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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Novel Architecture for Attack-Resilient Wide-Area Protection and Control System in Smart Grid

Wide-area protection and control (WAPAC) systems are widely applied in the energy management system (EMS) that rely on a wide-area communication network to maintain system stability, security, and reliability. As technology and grid infrastructure evolve to develop more advanced WAPAC applications, however, so do the attack surfaces in the grid infrastructure. This paper presents an attack-resilient system (ARS) for the WAPAC cybersecurity by seamlessly integrating the network intrusion detection system (NIDS) with intrusion mitigation and prevention system (IMPS). In particular, the proposed NIDS utilizes signature and behavior-based rules to detect attack reconnaissance, communication failure, and data integrity attacks. Further, the proposed IMPS applies state transition-based mitigation and prevention strategies to quickly restore the normal grid operation after cyberattacks. As a proof of concept, we validate the proposed generic architecture of ARS by performing experimental case study for wide-area protection scheme (WAPS), one of the critical WAPAC applications, and evaluate the proposed NIDS and IMPS components of ARS in a cyber-physical testbed environment. Our experimental results reveal a promising performance in detecting and mitigating different classes of cyberattacks while supporting an alert visualization dashboard to provide an accurate situational awareness in real-time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

On/Off State Classification of a Reactor Facility Using Gas Effluence Measurements

Inferring on/off operational state of a reactor facility using measurements from an independent monitoring system is critical to the assessment of its compliance to agreements. In this paper, we consider the problem of inferring on/off state of a reactor facility using measurements of Ar-41, Cs-138, and Xe-138 gas effluence types collected at the facility’s off-gas stack. We present classifiers based on thresholding measurements of individual effluence types, and then present fusers that combine their outputs or measurements. We present five fusers based on simple majority rule, Chow’s pattern recognition function, Fisher’s combined p-value statistic, physics-based Poisson radiation counts model, and correlation coefficient method. In addition, we also test five machine learning methods based on non-linear classifiers, which are available as R packages. Finally, our results show that: (i) these gas effluence measurements are effective in inferring on/off state of a reactor facility; for example, best fusers achieve ~97% detection at ~1% false alarm rate, and (ii) fusers that combine all effluence types based on physics-based models, correlation coefficient and Fisher’s method outperform simple majority rule, Chow’s fusers and machine learning methods, as well as when they are applied to individual and pairs of effluence types.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Software For Detecting, Analyzing, And Mitigating Anomalous Network Packets Through A Multi Dimensional Latent Space Representation

The code ingests network packet payloads, classifies the payload as anomalous or normal, and plots the payload in a 3-D latent space representation. It also enables user interaction with the representation to allow for the user to click on the packet payload in the latent space and determine host id, network topology, and access the raw packet data.

Anderson, MatthewW.↗
DOE OSTI2024

DER Translate

SAND2024-13723O This software translates and maps any .xlsx-based distributed energy resource (DER) device from the SunSpec certification registry (https://sunspec.org/certified-registry/) to a JSON-based DER models map. It is then read by DER monitoring tools for applications such as network intrusion detection and system health monitoring. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Fragkos, Georgios↗
DOE OSTI2024

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗
DOE OSTI2012

Second Line of Defense Master Spares Catalog

This catalog is intended to be a comprehensive listing of repair parts, components, kits, and consumable items used on the equipment deployed at SLD sites worldwide. The catalog covers detection, CAS, network, ancillary equipment, and tools. The catalog is backed by a Master Parts Database which is used to generate the standard report views of the catalog. The master parts database is a relational database containing a record for every part in the master parts catalog along with supporting tables for normalizing fields in the records. The database also includes supporting queries, database maintenance forms, and reports.

Henderson, Dale L.↗
DOE OSTI2015

Inferring Organizational Structure from Behavior

In this project, we researched new techniques for detecting hidden networks of individuals and institutions by introducing the use of temporal correlations among behaviors, leveraging both information sources and metadata. We validated the algorithms using the Wikipedia edit history. The rapid increase in crowd-sourced applications like Wikipedia is providing a rich set of data with both a record of behaviors and a set of direct interactions among individuals. Data sets with network ground truth are needed to develop and validate models, before applying them to national security settings where content and meta-data alone are available.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Data Fusion via Neural Network Entropy Minimization for Target Detection and Multi-Sensor Event Classification

Broadly applicable solutions to multimodal and multisensory fusion problems across domains remain a challenge because effective solutions often require substantive domain knowledge and engineering. The chief questions that arise for data fusion are in when to share information from different data sources, and how to accomplish the integration of information. The solutions explored in this work remain agnostic to input representation and terminal decision fusion approaches by sharing information through the learning objective as a compound objective function. The objective function this work uses assumes a one-to-one learning paradigm within a one-to-many domain which allows the assumption that consistency can be enforced across the one-to-many dimension. The domains and tasks we explore in this work include multi-sensor fusion for seismic event location and multimodal hyperspectral target discrimination. We find that our domain- informed consistency objectives are challenging to implement in stable and successful learning because of intersections between inherent data complexity and practical parameter optimization. While multimodal hyperspectral target discrimination was not enhanced across a range of different experiments by the fusion strategies put forward in this work, seismic event location benefited substantially, but only for label-limited scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

The recent increase of atmospheric methane from 10 years of ground-based NDACC FTIR observations since 2005

Changes of atmospheric methane total columns (CH 4 ) since 2005 have been evaluated using Fourier transform infrared (FTIR) solar observations carried out at 10 ground-based sites, affiliated to the Network for Detection of Atmospheric Composition Change (NDACC). From this, we find an increase of atmospheric methane total columns of 0.31 ± 0.03 % year –1 (2 σ level of uncertainty) for the 2005–2014 period. Comparisons with in situ methane measurements at both local and global scales show good agreement. We used the GEOS-Chem chemical transport model tagged simulation, which accounts for the contribution of each emission source and one sink in the total methane, simulated over 2005–2012. After regridding according to NDACC vertical layering using a conservative regridding scheme and smoothing by convolving with respective FTIR seasonal averaging kernels, the GEOS-Chem simulation shows an increase of atmospheric methane total columns of 0.35 ± 0.03 % year –1 between 2005 and 2012, which is in agreement with NDACC measurements over the same time period (0.30 ± 0.04 % year –1 , averaged over 10 stations). Analysis of the GEOS-Chem-tagged simulation allows us to quantify the contribution of each tracer to the global methane change since 2005. We find that natural sources such as wetlands and biomass burning contribute to the interannual variability of methane. However, anthropogenic emissions, such as coal mining, and gas and oil transport and exploration, which are mainly emitted in the Northern Hemisphere and act as secondary contributors to the global budget of methane, have played a major role in the increase of atmospheric methane observed since 2005. Furthermore based on the GEOS-Chem-tagged simulation, we discuss possible cause(s) for the increase of methane since 2005, which is still unexplained.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

The use of Doppler radar to help forecast the development of thunderstorms

The role of Doppler radars in forecasting the location and timing of the initiation of thunderstorms both over Kennedy Space Center and central Florida is analyzed. The data used in this analysis was collected with two Doppler radars with high temporal and spatial resolution throughout the troposphere. Previous studies of thunderstorm initiation in the vicinity of Kennedy Space Center, including synoptic and site-specific observations are outlined. As a result of the analysis of nine cases of thunderstorm initiation, it is concluded that an expert system could be developed that would take input data from the existing field mill network, instrumented tower network, lightning detection system, from sounding, and from Doppler-radar-based algorithms. Such a system would be able to determine a probability of thunderstorm development in the next 10, 20, and 30 minutes for the area of interest.

Eilts, Michael D.↗
NASA NTRS1992

Automated screening of propulsion system test data by neural networks, phase 1

The evaluation of propulsion system test and flight performance data involves reviewing an extremely large volume of sensor data generated by each test. An automated system that screens large volumes of data and identifies propulsion system parameters which appear unusual or anomalous will increase the productivity of data analysis. Data analysts may then focus on a smaller subset of anomalous data for further evaluation of propulsion system tests. Such an automated data screening system would give NASA the benefit of a reduction in the manpower and time required to complete a propulsion system data evaluation. A phase 1 effort to develop a prototype data screening system is reported. Neural networks will detect anomalies based on nominal propulsion system data only. It appears that a reasonable goal for an operational system would be to screen out 95 pct. of the nominal data, leaving less than 5 pct. needing further analysis by human experts.

Hoyt, W. Andes↗
NASA NTRS1992

The NDSC Primary Site at the Observatoire De Haute-provence: Ozone and Aerosols Observations (1986-1992)

The primary site of the newly implemented Network for Detection of Stratospheric Changes (NDSC) includes three main sites in the alpine regions of southern Europe. At one of these observatories, a coherent set of experimental systems has been established to monitor on a long-term basis ozone, aerosols, minor constituents, and temperature vertical distributions in the troposphere and stratosphere. Such techniques include several lidar systems, balloon-borne sondes and ultraviolet visible spectrometry. Lidar measurements of stratospheric aerosols are performed on a routine basis, since 1980. These include the vertical distribution of the extinction and backscattering coefficients from the tropopause. Recently, measurements performed following the eruption of Mount Pinatubo, have allowed researchers to follow the time evolution of the aerosol cloud in middle latitude regions.

Megie, G.↗