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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Using Machine Learning Algorithm to Detect Blowing Snow and Fog in Antarctica Based on Ceilometer and Surface Meteorology Systems

Blowing snow is a common weather phenomenon in Antarctica and plays an important role in the water vapor cycle and ice sheet mass balance. Although it has a significant impact on the climate of Antarctica, people do not know much about this process. Fog events are difficult to distinguish from blowing snow events using existing detection algorithms by a ceilometer. In this study, based on ceilometer, the meteorological parameters observed by surface meteorology systems are further combined to detect blowing snow and fog using the AdaBoost algorithm. The weather phenomena recorded by human observers are ‘true’. The dataset is collected from 1 January 2016 to 31 December 2016 at the AWARE site. Among them, three-quarters of the data are used as the training set and the rest of the data as the testing set. The classification accuracy of the proposed algorithm for the testing set is about 94%. Compared with the Loeb method, the proposed algorithm can detect 89.12% of blowing snow events and 76.10% of fog events, while the Loeb method can only identify 64.29% of blowing snow events and 31.87% of fog events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hybrid Analytics Solution to Improve Coal Power Plant Operations

This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Leak detection in a subcritical boiler

Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Furthermore, because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coalfired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.

42 ENGINEERING↗
NASA NTRS1987

A five component electro-optical positioning system

The development of a five-component electrooptical positioning system for detecting the location of wind tunnel models within the test section is discussed. The system consists of three low power helium-neon lasers, five linear photodiode arrays, an assembly of optics that includes lenses and mirrors, and a signal conditioner. The system has been successfully installed and is currently in use at the 13-inch magnetic suspension and balance system (MSBS) at NASA Langley Research Center. Initially the system was developed as an auxiliary model position and attitude detecting system for that facility, but it has since been modified and interfaced with a PDP minicomputer to provide position feedback for the control loop.

Tcheng, Ping↗
DOE OSTI2024

Blowing in the dark matter wind

Abstract Interactions between dark matter and ordinary matter will transfer momentum, and therefore give rise to a force on ordinary matter due to the dark matter ‘wind.’ We show that this force can be maximal in a realistic model of dark matter, meaning that an order-1 fraction of the dark matter momentum incident on a target of ordinary matter is reflected. The model consists of light (m ϕ ≲ eV) scalar dark matter with an effective interaction$$ {\phi}^2\overline{\psi}\psi $$ ϕ 2 ψ ¯ ψ , whereψis an electron or nucleon field. If the coupling is repulsive and sufficiently strong, the fieldϕis excluded from ordinary matter, analogous to the Meissner effect for photons in a superconductor. We show that there is a large region of parameter space that is compatible with existing constraints, where the force is large enough to be detected by existing force probes, such as satellite tests of the equivalence principle and torsion balance experiments. However, shielding of the dark matter by ordinary matter prevents existing experiments from being sensitive to the dark matter force. We show that precise measurements of spacecraft trajectories proposed to test long distance modifications of gravity are sensitive to this force for a wide range of parameters.

Physics↗
NASA NTRS1983

Use of thermal inertia determined by HCMM to predict nocturnal cold prone areas in Florida

Pairs of HCMM day-night thermal infrared (IR) data were selected during the 1978-79 winter to examine patterns of surface temperature and thermal inertia (TI) of peninsular Florida. The GOES and NOAA-6 thermal IR, as well as National Climatic Center temperatures and rainfall, were also used. The HCMM apparent thermal inertia (ATI) images closely corresponded to the general soil map of Florida, based on soil drainage classes. Areas with low ATI overlay well-drained soils, such as deep sands and drained organic soils, whereas with high ATI overlay areas with wetlands and bodies of water. The HCMM ATI images also corresponded well with GOES-detected winter nocturnal cold-prone areas. Use of HCMM data with Carlson's energy balance model showed both high moisture availability (MA) and high thermal inertia (TI) of wetland-type surfaces and low MA and low TI of upland, well-drained soils. Since soil areas with low TI develop higher temperatures during the day, then antecedent patterns of highest maximum daytime surface temperature can also be used to predict nocturnal cold-prone areas in Florida.

Allen, L. H., Jr.↗
NASA NTRS1983

Identifying environmental features for land management decisions

Pairs of HCMM day-night thermal infrared (IR) data were selected to examine patterns of surface temperature and thermal inertia (TI) of peninsular Florida. GOES and NOAA-6 thermal IR, as well as National Climatic Center temperatures and rainfall, were also used. The HCMM apparent thermal inertia (ATI) images closely correspond to the General Soil Map of Florida, based on soil drainage classes. Areas with low ATI overlay well-drained soils, such as deep sands and drained organic soils. Areas with high ATI overlay areas with wetlands and bodies of water. The HCMM ATI images also correspond well with GOES-detected winter nocturnal cold-prone areas. Use of HCMM data with Carlson's energy balance model shows both high moisture availability (MA) and high thermal inertia (TI) of wetland-type surfaces and low MA and low TI of upland, well-drained soils. Since soil areas with low TI develop higher temperatures during the day, then antecedent patterns of highest maximum daytime surface temperature can also be used to predict nocturnal cold-prone areas in Florida.

Source record↗
NASA NTRS1998

Distributed Parallel Processing and Dynamic Load Balancing Techniques for Multidisciplinary High Speed Aircraft Design

Multidisciplinary design optimization (MDO) for large-scale engineering problems poses many challenges (e.g., the design of an efficient concurrent paradigm for global optimization based on disciplinary analyses, expensive computations over vast data sets, etc.) This work focuses on the application of distributed schemes for massively parallel architectures to MDO problems, as a tool for reducing computation time and solving larger problems. The specific problem considered here is configuration optimization of a high speed civil transport (HSCT), and the efficient parallelization of the embedded paradigm for reasonable design space identification. Two distributed dynamic load balancing techniques (random polling and global round robin with message combining) and two necessary termination detection schemes (global task count and token passing) were implemented and evaluated in terms of effectiveness and scalability to large problem sizes and a thousand processors. The effect of certain parameters on execution time was also inspected. Empirical results demonstrated stable performance and effectiveness for all schemes, and the parametric study showed that the selected algorithmic parameters have a negligible effect on performance.

Krasteva, Denitza T.↗
DOE OSTI2022

Open-circuit submodule fault diagnosis in MMCs using support vector machines

Series connection of semiconductor submodules (SM) in a modular multilevel converter (MMC) makes the MMC prone to open-circuit (OC) IGBT failures inside SMs. If left undetected, these faults degrade the operation of the MMC and lead to its instability. This article proposes a method to detect, localise, and classify single OC SM faults in an MMC using support vector machines (SVM) trained with data obtained from the capacitor voltage balancing block of the MMC control system. The proposed method relies on data extracted from the sorted capacitor voltage arrays of the upper and lower phase arms. Therefore, it does not require extra measurements and hardware. Additionally, it offers a fixed time for detecting and localising OC SM faults. This method is easy to implement as SVM has a simple decision function. Time-domain simulation case studies are performed on a three-phase nine-level MMC to evaluate the performance of the proposed method.

42 ENGINEERING↗
DOE OSTI2025

Single-element balanced detector giving 65 dB CMRR at 30 MHz

We present a simple design for a single-element balanced detector (BD) that utilizes optical fibers in the sensing and reference channels with path length differences set to detect the differential signal at a desired frequency. With this approach, we easily achieve a common-mode rejection ratio of 65 dB, corresponding to the shot-noise limit of our setup. The CMRR demonstration is made in the MHz frequency range but could be extended to the kHz or GHz range. Using a single detector, the BD achieves stable CMRR over extended periods and does not require careful matching of detectors and amplification electronics. We demonstrate the single-element balanced detector design using the optical Kerr effect induced by a 30 MHz pulsed laser, showing a significant improvement over similar experiments using a commercial balanced detector.

Badilla-Nunez, Kelly [Georgia Institute of Technol↗
NASA NTRS2012

NASA Tech Briefs, September 2012

Topics covered include: Beat-to-Beat Blood Pressure Monitor; Measurement Techniques for Clock Jitter; Lightweight, Miniature Inertial Measurement System; Optical Density Analysis of X-Rays Utilizing Calibration Tooling to Estimate Thickness of Parts; Fuel Cell/Electrochemical Cell Voltage Monitor; Anomaly Detection Techniques with Real Test Data from a Spinning Turbine Engine-Like Rotor; Measuring Air Leaks into the Vacuum Space of Large Liquid Hydrogen Tanks; Antenna Calibration and Measurement Equipment; Glass Solder Approach for Robust, Low-Loss, Fiber-to-Waveguide Coupling; Lightweight Metal Matrix Composite Segmented for Manufacturing High-Precision Mirrors; Plasma Treatment to Remove Carbon from Indium UV Filters; Telerobotics Workstation (TRWS) for Deep Space Habitats; Single-Pole Double-Throw MMIC Switches for a Microwave Radiometer; On Shaft Data Acquisition System (OSDAS); ASIC Readout Circuit Architecture for Large Geiger Photodiode Arrays; Flexible Architecture for FPGAs in Embedded Systems; Polyurea-Based Aerogel Monoliths and Composites; Resin-Impregnated Carbon Ablator: A New Ablative Material for Hyperbolic Entry Speeds; Self-Cleaning Particulate Prefilter Media; Modular, Rapid Propellant Loading System/Cryogenic Testbed; Compact, Low-Force, Low-Noise Linear Actuator; Loop Heat Pipe with Thermal Control Valve as a Variable Thermal Link; Process for Measuring Over-Center Distances; Hands-Free Transcranial Color Doppler Probe; Improving Balance Function Using Low Levels of Electrical Stimulation of the Balance Organs; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; PMA-Linked Fluorescence for Rapid Detection of Viable Bacterial Endospores; Portable Intravenous Fluid Production Device for Ground Use; Adaptation of a Filter Assembly to Assess Microbial Bioburden of Pressurant Within a Propulsion System; Multiplexed Force and Deflection Sensing Shell Membranes for Robotic Manipulators; Whispering Gallery Mode Optomechanical Resonator; Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles; Self-Sealing Wet Chemistry Cell for Field Analysis; General MACOS Interface for Modeling and Analysis for Controlled Optical Systems; Mars Technology Rover with Arm-Mounted Percussive Coring Tool, Microimager, and Sample-Handling Encapsulation Containerization Subsystem; Fault-Tolerant, Real-Time, Multi-Core Computer System; Water Detection Based on Object Reflections; SATPLOT for Analysis of SECCHI Heliospheric Imager Data; Plug-in Plan Tool v3.0.3.1; Frequency Correction for MIRO Chirp Transformation Spectroscopy Spectrum; Nonlinear Estimation Approach to Real-Time Georegistration from Aerial Images; Optimal Force Control of Vibro-Impact Systems for Autonomous Drilling Applications; Low-Cost Telemetry System for Small/Micro Satellites; Operator Interface and Control Software for the Reconfigurable Surface System Tri-ATHLETE; and Algorithms for Determining Physical Responses of Structures Under Load.

Source record↗
NASA NTRS2024

A Physics-Based Antarctic Melt Detection Technique: Combining Advanced Microwave Scanning Radiometer 2, Radiative-Transfer Modeling, and Firn Modeling

Surface melt on ice shelves has been linked to hydrofracture and subsequent ice shelf breakup. Since the 1990s, scientists have been using microwave radiometers to detect melt on ice shelves and ice sheets by applying various statistical thresholding techniques to identify significant increases in brightness temperature that are associated with melt. In this study, instead of using a fixed threshold, we force the Snow Radiative Transfer model (SMRT) with outputs from the Community Firn Model (CFM) to create a dynamic, physics-based threshold for melt. In the process, we also combine our method with statistical thresholding techniques and produce microwave grain size information in the process. We run this “Hybrid Method” across the Larsen C ice shelf as well as thirteen sites on the Antarctic Ice Sheet. Melt and non-melt days from the Hybrid Method and three statistical thresholding techniques match with surface energy balance within 94±1%; the effect of melt on the passive microwave is mostly binary and thus largely detectable by statistical thresholding techniques as well as physics-based techniques. Rather than always replacing statistical thresholding techniques with the Hybrid Method, we recommend using the Hybrid Method in studies where melt volume or grain size is of interest. In this study, we show that the Hybrid Method can be used to (a) model dry snow brightness temperatures of Antarctic snow and (b) derive a measure of grain size; therefore, it is an important step forwards towards using firn and radiative transfer modeling to quantify melt rather than to simply detect melt days.

Marissa E Dattler↗
DOE OSTI2025

Detectable ship tracks account for just 5% of aerosol indirect forcing from ship emissions

Ship emissions are a major source of aerosols over oceans, affecting both air quality and energy balance of the climate. However, estimates of their climate forcing diverge between studies relying on visible ship-tracks and those based on models. Here we show that forcing due to visible ship-tracks accounts for just 5% of the total forcing over the southeast Atlantic shipping-lane. Most forcing from ship emissions comes from aerosols that do not form detectable ship-tracks. They are only tips of the iceberg. We make three forcing calculations, one bottom-up based on visible ship-tracks, one top-down based on spatial relationships, and a hybrid approach that combines top-down or model estimated cloud droplet number concentration changes and cloud adjustments. Although the forcing based on machine learning detected ship tracks is an order of magnitude greater than prior results using manually detected ship-tracks, it remains only 5% of that inferred by top-down or cloud adjustment based methods for pre-2020 shipping. The top-down and the combined cloud adjustments methods show similar forcing for the post-2020 reduction in ships’ sulfur emission, although the methods have important regional differences in cloud adjustments that need further investigation. Our results reconcile a long-standing discrepancy in the literature and have important implications for aerosol indirect forcing and marine cloud brightening.

Yuan, Tianle [NASA Goddard Space Flight Center (GS↗
NASA NTRS2011

What Dominates the Coronal Emission Spectrum During the Cycle of Impulsive Heating and Cooling?

The smoking gun of small-scale, impulsive events heating the solar corona is expected to be the presence of a hot ( > 5 MK) plasma component. Evidence for this has been scarce, but has gradually begun to accumulate due to recent studies designed to constrain the high temperature part of the emission measure distribution. However, the detected hot component is often weaker than models predict and this is due in part to the common modeling assumption that the ionization balance remains in equilibrium. The launch of the latest generation of space-based observing instrumentation aboard Hinode and the Solar Dynamics Observatory (SDO) has brought the matter of the ionization state of the plasma firmly to the forefront. It is timely to consider exactly what emission current instruments would detect when observing a corona heated impulsively on small-scales by nanoflares. Only after we understand the full effects of nonequilibrium ionization can we draw meaningful conclusions about the plasma that is (or is not) present. We have therefore performed a series of hydrodynamic simulations for a variety of different nanoflare properties and initial conditions. Our study has led to several key conclusions. 1. Deviations from equilibrium are greatest for short-duration nanoflares at low initial coronal densities. 2. Hot emission lines are the most affected and are suppressed sometimes to the point of being invisible. 3. The emission detected in all of the SDO-AIA channels is generally dominated by warm, over-dense, cooling plasma. 4. It is difficult not to create coronal loops that emit strongly at 1.5 MK and in the range 2 to 5 MK, which are the most commonly observed kind, for a broad range of nanoflare scenarios. 5. The Fe XV (284.16 ) emission in most of our models is about 10 times brighter than the Ca XVII (192.82 ) emission, consistent with observations. Our overarching conclusion is that small-scale, impulsive heating inducing a nonequilibrium ionization state leads to predictions for observable quantities that are entirely consistent with what is actually observed.

Bradshaw, Stephen J.↗
NASA NTRS2013

Orion MPCV Touchdown Detection Threshold Development and Testing

A robust method of detecting Orion Multi ]Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post ]landing segment of the Flight Software (FSW). The vehicle crew is the prime input for touchdown detection, followed by an autonomous FSW algorithm, and finally a strictly time based backup timer. RCS thrusters must be inhibited before submersion in water to protect against possible damage due to firing these jets under water. In addition, neglecting to declare touchdown will not allow the vehicle to transition to post ]landing activities such as activating the Crew Module Up ]righting System (CMUS), resulting in possible loss of communication and difficult recovery. A previous AIAA paper gAssessment of an Automated Touchdown Detection Algorithm for the Orion Crew Module h concluded that a strictly Inertial Measurement Unit (IMU) based detection method using an acceleration spike algorithm had the highest safety margins and shortest detection times of other methods considered. That study utilized finite element simulations of vehicle splashdown, generated by LS ]DYNA, which were expanded to a larger set of results using a Kriging surface fit. The study also used the Decelerator Systems Simulation (DSS) to generate flight dynamics during vehicle descent under parachutes. Proto ]type IMU and FSW MATLAB models provided the basis for initial algorithm development and testing. This paper documents an in ]depth trade study, using the same dynamics data and MATLAB simulations as the earlier work, to further develop the acceleration detection method. By studying the combined effects of data rate, filtering on the rotational acceleration correction, data persistence limits and values of acceleration thresholds, an optimal configuration was determined. The lever arm calculation, which removes the centripetal acceleration caused by vehicle rotation, requires that the vehicle angular acceleration be derived from vehicle body rates, necessitating the addition of a 2nd order filter to smooth the data. It was determined that using 200 Hz data directly from the vehicle IMU outperforms the 40 Hz FSW data rate. Data persistence counter values and acceleration thresholds were balanced in order to meet desired safety and performance. The algorithm proved to exhibit ample safety margin against early detection while under parachutes, and adequate performance upon vehicle splashdown. Fall times from algorithm initiation were also studied, and a backup timer length was chosen to provide a large safety margin, yet still trigger detection before CMUS inflation. This timer serves as a backup to the primary acceleration detection method. Additionally, these parameters were tested for safety on actual flight test data, demonstrating expected safety margins.

Daum, Jared↗
DOE OSTI2025

Detecting isolated resonance curves using fixed frequency voltage control tests

Isolated resonance curves, or isolas, are resonance branches of the harmonically forced system that exist separately from the main nonlinear forced response curve, leading to excessive vibrations. Traditional stepped or swept sine simulations and tests rely on continuation along the frequency parameter, typically resulting in a jump phenomenon along the primary resonance branch, prior to the disconnected isola. The main objective of this research is to propose an approach to identify isolated resonance curves by performing continuation along the input amplitude that initializes the response from a low-amplitude solution in the linear regime. Furthermore, this is achieved with the open-loop fixed frequency voltage control method that continues along the shaker voltage parameter and measures the so-called S-curves, which are theoretically a continuous solution branch that connect to the isola. The methodology is demonstrated on a fixture-wing-pylon assembly with a vibro-impact nonlinearity localized in a pylon subcomponent attachment. Multi-harmonic balance simulations are deployed to compute both the nonlinear forced response curves and S-curves to demonstrate the isola detection strategy on a reduced-order finite element model of the nonlinear system. Swept sine and fixed frequency voltage control tests are then conducted on the physical structure to demonstrate the isola detection experimentally, revealing the existence of the large amplitude vibrations that are undetected in the forces levels and frequencies measured with traditional frequency sweeping.

Characterization and Analytical Technique↗
DOE OSTI2025

A Rhenium Bis -tetramethylphenanthroline Catalyst for CO 2 Reduction to Formate

Catalytic CO 2 reduction reactions featuring high selectivity toward formate are relatively rare. In some homogeneous molecular CO 2 -reducing electrocatalysis, using triethylamine (TEA) and isopropanol (IPA) as additives improves catalytic performance in producing formate. In this paper, we investigate whether the rhenium(I) bis-diimine dicarbonyl complexes, cis-[Re(N^N) 2 (CO) 2 ] + , where N^N is 2,2’-bipyridine ([1] + ) or 3,4,7,8-tetramethyl-1,10-phenanthroline ([2] + ), are capable of electrocatalytically reducing CO 2 to formate in acetonitrile containing TEA and IPA. Catalyst [1] + was ineffective at CO 2 reduction, yielding formate quantities comparable to those produced in experiments without the catalyst. Catalyst [2] + , however, is a promising electrocatalyst for the CO 2 reduction reaction in the presence of TEA and IPA, with formate being produced in millimolar concentrations (10.5 mM), as detected by 1 H NMR spectroscopy after 6 h electrolysis (formate Faradaic efficiency = 11%, with the major balance going to H 2 ). Upon more detailed examination, [2] + exhibited a turnover frequency (TOF) of 12 s –1 for formate, comparable to other leading molecular catalysts that competently execute this reduction. Combinations of spectroscopy, electrochemistry, and theory were used to better understand the mechanism of CO 2 reduction by [2] + . Fourier transform infrared spectroelectrochemical (FTIR-SEC) data provided no evidence for CO ligand dissociation or substitution upon one- and two-electron reduction of [2] + , suggesting that a mechanism distinct from one that is metal-hydride-based is operative in catalysis. Computational studies guide mechanistic investigations toward the proposed formation of a hydrophenanthroline-based intermediate responsible for hydride transfer to CO 2 and electrocatalytic formate production from [2] + .

Beverages↗
DOE OSTI2025

Analysing a multi‐stage cyber threat and its impact on the power system

Abstract Electric power systems are composed of physical and cyber sub‐systems. The sub‐systems depend on each other. If the cyber sub‐system is compromised by a cyber threat, what is the impact on the physical system? This paper presents a case study that shows the steps of a multi‐stage cyber threat involving a database injection attack, and what happens to the power system if this threat is not detected in its early stages. The threat first affects one utility but it can spread to the balancing authority, which is responsible for keeping the voltage and frequency stable in the power grid. During the cyber threat, the authors also show defence tools, such as a cyber‐physical data fusion tool that displays and analyses power and cyber telemetry.

Al Homoud, Leen [Texas A&amp,M University College ↗