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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Correlation between macro- and nano-scopic measurements of carbon nanostructured paper elastic modulus

Extensive work has been done in order to determine the bulk elastic modulus of isotropic samples from force curves acquired with atomic force microscopy. However, new challenges are encountered given the development of new materials constructed of one-dimensional anisotropic building blocks, such as carbon nanostructured paper. In the present work, we establish a reliable framework to correlate the elastic modulus values obtained by amplitude modulation atomic force microscope force curves, a nanoscopic technique, with that determined by traditional macroscopic tensile testing. In order to do so, several techniques involving image processing, statistical analysis, and simulations are used to find the appropriate path to understand how macroscopic properties arise from anisotropic nanoscale components, and ultimately, being able to calculate the value of bulk elastic modulus.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Contribution of the backstreaming ions to the self-magnetic pinch (SMP) diode current

The results presented here were obtained with a self-magnetic pinch (SMP) diode mounted at the front high voltage end of the RITS accelerator. RITS is a Self-Magnetically Insulated Transmission Line (MITL) voltage adder that adds the voltage pulse of six 1.3 MV inductively insulated cavities. The RITS driver together with the SMP diode has produced x-ray spots of the order of 1 mm in diameter and doses adequate for the radiographic imaging of high area density objects. Although, through the years, a number of different types of radiographic electron diodes have been utilized with SABER, HERMES III and RITS accelerators, the SMP diode appears to be the most successful and simplest diode for the radiographic investigation of various objects. Our experiments had two objectives: first to measure the contribution of the back-streaming ion currents emitted from the anode target and second to try to evaluate the energy of those ions and hence the Anode-Cathode (A-K) gap actual voltage. In any very high voltage inductive voltage adder utilizing MITLs to transmit the power to the diode load, the precise knowledge of the accelerating voltage applied on the A-K gap is problematic. This is even more difficult in an SMP diode where the A-K gap is very small (~1 cm) and the diode region very hostile. The accelerating voltage quoted in the literature is from estimates based on the measurements of the anode and cathode currents of the MITL far upstream from the diode and utilizing the para-potential flow theories and inductive corrections. Thus, it would be interesting to have another independent measurement to evaluate the A-K voltage. The diode's anode is made of a number of high-Z metals in order to produce copious and energetic flash x-rays. It was established experimentally that the back-streaming ion currents are a strong function of the anode materials and their stage of cleanness. We have measured the back-streaming ion currents emitted from the anode and propagating through a hollow cathode tip for various diode configurations and different techniques of target cleaning treatment: namely, heating at very high temperatures with DC and pulsed current, with RF plasma cleaning, and with both plasma cleaning and heating. In conclusion, we have also evaluated the A-K gap voltage by energy filtering technique. Experimental results in comparison with LSP simulations are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Capillary evaporation of the ionic liquid [EMIM][BF 4 ] in nanoscale solvophobic confinement

We report that solvent density fluctuations play a crucial role in liquid-vapor transitions in solvophobic confinement and can also be important for understanding solvation of polar and apolar solutes. In the case of ionic liquids (ILs), density fluctuations can be used to understand important processes in the context of nanoscale aggregation and colloidal self-assemblies. In this article, we explore the nature of density fluctuations associated with capillary evaporation of the IL 1-ethyl-3-methylimidazolium tetrafluoroborate ([EMIM][BF4]) in the confined region of model solvophobic nanoscale sheets by using molecular dynamics simulations combined with non-Boltzmann sampling techniques. We demonstrate that density fluctuations of the confined IL play an important role in capillary evaporation, suggesting analogies to dewetting transitions involving water. Lastly, significant changes in the interfacial structure of the IL are also detailed and suggested to underlie a non-classical (non-parabolic) dependence of the free energy barrier to evaporation on the degree of confinement.

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

Modeling laser-driven ion acceleration with deep learning

Developments in machine learning promise to ameliorate some of the challenges of modeling complex physical systems through neural-network-based surrogate models. High-intensity, short-pulse lasers can be used to accelerate ions to mega-electronvolt energies, but to model such interactions requires computationally expensive techniques such as particle-in-cell simulations. Multilayer neural networks allow one to take a relatively sparse ensemble of simulations and generate a surrogate model that can be used to rapidly search the parameter space of interest. In this study, we created an ensemble of over 1,000 simulations modeling laser-driven ion acceleration and developed a surrogate to study the resulting parameter space. A neural-network-based approach allows for rapid feature discovery not possible for traditional parameter scans given the computational cost. A notable observation made during this study was the dependence of ion energy on the pre-plasma gradient length scale. While this methodology harbors great promise for ion acceleration, it has ready application to all topics in which large-scale parameter scans are restricted by significant computational cost or relatively large, but sparse, domains.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Editorial for the Collection "Preparatory Work for the American Wake Experiment (AWAKEN)"

The American WAKE experimeNt (AWAKEN) is a large field campaign focused on gathering observations for improved understanding of atmospheric and wind power plant flow physics, one of the outstanding needs for the wind energy community as described in the Science paper by Veers et al.1 "Grand challenges in wind energy." AWAKEN was planned over several years with an international consortium of numerous stakeholders, including national laboratories, academic researchers, wind turbine manufacturers, and wind farm operators. A highlight of the AWAKEN campaign is the extensive use of remote sensing instrumentation to characterize the atmosphere and its interactions with wind power plants, enabled by recent developments in lidar, radar, and thermodynamic profiling technology. Advanced modeling techniques like mesoscale and large-eddy simulations (LES) also played an important role in the preparation of the experiment and the interpretation of the experimental data collected. This special-topic issue for the Journal of Renewable and Sustainable Energy presents a collection of 12 papers that describe the preparatory work and some initial analyses from the AWAKEN campaign. An overview of the contents of the various papers in this special issue is provided in Sec. II.

17 WIND ENERGY↗
DOE OSTI2021

Foreword: Selected papers from the 2020 Nuclear and Emerging Technologies for Space Topical Meeting (NETS 2020)

Humanity’s curiosity of and intrigue for exploring space has been with our species since we first looked up into the night sky. This age-old curiosity has driven humankind to innovate technologies for millennia, including efforts ranging from the construction of Stonehenge to track the annual movements of the sun to the investigation of advanced propulsion systems capable of transporting people to distant planets. Today’s technical communities dedicated to researching and developing innovative technologies for space exploration have seen a recent reinvigoration. Over the past few years, impressive progress made by industry, with exceptional support from government agencies, to reestablish and develop new capabilities has renewed confidence in humanity’s ability to reach the stars—a confidence that has not been present since the days of the Apollo program. Moreover, history shows that innovation and collaboration within the scientific and engineering communities reaches unparalleled pinnacles during periods of astrophilia. Finally, given the advancements in computational capacities for advanced modeling and simulation, unprecedented breakthroughs in commercializing advanced manufacturing techniques, and powerful collaborative relationships between industry and national scientific organizations, today we are limited only by our own imaginations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Visualization of R410A Flow Boiling Inside Horizontal Smooth Tubes under Diabatic Conditions

This article presents a novel approach to visualize the flow boiling in round tubes under “diabatic conditions”. In the visualization test section, a 3D printed round tube is placed inside a glass tube with secondary fluid at a higher temperature flowing in the annulus between the two tubes thus providing diabatic conditions. Experimental work was conducted for evaporating R410A flow in a horizontal smooth round tube with the inner diameter of 6.3 mm. Compared to the traditional adiabatic visualization technique, the more realistic evaporative condition is simulated and the developing evaporation process is captured. New insights for the flow behavior at low vapor quality are brought by this diabatic method. The vapor plug occurs at very low vapor quality, and this is attributed to the coalescence of bubbles generated on the heated tube wall. For the intermittent flow, liquid slug triggered by Kelvin–Helmholtz instability affects the nucleation on the tube wall. It brings the fresh liquid to rewet the dry surface and activate the nucleation sites. Finally, heat flux condition affects the heat transfer mechanisms during the flow boiling, and the heat transfer through the nucleate boiling mechanism increases as the heat flux increases.

3D printed↗
DOE OSTI2022

Bibliometric review and recent advances in total scattering pair distribution function analysis: 21 years in retrospect

Global research activities have been driven by the quest to develop and characterize novel materials for technological advancements. The total scattering pair distribution function (TSPDF) is a powerful and versatile characterization technique for examining the structural details of diverse complex materials including liquid, amorphous, disordered crystalline, and nanostructured materials. Thus, it is critical to keep track of research progress, identify research gaps, and future research directions of the application of the TSPDF technique in materials development and discovery. In this work, a bibliometric analysis of literature regarding the TSPDF technique between 2000 and 2021 was conducted using datasets retrieved from the Web of Science database. The research trends based on publication outputs, research subject distribution, co-authorships among institutions, countries/regions, co-citation of referenced sources, and keyword co-occurrence are evaluated and discussed herein. The impact of the TSPDF technique is projected to increase due to its importance in probing emerging functional materials, and the advances in specialized facilities and instrumentation among the scientific communities engaged with it. Finally, current and emerging research hotspots related to TSPDF technique such as catalysis, computer modeling and simulation, pharmaceutics, machine learning, hydrogen storage, battery materials, and layered structured materials are also identified and discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Efficient flexible characterization of quantum processors with nested error models

We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its wildcard error (a metric of the amount of unmodeled error) at each step. Each best-fit model, along with a quantification of its unmodeled error, constitutes a characterization of the processor. We explain how quantum processor models can be compared with experimental data and to each other. We demonstrate the technique by using it to characterize a simulated noisy two-qubit processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A mesoscopic digital twin that bridges length and time scales for control of additively manufactured metal microstructures

We present our recent development of an integrated mesoscale digital twin (DT) framework for relating processing conditions, microstructures, and mechanical responses of additively manufactured (AM) metals. In particular, focusing on the laser powder bed fusion technique, we describe how individual modeling and simulation capabilities are coupled to investigate and control AM microstructural features at multiple length and time scales. We review our prior case studies that demonstrate the integrated modeling schemes, in which high-fidelity melt pool dynamics simulations provide accurate local thermal profiles and histories to subsequent AM microstructure simulations. We also report our new mechanical response modeling results for predicted AM microstructures. In addition, we illustrate how our DT framework has been validated through modeling–experiment integration, as well as how it has been practically utilized to guide and analyze AM experiments. Finally, we share our perspectives on future directions of further development of the DT framework for more efficient, accurate predictions and wider ranges of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning a general model of single phase flow in complex 3D porous media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Effect of centrality bin width corrections on two-particle number and transverse momentum differential correlation functions

Two-particle number and transverse momentum differential correlation functions are powerful tools for unveiling the detailed dynamics and particle production mechanisms involved in relativistic heavy-ion collisions. Measurements of transverse momentum correlators P 2 and G 2 , in particular, provide added information not readily accessible with better known number correlation functions R 2 . However, it is found that the R 2 and G 2 correlators are somewhat sensitive to the details of the experimental procedure used to measure them. They exhibit, in particular, a dependence on the collision centrality bin width, which may have a rather detrimental impact on their physical interpretation. A technique to correct these correlators for collision centrality bin-width averaging is presented. The technique is based on the hypothesis that the shape of single- and pair-probability densities vary slower with collision centrality than the corresponding integrated yields. In conclusion, the technique is tested with Pb-Pb simulations based on the HIJING and ultrarelativistic quantum molecular dynamics models and shown to enable a precision better than 1% for particles in the kinematic range 0.2 ≤ p T ≤ 2.0 GeV/c.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Neural simulation-based inference approach for characterizing the Galactic Center γ-ray excess

The nature of the Fermi γ-ray Galactic Center Excess (GCE) has remained a persistent mystery for over a decade. Although the excess is broadly compatible with emission expected due to dark matter annihilation, an explanation in terms of a population of unresolved astrophysical point sources e.g., millisecond pulsars, remains viable. The effort to uncover the origin of the GCE is hampered in particular by an incomplete understanding of diffuse emission of Galactic origin. This can lead to spurious features that make it difficult to robustly differentiate smooth emission, as expected for a dark matter origin, from more “clumpy” emission expected from a population of relatively bright, unresolved point sources. Here, we use recent advancements in the field of simulation-based inference, in particular density estimation techniques using normalizing flows, in order to characterize the contribution of modeled components, including unresolved point source populations, to the GCE. Compared to traditional techniques based on the statistical distribution of photon counts, our machine learning-based method is able to utilize more of the information contained in a given model of the Galactic Center emission, and in particular can perform posterior parameter estimation while accounting for pixel-to-pixel spatial correlations in the γ-ray map. This makes the method demonstrably more resilient to certain forms of model misspecification. On application to Fermi data, the method generically attributes a smaller fraction of the GCE flux to unresolved point sources when compared to traditional approaches. We nevertheless infer such a contribution to make up a non-negligible fraction of the GCE across all analysis variations considered, with at least $38^{+9}_{-19}$% of the excess attributed to unresolved point sources in our baseline analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Component Particle Structure in Heterogeneous Disordered Ensembles Extracted from High-Throughput Fluctuation X-Ray Scattering

The ring angular correlation function is a characteristic feature determined by the particle structure. Averaging over a large number of ring angular correlation functions calculated from x-ray diffraction patterns will cancel out the cross correlations between different particles and converge to the autocorrelation functions of single particles. Applied on heterogeneous disordered ensembles, the retrieved function is a linear combination of a single-particle autocorrelation function multiplied by the molar ratios in a heterogeneous system. Using this relation, the ring angular correlation functions of the individual component particles in the heterogeneous system can be retrieved through the high throughput fluctuation x-ray scattering technique. This method is demonstrated with a simulated heterogeneous system composed of nanorods, nanoprism, and nanorice.

Fluctuation X-ray Scattering, high throughput, Het↗
DOE OSTI2015

A Novel Phase-Shift Control of Semibridgeless Active Rectifier for Wireless Power Transfer

We investigated a novel phase-shift control of a semibridgeless active rectifier (S-BAR) in order to utilize the S-BAR in wireless energy transfer applications. The standard receiver-side rectifier topology is developed by replacing rectifier lower diodes with synchronous switches controlled by a phase-shifted PWM signal. Moreover, theoretical and simulation results showthat with the proposed control technique, the output quantities can be regulated without communication between the receiver and transmitter. In order to confirm the performance of the proposed converter and control, experimental results are provided using 8-, 15-, and 23-cm air gap coreless transformer which has dimension of 76 cm x 76 cm, with 120-V input and the output power range of 0 to 1kW with a maximum efficiency of 94.4%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Differentially Private Distributed Sensing

The growth of the Internet of Things (IoT) creates the possibility of decentralized systems of sensing and actuation, potentially on a global scale. IoT devices connected to cloud networks can offer Sensing and Actuation as a Service (SAaaS) enabling networks of sensors to grow to a global scale. But extremely large sensor networks can violate privacy, especially in the case where IoT devices are mobile and connected directly to the behaviors of people. The thesis of this paper is that by adapting differential privacy (adding statistically appropriate noise to query results) to groups of geographically distributed sensors privacy could be maintained without ever sending all values up to a central curator and without compromising the overall accuracy of the data collected. This paper outlines such a scheme and performs an analysis of differential privacy techniques adapted to edge computing in a simulated sensor network where ground truth is known. The positive and negative outcomes of employing differential privacy in distributed networks of devices are discussed and a brief research agenda is presented.

Differential Privacy↗
DOE OSTI2025

Multiple Changepoint Detection for Non‐Gaussian Time Series

ABSTRACT This article combines methods from existing techniques to identify multiple changepoints in non‐Gaussian autocorrelated time series. A transformation is used to convert a Gaussian series into a non‐Gaussian series, enabling penalized likelihood methods to handle non‐Gaussian scenarios. When the marginal distribution of the data is continuous, the methods essentially reduce to the change of variables formula for probability densities. When the marginal distribution is count‐oriented, Hermite expansions and particle filtering techniques are used to quantify the scenario. Simulations demonstrating the efficacy of the methods are given and two data sets are analyzed: 1) the proportion of home runs hit by Major League Baseball batters from 1920 to 2023 and 2) a six‐dimensional series of tropical cyclone counts from the Earth's basins of generation from 1980 to 2023. In the first series, beta marginal distributions are used to describe the proportions; in the second, Poisson marginal distributions seem appropriate.

Lund, Robert [Department of Statistics University ↗
DOE OSTI2020

Structural Analysis Approach for the Defense Programs Package 3 (DPP-3)

The Pacific Northwest National Laboratory (PNNL) is the design authority for a new Type B hazardous materials transportation package designated as the Defense Programs Package 3 (DPP-3) for the U.S. Department of Energy (DOE) National Nuclear Security Administration (NNSA). The DPP-3 has been developed using similar materials and fabrication methods employed in previous U.S. Nuclear Regulatory Commission (NRC), DOE, and NNSA certified packages. The DPP-3 design criteria are derived from the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC), NNSA guidance and NRC regulatory guides in order to safely and securely transport a variety of payloads. Final regulatory approval by the NNSA will require physical testing to demonstrate that the containment vessel (CV) remains leaktight after enduring the entire regulatory testing sequence prescribed in Title 10 of the Code of Federal Regulations Part 71 (10 CFR 71). In order to gain confidence that the DPP-3 will remain leaktight after testing, the DPP-3 has been structurally analyzed using the Finite Element Analysis (FEA) software LS-DYNA. The FEA analyses serve two general purposes: first, they aid in design and development of the package, and second, they advise as to which drop orientations are expected to cause the most damage during regulatory testing. This paper will discuss how the design criteria are incorporated into analytical techniques needed to evaluate the FEA structural simulation results for 10 CFR 71 conditions to give confidence the DPP-3 testing campaign will be successful.

Sakalaukus Jr., Peter J.↗