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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Absolute nuclear material assay using count distribution (LAMBDA) space

A method of absolute nuclear material assay of an unknown source comprising counting neutrons from the unknown source and providing an absolute nuclear material assay utilizing a model to optimally compare to the measured count distributions. In one embodiment, the step of providing an absolute nuclear material assay comprises utilizing a random sampling of analytically computed fission chain distributions to generate a continuous time-evolving sequence of event-counts by spreading the fission chain distribution in time.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

PhytoOracle: Scalable, modular phenomics data processing pipelines

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to ( i ) improve data processing efficiency; ( ii ) provide an extensible, reproducible computing framework; and ( iii ) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

A NUMERICAL STUDY OF DIFFUSIVE COSMIC-RAY TRANSPORT WITH ADIABATIC FOCUSING

Focused particle transport in a nonuniform large-scale magnetic field is investigated numerically in the case of isotropic pitch-angle scattering. Evolving particle density profiles and distribution moments are computed from solutions of a system of stochastic differential equations, equivalent to the original Fokker-Planck equation for the particle distribution. Conflicting analytical predictions for the transport coefficients in the diffusion limit, independently calculated by Beeck and Wibberenz and Shalchi, are compared with the numerical results. The reasons for the discrepancies among the analytical and numerical treatments, as well as the general limitations of the diffusion model, are discussed. The telegraph equation, derived in a higher-order expansion of the particle distribution function, is shown to describe the particle transport much more accurately than the diffusion model, especially ahead of a moving density pulse.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-G-IeP4-14: Prostate Brachytherapy Activity Measurement and Source Localization by Using a Dual Photon Emission Computed Tomography System: A Feasibility Study

Purpose: To monitor the activity distribution and needle position during and after implantation in operating rooms. Methods: Simulation studies were conducted to assess the feasibility of measurement activity distribution and seed localization using the DuPECT system. The system consists of a LaBr3-based probe and planar detection heads, a collimation system, and a coincidence circuit. The two heads can be manipulated independently. Simplified Yb-169 brachytherapy seeds were used. A water-filled cylindrical phantom with a 40-mm diameter and 40-mm length was used to model a simplified prostate of the Asian man. Two simplified seeds were placed at a radial distance of 10 mm and tangential distance of 10 mm from the center of the phantom. The probe head was arranged perpendicular to the planar head. Results of various imaging durations were analyzed and the accuracy of the seed localization was assessed by calculating the centroid of the seed. Results: The reconstructed images indicate that the DuPECT can measure the activity distribution and locate the seeds dwelt in different positions intraoperatively. The calculated centroid on average turned out to be accurate within the pixel size of 0.5 mm. The two sources were identified when the duration is longer than 15 s. The sensitivity measured in water was merely 0.07 cps/MBq. Conclusion: Preliminary results show that the measurement of the activity distribution and seed localization are feasible using the DuPECT system intraoperatively. It indicates the DuPECT system has potential to be an approach for dose-distribution-validation. The efficacy of acvtivity distribution measurement and source localization using the DuPECT system will evaluated in more realistic phantom studies (e.g., various attenuation materials and greater number of seeds) in the future investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Neutron Time Interval Distributions with Background Neutrons

A single cosmic ray air shower event can produce multiple neutrons. The arrival times of neutron counts from such an event creates a clustering pattern distinctly different from random sources. A theory for the time interval distribution between neutron counts from both a correlated source and cosmic ray air showers is given and a method is developed to compute the probability distributions for a cosmic ray air shower to create detected neutrons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

CAN A LONG NANOFLARE STORM EXPLAIN THE OBSERVED EMISSION MEASURE DISTRIBUTIONS IN ACTIVE REGION CORES?

All theories that attempt to explain the heating of the high-temperature plasma observed in the solar corona are based on short bursts of energy. The intensities and velocities measured in the cores of quiescent active regions, however, can be steady over many hours of observation. One heating scenario that has been proposed to reconcile such observations with impulsive heating models is the 'long nanoflare storm', where short-duration heating events occur infrequently on many sub-resolution strands; the emission of the strands is then averaged together to explain the observed steady structures. In this Letter, we examine the emission measure distribution predicted for such a long nanoflare storm by modeling an arcade of strands in an active region core. Comparisons of the computed emission measure distributions with recent observations indicate that the long nanoflare storm scenario implies greater than five times more 1 MK emission than is actually observed for all plausible combinations of loop lengths, heating rates, and abundances. We conjecture that if the plasma had 'super coronal' abundances, the model may be able to match the observations at low temperatures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Anomalous small-angle X-ray scattering of nanoporous two-phase atomistic models for amorphous silicon–germanium alloys

The present work deals with a detailed analysis of the anomalous small-angle X-ray scattering in amorphous silicon–germanium alloy using the simulation technique. We envisage the nanoporous two-phase alloy model consisting in a mixture of Ge-rich and Ge-poor domains and voids at the nanoscale. By substituting Ge atoms for Si atoms in nanoporous amorphous silicon network, compositionally heterogeneous alloys are generated with various composition-contrasts between the two phases. After relaxing the as-generated structure, we compute its radial distribution function, and then we deduce by the Fourier transform technique its anomalous X-ray scattering pattern. Using a smoothing procedure, the computed X-ray scattering patterns are corrected for the termination errors due to the finite size of the model, allowing so a rigorous quantitative analysis of the anomalous small-angle scattering. Our simulation shows that, as expected, the anomalous small-angle X-ray scattering technique is a tool of choice for characterizing compositional heterogeneities coexisting with structural inhomogeneities in an amorphous alloy. Furthermore, the sizes of the compositional nanoheterogeneities, as measured by anomalous small-angle X-ray scattering technique, are X-ray energy independent. A quantitative analysis of the separated reduced anomalous small-angle X-ray scattering, as defined in this work, provided a good estimate of their size.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ARQUIN: Architectures for Multinode Superconducting Quantum Computers

Many proposals to scale quantum technology rely on modular or distributed designs wherein individual quantum processors, called nodes, are linked together to form one large multinode quantum computer (MNQC). One scalable method to construct an MNQC is using superconducting quantum systems with optical interconnects. However, internode gates in these systems may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require improvements in entanglement generation, use of entanglement distillation, and optimized software and compilers. Still, it remains unclear what performance is possible with current hardware and what performance algorithms require. In this article, we employ a systems analysis approach to quantify overall MNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. We show how to navigate tradeoffs in entanglement generation and distillation in the context of algorithm performance, lay out how compilers and software should balance between local and internode gates, and discuss when noisy quantum internode links have an advantage over purely classical links. Here, we find that a factor of 10–100× better link performance is required and introduce a research roadmap for the co-design of hardware and software towards the realization of early MNQCs. While we focus on superconducting devices with optical interconnects, our approach is general across MNQC implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles

Heat transfer in directly-irradiated high-temperature solid–gas flows laden with polydisperse particles is investigated using a novel transient three-dimensional computational fluid dynamics model. The model couples particle–gas hydrodynamics of solid–gas flows laden with polydisperse particles, radiative heat transfer in non-grey absorbing, emitting and anisotropically-scattering multi-component participating media, conduction heat transfer in the gas phase, and interfacial convection heat transfer. The multiphase particle-in-cell method is used to predict high-fidelity solid–gas flow characteristics, such as the local discrete particle size distribution, with increased computational efficiency by combining the advantages of both Eulerian and Lagrangian methods. The multi-component radiative transfer model is implemented using an advanced collision-based Monte Carlo ray-tracing method. The number of the prescribed discrete particle components is found to be the key parameter affecting the computational accuracy and efficiency, which primarily depends on the size distribution of the particles. For the model particle–gas flow featuring free-falling Gamma-distributed ceramic particles exposed to concentrated solar irradiation, the particle volume fraction, radiative, fluid flow and thermal characteristics appear to converge with the increasing number of the discrete particle components. Five particle components are sufficient to obtain physically meaningful results. A further increase in the number of the particle components only slightly increases the accuracy of the numerical predictions at the expense of a rapidly increasing computational time. For five particle components, the particle vertical velocity at the receiver exit for particles with the diameter of 43.4 μm is 57% of that for the particles with the diameter of 202.8 μm. The temperatures of these two particle components increase from the initial ambient values by factors of 2 and 1.2, respectively, during the simulation time. In conclusion, the model developed allows for increased fidelity of particle–gas flow simulations with significant radiative effects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Atomistic Investigations of the Effects of Si/Al Ratio and Al Distribution on the Adsorption Selectivity of n -Alkanes in Brønsted-Acid Zeolites

The adsorption of n -alkanes onto Brønsted-acid sites is a key step in the catalytic cracking of alkanes. Employing configurational-bias Monte Carlo simulations, we have investigated how the ratio of equilibrium adsorption constants for central C-C bonds relative to terminal bonds of n -alkanes (i.e., the adsorption selectivity ratio) in Brønsted-acid zeolites is influenced by the Si/Al ratio and the Al distribution. A new computational approach was implemented, and the developed force field was validated by a comprehensive comparison between simulation results and experimental data for a number of Brønsted-acid zeolites. While the adsorption selectivity seems to be relatively insensitive to the Si/Al ratio, our results reveal that the Al distribution plays a crucial role in determining the adsorption selectivity. Changes in the Al distribution result in a change of as much as 2-fold in the adsorption selectivity ratio for n -hexane. The selectivity generally shows larger variations with respect to Al distribution in zeolites with a larger Si/Al ratio. The two factors identified by this work that substantially influence the selectivity ratio are the siting of Al atoms among T-sites and their spatial proximity, and an atomic-level understanding of each of these effects was achieved. The siting of Al atoms at more or less selective T-sites significantly influences the overall selectivity ratio, and Al atoms in close proximity can synergistically enhance the adsorption of central C-C bonds, leading to a higher selectivity ratio relative to isolated Al atoms. Finally, we anticipate that these results will have important implications for future large-scale computational screenings and the development of advanced synthesis approaches to target certain Al distributions in zeolites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

An adjoint method for neoclassical stellarator optimization

Stellarators remain an enticing route to steady-state fusion power. However, to achieve the required confinement, the magnetic geometry must be highly optimized. This optimization requires navigating high-dimensional spaces, often necessitating the use of gradient-based methods. The gradient of the neoclassical fluxes is expensive to compute with classical methods, requiring $O(N)$ flux computations, where $N$ is the number of parameters. To reduce the cost of the gradient computation, we present an adjoint method for computing the derivatives of moments of the neoclassical distribution function for stellarator optimization. The linear adjoint method allows derivatives of quantities which depend on solutions of a linear system, such as moments of the distribution function, to be computed with respect to many parameters from the solution of only two linear systems. This reduces the cost of computing the gradient to the point that the finite-collisionality neoclassical fluxes can be used within an optimization loop. With the neoclassical adjoint method, we compute solutions of the drift kinetic equation and an adjoint drift kinetic equation to obtain derivatives of neoclassical quantities with respect to geometric parameters. When the number of parameters in the derivative is large ( $O(10^{2})$ ), this adjoint method provides up to a factor of 200 reduction in cost. We demonstrate adjoint-based optimization of the field strength to obtain minimal bootstrap current on a surface. With adjoint-based derivatives, we also compute the local sensitivity to magnetic perturbations on a flux surface and identify regions where tight tolerances on error fields are required for control of the bootstrap current or radial transport. Moreover, the solve for the ambipolar electric field is accelerated using a Newton method with derivatives obtained from the adjoint method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Optimal Demand Response Incorporating Distribution LMP with PV Generation Uncertainty

The utilization of aggregated demand-side flexibility via demand response (DR) has become a promising pathway for the integration of renewable energy resources in power systems. Nowadays, there are several management strategies for DR such as the price-based transactive control strategies. However, many of such existing price-based control strategies neglect the physics and operational constraints of the underlying distribution networks when computing the price, raising concerns regarding their theoretical and practical values. This paper studies this issue and investigates optimal DR (ODR) by incorporating the distribution locational marginal price (DLMP). In particular, we discuss DR in connection with DLMPs and propose a multiperiod bilevel optimization problem to find the ODR strategy. Here, the objective is to minimize the peak load, load fluctuation, and payments of load aggregators. In addition, a robust bilevel ODR model is formulated to provide a robust ODR strategy while minimizing operating costs under the worst-case realization of uncertainties; this mitigates the impact of forecasting errors on renewable energy resources. Then, we propose an efficient solution approach by employing the Karush-Kuhn-Tucker conditions and strong duality. Simulation results are presented to illustrate the mutual impacts of the interaction between DR and DLMP and the benefits of the robust ODR strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

QCOR; A Language Extension Specification for the Heterogeneous Quantum-Classical Model of Computation

Quantum computing (QC) is an emerging computational paradigm that leverages the laws of quantum mechanics to perform elementary logic operations. Existing programming models for QC were designed with fault-tolerant hardware in mind, envisioning stand-alone applications. However, the susceptibility of near-term quantum computers to noise limits their stand-alone utility. To better leverage limited computational strengths of noisy quantum devices, hybrid algorithms have been suggested whereby quantum computers are used in tandem with their classical counterparts in a heterogeneous fashion. This modus operandi calls out for a programming model and a high-level programming language that natively and seamlessly supports heterogeneous quantum-classical hardware architectures in a single-source-code paradigm. Motivated by the lack of such a model, we introduce a language extension specification, called QCOR, which enables single-source quantum-classical programming. Programs written using the QCOR library–based language extensions can be compiled to produce functional hybrid binary executables. After defining QCOR’s programming model, memory model, and execution model, we discuss how QCOR enables variational, iterative, and feed-forward QC. Additionally, QCOR approaches quantum-classical computation in a hardware-agnostic heterogeneous fashion and strives to build on best practices of high-performance computing. The high level of abstraction in the language extension is intended to accelerate the adoption of QC by researchers familiar with classical high-performance computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Applying the Risk Management Framework: The Distributed Energy Resource Risk Manager

As part of a multiyear effort, the National Renewable Energy Laboratory (NREL) has dedicated resources to understand and identify cybersecurity weaknesses in distributed energy resources (DERs) by performing assessments. Due to a lack of standardization and rapidly increasing adoption of DERs, there is a critical need to address cybersecurity needs for DER systems in an interactive way. Furthermore, federal agencies, which are required to obtain an authority to operate, are challenged by the complexities of including their DERs. To help meet this need, in early 2020, NREL released the Distributed Energy Resources Cybersecurity Framework (DERCF) and accompanying Web application. This process is supported by the Risk Management Framework (RMF) developed by the National Institute of Standards and Technology. This project, referred to as the DERCF RMF application, expands on the existing DERCF work to include methods that support walking a user through the seven RMF steps. The tool will be available for download at no cost from [link ]. The purpose of this paper is to describe the steps the DERCF team at NREL took to understand Steps 1-5 of the RMF process. Additionally, this document will identify future work on the first five steps as well as a plan for Steps 6 and 7.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

GridAPPS-D™

Distribution utilities need better tools to get the full benefit of the abundance of data within their systems. GridAPPS-D™ is a free, open-source, data integration and application development platform. It enables development of portable, advanced applications by standardizing the data exchange interfaces between devices in the field, distributed apps in the systems, and applications in the control room. Contact: Ron Melton, ron.melton@pnnl.gov. For developers: https://github.com/GRIDAPPSD.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Lattice QCD calculation of the pion generalized parton distribution

We present the results of a Lattice QCD computation of pion generalized parton distribution (GPD), employing perturbative matching up to next-to-next-to-leading order (NNLO). The computations are based on an ensemble of Nf=2+1 highly improved staggered quarks (HISQ) with a pion mass of 300 MeV and a lattice spacing of 0.04 fm. Centered on the zero-skewness limit, we utilize a recently proposed Lorentz-invariant definition of GPD, which is derived from Lorentz-invariant amplitudes. We analyze and compare these amplitudes in both Breit and non-Breit kinematic frames at comparable momentum transfers, validating their frame-independent nature. To obtain light-cone GPD, we integrate hybrid scheme renormalization with the large momentum effective theory (LaMET). Moreover, we determine the first three iso-vector generalized form factors (GFFs) of the pion using the ratio scheme renormalization and leading-twist factorization, achieving NNLO accuracy.

Ding, Heng-Tong↗
DOE OSTI2022

Large-scale frictionless jamming with power-law particle size distributions

Due to significant computational expense, discrete element method simulations of jammed packings of size-dispersed spheres with size ratios greater than 1:10 have remained elusive, limiting the correspondence between simulations and real-world granular materials with large size dispersity. Here, invoking a recently developed neighbor binning algorithm, we generate mechanically stable jammed packings of frictionless spheres with power-law size distributions containing up to nearly 4 000 000 particles with size ratios up to 1:100. By systematically varying the width and exponent of the underlying power laws, we analyze the role of particle size distributions on the structure of jammed packings. The densest packings are obtained for size distributions that balance the relative abundance of large-large and small-small particle contacts. Although the proportion of rattler particles and mean coordination number strongly depend on the size distribution, the mean coordination of nonrattler particles attains the frictionless isostatic value of six in all cases. The size distribution of nonrattler particles that participate in the load-bearing network exhibits no dependence on the width of the total particle size distribution beyond a critical particle size for low-magnitude exponent power laws. This signifies that only particles with sizes greater than the critical particle size contribute to the mechanical stability. However, for high-magnitude exponent power laws, all particle sizes participate in the mechanical stability of the packing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗