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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine Learning in Power System Operations: Training Data

Reliability and stability of the electric grid today has depended upon operations of the grid which include the protective relay. Today, the electricity sector faces new challenges with the shift of generation resource characteristics away from the traditional “big iron” generation to inverter-based resources (IBR) which shift the physics and assumption used in grid operation and protection. These changing conditions represent new challenges for protective relays (identification of faults) and increased challenges for protection engineers (correct settings and configuration, reduction of mis-operations), both issues recognized in research and industry. Finding new approaches to reduce mis-operations in relaying and new approaches to fault identification is critical to grid operations. Using today’s modern technology of embedded systems, edge computing, machine learning (ML), and communications we can help address challenges and augment and improve on existing power system operations methodologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Persistent Acoustic Sensing for Monitoring A Reactor Facility - Oral Presentation

Measurements over the past few years, taking place within the Multi-Informatics for Nuclear Operations Scenarios (MINOS) project, show that infrasound and low-frequency acoustic monitoring can detect, and often quantify, activities that occur on-site at a large research reactor. Observable activities include: crane translation, lifting, and lowering; differentiation between loaded and unloaded crane operations; access door opening and closing; vehicle operations; and cooling tower fan operation. Advanced data analytic and spectral feature extraction methods can be used to interpret selected signatures to reach a deeper understanding of different reactor activities. These measurements are being conducted using a network of smartphones that continuously operate in conjunction with cloud-based architectures. A recent addition to the system is the development and deployment of a real-time, cloud-based analytic framework that supports near-real-time alarming which can facilitate tip-and-cue protocols. This paper will present recent research advances in this area including studies to explore the transferability of learned parameters from one smartphone to another, the detectability of events from multiple sensors at different locations simultaneously, and the feasibility of porting analytical tools directly to the smartphones to allow edge computing with optimized configurations.

42 ENGINEERING↗
DOE OSTI2024

Privacy by Design in Distributed Edge Systems: Innovating Secure Workflows for Smart Cities

The proliferation of distributed edge systems, such as those in smart cities, healthcare, and industrial IoT, offers unprecedented opportunities for data processing closer to its source, thereby reducing latency and enhancing efficiency. However, these systems also present significant privacy challenges due to the handling of sensitive data from multiple sources. This article explores the critical need for designing privacy-preserving workflows in distributed edge systems to ensure data security while maximizing the potential of edge computing. By examining the challenges, technological advancements, and potential of privacy-by-design approaches, we highlight the importance of integrating advanced privacy-preserving techniques like federated learning, differential privacy, homomorphic encryption, secure multi-party computation, and zero-knowledge proofs. These innovations are crucial for enhancing data security, regulatory compliance, and public trust in smart city applications, ultimately leading to safer and more efficient urban environments.

Kotevska, Olivera↗
DOE OSTI2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environments and operational constraints. Harnessing this data for scientific discovery demands real-time inference and decision-making, intelligent data reduction, and efficient processing architectures beyond current capabilities. Crucial to the success of this experimental paradigm are several emerging technologies, such as artificial intelligence and machine learning (AI/ML) and silicon microelectronics, and the advent of quantum algorithms and processing. Their intersection includes areas of research such as low-power and low-latency devices for edge computing, heterogeneous accelerator systems, reconfigurable hardware, novel codesign and synthesis strategies, readout for cryogenic or high-radiation environments, and analog computing. This white paper presents a community-driven vision to identify and prioritize research and development opportunities in hardware-based ML systems and corresponding physics applications, contributing towards a successful transition to the new data frontier of fundamental science.

Gonski, Julia [SLAC]↗
DOE OSTI2021

Real-Time Evolution and Deployment of Neuromorphic Computing at The Edge

Extremely low power neuromorphic systems are well-suited for deployment to the edge for many applications. In many use cases of neuromorphic computing for control, a spiking neural network is trained off-line using a simulation and then deployed to a neuromorphic system at the edge, where it will operate without ongoing training or learning. However, it may be desirable to continue training or learning at the edge to refine or adapt to the real-world system. In this work, we propose an approach for performing real-time evolutionary optimization for spiking neural networks for neuromorphic deployment at the edge. In particular, we propose a combination of simulation and real-world evaluations, along with feedback from the real-world environment, to train spiking neural networks for continuous deployment to the edge. We show that the real-time evolution at the edge approach achieves comparable performance to an evolution approach that requires constant evaluation in the realworld environment.

Schuman, Catherine↗
NASA NTRS1980

Wing and leading-edge thrust

Computer program predicts leading-edge thrust for wings of arbitrary planform at supersonic speeds. Methods used in program are based on linearized wing theory. Program first calculates lifting pressures, lift coefficients, drag coefficients, moment coefficients, and lift distributions by using aft-element sensing technique. Next, empirical function calculates set of adjusted pressure-coefficient locations along leading edge. This information is then used to determine limiting value of singularity parameter and value of local leading-edge thrust coefficient.

Carlson, H. W.↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
DOE OSTI2022

Integrated Experimental and Computational K-Edge X-ray Absorption Near-Edge Structure Analysis of Vanadium Catalysts

X-ray Absorption Near-Edge Structure (XANES) spectroscopy is a powerful tool to reveal key structural and electronic features of isolated catalytic sites, yet insights into molecular structure and more detailed orbital analysis through a combination of experimental and computed XANES analysis are necessary for accurate interpretation of the spectra, especially when significant heterogeneity exits among the catalytic sites. Herein, we present an integrated computational and experimental strategy to determine both primary and secondary bonding interactions within the XANES pre-edge region for organovanadium complexes, which was developed using a series of well-defined molecular vanadium complexes and then applied to the characterization of a supported organovanadium olefin hydrogenation catalyst. Time-dependent density functional theory is used to predict the energy of pre-edge XANES features for a series of vanadium complexes with a variety of oxidation states and local coordination environments. Further, a calibration scheme incorporating different density functionals and basis sets is established, resulting in an optimized scheme that accurately predicts pre-edge energies with a mean absolute error of 0.40 eV. Second-shell coordination (e.g., V---V) effects within XANES are identified through the analysis of the computed dominant orbital contributions for multi-vanadium complexes. Orbital analysis also provided confirmation that the vanadium-hydride formation combined with the heterogeneity of the catalytic active species in ole-fin hydrogenation caused the energy shift and broadening of the pre-edge peak after hydrogen treatment of the silica-supported organovanadium pre-catalyst. This work further elucidates computational XANES simulations and techniques potentially guiding characterization in surface organometallic chemistry.

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

Spectral Signatures of Ultrafast Excited-State Intramolecular Proton Transfer from Computational Multi-edge Transient X-ray Absorption Spectroscopy

Excited state intramolecular proton transfer (ESIPT) is a fundamental chemical process with several applications. Ultrafast ESIPT involves coupled electronic and atomic motions and has been primarily studied using femtosecond optical spectroscopy. X-ray spectroscopy is particularly useful because it is element-specic and enables direct, individual probes of the proton donating and accepting atoms. Here, we report a computational study to resolve the ESIPT in 10-Hydroxybenzo[h]quinoline (HBQ), an intramolecularly hydrogen bonded compound, using time-dependent density functional theory combined with ab initio molecular dynamics (AIMD) and time-resolved X-ray absorption spectroscopy (XAS) computations to track the ultrafast excited-state dynamics. Overall, our results reveal clear X-ray spectral signatures of coupled electronic and atomic motions during and following ESIPT at the oxygen and nitrogen K-edge paving the way for future experiments at X-ray free electron lasers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1933

A Method for Computing Leading-Edge Loads

In this report a formula is developed that enables the determination of the proper design load for the portion of the wing forward of the front spar. The formula is inherently rational in concept, as it takes into account the most important variables that affect the leading-edge load, although theoretical rigor has been sacrificed for simplicity and ease of application. Some empirical corrections, based on pressure distribution measurements on the PW-9 and M-3 airplanes have been introduced to provide properly for biplanes. Results from the formula check experimental values in a variety of cases with good accuracy in the critical loading conditions. The use of the method for design purposes is therefore felt to be justified and is recommended.

Rhode, Richard V↗
NASA NTRS2004

Characterization of Unsteady Flow Structures Near Landing-Edge Slat: 2D Computations - Part 2

In our previous computational studies of a generic high-lift configuration, quasi-laminar (as opposed to fully turbulent) treatment of the slat cove region proved to be an effective approach for capturing the unsteady dynamics of the cove flow field. Combined with acoustic propagation via Ffowes Williams and Hawkings formulation, the quasi-laminar simulations captured some important features of the slat cove noise measured with microphone array techniques. However. a direct assessment of the computed cove flow field was not feasible due to the unavailability of off-surface flow measurements. To remedy this shortcoming, we have undertaken a combined experiment and computational study aimed at characterizing the flow structures and fluid mechanical processes within the slat cove region. Part I of this paper outlines the experimental aspects of this investigation focused on the 30P30N high-lift configuration; the present paper describes the accompanying computational results including a comparison between computation and experiment at various angles of attack. Even through predictions of the time-averaged flow field agree well with the measured data, the study indicates the need for further refinement of the zonal turbulence approach in order to capture the full dynamics of the cove's fluctuating flow field.

Khorrami, Mehdi↗
NASA NTRS1993

Vortex developments over steady and accelerated airfoils incorporating a trailing edge jet

Computational and experimental studies are conducted to investigate the influence of a trailing edge jet on flow separation and subsequent vortex formation over steady and accelerated airfoils at high angles of attack. A computer code, employing the stream function-vorticity approach, is developed and utilized to conduct numerical experiments on the flow problem. To verify and economize such efforts, an experimental system is developed and incorporated into a subsonic wind tunnel where streamline and vortex flow visualization experiments are conducted. The study demonstrates the role of the trailing edge jet in controlling flow separation and subsequent vortex development for steady and accelerating flow at angles past the static stall angle of attack. The results suggest that the concept of the trailing edge jet may be utilized to control the characteristics of unsteady separated flows over lifting surfaces. This control possibility seems to be quite effective and could have a significant role in controlling unsteady separated flows.

Finaish, F.↗
DOE OSTI2020

Using new edges for anomaly detection in computer networks

Creation of new edges in a network may be used as an indication of a potential attack on the network. Historical data of a frequency with which nodes in a network create and receive new edges may be analyzed. Baseline models of behavior among the edges in the network may be established based on the analysis of the historical data. A new edge that deviates from a respective baseline model by more than a predetermined threshold during a time window may be detected. The new edge may be flagged as potentially anomalous when the deviation from the respective baseline model is detected. Probabilities for both new and existing edges may be obtained for all edges in a path or other subgraph. The probabilities may then be combined to obtain a score for the path or other subgraph. A threshold may be obtained by calculating an empirical distribution of the scores under historical conditions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Computational Investigation of Flap-Edges

The current study expands the application of computational fluid dynamics to three-dimensional multi-element high-lift systems by investigating the flow dynamics created by a slat edge. Flow is computed over a three-element high-lift configuration using an incompressible Navier-Stokes solver with structured, overset grids processed assuming full turbulence with the one-equation Baldwin-Barth turbulence model. The geometry consists of an unswept wing, which spans the wind tunnel test section, a single element half-span Fowler flap, and a three-quarter span slat. Results are presented for the wing configured for landing with a chord based Reynolds number of 3.7 million. Results for the three-quarter span slat case are compared to the full-span slat and two-dimensional investigations.

Cummings, Russell M.↗
NASA NTRS1992

Navier-Stokes computation of wing leading edge tangential blowing for a tilt rotor in hover

The effect of a thin tangential jet located at the leading edge of the wing of a tilt rotor configuration in hover is computed using the thin-layer Navier-stokes equations. Computations showed that leading edge tangential blowing is effective in reducing the download caused by the impingement of the rotor download caused by the impingement of the rotor downwash on the wing. Results from the numerical model support previous experimental findings that download reduction is due mainly to a decrease in upper surface pressure and not an increase in pressure on the lower surface. The numerical solution clearly shows that because of the three-dimensionality of the flow field, the download could be reduced further by allowing a spanwise variation in blowing strength.

Fejtek, Ian↗