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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enabling Modular Autonomous Feedback‐Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration

Abstract Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high‐throughput characterization, automatic analysis, and machine learning. Within a MAP, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or to generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein, the authors present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. They demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which the authors demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experimental orchestration, which to the best of the authors’ knowledge, is demonstrated for the first time herein.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Runtime power allocation approach for GAMESS hybrid CPU‐GPU implementation

Summary To improve power consumption of applications at the runtime, modern processors provide frequency scaling capabilities, which along with workload optimization, are also available on GPU accelerators. In this work, a runtime strategy is proposed to distribute a given power allocation among the host components and the GPU according to the current application performance and power usage, such that GPU execution is prioritized over CPU for power allocation to maximize application performance. Next, the strategy is tailored to an application, a quantum‐chemistry package GAMESS for ab initio electronic structure calculations. Specifically, GAMESS hybrid CPU–GPU implementation as provided in the Libcchem library is considered. Experiments, performed on a 28‐core node with a Kepler GPU, resulted in performance gains of up to 50% under the proposed strategy and the largest power allocation considered here as compared with the scenario when this allocation was equally distributed among the computing‐platform components.

Sundriyal, Vaibhav↗
DOE OSTI2022

A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.

Bernholdt, David↗
DOE OSTI2012

Universality of the Volume Bound in Slow-Roll Eternal Inflation

It has recently been shown that in single field slow-roll inflation the total volume cannot grow by a factor larger than e{sup S{sub dS}/2} without becoming infinite. The bound is saturated exactly at the phase transition to eternal inflation where the probability to produce infinite volume becomes non zero. We show that the bound holds sharply also in any space-time dimensions, when arbitrary higher-dimensional operators are included and in the multi-field inflationary case. The relation with the entropy of de Sitter and the universality of the bound strengthen the case for a deeper holographic interpretation. As a spin-off we provide the formalism to compute the probability distribution of the volume after inflation for generic multi-field models, which might help to address questions about the population of vacua of the landscape during slow-roll inflation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Universal hydrodynamic flow in holographic planar shock collisions

We study the collision of planar shock waves in AdS 5 as a function of shock profile. In the dual field theory the shock waves describe planar sheets of energy whose collision results in the formation of a plasma which behaves hydrodynamically at late times. We find that the post-collision stress tensor near the light cone exhibits transient non-universal behavior which depends on both the shock width and the precise functional form of the shock profile. However, over a large range of shock widths, including those which yield qualitative different behavior near the future light cone, and for different shock profiles, we find universal behavior in the subsequent hydrodynamic evolution. In addition, we compute the rapidity distribution of produced particles and find it to be well described by a Gaussian.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Convergence of sum-up rounding schemes for cloaking problems governed by the Helmholtz equation

In this work, we consider the problem of designing a cloak for waves described by the Helmholtz equation from an integer programming point of view. The problem can be modeled as a PDE-constrained optimization problem with integer-valued control inputs that are distributed in the computational domain. A first-discretize-then-optimize approach results in a large-scale mixed-integer nonlinear program that is in general intractable because of the large number of integer variables that arise from the discretization of the domain. Instead, we propose an efficient algorithm that is able to approximate the local infima of the underlying nonconvex infinite-dimensional problem arbitrarily close without the need to solve the discretized finite-dimensional integer programs to optimality. We optimize only the continuous relaxations of the approximations for local minima and then apply the sum-up rounding methodology to obtain integer-valued controls. If the solutions of the discretized continuous relaxations converge to a local minimizer of the continuous relaxation, then the resulting discrete-valued control sequence converges weakly \(^*\) in \(L^\infty\) to the same local minimizer. These approximation properties follow under suitable refinements of the involved discretization grids. Our results use familiar concepts arising from the analytical properties of the underlying PDE and complement previous results, derived from a topology optimization point of view.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Zonal-Based Emission Source Term Model for Predicting Particulate Emission Factors in Wildfire Simulations

A physics/chemistry-based numerical model for predicting the emission of fine particles from wildfires is proposed. This model implements the fundamental mechanisms of soot formation in a combustion environment: soot nucleation, surface growth, agglomeration, oxidation, and particle fragmentation. These mechanisms occur on a scale too fine for the discretization of most wildfire models, which need to simulate landscape-scale dynamics. As a result this model implements a zonal approach, where the computed soot particle distribution is partitioned into process zones within a single resolved grid cell. These process zones include: an inception zone (for nucleation), a heating zone (for coagulation, surface growth, and fragmentation), a reaction zone (for oxidation), and a quenched zone (for atmospheric processes). Governing mechanisms are applied to the appropriate zones to predict total particle growth and emission. Additionally, the proposed model is implemented into HIGRAD/FIRETEC, a physics-based wildfire simulation code which couples interactions between fire, fuels, atmosphere, and topography on a landscape scale. Fire simulations among grasslands and conifer forests are performed and compared against experimental data for emission factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

High-Energy X-ray Tomographic Analysis of Precursor Metal Powders (Ti-6Al-4V) Used for Additive Manufacturing

We utilized high-energy x-ray tomography to characterize Ti-6Al-4V metal powders (both as-received and recycled) used in powder-bed additive manufacturing process. The image processing workflow was developed to process and analyze large amount of data objectively by computer program. The distribution of size and shape of the metal particles as well as defect (mainly porosity) inside the particles was analyzed with the statistical representation and resolution in micrometer. The result revealed that circular-shaped porosity with various sizes could be embedded in the powder particles. These porosities could potentially be transferred to the 3D printed part and critically affect the mechanical performance of the component. The present study shows the effectiveness of characterizing metal powders using x-ray imaging techniques where sufficient number of particles can be sampled within tens of minutes with a minimum sample preparation and high accuracy. Clear structural differences in the as-received and recycled powders were delineated that helps in determining the feasibility of using the recycled powders.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Patient-Specific Quality Assurance for the Delivery of {sup 60}Co Intensity Modulated Radiation Therapy Subject to a 0.35-T Lateral Magnetic Field

Purpose: This work describes a patient-specific dosimetry quality assurance (QA) program for intensity modulated radiation therapy (IMRT) using ViewRay, the first commercial magnetic resonance imaging-guided RT device. Methods and Materials: The program consisted of: (1) a 1-dimensional multipoint ionization chamber measurement using a customized 15-cm{sup 3} cube-shaped phantom; (2) 2-dimensional (2D) radiographic film measurement using a 30- × 30- × 20-cm{sup 3} phantom with multiple inserted ionization chambers; (3) quasi-3D diode array (ArcCHECK) measurement with a centrally inserted ionization chamber; (4) 2D fluence verification using machine delivery log files; and (5) 3D Monte Carlo (MC) dose reconstruction with machine delivery files and phantom CT. Results: Ionization chamber measurements agreed well with treatment planning system (TPS)-computed doses in all phantom geometries where the mean ± SD difference was 0.0% ± 1.3% (n=102; range, −3.0%-2.9%). Film measurements also showed excellent agreement with the TPS-computed 2D dose distributions where the mean passing rate using 3% relative/3 mm gamma criteria was 94.6% ± 3.4% (n=30; range, 87.4%-100%). For ArcCHECK measurements, the mean ± SD passing rate using 3% relative/3 mm gamma criteria was 98.9% ± 1.1% (n=34; range, 95.8%-100%). 2D fluence maps with a resolution of 1 × 1 mm{sup 2} showed 100% passing rates for all plan deliveries (n=34). The MC reconstructed doses to the phantom agreed well with planned 3D doses where the mean passing rate using 3% absolute/3 mm gamma criteria was 99.0% ± 1.0% (n=18; range, 97.0%-100%), demonstrating the feasibility of evaluating the QA results in the patient geometry. Conclusions: We developed a dosimetry program for ViewRay's patient-specific IMRT QA. The methodology will be useful for other ViewRay users. The QA results presented here can assist the RT community to establish appropriate tolerance and action limits for ViewRay's IMRT QA.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Multi-GPU porting of a phase-change cascaded lattice Boltzmann method for three-dimensional pool boiling simulations

The Lattice Boltzmann method (LBM) has proven effective in simulating phase-change phenomena, such as melting, solidification, evaporation, and boiling. In this work, we develop a highly parallelized multi-GPU implementation of LBM for three-dimensional pool boiling simulations. The code is based on the OpenACC programming model, which enables the code to be deployed efficiently on multi-core CPUs, GPUs, and potentially other accelerators, without the need for architecture-specific rewrites. To support large-scale simulations, the domain is decomposed and distributed across multiple compute nodes using MPI. We demonstrate that the code exhibits excellent scaling properties, with ideal strong-scaling running with up to 256 GPUs on the MareNostrum5 cluster.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Rapid Atomic Ordering Transformation toward Intermetallic Nanoparticles

Chemically ordered intermetallic nanoparticles are promising candidates for energy-related applications such as electrocatalysis. However, the synthesis of intermetallics generally requires long annealing (several hours) to achieve the ordered structure, which causes nanoparticles agglomeration and diminished performance, particularly for catalysis. Herein, we demonstrate a new rapid Joule heating approach that can synthesize highly ordered and well-dispersed intermetallic nanoparticles. As a proof-of-concept, we synthesized fully ordered Pd 3 Pb intermetallic nanoparticles that feature small size distribution (~6 nm). Computational analysis of the L1 2 Pd 3 Pb material suggests that this rapid atomic ordering transformation can be attributed to a vacancy-mediated diffusion mechanism. Moreover, the nanoparticles demonstrate excellent electrocatalytic activity and exceptional stability for the oxygen reduction reaction (ORR), retaining >95% of the current density over 10 h of chronoamperometry test with negligible structural and compositional changes. Furthermore, this study demonstrates a new strategy of providing a new direction for intermetallic synthesis and catalyst discovery.

25 ENERGY STORAGE↗
DOE OSTI2012

Molecular Dynamic Simulations of the Effect on the Hydration of Nafion in the Presence of a Platinum Nanoparticle

Platinum catalysts play a critical role in fuel cell technology. Current optimization efforts focus on reducing the amount of Pt in the system and optimizing the utilization of that which remains. The effect of the presence of Pt nanoparticles on the local structure and morphology of the polymer electrolyte membrane, water, and hydronium ions has been studied at molecular level in this work. Classical molecular dynamics simulation has been used to examine a system containing a 4 nm fcc cubic ({100} face) platinum nanoparticle at the center surrounded by Nafion polymer, water molecules, and hydronium ions at λ = 3, 6, 9, 15, and 22. The changes in density and orientation distribution of sulfonic acid groups in the side-chains, water, and hydronium as a function of distance from platinum surface are analyzed in this study. Sulfonic acid groups and hydronium ions show a very high increase in density near the platinum surface, and they approach the bulk value as they move away from the platinum surface. At lower water contents (λ = 3 and 6), water is strongly attracted to platinum surface, increasing the density near the platinum surface. However, at the highest humidity level studied, the density of water farthest from the platinum surface (>20 Å) is higher than the bulk value and the density of water nearest to the platinum surface. The above observed phenomenon is explained using the probability distribution of orientation computed at various distances from platinum surface. As the water content increases, sulfonic acid groups show a preferential orientation for the side-chains to align themselves horizontally on the platinum than vertically, thereby covering a larger area of platinum and pushing the water away from the platinum surface. This causes the water density to drop near the platinum surface. Water molecules and hydronium ions show preference to certain orientations near the platinum surface, but usually to none as they move away from the platinum surface.

Chemistry↗
DOE OSTI2021

Thermal Experiments for Fractured Rock Characterization: Theoretical Analysis and Inverse Modeling

Abstract Field‐scale properties of fractured rocks play a crucial role in many subsurface applications, yet methodologies for identification of the statistical parameters of a discrete fracture network (DFN) are scarce. We present an inversion technique to infer two such parameters, fracture density and fractal dimension, from cross‐borehole thermal experiments data. It is based on a particle‐based heat‐transfer model, whose evaluation is accelerated with a deep neural network (DNN) surrogate that is integrated into a grid search. The DNN is trained on a small number of the heat‐transfer model runs and predicts the cumulative density function of the thermal field. The latter is used to compute fine posterior distributions of the (to be estimated) parameters. Our synthetic experiments reveal that fracture density is well constrained by data, while fractal dimension is harder to determine. Adding nonuniform prior information related to the DFN connectivity improves the inference of this parameter.

Zhou, Zitong↗
DOE OSTI2014

Statistics of reversible transitions in two-state trajectories in force-ramp spectroscopy

A possible way to extract information about the reversible dissociation of a molecular adhesion bond from force fluctuations observed in force ramp experiments is discussed. For small loading rates the system undergoes a limited number of unbinding and rebinding transitions observable in the so-called force versus extension (FE) curves. The statistics of these transient fluctuations can be utilized to estimate the parameters for the rebinding rate. This is relevant in the experimentally important situation where the direct observation of the reversed FE-curves is hampered, e.g., due to the presence of soft linkers. I generalize the stochastic theory of the kinetics in two-state models to the case of time-dependent kinetic rates and compute the relevant distributions of characteristic forces. While for irreversible systems there is an intrinsic relation between the rupture force distribution and the population of the free-energy well of the bound state, the situation is slightly more complex if reversible systems are considered. For a two-state model, a “stationary” rupture force distribution that is proportional to the population can be defined and allows to consistently discuss quantities averaged over the transient fluctuations. While irreversible systems are best analyzed in the soft spring limit of small pulling device stiffness and large loading rates, here I argue to use the stiffness of the pulling device as a control parameter in addition to the loading rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Propagation of Dirac electrons in Cantor graphene multilayers

In this work we use the standard T-matrix method to study the tunneling of Dirac electrons through graphene multilayers. A graphene sheet is deposited on top of slabs of Silicon-Oxide (SiO{sub 2}) and Silicon-Carbide (SiC) substrates, in which we applied the Cantor’s series. We calculate the transmittance as a function of energy for different incident angles and different generations of the Cantor’s series. Comparing the transmittance, we found three types of self-similarity: (a) local - into generations, (b) between incident angles and (c) between generations. We also compute the angular distribution of the transmittance for fixed energies finding a self-similar pattern between generations. To our knowledge is the first time that four different self-similar patterns are presented in Cantor-based multilayers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Chaotic neural dynamics facilitate probabilistic computations through sampling

Cortical neurons exhibit highly variable responses over trials and time. Theoretical works posit that this variability arises potentially from chaotic network dynamics of recurrently connected neurons. Here, we demonstrate that chaotic neural dynamics, formed through synaptic learning, allow networks to perform sensory cue integration in a sampling-based implementation. We show that the emergent chaotic dynamics provide neural substrates for generating samples not only of a static variable but also of a dynamical trajectory, where generic recurrent networks acquire these abilities with a biologically plausible learning rule through trial and error. Furthermore, the networks generalize their experience in the stimulus-evoked samples to the inference without partial or all sensory information, which suggests a computational role of spontaneous activity as a representation of the priors as well as a tractable biological computation for marginal distributions. These findings suggest that chaotic neural dynamics may serve for the brain function as a Bayesian generative model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

High-Fidelity Multiphysics Modeling of a Heat Pipe Microreactor Using BlueCrab

Researchers who are actively developing nuclear microreactors are planning to employ innovative designs and features using traditional commercial modeling tools that may be inadequate for their design and licensing activities. The codes developed under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program provide flexibility in terms of geometry modeling and multiphysics coupling and are particularly well suited for modeling novel microreactor concepts. To test the maturity of these codes, this paper introduces a conceptual heat pipe microreactor (HP-MR) designed to gather various technologies of interest to microreactor developers such as control drums, heat pipes, and hydride moderators. Here, the objective of this effort is to demonstrate NEAMS tools capability to perform high-fidelity multiphysics simulations, using coupled neutronics (via the Griffin code), heat conduction (via the BISON code), heat pipe modeling (via the Sockeye code), and hydrogen redistribution in hydride metal moderator (via the SWIFT code). Codes are coupled in-memory through the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which permits flexible multiphysics data transfer schemes. The analysis confirmed two key aspects of the HP-MR concept: (1) its ability to follow the power load requested from the heat pipe and (2) its ability to avoid heat pipe cascading failure unless designed with high power close to operating failure limits of its heat pipes. The developed computational model was distributed publicly on the Virtual Test Bed for training purposes to accelerate adoption by industry and to provide a high-fidelity multiphysics solution for benchmarking against other tools. Additional multiphysics analyses including other transients and coupled physics were identified as necessary future work, together with a focus on validating multiphysics behavior against experiments.

Microreactor↗
DOE OSTI2011

TURBULENT CLUSTERING OF PROTOPLANETARY DUST AND PLANETESIMAL FORMATION

We study the clustering of inertial particles in turbulent flows and discuss its applications to dust particles in protoplanetary disks. Using numerical simulations, we compute the radial distribution function (RDF), which measures the probability of finding particle pairs at given distances, and the probability density function of the particle concentration. The clustering statistics depend on the Stokes number, St, defined as the ratio of the particle friction timescale, {tau}{sub p}, to the Kolmogorov timescale in the flow. In agreement with previous studies, we find that, in the dissipation range, the clustering intensity strongly peaks at St {approx_equal} 1, and the RDF for St {approx} 1 shows a fast power-law increase toward small scales, suggesting that turbulent clustering may considerably enhance the particle collision rate. Clustering at inertial-range scales is of particular interest to the problem of planetesimal formation. At these large scales, the strongest clustering is from particles with {tau}{sub p} in the inertial range. Clustering of these particles occurs primarily around a scale where the eddy turnover time is {approx}{tau}{sub p}. We find that particles of different sizes tend to cluster at different locations, leading to flat RDFs between different particles at small scales. In the presence of multiple particle sizes, the overall clustering strength decreases as the particle size distribution broadens. We discuss particle clustering in two recent models for planetesimal formation. We argue that, in the model based on turbulent clustering of chondrule-size particles, the probability of finding strong clusters that can seed planetesimals may have been significantly overestimated. We discuss various clustering mechanisms in simulations of planetesimal formation by gravitational collapse of dense clumps of meter-size particles, in particular the contribution from turbulent clustering due to the limited numerical resolution.

79 ASTRONOMY AND ASTROPHYSICS↗