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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Implosion dynamics of triple-nozzle gas-puff z pinches on COBRA

Experiments on the 1-MA, 220-ns COBRA generator at Cornell University were conducted to provide detailed measurements of structured cylindrical gas-puff z pinches. In the experiments, a 7 cm diameter triple-nozzle gas valve assembly with concentric outer and inner annular nozzles and a central gas jet initialize the z-pinch load with various working gases, radial density profiles, and externally applied axial magnetic fields. Planar laser-induced fluorescence provides a measure of the initial neutral gas density of the load, while three-frame laser shearing interferometry and multi-frame extreme ultraviolet (XUV) cameras reveal the formation and propagation of a magneto-Rayleigh–Taylor (MRT) unstable shock layer. Implosion trajectories are compared to simple, experimentally informed models and found to be in good agreement. Differences in the structure of the accelerating plasma sheath and evolution of the MRT instability are observed for different gas species and axial magnetic field strengths, correlating with differences in pinch uniformity and x-ray emission. Here, the average instability growth is compared to linear MRT theory predictions using the instantaneous acceleration of the best-fit implosion models and characteristic instability wavelength, with the effective Atwood number and seed perturbation size as fit parameters. For high density argon center jets, ionization prior to the arrival of the imploding plasma sheath suggests a heating mechanism consistent with photoionization by XUV self-emission.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Physics-based compact modeling of electro-thermal memristors: Negative differential resistance, local activity, and non-local dynamical bifurcations

Leon Chua's Local Activity theory quantitatively relates the compact model of an isolated nonlinear circuit element, such as a memristor, to its potential for desired dynamical behaviors when externally coupled to passive elements in a circuit. However, the theory's use has often been limited to potentially unphysical toy models and analyses of small-signal linear circuits containing pseudo-elements (resistors, capacitors, and inductors), which provide little insight into required physical, material, and device properties. Furthermore, the Local Activity concept relies on a local analysis and must be complemented by examining dynamical behavior far away from the steady-states of a circuit. In this work, we review and study a class of generic and extended one-dimensional electro-thermal memristors (i.e., temperature is the sole state variable), re-framing the analysis in terms of physically motivated definitions and visualizations to derive intuitive compact models and simulate their dynamical behavior in terms of experimentally measurable properties, such as electrical and thermal conductance and capacitance and their derivatives with respect to voltage and temperature. Within this unified framework, we connect steady-state phenomena, such as negative differential resistance, and dynamical behaviors, such as instability, oscillations, and bifurcations, through a set of dimensionless nonlinearity parameters. In particular, we reveal that the reactance associated with electro-thermal memristors is the result of a phase shift between oscillating current and voltage induced by the dynamical delay and coupling between the electrical and thermal variables. We thus, demonstrate both the utility and limitations of local analyses to understand non-local dynamical behavior. Critically for future experimentation, the analyses show that external coupling of a memristor to impedances within modern sourcing and measurement instruments can dominate the response of the total circuit, making it impossible to characterize the response of an uncoupled circuit element for which a compact model is desired. However, these effects can be minimized by proper understanding of the Local Activity theory to design and utilize purpose-built instruments.

Brown, Timothy D. (ORCID:0000000347068355)↗
DOE OSTI2024

Physical discovery in representation learning via conditioning on prior knowledge

Recent advances in electron, scanning probe, optical, and chemical imaging and spectroscopy yield bespoke data sets containing the information of structure and functionality of complex systems. In many cases, the resulting data sets are underpinned by low-dimensional simple representations encoding the factors of variability within the data. The representation learning methods seek to discover these factors of variability, ideally further connecting them with relevant physical mechanisms. However, generally, the task of identifying the latent variables corresponding to actual physical mechanisms is extremely complex. Here, we present an empirical study of an approach based on conditioning the data on the known (continuous) physical parameters and systematically compare it with the previously introduced approach based on the invariant variational autoencoders. The conditional variational autoencoder (cVAE) approach does not rely on the existence of the invariant transforms and hence allows for much greater flexibility and applicability. Interestingly, cVAE allows for limited extrapolation outside of the original domain of the conditional variable. However, this extrapolation is limited compared to the cases when true physical mechanisms are known, and the physical factor of variability can be disentangled in full. We further show that introducing the known conditioning results in the simplification of the latent distribution if the conditioning vector is correlated with the factor of variability in the data, thus allowing us to separate relevant physical factors. We initially demonstrate this approach using 1D and 2D examples on a synthetic data set and then extend it to the analysis of experimental data on ferroelectric domain dynamics visualized via piezoresponse force microscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Improved Method for Evaluating and Specifying the Chromaticity of Light Sources

This article recommends a method for calculating and specifying light source chromaticity using the CIE 2015 10° color matching functions (CMFs), which, according to analysis of existing psychophysical experiment data, can reduce visual mismatch compared to specifications based on the traditional CIE 1931 2° CMFs. Specifically, this work evaluates, documents, and recommends for adoption a supporting system of measures to be used with the CIE 2015 10° CMFs: a new uniform chromaticity scale (UCS) diagram with coordinates (s, t), a measure of correlated color temperature (CCTst), and a measure of distance from the Planckian locus (Dst). It also presents options for updating nominal classification quadrangles. A complete method of this nature has not yet been standardized, which may be contributing to the slow uptake of the CIE 2015 CMFs. The proposed tools are analogous to u, v, CCT, Duv, and the ANSI C78.377 nominal classification quadrangles that are currently specified in the CIE 1960 UCS using the CIE 1931 2° CMFs. While conceptually equivalent, the differences between the current standard method and the new st system are important for reducing unintended mismatch in the chromaticity of light. Furthermore, the implications of changing chromaticity specification methods are identified by a comparison over a diverse set of real light source SPDs. Finally, as a step toward improving the design and specification of light sources for illumination purposes, we propose a process for implementing the recommendations.

42 ENGINEERING↗
DOE OSTI2022

Web application for machining parameter recommendation using visual analytics

The computer codes create a web application including multiple user interfaces, visualizations, interaction modules between the user, and visualizations. The visualizations will be interactive, allowing users to query the data directly, and they will be arranged in a dashboard. When selections are made in one visualization, filters will be applied to all other visualizations providing a coordinated system for asking questions about the data. The visualization can be utilized for manufacturing data management, analysis, and recommendation.

Chae, Junghoon↗
DOE OSTI2023

PRESSURE-FILM OPEN SOURCE SCANNING AND MAPPING

SF-22-099 Pressure-film Open Source Scanning and Mapping (POSSM) is software that analyses images of pressure-film (scans or photographs). POSSM collects data from that analysis in order to produce a number of visual aides, including pressure maps, histograms, and 3d surface plots. POSSM is designed to be able to analyze an entire folder full of images, exporting numeric data as .csv files and visual graphics as .png files.

Grider, Patrick↗
DOE OSTI2022

CALORIE: A Constraint Language and Optimizing Runtime for Exascale Power Management (Final Report)

This final technical report summarizes the key accomplishments on the CALORIE project, a DOE Early Career award received by PI Henry Hoffmann at the University of Chicago. CALORIE’s main goal was to create principled methodologies, tools, and practices to help scientists and high-performance computing (HPC) operators maximize the performance and insights obtained from scientific computing applications in the face of exascale power constraints. The project accomplished these goals by completing the following objectives: • Designing a language for describing application goals (including constraints and objectives) and system capabilities. The application goals will include things like which simulations or simulations plus in situ analysis will be run together, what the power constraints are, and what requirements there are for in situ analysis (for example, a desired frame rate for visualization). The system capabilities include all components that can be adjusted to tradeoff power and performance. • Designing a runtime system that takes specified goals and capabilities and dynamically determines what capabilities to use to meet the goals. This runtime adapts to changes in goals, application behavior, or available capabilities to automatically maintain the goals despite unexpected disturbances. • Developing a foundational understanding of how power constraints affect the problem of scheduling applications in large-scale systems. This report provides an overview of the accomplishments related to each of these key objectives.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Integrated Research Infrastructure Architecture Blueprint Activity (Final Report 2023)

The complexity of scientific pursuits is increasing rapidly with aspects that require dynamic integration of experiment, observation, theory, modeling, simulation, visualization, machine learning (ML), artificial intelligence (AI), and analysis. Research projects across the Department of Energy (DOE) are increasingly data and compute intensive. Innovative research teams are accelerating the pace of discovery by using high-performance computational and data tools in their research workflows and leveraging multiple research infrastructures. Additionally, several recent high-level U.S. government reports underscore the necessity of a new advanced computing ecosystem for international competitiveness and national security. International competitors are moving forward with major research infrastructure integration efforts that seek to capture a competitive advantage in the global innovation race. Owing to its unparalleled constellation of world-class experimental and observational facilities and high-performance and extreme-scale computational, data, and networking infrastructure, DOE is positioned to be a global leader in this new era of integrated science. However, this new integration paradigm will demand continuing evolution to ensure the U.S. remains a global leader in research and innovation. The DOE Office of Science (SC) has seized on the strategic importance of integration and has adopted a vision for Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation. To respond to the evolving computational requirements of research and the competitive international innovation landscape, experimental facilities could be connected with high performance computing resources for near real-time analysis, and resources should be provided for merging enormous and diverse data for AI/ML techniques and analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

An Online Prototype Toolset for Predicting and Optimizing P&T Performance (FY23 Status Report)

A new web-based toolset is being developed to support ongoing remediation optimization efforts and implementation of an adaptive site management strategy for the 200 West Area Pump-and-Treat (P&T) system at the Hanford Site. This toolset, comprising the well performance index tool and the well optimization pre-screening tool, will offer a user-friendly interface to predict and optimize the P&T well network’s performance at a preliminary level. Efforts in fiscal year (FY) 2023 focused on three main components: updating the existing deep learning model for predicting P&T performance, designing and developing a prototype of a web-based performance index tool, and initiating the conceptual design of the well optimization pre-screening tool. The well performance index tool is based on a pre-trained deep learning model that allows users to select a target contaminant and well screen length, then visualize the predicted performance of potential new wells across the site. The well optimization pre-screening tool includes two separate modules: the pre-computed scenario viewer, which organizes and visualizes offline optimization simulation results, and the quick analysis module, which provides real-time model prediction using user-specified well locations. In FY24, the plan is to add web-based applications to SOCRATES for both the well performance prediction tool and the optimization prescreening tool, with accompanying user and theory guides. These tools are intended to enable an accessible, easily applied, and transparent approach to remedy planning and decision-making.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

OptiBench: An Optimization Benchmark Tool for Renewable Energy Problems

We propose a benchmark framework and visualization tool, OptiBench, for analyzing the performance of state-of-the-art optimization solvers across a variety of optimization problems in renewable energy research. Our framework is designed from the ground up in the Julia programming language and enables analysis at scale on high performance computing (HPC) systems. Our visualization tool allows effortless evaluation of optimization solver performance, robustness, and accuracy through intuitive plots, e.g., performance profiles, heat maps, and distribution plots. We have tested three benchmark suites relevant to the modeling of renewable energy systems, viz., CUTEst, PGLib-OPF, and WaterTAP water treatment optimization problems. We illustrate benchmarking of CUTEst using OptiBench on the National Laboratory of the Rockies's (NLR) HPC Kestrel. Our findings indicate that MA57 HSL linear solver demonstrated the best overall performance for an experimental IPOPT implementation. Our work is ongoing and we intend to add support for more optimization solvers and benchmark test suites in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Aerosol Model Benchmarking Repository: A toolkit for model intercomparison

The Aerosol Model Benchmarking Repository and Standards (AMBRS) project was initiated to provide tools and to establish community standards for benchmarking aerosol models. This report describes a set of open-source tools for building, running, and analyzing aerosol box model simulations in a standardized framework. The framework consists of three core components: AMBuilder, a CMake-based build system that compiles supported models consistently; AMBRS, a Python module that defines unified numerical experiments and executes them with aligned inputs; and PyParticle, an aerosol analysis package that standardizes output, computes diagnostics, and visualizes simulation results. Together, these tools enable reproducible intercomparison of aerosol schemes and support process-level evaluation of how model simplifications affect predictions of size distributions, cloud condensation nuclei activity, and other relevant properties relevant for the Earth-Energy system. Beyond its role in benchmarking, AMBRS provides a platform for studying aerosol processes across scales and can be used to generate training data for AI/ML applications in support of a broader hierarchical aerosol modeling strategy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Warning Signs of Potential Black Swan Outbreaks in Infectious Disease

Black swan events in infectious disease describe rare but devastatingly large outbreaks. While experts are skeptical that such events are predictable, it might be possible to identify the warning signs of a black swan event. Specifically, following the initiation of an outbreak, key differentiating features could serve as alerts. Such features could be derived from meta-analyses of large outbreaks for multiple infectious diseases. We hypothesized there may be common features among the pathogen, environment, and host epidemiological triad that characterize an infectious disease black swan event. Using Los Alamos National Laboratory’s tool, Analytics for Investigation of Disease Outbreaks, we investigated historical disease outbreak information and anomalous events for several infectious diseases. By studying 32 different infectious diseases and global outbreaks, we observed that in the past 20–30 years, there have been potential black swan events in the majority of infectious diseases analyzed. Importantly, these potential black swan events cannot be attributed to the first introduction of the disease to a susceptible host population. This paper describes our observations and perspectives and illustrates the value of broad analysis of data across the infectious disease realm, providing insights that may not be possible when we focus on singular infectious agents or diseases. Data analytics could be developed to warn health authorities at the beginning of an outbreak of an impending black swan event. Such tools could complement traditional epidemiological modeling to help forecast future large outbreaks and facilitate timely warning and effective, targeted resource allocation for mitigation efforts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Deep Dive Topic: Analysis

This section focuses on analysis of I/O behavior and the feedback resulting from that analysis. We define analysis of I/O behavior as interpreting and deriving meaning from I/O instrumentation data. We define feedback as the product of the analysis process. Feedback can be thought of as the link between analysis and the subsequent response to that analysis, such as I/O tuning or policy decisions (see Section 4.4).Analysis and feedback may be consumed by either human stakeholders or machine algorithms. If it is to be consumed by human stakeholders, then the analysis process will likely emphasize understandable language and visualization techniques. If it is to be consumed by machine algorithms, then it will likely emphasize the use of machine-parsable, consistent formats that are suitable for ingestion by policy engines and data-mining tools.

Snyder, Shane↗
DOE OSTI2021

Internal curing of cement pastes by means of superabsorbent polymers visualized by neutron tomography

Highlights: • The kinetics of water release from SAPs were studied by neutron tomography. • The time window for internal curing was linked to the water release from SAPs. • The water release links to the SAP effectiveness to mitigate autogenous shrinkage. • One SAP type was effective while another prematurely released its stored water. Superabsorbent polymers (SAPs) are used to counteract self-desiccation in order to mitigate autogenous shrinkage, a problem in cementitious systems with a low water-to-cement ratio. The release kinetics during internal curing are of importance as not all SAP types are able to efficiently mitigate autogenous shrinkage. In this study, neutron tomography is used to study and visualize the water release kinetics over time. Per-voxel analysis of the time-attenuation curve was performed using piecewise-constant functions. Two different SAP types were studied, one being able to mitigate autogenous shrinkage and one quickly releasing its stored water after final setting. The tomography results correspond to autogenous shrinkage measurements and nuclear magnetic resonance tests. The visualization provides information on the time of water release by the SAPs after setting and the time window of internal curing. This opens additional insights towards the application of SAPs in the construction sector and provides information on the mechanism of internal curing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Compilation of a Solar Mirror Materials Database and an Analysis of Natural and Accelerated Mirror Exposure and Degradation

The National Renewable Energy Laboratory (NREL) has been conducting exposure experiments on solar reflectors for over four decades. Thousands of mirror samples from over one hundred suppliers have been exposed to and monitored in a range of relevant environments. These test conditions include outdoor test settings and several controlled laboratory environments. These samples have been rigorously individually characterized using a series of reflectance measurements, visual inspections, and in some cases, in-depth composition analysis to identify degradation modes, reflectance losses, and other mirror properties integral to understanding the solar reflector's life cycle. Here, this paper compiles the decades of measurement data into a concise statistical analysis. It includes exposure and degradation data for numerous reflector types, including secondary-surface reflector permutations of polymer and glass superstrates with silver and aluminum reflectors as well as front-surface reflectors. The results herein are intended to analyze environmental stressors and degradation trends among various historical and state-of-the-art solar reflectors. It may be used to support solar reflector design, effective testing methodology, and inform manufacturing decisions moving forward. Presented are the results of the compiled database and an initial analysis for degradation rate modeling using full-spectrum and wavelength-dependent approaches. The database is a growing resource hosted on a live, publicly accessible website. In conjunction with the analysis presented here, it provides a valuable resource to the solar reflector manufacturing and testing industry.

14 SOLAR ENERGY↗
DOE OSTI2021

The Marine and Hydrokinetic ToolKit (MHKiT) for Data Quality Control and Analysis [Slides]

The ability to collect, ingest, condition, reduce, quality control, process, visualize, and store data in a standardized way is critical at all stages of Marine Energy (ME) research and technology/project development. MHKiT is an open-source, standardized suite of ME data processing functions that provides the ability to ingest, condition, reduce, quality control, process, visualize and store ME data. MHKiT is developed in both Python and Matlab.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Examination of Intergranular Crack on SC0234

The microstructure of the SC0234 weld was evaluated per DA-SPEC-01067, ''General Purpose Heat Source (GPHS) Plutonium-238 Dioxide Fueled Clad Product Specification'' and it was determined that the weld microstructure conformed to the quality requirements. During the examination of weld cross section, the metallographic analysis revealed the presence of a surface crack. Prior visual examination per RPS-TA55-303 had not revealed the crack, nor did the surface photography performed per RPS-TA55-302. The presence of the crack does not violate any of the product specifications called out on DA-SPEC-01067. Although there is a well-documented history of weld hot crack susceptibility in the early development of the DOP-26 iridium alloy, a surface crack such as this had not been documented during welding at Los Alamos. In the interest of better understanding the cause; the product engineer/program recommended further examination of the crack. This report discusses the examination of the crack found in the weld cross section of simulant clad SC0234. Metallography, Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy techniques (EDS) where used in the analysis of the crack and the surrounding weld microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗