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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Using spatio-temporal graph neural networks to estimate fleet-wide photovoltaic performance degradation patterns

Accurate estimation of photovoltaic (PV) system performance is crucial for determining its feasibility as a power generation technology and financial asset. PV-based energy solutions offer a viable alternative to traditional energy resources due to their superior Levelized Cost of Energy (LCOE). A significant challenge in assessing the LCOE of PV systems lies in understanding the Performance Loss Rate (PLR) for large fleets of PV systems. Estimating the PLR of PV systems becomes increasingly important in the rapidly growing PV industry. Precise PLR estimation benefits PV users by providing real-time monitoring of PV module performance, while explainable PLR estimation assists PV manufacturers in studying and enhancing the performance of their products. However, traditional PLR estimation methods based on statistical models have notable drawbacks. Firstly, they require user knowledge and decision-making. Secondly, they fail to leverage spatial coherence for fleet-level analysis. Additionally, these methods inherently assume the linearity of degradation, which is not representative of real world degradation. To overcome these challenges, we propose a novel graph deep learning-based decomposition method called the Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR). PV-stGNN-PLR decomposes the power timeseries data into aging and fluctuation components, utilizing the aging component to estimate PLR. PV-stGNN-PLR exploits spatial and temporal coherence to derive PLR estimation for all systems in a fleet and imposes flatness and smoothness regularization in loss function to ensure the successful disentanglement between aging and fluctuation. We have evaluated PV-stGNN-PLR on three simulated PV datasets consisting of 100 inverters from 5 sites. Experimental results show that PV-stGNN-PLR obtains a reduction of 33.9% and 35.1% on average in Mean Absolute Percent Error (MAPE) and Euclidean Distance (ED) in PLR degradation pattern estimation compared to the state-of-the-art PLR estimation methods.

14 SOLAR ENERGY↗
DOE OSTI2015

Transgenic expression of the dicotyledonous pattern recognition receptor EFR in rice leads to ligand-dependent activation of defense responses

Plant plasma membrane localized pattern recognition receptors (PRRs) detect extracellular pathogen-associated molecules. PRRs such as Arabidopsis EFR and rice XA21 are taxonomically restricted and are absent from most plant genomes. Here we show that rice plants expressing EFR or the chimeric receptor EFR::XA21, containing the EFR ectodomain and the XA21 intracellular domain, sense both Escherichia coli- and Xanthomonas oryzae pv. oryzae (Xoo) -derived elf18 peptides at sub-nanomolar concentrations. Treatment of EFR and EFR::XA21 rice leaf tissue with elf18 leads to MAP kinase activation, reactive oxygen production and defense gene expression. Although expression of EFR does not lead to robust enhanced resistance to fully virulent Xoo isolates, it does lead to quantitatively enhanced resistance to weakly virulent Xoo isolates. EFR interacts with OsSERK2 and the XA21 binding protein 24 (XB24), two key components of the rice XA21-mediated immune response. Rice-EFR plants silenced for OsSERK2 , or overexpressing rice XB24 are compromised in elf18-induced reactive oxygen production and defense gene expression indicating that these proteins are also important for EFR-mediated signaling in transgenic rice. Taken together, our results demonstrate the potential feasibility of enhancing disease resistance in rice and possibly other monocotyledonous crop species by expression of dicotyledonous PRRs. Our results also suggest that Arabidopsis EFR utilizes at least a subset of the known endogenous rice XA21 signaling components.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Fluorescent Crimean-Congo hemorrhagic fever virus illuminates tissue tropism patterns and identifies early mononuclear phagocytic cell targets in Ifnar -/- mice

Crimean-Congo hemorrhagic fever virus (CCHFV, order Bunyavirales, family Nairoviridae, genus Orthonairovirus) is the tick-borne etiological agent of Crimean-Congo hemorrhagic fever (CCHF) in humans. Animals are generally susceptible to CCHFV infection but refractory to disease. Small animal models are limited to interferon-deficient mice, that develop acute fatal disease following infection. Here, using a ZsGreen1- (ZsG) expressing reporter virus (CCHFV/ZsG), we examine tissue tropism and dissemination of virus in interferon-α/β receptor knock-out (Ifnar -/- ) mice. We demonstrate that CCHFV/ZsG retains in vivo pathogenicity comparable to wild-type virus. Interestingly, despite high levels of viral RNA in all organs assessed, 2 distribution patterns of infection were observed by both fluorescence and immunohistochemistry (IHC), corresponding to the permissiveness of organ tissues. To further investigate viral dissemination and to temporally define cellular targets of CCHFV in vivo, mice were serially euthanized at different stages of disease. Flow cytometry was used to characterize CCHFV-associated alterations in hematopoietic cell populations and to classify infected cells in the blood, lymph node, spleen, and liver. ZsG signal indicated that mononuclear phagocytic cells in the lymphatic tissues were early targets of infection; in latestage infection, overall, the highest levels of signal were detected in the liver, and ZsG was found in both antigen-presenting and lymphocyte cell populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Extracting information from X-ray diffraction patterns containing Laue oscillations

The presence of Laue oscillations in a film grown on a solid surface is broadly taken as indicating a high quality, crystallographically aligned film of the targeted compound. In this paper we briefly review the origins of both Laue oscillations and Kiessig fringes and show how they can be used together to determine if extra thickness exists above or below the coherently diffracting domains. The differences between experimental and “ideal” films are discussed and the effect of structural features (roughness, different thickness coherently diffracting domains and thickness in addition to the coherently diffracting domains) are illustrated with experimental and simulated data for metal and mixed-metal chalcogenide films of titanium, bismuth, vanadium/iron, and bismuth/molybdenum. Examples are given showing how quantitative information can be extracted from experimental diffraction patterns.

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

Patterns and controls on island-wide aboveground biomass accumulation in second-growth forests of Puerto Rico

This dataset includes two products from Martinuzzi et al. (2022): "biomass.tif" is a 26-m resolution forest biomass (AGB) map for Puerto Rico derived from NASA G-LiHT lidar data and forest inventory data (FIA plots), in raster format. "input_multivariate_v2.shp" is a point shapefile with information on forest age, substrate, past land use, topographic wetness, slope, and precipitation, for each forest pixel. These two datasets can be used to evaluate spatial patterns of AGB in second-growth forests across transects of lidar data in humid forests of Puerto Rico, and to analyze relationship(s) between AGB and environmental variables. Additional information on these products can be found on the supporting file called "Readme.txt" included within the data archive, as well as in the original manuscript by Martinuzzi et al (2022).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Generation of Homogeneous and Patterned Electron Beams using a Microlens Array Laser-Shaping Technique

In photocathodes the achievable electron-beam parameters are controlled by the laser used to trigger the photoemission process. Non-ideal laser distribution hampers the final beam quality. Laser inhomogeneities, for instance, can be "amplified" by space-charge force and result in fragmented electron beams. To overcome this limitation laser shaping methods are routinely employed. In the present paper we demonstrate the use of simple microlens arrays to dramatically improve the transverse uniformity. We also show that this arrangement can be used to produce transversely-patterned electron beams. Our experiments are carried out at the Argonne Wakefield Accelerator facility.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Statistical patterns of theory uncertainties

A comprehensive uncertainty estimation is vital for the precision program of the LHC. While experimental uncertainties are often described by stochastic processes and well-defined nuisance parameters, theoretical uncertainties lack such a description. We study uncertainty estimates for cross-section predictions based on scale variations across a large set of processes. We find patterns similar to a stochastic origin, with accurate uncertainties for processes mediated by the strong force, but a systematic underestimate for electroweak processes. We propose an improved scheme, based on the scale variation of reference processes, which reduces outliers in the mapping from leading order to next-to-leading-order in perturbation theory.

Ghosh, Aishik↗
DOE OSTI2013

Nanostructure Patterning Under Energetic Particle Beam Irradiation

Energetic ion bombardment can lead to the development of complex and diverse nanostructures on or beneath the material surface through induced self-organization processes. These self-organized structures have received particular interest recently as promising candidates as simple, inexpensive, and large area patterns, whose optical, electronic and magnetic properties are different from those in the bulk materials. Compared to the low mass efficiency production rate of lithographic methods, these self-organized approaches display new routes for the fabrication of nanostructures over large areas in a short processing time at the nanoscale, beyond the limits of lithography. Although it is believed that surface nanostructure formation is based on the morphological instability of the sputtered surface, driven by a kinetic balance between roughening and smoothing actions, the fundamental mechanisms and experimental conditions for the formation of these nanostructures has still not been well established, the formation of the 3-D naopatterns beneath the irradiated surface especially needs more exploration.

42 ENGINEERING↗
DOE OSTI2014

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation and Completion of Episodic Information

Adult neurogenesis in the hippocampus region of the brain is a neurobiological process that is believed to contribute to the brain's advanced abilities in complex pattern recognition and cognition. Here, we describe how realistic scale simulations of the neurogenesis process can offer both a unique perspective on the biological relevance of this process and confer computational insights that are suggestive of novel machine learning techniques. First, supercomputer based scaling studies of the neurogenesis process demonstrate how a small fraction of adult-born neurons have a uniquely larger impact in biologically realistic scaled networks. Second, we describe a novel technical approach by which the information content of ensembles of neurons can be estimated. Finally, we illustrate several examples of broader algorithmic impact of neurogenesis, including both extending existing machine learning approaches and novel approaches for intelligent sensing.

Aimone, James Bradley↗
DOE OSTI2015

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information.

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information - Sandia researchers developed novel methods and metrics for studying the computational function of neurogenesis, thus generating substantial impact to the neuroscience and neural computing communities. This work could benefit applications in machine learning and other analysis activities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Peeking Network States with Clustered Patterns

Network traffic monitoring has long been a core element for effec- tive network management and security. However, it is still a chal- lenging task with a high degree of complexity for comprehensive analysis when considering multiple variables and ever-increasing traffic volumes to monitor. For example, one of the widely con- sidered approaches is to scrutinize probabilistic distributions, but it poses a scalability concern and multivariate analysis is not gen- erally supported due to the exponential increase of the complexity. In this work, we propose a novel method for network traffic moni- toring based on clustering, one of the powerful deep-learning tech- niques. We show that the new approach enables us to recognize clustered results as patterns representing the network states, which can then be utilized to evaluate “similarity” of network states over time. In addition, we define a new quantitative measure for the similarity between two compared network states observed in dif- ferent time windows, as a supportive means for intuitive analysis. Finally, we demonstrate the clustering-based network monitoring with public traffic traces, and show that the proposed approach us- ing the clustering method has a great opportunity for feasible, cost- effective network monitoring.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

What Use Patterns Were Observed for PEV Drivers at Publicly Accessible AC Level 2 EVSE Sites?

The EV Project deployed over 4,000 ACL2 EVSE for drivers to charge their plug-in electric vehicle (PEV) when away-from-home. The vast majority of these EVSE stations were installed to be available to all PEV drivers at publicly accessible locations. Some were also deployed for use at workplaces and fleets. This paper examines only the use patterns of PEV drivers using the EVSE intended to be publicly accessible.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Shear Alignment of Diblock Copolymers for Patterning Nanowire Meshes

Metallic nanowire meshes are useful as cheap, flexible alternatives to indium tin oxide – an expensive, brittle material used in transparent conductive electrodes. We have fabricated nanowire meshes over areas up to 2.5 cm 2 by: 1) mechanically aligning parallel rows of diblock copolymer (diBCP) microdomains; 2) selectively infiltrating those domains with metallic ions; 3) etching away the diBCP template; 4) sintering to reduce ions to metal nanowires; and, 5) repeating steps 1 – 4 on the same sample at a 90° offset. We aligned parallel rows of polystyrene-b-poly(2-vinylpyridine) [PS(48.5 kDa)-b-P2VP(14.5 kDa)] microdomains by heating above its glass transition temperature (T g ≈ 100°C), applying mechanical shear pressure (33 kPa) and normal force (13.7 N), and cooling below T g . DiBCP samples were submerged in aqueous solutions of metallic ions (15 – 40 mM ions; 0.1 – 0.5 M HCl) for 30 – 90 minutes, which coordinate to nitrogen in P2VP. Subsequent ozone-etching and sintering steps yielded parallel nanowires. We aimed to optimize alignment parameters (e.g. shear and normal pressures, alignment duration, and PDMS thickness) to improve the quality, reproducibility, and scalability of meshes. We also investigated metals other than Pt and Au that may be patterned using this technique (Cu, Ag).

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Exploring the Use of Activity Patterns for Smart Monitoring of Nuclear Facilities

The world is at an inflection point where our ability to collect data now far outpaces our ability to make use of it. LANL has a number of efforts to help us pull more meaningful insights out of our data and target resources to where they will be most impactful. We are exploring an approach to recognizing activity patterns across disparate data streams for a more holistic view of nuclear facility monitoring.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Determining Patterns from Radiation Portal Monitor Data: Enabling Data Insight with Visual and Interactive Exploratory Data Analysis

Smuggling of nuclear and radiological material is a complex problem that will need to be analyzed from a variety of angles in order to effectively combat something so rare, yet so hazardous. One crucial tool in the effort to detect and deter smuggling of rad/nuc materials is the radiation portal monitor (RPM)—machines that scan passengers at airports, vehicles and trains at border crossings, and shipping containers at ports throughout the world. While data from RPMs are regularly analyzed at the individual lane level to ensure monitor health and good operation, aggregate analysis of the data has not gone far beyond summary statistics such as number of occupancies and alarm rates. In particular, there are opportunities to carry out interactive exploratory data analysis with the help of tools like the R package Shiny and methods that lend themselves to the visual display of spatiotemporal correlations such as spatial PCA and detrended cross-correlation analysis. By doing so, we discover interesting spatiotemporal patterns in the data that point to specific events or anomalous moments in time that warrant further analysis.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

An FPGA-based Pattern Recognition Associative Memory

Pattern recognition associative memory (PRAM) devices are parallel processing engines which are used to tackle the complex combinatorics of track nding algorithms, particularly for silicon based tracking triggers. PRAM development has been mostly limited to the realm of ASICs, which often leads to lengthy and expensive design cycles. FPGAs allow for quick iterations, making them an ideal hardware platform for designing and evaluating new PRAM features before committing to silicon. In this paper we present our FPGA-based PRAM designs and discuss how logic blocks which were originally developed for ASICs have been redesigned to take advantage of modern FPGA architectures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Enhanced Light Extraction from Low Cost White OLEDs Fabricated on Novel Patterned Substrates” (Final Report)

Organic LEDs (OLEDs) are a very attractive emerging solid state lighting (SSL) technology. Currently, one of the main challenges is to increase the extraction of the light generated inside the OLED into the forward (viewing) hemisphere. In conventional OLEDs fabricated on a transparent flat anode coated on glass the outcoupling factor is only about 20%. About 50% of the light is lost at the metal cathode (surface plasmon excitation), and waveguided internally in the organic layers and the transparent anode. Another ~30% is waveguided in the substrate to its edges. The research addressed this issue of outcoupling by evaluating OLEDs fabricated on corrugated plastic substrates manufactured in a cost-effective approach. It demonstrated that the outcoupling from such OLEDs can exceed 50% by mitigating plasmon–related loss and internal waveguiding, even without the addition of a microlens array or a hemispherical lens, either of which extracts the light trapped in the substrate. Simulations conducted in parallel with the experimental effort demonstrated how the corrugation assists in the outcoupling. The project also evaluated the role of the corrugation pitch and height in determining the outcoupling factor and other properties of the OLEDs. The technical effectiveness and economic feasibility of the project lie in the patterning of the extracting plastic substrates in an approach that is scalable to roll-to-roll (R2R) manufacturing. R2R processes are drastically lower-cost than batch or single-unit fabrication. The corrugated plastic substrates studied are part of an integrated substrate that includes also a microlens array at the air-side of the substrate and a conductive electrode. The project that was a university-industry collaboration is of major benefit to the public as it demonstrates the feasibility of manufacturing highly efficient OLEDs for SSL in a R2R process, which would drastically reduce the manufacturing cost and increase production in the USA. SSL is efficient and environmentally-friendly. It reduces electricity consumption, and hence lighting cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Basic Research of Intrinsic Tamper indication Markings and Patterns defined by Pulsed Laser Irradiation

With our previous research, it was found that surface asperities or roughness must be present to create periodic surface structures upon laser exposure. In particular, an initial rough surface morphology (such as that found with a machined surface) provides multiple sites for light scattering, which underlies the formation of periodic ripple morphologies. Light scattering from a random surface creates patterns of periodic structures (with complex orientations) that could be used as intrinsic markings for tagging materials and equipment. Despite these initial findings, the fundamental mechanisms that give rise to periodic surface structures and their characteristic shapes were not identified in prior research.

36 MATERIALS SCIENCE↗