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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extraction of the neutron F 2 structure function from inclusive proton and deuteron deep-inelastic scattering data

The available world deep-inelastic scattering (DIS) data on proton and deuteron structure functions F 2 p , F 2 d , and their ratios are leveraged to extract the free neutron F 2 n structure function, the F 2 n / F 2 p ratio, and associated uncertainties using the latest nuclear effect calculations in the deuteron. Special attention is devoted to the normalization of the proton and deuteron experimental datasets and to the treatment of correlated systematic errors, as well as the quantification of procedural and theoretical uncertainties. The extracted F 2 n dataset is utilized to evaluate the Q 2 dependence of the Gottfried sum rule and the nonsinglet F 2 p − F 2 n moments. To facilitate replication of our study, as well as for general applications, we provide a comprehensive DIS database including all recent Jefferson Lab 6 GeV measurements, the extracted F n 2 , a modified CTEQ-JLab global parton distribution function fit named CJ15nlo_mod, and grids with calculated proton, neutron, and deuteron DIS structure functions. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Architecture of a Residential Solid State Power Substation (SSPS) Node

High integration rates of new loads and distributed generation at the edge of the grid are posing new challenges. However, existing smart power electronic systems are not designed to coordinate and maximize grid support or provide multiple grid services simultaneously. This work presents the application of a solid-state power substation (SSPS) to residential systems to increase this coordination and reduce future challenges. The proposed residential SSPS is validated in simulation including power electronic converter models, feeder models, and optimization.

Krishna Moorthy, Radha↗
DOE OSTI2020

Networked Microgrid Operations: Supporting a Resilient Electric Power Infrastructure

Modern electric power systems operate using large generating units managed with a centralized control structure. The current systems are the result of over a hundred years of technological development and consolidation to leverage economies of scale. While the existing systems have proven cost effective and reliable, modern systems are experiencing a wide range of operational challenges that are causing a reexamination of the centralized control structure. Despite the nearly universal adoption of centralized control, electric power systems are fractal in their operational requirements. Specifically, the fundamental operational requirements are the same, regardless of the system size. While past technologies have not allowed for exploitation of this fractal behavior, emerging technologies are making it possible; these technologies include grid-forming inverters, modern telecommunications systems, and distributed control architectures. Here we show emerging technologies that allow the fractal operational requirements of electric power systems to be exploited as networked microgrids to increase the resiliency of the world’s critical electrical infrastructure.

Schneider, Kevin P.↗
DOE OSTI2021

Review of Intrusion Detection Methods and Tools for Distributed Energy Resources

Recent trends in the growth of distributed energy resources (DER) in the electric grid and newfound malware frameworks that target internet of things (IoT) devices is driving an urgent need for more reliable and effective methods for intrusion detection and prevention. Cybersecurity intrusion detection systems (IDSs) are responsible for detecting threats by monitoring and analyzing network data, which can originate either from networking equipment or end-devices. Creating intrusion detection systems for PV/DER networks is a challenging undertaking because of the diversity of the attack types and intermittency and variability in the data. Distinguishing malicious events from other sources of anomalies or system faults is particularly difficult. New approaches are needed that not only sense anomalies in the power system but also determine causational factors for the detected events. In this report, a range of IDS approaches were summarized along with their pros and cons. Using the review of IDS approaches and subsequent gap analysis for application to DER systems, a preliminary hybrid IDS approach to protect PV/DER communications is formed in the conclusion of this report to inform ongoing and future research regarding the cybersecurity and resilience enhancement of DER systems.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Blockchain for Fault-Tolerant Grid Operations Version 2.0

This report explores the potential of distributed ledger technology (DLT) as a transformative tool to enhance fault-tolerant operations in electrical distribution systems. Leveraging DLT's core attributes, including an immutable decentralized ledger, distributed consensus mechanisms, and state replication capabilities, this study focuses on three critical use cases. A central aspect of this research centers on the utilization of a consensus-driven ledger, providing actors within the system, such as distributed resources, with access to a reliable data repository. This empowers these actors to collaborate effectively and make informed decisions, all securely recorded on the blockchain. The first use case concentrates on data configuration, utilizing mathematical criteria---particularly, the chi-squared test for gross error detection---to identify trustworthy sensors for advanced decision-making. Building upon this foundation of trust, the second use case, topology identification, accurately determines circuit breaker states, unveiling the distribution network's topology. Ultimately, the third use case leverages this trust to execute switching actions, reconfiguring feeders and restoring power to disconnected customers after fault events. The concept of trust serves as a cornerstone in this approach, marking a departure from traditional fault location, isolation, and service restoration (FLISR) methods. Additionally, the blockchain-based architecture introduces decentralization, empowering disconnected areas to make autonomous decisions, even when communication with a central control center is disrupted. The primary contributions of this report are twofold: (1) a novel approach for evaluating distribution system voltage areas while preserving data ownership and (2) the implementation of interactions between distribution network areas using the actor model. Unlike the previous sequential approach for evaluating the area connection voltages, which required a radial network topology, this study's area model reduction enables a more versatile approach. The area model reduction addresses issues of prolonged data waiting times and multiple points of failure within the previous approach. Notably, the presented evaluation for the reduced network model area connection reveals a significant increase in the differences in voltage magnitudes. Simulation and evaluation of area agents across four distinct cases elucidate the area-level interaction behavior during a fault event. Simulations demonstrate that the proposed distributed FLISR (DFLISR) approach can successfully restore service to an affected area. Varying message delays and message loss probabilities in each simulation case underscore their impacts on restoration times, ranging from 3 min and 32 s to 6 min and 19 s. In contrast, power is not restored in an area in one of our simulation cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

WHISPER: Wireless Home Identification and Sensing Platform for Energy Reduction

Many regions of the world benefit from heating, ventilating, and air-conditioning (HVAC) systems to provide productive, comfortable, and healthy indoor environments, which are enabled by automatic building controls. Due to climate change, population growth, and industrialization, HVAC use is globally on the rise. Unfortunately, these systems often operate in a continuous fashion without regard to actual human presence, leading to unnecessary energy consumption. As a result, the heating, ventilation, and cooling of unoccupied building spaces makes a substantial contribution to the harmful environmental impacts associated with carbon-based electric power generation, which is important to remedy. For our modern electric power system, transitioning to low-carbon renewable energy is facilitated by integration with distributed energy resources. Automatic engagement between the grid and consumers will be necessary to enable a clean yet stable electric grid, when integrating these variable and uncertain renewable energy sources. We present the WHISPER (Wireless Home Identification and Sensing Platform for Energy Reduction) system to address the energy and power demand triggered by human presence in homes. The presented system includes a maintenance-free and privacy-preserving human occupancy detection system wherein a local wireless network of battery-free environmental, acoustic energy, and image sensors are deployed to monitor homes, record empirical data for a range of monitored modalities, and transmit it to a base station. Several machine learning algorithms are implemented at the base station to infer human presence based on the received data, harnessing a hierarchical sensor fusion algorithm. Results from the prototype system demonstrate an accuracy in human presence detection in excess of 95%; ongoing commercialization efforts suggest approximately 99% accuracy. Using machine learning, WHISPER enables various applications based on its binary occupancy prediction, allowing situation-specific controls targeted at both personalized smart home and electric grid modernization opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Downscaling atmospheric chemistry simulations with physically consistent deep learning

Abstract. Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrates the downscaling capabilities of modern CNN-based single image super resolution and video super-resolution schemes and develops modifications to these schemes to ensure they are appropriate for use with physical science data. The CNN-based video super-resolution schemes in particular incur only 39 % to 54 % of the grid-cell-level error of interpolation schemes and generate outputs with extremely realistic small-scale variability based on multiple perceptual quality metrics while performing a large (8×10) increase in resolution in the spatial dimensions. Methods are introduced to strictly enforce physical conservation laws within CNNs, perform large and asymmetric resolution changes between common model grid resolutions, account for non-uniform grid-cell areas, super-resolve lognormally distributed datasets, and leverage additional inputs such as high-resolution climatologies and model state variables. High-resolution chemistry simulations are critical for modeling regional air quality and for understanding future climate, and CNN-based downscaling has the potential to generate these high-resolution simulations and ensembles at a fraction of the computational cost.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Subgrid resolution of flow and force fields.

By means of spline fitting, both while converting a Lagrangian distribution of field sources onto an Eulerian grid, and while interpolating the field from its Eulerian grid to the Lagrangian positions of the responding elements, one achieves effective resolution down to about one-eight of a grid mesh unit. One also avoids discontinuities and noise due to cell boundary crossings.

Buneman, O.↗
NASA NTRS1980

Finite difference grid generation by multivariate blending function interpolation

The General Interpolants Method (GIM) code which solves the multidimensional Navier-Stokes equations for arbitrary geometric domains is described. The geometry module in the GIM code generates two and three dimensional grids over specified flow regimes, establishes boundary condition information and computes finite difference analogs for use in the GIM code numerical solution module. The technique can be classified as an algebraic equation approach. The geometry package uses multivariate blending function interpolation of vector-values functions which define the shapes of the edges and surfaces bounding the flow domain. By employing blending functions which conform to the cardinality conditions the flow domain may be mapped onto a unit square (2-D) or unit cube (3-D), thus producing an intrinsic coordinate system for the region of interest. The intrinsic coordinate system facilitates grid spacing control to allow for optimum distribution of nodes in the flow domain.

Anderson, P. G.↗
NASA NTRS1989

The 3-D Euler and Navier-Stokes calculations for aircraft components

An explicit multistage Runge-Kutta type of time-stepping scheme is used for solving transonic flow past a transport type wing/fuselage configuration. Solutions for both Euler and Navier-Stokes equations are obtained for quantitative assessment of boundary layer interaction effects. The viscous solutions are obtained on both a medium resolution grid of approximately 270,000 points and a find grid of 460,000 points to assess the effects of grid density on the solution. Computed pressure distributions are compared with the experimental data.

Vatsa, Veer N.↗
NASA NTRS1991

Transient multidimensional analysis of nonconventional heat pipes with uniform and nonuniform heat distributions

A numerical analysis of transient heat pipe performance including nonconventional heat pipes with nonuniform heat distributions is presented. A body-fitted grid system was applied to a three-dimensional wall and wick model, which was coupled with a transient compressible quasi-one-dimensional vapor flow model. The numerical results were first compared with experimental data from cylindrical heat pipes with good agreement. Numerical calculations were then made for a leading edge heat pipe with localized high heat fluxes. Performance characteristics different from conventional heat pipes are illustrated and some operating limits concerning heat pipe design are discussed.

Cao, Y.↗
NASA NTRS1994

Forced free-shear layer measurements

Detailed three-dimensional three-component phase averaged measurements of the spanwise and streamwise vorticity formation and evolution in acoustically forced plane free-shear flows have been obtained. For the first time, phase-averaged measurements of all three velocity components have been obtained in both a mixing layer and a wake on three-dimensional grids, yielding the spanwise and streamwise vorticity distributions without invoking Taylor's hypothesis. Initially, two-frequency forcing was used to phase-lock the roll-up and first pairing of the spanwise vortical structures in a plane mixing layer. The objective of this study was to measure the near-field vortical structure morphology in a mixing layer with 'natural' laminar initial boundary layers. For the second experiment the second and third subharmonics of the fundamental roll-up frequency were added to the previous two-frequency forcing in order to phase-lock the roll-up and first three pairings of the spanwise rollers in the mixing layer. The objective of this study was to determine the details of spanwise scale changes observed in previous time-averaged measurements and flow visualization of unforced mixing layers. For the final experiment, single-frequency forcing was used to phase-lock the Karman vortex street in a plane wake developing from nominally two-dimensional laminar initial boundary layers. The objective of this study was to compare measurements of the three-dimensional structure in a wake developing from 'natural' initial boundary layers to existing models of wake vortical structure.

Leboeuf, Richard L.↗
NASA NTRS1997

Wing Weight Optimization Under Aeroelastic Loads Subject to Stress Constraints

A minimum weight optimization of the wing under aeroelastic loads subject to stress constraints is carried out. The loads for the optimization are based on aeroelastic trim. The design variables are the thickness of the wing skins and planform variables. The composite plate structural model incorporates first-order shear deformation theory, the wing deflections are expressed using Chebyshev polynomials and a Rayleigh-Ritz procedure is adopted for the structural formulation. The aerodynamic pressures provided by the aerodynamic code at a discrete number of grid points is represented as a bilinear distribution on the composite plate code to solve for the deflections and stresses in the wing. The lifting-surface aerodynamic code FAST is presently being used to generate the pressure distribution over the wing. The envisioned ENSAERO/Plate is an aeroelastic analysis code which combines ENSAERO version 3.0 (for analysis of wing-body configurations) with the composite plate code.

Kapania, Rakesh K.↗
NASA NTRS2001

An XML-Based Protocol for Distributed Event Services

This viewgraph presentation provides information on the application of an XML (extensible mark-up language)-based protocol to the developing field of distributed processing by way of a computational grid which resembles an electric power grid. XML tags would be used to transmit events between the participants of a transaction, namely, the consumer and the producer of the grid scheme.

Smith, Warren↗
NASA NTRS2010

An Improved Neutron Transport Algorithm for HZETRN

Long term human presence in space requires the inclusion of radiation constraints in mission planning and the design of shielding materials, structures, and vehicles. In this paper, the numerical error associated with energy discretization in HZETRN is addressed. An inadequate numerical integration scheme in the transport algorithm is shown to produce large errors in the low energy portion of the neutron and light ion fluence spectra. It is further shown that the errors result from the narrow energy domain of the neutron elastic cross section spectral distributions, and that an extremely fine energy grid is required to resolve the problem under the current formulation. Two numerical methods are developed to provide adequate resolution in the energy domain and more accurately resolve the neutron elastic interactions. Convergence testing is completed by running the code for various environments and shielding materials with various energy grids to ensure stability of the newly implemented method.

Slaba, Tony C.↗
NASA NTRS2016

Harmonizing Landsat and Sentinel-2 Reflectances for Better Land Monitoring

When combined, Landsat and ESA Sentinel-2 observations can provide 2-4 day coverage for the global land area. A collaboration among NASA GSFC (Goddard Space Flight Center), University of Maryland, and NASA Ames has developed a processing chain to create seamless, "harmonized" reflectance products using standardized atmospheric correction, BRDF (Bidirectional Reflectance Distribution Function) adjustment, spectral bandpass adjustment, and gridding algorithms. These products point the way to a "30-m MODIS (Moderate Resolution Imaging Spectroradiometer)" capability for agricultural and ecosystem monitoring by leveraging international sensors.

GEO-GLAM↗
DOE OSTI2023

Large-Eddy Simulation of Flow Over Boeing Gaussian Bump Using Multiagent Reinforcement Learning Wall Model: Preprint

We develop a wall model for large-eddy simulation (LES) that takes into account various pressure-gradient effects using multi-agent reinforcement learning. The model is trained using low-Reynolds-number flow over periodic hills with agents distributed on the wall at various computational grid points. It utilizes a wall eddy-viscosity formulation as the boundary condition to apply the modeled wall shear stress. Each agent receives states based on local instantaneous flow quantities at an off-wall location, computes a reward based on the estimated wall-shear stress, and provides an action to update the wall eddy viscosity at each time step. The trained wall model is validated in wall-modeled LES of flow over periodic hills at higher Reynolds numbers, and the results show the effectiveness of the model on flow with pressure gradients. The analysis of the trained model indicates that the model is capable of distinguishing between the various pressure gradient regimes present in the flow. To further assess the robustness of the developed wall model, simulations of flow over the Boeing Gaussian bump are conducted at a Reynolds number of 2 x 10^6, based on the free-stream velocity and the bump width. The results of mean skin friction and pressure on the bump surface, as well as the velocity statistics of the flow field, are compared to those obtained from equilibrium wall model (EQWM) simulations and published experimental data sets. The developed wall model is found to successfully capture the acceleration and deceleration of the turbulent boundary layer on the bump surface, providing better predictions of skin friction near the bump peak and exhibiting comparable performance to the EQWM with respect to the wall pressure and velocity field. We also conclude that the subgrid-scale model is crucial to the accurate prediction of the flow field, in particular the prediction of separation.

boundary layer↗