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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Gaussian process regression for radiological contamination mapping- Applied to optimal motion planning for mobile sensor platforms [Slides]

Want to achieve best representative characterization of the entire area efficiently and accurately-Unmanned aerial/ground vehicles (UAV/UGVs) for contamination mapping. Some major challenges include: Limited battery life (move smart), Human operated (fully autonomous controls) and Many measurements (predictive mapping capabilities). The objective: Develop fully autonomous controls for mobile sensor platforms to improve efficiency and maintain performance.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Status of ANS-8 and TC85/SC5/WG8 NCS Consensus Standards [Slides]

This presentation covers ANS-8 and its status. The presentation starts with an introduction into ongoing projects. Including touching upon on ANS standard development steps and a status report. Finally, the lecture covers ISO WG8 Standards. with a special focus on recent ISO TC85/SC5 Plenary in Tsukuba, Japan and ISO development process + road map and a final status report.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

High Refractive Index Adhesives for Laser Glass Cladding Applications (ABBREVIATED Report)

To eliminate parasitic light oscillations (amplified spontaneous emission (ASE)), high energy laser systems often utilize polymeric materials to adhere optically absorptive cladding materials to laser gain media (glass or crystal). Most of these polymeric optical adhesives are index matched to lower index gain media, and there was no capability to achieve refractive indices (RI) greater than 1.60 with low color, while also maintaining mechanical compliance to serve as adhesives for cladding applications. The completion of LDRD 23-FS-043 shows we can chemically develop novel suitable adhesive candidates with refractive indices above 1.64 at 532 nm while also exhibiting Shore A hardness between 50-90, with high optical clarity, low color, and minimal haze for films ~1-2 mm thick (84 %Transmission at 532 nm). This will enable us to begin mapping a process space to allow future customizable adhesive formulations for building a variety of laser systems with tunable refractive index matching for various gain and cladding media.

36 MATERIALS SCIENCE↗
DOE OSTI2022

In-Line Membrane Thickness Mapping with Real-Time Data Processing

The goal of this project is commercialization of a novel, patented by NREL, non-contact, in-line quality control thickness mapping tool that will enable 100% area inspection of multilayer polymer film assemblies, such as a PEM on a casting substrate, during continuous high-volume R2R manufacturing.

ENGINEERING,HYDROGEN↗
DOE OSTI2021

Dynamic recrystallization of a wrought magnesium alloy: Grain size and texture maps and their application for mechanical behavior predictions

Effect of dynamic recrystallization (DRX) on the grain refinement and texture modification was studied by conducting a series of hot compression on AZ31B Mg alloy. Processing-grain size-texture maps were established as a function of temperature, strain rate, strain, and the Zener-Hollomon parameter (Z). Moreover, influence of simultaneous changes in the grain size and texture on tensile yield strength and ductility of the hot-worked Mg alloy was studied using the grain size and texture maps established. The processing-grain size map showed that the DRX grain size decreased with the increase in Z, also revealing various characteristics ranging from a grain growth, grain refinement, to a bimodal distribution of ultrafine grains and partially recrystallized grains. The effect of twinning on the grain refinement was also evident at high Z conditions. The processing-texture map revealed that the initial fiber texture was altered significantly to a shear, off-normal, or extension-twin texture with the increase in Z. The Schmid-factor maps were calculated to identify a dominant deformation mode during a subsequent tensile deformation of the hot-worked samples. Finally, a corresponding Hall-Petch relationship for each dominant deformation mode was used to establish tensile yield-strength maps, which agree well with the measured data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Using Systems Theoretic Process Analysis and Causal Analysis to Map and Manage Organizational Information to Enable Digitalization and Information Automation

The overarching goal of this Light Water Reactor Sustainability Program–supported research and development project is to provide planning tools and comprehensive guidance to utilities considering or undertaking full nuclear plant modernization. The results of this research will provide the nuclear industry with a comprehensive and usable solution, including guidance, lessons learned, methods, and planning tools. This research is currently working to provide guidance on digitalization and information automation to enable the evolution of data to information, insight, and action—thereby allowing utilities to operate safely and cost-competitively with all other electrical generation sources. Light Water Reactor Sustainability Program researchers have also recently started investigating how human and technology integration principles, information automation, and digitalization enable data evolution. These researchers are currently in the process of validating the use of System-Theoretic Process Analysis to define high-level safety constraints in the United States Nuclear Regulatory Commission’s problem identification and resolution process (i.e., a plant compliance information gathering activity). The next step in this research, which is described in the following sections of this report, is to map out data evolution in a use case to identify inefficiencies in another aspect of plant compliance information gathering and communication activities—event investigations and root cause analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Atomic fluctuations in electronic materials revealed by dephasing

The microscopic origin and timescale of the fluctuations of the energies of electronic states has a significant impact on the properties of interest of electronic materials, with implication in fields ranging from photovoltaic devices to quantum information processing. Spectroscopic investigations of coherent dynamics provide a direct measurement of electronic fluctuations. Modern multidimensional spectroscopy techniques allow the mapping of coherent processes along multiple time or frequency axes and thus allow unprecedented discrimination between different sources of electronic dephasing. Exploiting modern abilities in coherence mapping in both amplitude and phase, we unravel dissipative processes of electronic coherences in the model system of CdSe quantum dots (QDs). The method allows the assignment of the nature of the observed coherence as vibrational or electronic. The expected coherence maps are obtained for the coherent longitudinal optical (LO) phonon, which serves as an internal standard and confirms the sensitivity of the technique. Fast dephasing is observed between the first two exciton states, despite their shared electron state and common environment. This result is contrary to predictions of the standard effective mass model for these materials, in which the exciton levels are strongly correlated through a common size dependence. In contrast, the experiment is in agreement with ab initio molecular dynamics of a single QD. Electronic dephasing in these materials is thus dominated by the realistic electronic structure arising from fluctuations at the atomic level rather than static size distribution. The analysis of electronic dephasing thereby uniquely enables the study of electronic fluctuations in complex materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Shareable FPGA compute engine

Systems, apparatuses, and methods for sharing an field programmable gate array compute engine are disclosed. A system includes one or more processors and one or more FPGAs. The system receives a request, generated by a first user process, to allocate a portion of processing resources on a first FPGA. The system maps the portion of processing resources of the first FPGA into an address space of the first user process. The system prevents other user processes from accessing the portion of processing resources of the first FPGA. Later, the system detects a release of the portion of the processing resources on the first FPGA by the first user process. Then, the system receives a second request to allocate the first FPGA from a second user process. In response to the second request, the system maps the first FPGA into an address space of the second user process.

Kegel, Andrew G.↗
DOE OSTI2022

Chemical Cartography with APOGEE: Mapping Disk Populations with a 2-process Model and Residual Abundances

We apply a novel statistical analysis to measurements of 16 elemental abundances in 34,410 Milky Way disk stars from the final data release (DR17) of APOGEE-2. Building on recent work, we fit median abundance ratio trends [X/Mg] versus [Mg/H] with a 2-process model, which decomposes abundance patterns into a "prompt" component tracing core-collapse supernovae and a "delayed" component tracing Type Ia supernovae. For each sample star, we fit the amplitudes of these two components, then compute the residuals Δ[X/H] from this two-parameter fit. The rms residuals range from ~0.01–0.03 dex for the most precisely measured APOGEE abundances to ~0.1 dex for Na, V, and Ce. The correlations of residuals reveal a complex underlying structure, including a correlated element group comprised of Ca, Na, Al, K, Cr, and Ce and a separate group comprised of Ni, V, Mn, and Co. Selecting stars poorly fit by the 2-process model reveals a rich variety of physical outliers and sometimes subtle measurement errors. Residual abundances allow for the comparison of populations controlled for differences in metallicity and [α/Fe]. Relative to the main disk (R = 3–13 kpc), we find nearly identical abundance patterns in the outer disk (R = 15–17 kpc), 0.05–0.2 dex depressions of multiple elements in LMC and Gaia Sausage/Enceladus stars, and wild deviations (0.4–1 dex) of multiple elements in ω Cen. The residual abundance analysis opens new opportunities for discovering chemically distinctive stars and stellar populations, for empirically constraining nucleosynthetic yields, and for testing chemical evolution models that include stochasticity in the production and redistribution of elements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Hyperpolarized relaxometry based nuclear T 1 noise spectroscopy in diamond

The origins of spin lifetimes in quantum systems is a matter of importance in several areas of quantum information. Spectrally mapping spin relaxation processes provides insight into their origin and motivates methods to mitigate them. In this paper, we map nuclear relaxation in a prototypical system of 13 C nuclei in diamond coupled to Nitrogen Vacancy (NV) centers over a wide field range (1 mT-7 T). Nuclear hyperpolarization through optically pumped NV electrons allows signal measurement savings exceeding million-fold over conventional methods. Through a systematic study with varying substitutional electron (P1 center) and 13 C concentrations, we identify the operational relaxation channels for the nuclei at different fields as well as the dominant role played by 13 C coupling to the interacting P1 electronic spin bath. These results motivate quantum control techniques for dissipation engineering to boost spin lifetimes in diamond, with applications including engineered quantum memories and hyperpolarized 13 C imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Radiation image reconstruction and uncertainty quantification using a Gaussian process prior

We propose a complete framework for Bayesian image reconstruction and uncertainty quantification based on a Gaussian process prior (GPP) to overcome limitations of maximum likelihood expectation maximization (ML-EM) image reconstruction algorithm. The prior distribution is constructed with a zero-mean Gaussian process (GP) with a choice of a covariance function, and a link function is used to map the Gaussian process to an image. Unlike many other maximum a posteriori approaches, our method offers highly interpretable hyperparamters that are selected automatically with the empirical Bayes method. Furthermore, the GP covariance function can be modified to incorporate a priori structural priors, enabling multi-modality imaging or contextual data fusion. Lastly, we illustrate that our approach lends itself to Bayesian uncertainty quantification techniques, such as the preconditioned Crank–Nicolson method and the Laplace approximation. The proposed framework is general and can be employed in most radiation image reconstruction problems, and we demonstrate it with simulated free-moving single detector radiation source imaging scenarios. We compare the reconstruction results from GPP and ML-EM, and show that the proposed method can significantly improve the image quality over ML-EM, all the while providing greater understanding of the source distribution via the uncertainty quantification capability. Furthermore, significant improvement of the image quality by incorporating a structural prior is illustrated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Characterization of Lithium Ion Battery Materials with Valence Electron Energy-Loss Spectroscopy

Abstract Cutting-edge research on materials for lithium ion batteries regularly focuses on nanoscale and atomic-scale phenomena. Electron energy-loss spectroscopy (EELS) is one of the most powerful ways of characterizing composition and aspects of the electronic structure of battery materials, particularly lithium and the transition metal mixed oxides found in the electrodes. However, the characteristic EELS signal from battery materials is challenging to analyze when there is strong overlap of spectral features, poor signal-to-background ratios, or thicker and uneven sample areas. A potential alternative or complementary approach comes from utilizing the valence EELS features (<20 eV loss) of battery materials. For example, the valence EELS features in LiCoO 2 maintain higher jump ratios than the Li–K edge, most notably when spectra are collected with minimal acquisition times or from thick sample regions. EELS maps of these valence features give comparable results to the Li–K edge EELS maps of LiCoO 2 . With some spectral processing, the valence EELS maps more accurately highlight the morphology and distribution of LiCoO 2 than the Li–K edge maps, especially in thicker sample regions. This approach is beneficial for cases where sample thickness or beam sensitivity limit EELS analysis, and could be used to minimize electron dosage and sample damage or contamination.

energy storage (including batteries and capacitors↗
DOE OSTI2023

Three‐Dimensional Broadband Interferometric Mapping and Polarization (BIMAP‐3D) Observations of Lightning Discharge Processes

Abstract Following on our earlier single‐station, 2‐dimensional (2D) broadband interferometric mapping and polarization (BIMAP) observations of lightning discharges, we recently deployed two BIMAP stations at Los Alamos National Laboratory to map the lightning sources and their polarization in full 3‐dimensional (3D) space (BIMAP‐3D). The two stations are separated by 11.5‐km and each station consists of four antenna sets (instead of three for the original BIMAP) that form a Y ‐shaped array for improved interferometric performance. In this paper, we report the BIMAP‐3D system design, a generalized and analytical 2D interferometry technique for noncoplanar antenna array, a two‐stage 3D mapping technique based on geometric triangulation and baseline‐based differential time of arrival, and a technique to reconstruct the polarization orientation in 3D space by combining the 2D polarization results from the two‐station observations. Along with description of the techniques, we demonstrate and discuss the initial lightning results, including 3D maps for a hybrid intracloud and cloud‐to‐ground flash and for a normal intracloud flash, development of abnormal K‐change leaders, and polarization signatures for a K‐change leader. We find that with the two‐stage 3D mapping techniques, the sources can be located to meters accuracy for a favorable event that occurs between the two stations. We also find the polarization vectors for the example K leader are mostly orthogonal to the leader channel after the full 3D polarization analysis. The main purpose of this paper is to report the BIMAP‐3D techniques and capabilities. Detailed analysis of more specific discharge processes will be reported in later studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Scalable Data-Intensive Geocomputation: A Design for Real-Time Continental Flood Inundation Mapping

The convergence of data-intensive and extreme-scale computing enables an integrated software and data ecosystem for scientific discovery. Developments in this realm will fuel transformative research in data-driven interdisciplinary domains. Geocomputation provides computing paradigms in Geographic Information Systems (GIS) for interactive computing of geographic data, processes, models, and maps. Because GIS is data-driven, the computational scalability of a geocomputation workflow is directly related to the scale of the GIS data layers, their resolution and extent, as well as the velocity of the geo-located data streams to be processed. Unique in high user interactivity and low end-to-end latency requirements, geocomputation applications will dramatically benefit from the convergence of high-end data analytics (HDA) and high-performance computing (HPC). The application level challenge, however, is to identify and eliminate computational bottlenecks that arise along a geocomputation workflow. Indeed, poor scalability at any of the workflow components is detrimental to the entire end-to-end pipeline. Here, we study a large geocomputation use case in flood inundation mapping that handles multiple national-scale geospatial datasets and targets low end-to-end latency. We discuss benefits and challenges for harnessing both HDA and HPC for data-intensive geospatial data processing and intensive numerical modeling of geographic processes. We propose an HDA+HPC geocomputation architecture design that couples HDA (e.g., Spark)-based spatial data handling and HPC-based parallel data modeling. Key techniques for coupling HDA and HPC to bridge the two different software stacks are reviewed and discussed.

Liu, Yan↗
DOE OSTI2023

Genome-resolved correlation mapping links microbial community structure to metabolic interactions driving methane production from wastewater

Anaerobic digestion of municipal mixed sludge produces methane that can be converted into renewable natural gas. To improve economics of this microbial mediated process, metabolic interactions catalyzing biomass conversion to energy need to be identified. Here, we present a two-year time series associating microbial metabolism and physicochemistry in a full-scale wastewater treatment plant. By creating a co-occurrence network with thousands of time-resolved microbial populations from over 100 samples spanning four operating configurations, known and novel microbial consortia with potential to drive methane production were identified. Interactions between these populations were further resolved in relation to specific process configurations by mapping metagenome assembled genomes and cognate gene expression data onto the network. Prominent interactions included transcriptionally active Methanolinea methanogens and syntrophic benzoate oxidizing Syntrophorhabdus , as well as a Methanoregulaceae population and putative syntrophic acetate oxidizing bacteria affiliated with Bateroidetes (Tenuifilaceae) expressing the glycine cleavage bypass of the Wood–Ljungdahl pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

FY 18 Status Report on the Computing Systems for the Yucca Mountain Project TSPA-LA Models and Inventory of Software used for Process Models

Sandia National Laboratories (SNL) continued evaluation of total system performance assessment (TSPA) computing systems for the previously considered Yucca Mountain Project (YMP). This was done to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, as directed by the National Nuclear Security Administration (NNSA), DOE 2010. This work is a continuation of the ongoing readiness evaluation reported in Lee and Hadgu (2014), Hadgu et al. (2015) and Hadgu and Appel (2016), and Hadgu et al. (2017). The TSPA computing hardware (2014 server cluster -CL2014) and storage system described in Hadgu et al. (2015) were used for the current analysis. One floating license of Gold Sim with Versions 9.60.300, 10.5, 11.1 and 12.0 was installed on the cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software were tested and installed to support the TSPA-type analysis on the server cluster. The FY18 task included developing an inventory of software used for the Yucca Mountain Project process models and preliminary assessment of status of the software; enhancing security of the cluster and setting a backup system. The 2014 server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Sculpting 2D Crystals via Membrane Contractions before and during Solidification

When phospholipids crystallize within the otherwise fluid membranes of giant unilamellar vesicles, the resulting molecularly thin “2D” solids exhibit great variety in their morphology evolution. For example, within membranes containing moderate amounts of the crystallizing component, crystals grow with a fixed morphology depending on vesicle size. Conversely for membranes containing large amounts of the crystallizing species, we find small compact crystals on vesicles of all sizes. However, on large vesicles, growing crystals sprout flower petals that lengthen progressively. These behaviors result from two combined mechanisms: first, like other 2D solids, the shear rigidity of phospholipid crystals renders them intolerant to morphologies with nonzero Gaussian curvature. As a result and especially at elevated membrane tension, the cost of bending elasticity is reduced at the expense of line energy by the formation of flowers as opposed to compact crystals. Second, the composition-dependent tension rise during cooling relaxes via water permeation of the membrane with a time constant scaling as R2. The amount of crystal formed for a small decrease in temperature determines this composition-dependent increase in stress from thermal contractions versus solidification. Surface Evolver computations were motivated using the predicted tension evolution to develop a processing space that maps to experimental observations for initial and growing crystal morphology. Important variable groups are identified, including a scaled ratio of bending to line energy, a vesicle-size-independent group for membrane contractions, and a time constant for stress relaxation. Though processing stresses ultimately relax, the crystal morphology persists well beyond the processing window.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗