accuracy. The lower layers experience repeating cycles of heating and cooling when the upper layers are added. As a result, the hardness is reduced owing to the tempering of martensite. In contrast, martensite formed in the upper layers is not tempered to the same extent and the hardness remains high. Therefore, the hardness of the part increases with the distance from the substrate. Variations in the heat input at different laser powers and scanning speeds significantly affect the extent of tempering. Finally, since the method used here can provide a quantitative understanding of the tempering of martensite and the spatial variation in hardness, it can be used to tailor the microstructure and hardness of heat treatable printed metallic parts.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Cloud fields derived from satellite and surface data during FIRE cirrus phase 2

The interpretation of surface and aircraft measurements of cloud properties taken during field programs must take into account the large-scale cloud and meteorological conditions. Cloud properties are also required at scales beyond the point and line data taken from ground and aircraft platforms. Satellite data can provide a quantitative description of these large-scale cloud properties. When derived from geostationary satellite data, the cloud fields constitute a unique source for evaluating the development and demise of a cloud system. Satellites, however, can only see the tops of clouds, so that cloud layers below the uppermost cloud deck may remain undetected resulting in a incomplete depiction of the cloud system. Some multilayer clouds are amenable to detection from satellites. Many, especially in midlatitude cyclonic systems, can only be observed from the surface. A combination of surface and satellite cloud observations should be the most complete quantification of large-scale cloudiness if there are sufficient surface measurements. During the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment Phase 2 (FIRE-2) Cirrus Intensive Field Observation (IFO) period (November 13 - December 7, 1991) conducted at Coffeyville, Kansas, cirrus observations were taken in a variety of conditions. The IFO area was selected for a variety of reasons including the relatively dense network of surface weather stations and special surface instrumentation sites. Thus, the FIRE-2 IFO presents an excellent opportunity to combine cloud observations from surface and satellite observations. This paper presents an analysis of cloud properties on a mesoscale grid using satellite cloud property retrievals, surface observer data, and rawinsonde temperature and humidity profiles.

Minnis, Patrick↗
DOE OSTI2025

Edge-driven transition between extended quantum anomalous Hall crystal and fractional Chern insulator in rhombohedral graphene multilayers

Fractional Chern insulators (FCI) with fractionally quantized Hall conductance at fractional fillings and an extended quantum anomalous Hall (EQAH) crystal with an integer quantized Hall conductance over an extended region of doping were recently observed in pentalayer graphene. One particularly puzzling observation is the transition between the EQAH and FCI regimes, driven either by temperature or electrical current. Here, in this study, we propose a scenario to understand these transitions based on the topologically protected gapless edge modes that are present in both the FCI and EQAH phases and should be most relevant at temperature scales below the energy gap. Our consideration is based on the simple assumption that the edge velocity in FCI is smaller than that in EQAHE and thus contributes to a higher entropy. We further argue that domains with opposite fractionally quantized Hall conductance are ubiquitous in the devices due to disorder, which gives rise to a network of edge modes. The velocity of the edge modes between domains is further reduced due to edge reconstruction. The edge velocity can also be reduced by current when the occupation of the edge mode approaches the gap edge. The edge entropy therefore drives the transition from EQAH to FCI either by temperature or current at a nonzero temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2003

The Solar Chromosphere/Corona Interface: FUV-EUV Observations and Modeling of Unresolved Coronal Funnels - I

A coronal funnel model, developed by Rabin (199l), was tested against a calibrated spectroheliogram recorded in 171 - 175 Angstrom bandpass. This image was recorded on board a sounding rocket experiment flown on 1994 November 3, called the Multi-Spectral Solar Telescope Array, II (MSSTA II), MSSTA, a joint project of Stanford University, the NASA Marshall Space Flight Center and the Lawrence Livermore National Laboratory, is an observing platform composed of a set of normal-incidence, multilayer-coated optics designed to obtain narrow bandpass, high resolution images (1 - 3 arc sec) at selected FUV, EUV and soft X-ray wavelengths (44 Angstroms - 1550 Angstroms). Using full-disk images centered at 1550 Angstroms (C IV) and 173 Angstroms (FE IX/X), the funnel model, which is based on coronal back-heating, was tested against the data incorporating observed constraints on global coverage and measured flux. Found, was a class of funnel models that could account for the quiescent, globally diffuse and unresolved emission seen in the 171 - 175 Angstrom bandpass, where the funnels are assumed to be rooted in the C IV supergranular network. These models, when incorporated with the Chianti spectral code, suggest that this emission is mostly of upper transition region origin and primarily composed of FE IX plasma. The funnels are found to have constrictions, Gamma approx. 6 - 20, which is in good agreement with the observations. Further, the fitted models simultaneously satisfy global areal constraints seen in both images; namely, that a global network of funnels must cover approx. 70 - 95 % of the total solar surface area seen in the 171 - 175 Angstrom image, and = 45 % of the disk area seen in the 1550 Angstrom bandpass. These findings support the configuration of the EUV magnetic network as suggested by Reeves et af. (1974) and put forth in more detail by Gabriel (1976). Furthermore, the models are in good agreement with differential emission measure estimates made of the transition region by Raymond & Doyle (1981) for temperatures, 250,000 K = T = 650,000 K, based on full-disk observations made on board by SkyLab.

Martinez-Galarce, D. S.↗
NASA NTRS1975

Periodic variations in stratospheric-mesospheric temperature from 20-65 km at 80 N to 30 S

Results on large-scale periodic variations of the stratospheric-mesospheric temperature field based on Meteorological Rocket Network (MRN) measurements are reported for a long-term (12-year) mean, the quasi-biennial oscillation (QBO), and the first three harmonics of the annual wave (annual wave, semi-annual wave, and terannual wave or 4-month variation). Station-to-station comparisons are tabulated and charted for amplitude and phase of periodic variations in the temperature field. Masking and biasing factors, such as diurnal tides, solar radiation variations, mean monthly variations, instrument lag, aerodynamic heating, are singled out for attention. Models of the stratosphere will have to account for these oscillations of different periods in the thermal field and related properties of the wind fields, with multilayered horizontal stratification with height taken into account.-

Nastrom, G. D.↗
NASA NTRS2003

Multilayer Patch Antenna Surrounded by a Metallic Wall

A multilayer patch antenna, similar to a Yagi antenna, surrounded by a metallic wall has been devised to satisfy requirements to fit within a specified size and shape and to generate a beam with a half-power angular width of <=40 deg. This antenna provides a gain of about 14 dB; in contrast, the gain of a typical single-patch antenna lies between 5 and 6 dB. This antenna can be considered an alternative to a two-dimensional array of patch antenna elements, or to a horn or helical antenna. Unlike a two-dimensional array of patches, this antenna can function without need for a power-division network (unless circular polarization is needed). The profile of this antenna is lower than that of a horn or a helical antenna designed for the same frequency. The primary disadvantage of this antenna, relative to a horn or a helical antenna, is that its footprint is slightly larger.

Zawadzki, Mark↗