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DOE OSTI2025

An Open-Access Repository of Synchrophasor Data Quality Examples: Curation and Example Applications

Synchrophasor measurements are critical in providing wide-area situational awareness to power system operators. However, data artifacts may be introduced due to various issues such as loss of communication, loss of GPS signal, internal clock error, and vendor-specific implementation of phasor estimation algorithms. Tools designed to provide actionable insights from synchrophasor data, hence, must be designed to be robust to these data quality issues. In this work, two years of synchrophasor data sourced from multiple electric utilities in the United States were analyzed to identify examples of data quality problems. These examples were then labeled and published in the Grid Event Signature Library, a publicly available repository of power system measurements hosted by the Oak Ridge National Laboratory. This paper describes the data curation process, and illustrates two application use cases where the dataset can be valuable to the research community. In the first use case, a random forest classifier is trained to distinguish power system disturbance signatures from data anomalies introduced in synchrophasor measurements due to clock errors. The second use case studies the impact of data quality issues on an example synchrophasor application (specifically, event start time determination). The choice of data quality problems investigated is informed by the examples in the repository curated in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

A Hierarchical Multi-Agent Based Anomaly Detection for Wide-Area Protection in Smart Grid

Future smart grid capabilities provide assurance to expand the advanced information and communication technologies to evolve into densely interconnected cyber physical system. Remedial Action Scheme (RAS), widely used for wide-area protection, relies on the interconnected networks and data sharing devices, which are exposed to the multitude of vulnerabilities. This paper presents our proposed approach to developing multi-agent based RAS scheme against the system-aware stealthy cyber-attacks. Specifically, we propose the two-level hierarchical architecture which consists of distributed local RAS controllers (RAScs) as local agents, operating at different zones/ areas, which are constantly monitored by an overseer, the central agent. The local controllers receive local and randomly changing outside zonal measurements and cyclically forwards to the overseer. The overseer identifies the corrupted controller using the anomaly detection algorithm which processes the measurements coming from the local controllers, compute measurement errors using local and outside zonal measurements, perform validation checks, and finally detect anomalies based on the two-step verification. Next, as a proof of concept, we have implemented and validated the proposed methodology in cyber physical environment at Iowa State’s PowerCyber testbed. We have also implemented the coordinated attack vectors which involve corrupting the local controller and later performing stealthy attacks on the system’s generator. We have evaluated its performance during the online testing in terms of detection rate and Iatency. The experimental results show that it is efficient in detecting different classes of attacks, including ramp and pulse attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Automating the interpretation of PM 2.5 time–resolved measurements using a data–driven approach

The rapid development of automated measurement equipment enables researchers to collect greater quantities of time-resolved data from indoor and outdoor environments. While significant, the interpretation of the resulting data can be a time-consuming effort. This paper introduces an automated process of interpreting PM 2.5 time-resolved data and differentiating PM 2.5 emissions resulting from indoor and outdoor sources. Here, we use Random Forest (RF), a machine learning approach, to study a dataset of 836 indoor emission events that occurred over a 2-week period in 18 apartments in California. In this paper, we show model development and evaluate its performance as the sample size and source vary. We discuss the characteristics of the dataset that tended to help the source identification and why. For example, we show that data from many events and from different apartments are essential for the model to be suitable for analyzing a new separate dataset. We also show that longitudinal data appear to be more helpful than the time frequency of measurements within a given apartment. We use the resulting RF model to analyze PM 2.5 data of an entirely separate dataset collected from 65 new homes in California. The RF model identifies 442 indoor emission events, with only a few misidentifications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Effect of Initial Structure on Performance of High-Entropy Oxide Anodes for Li-Ion Batteries

Two different high-entropy oxide materials were synthesized and studied as Li-ion battery anodes. The two materials have the same active metal constituents but different inactive elements which result in different initial crystalline structures: rock salt for (MgFeCoNiZn)O and spinel for (TiFeCoNiZn)3O4. Local structural studies of the metal elements in these two materials over extended electrochemical cycling reveal that the redox processes responsible for the electrode capacity are independent of the initial crystallographic structure and that the capacity is solely dependent on the initial random distribution of the metal atoms and the amount of active metals in the starting material.

25 ENERGY STORAGE↗

NASA NTRS1973

A field ionization study of octan-2-one

Electron-impact studies on deuterated aliphatic ketones have demonstrated that partial H/D randomization tends to occur prior to fragmentation. The scope of the studies is extended to include the kinetics and mechanisms of the fragmentation processes induced by field ionization of octan-2-one at very short times within the very high field in the vicinity of the blade emitter and at longer times in the low field regions.

Derrick, P. J.↗

NASA NTRS1975

Frequency stability requirements for two way range rate tracking

Accuracy limitations to two way range rate Doppler tracking due to master (reference) oscillator frequency instabilities are discussed. Theory is developed to treat both the effects of random and nonrandom oscillator instabilities. The nonrandom instabilities treated are drift, environmental effects, and coherent phase modulation. The effects of random instabilities on range rate accuracy are shown to be describable in terms of sigma y (2, T, tau). For the typical noise processes encountered in precision oscillators, range rate error is related to the more familiar sigma y (tau) and script L (f). Three examples are discussed to show how to determine range rate error from given sigma y (tau) or script L (f) curves, and approximations are developed to simplify the treatment of complex systems. An error analysis of range determined from rate data is also given.

Reinhardt, V.↗

NASA NTRS1978

A comparative study of Conroy and Monte Carlo methods applied to multiple quadratures and multiple scattering

An efficient numerical method of multiple quadratures, the Conroy method, is applied to the problem of computing multiple scattering contributions in the radiative transfer through realistic planetary atmospheres. A brief error analysis of the method is given and comparisons are drawn with the more familiar Monte Carlo method. Both methods are stochastic problem-solving models of a physical or mathematical process and utilize the sampling scheme for points distributed over a definite region. In the Monte Carlo scheme the sample points are distributed randomly over the integration region. In the Conroy method, the sample points are distributed systematically, such that the point distribution forms a unique, closed, symmetrical pattern which effectively fills the region of the multidimensional integration. The methods are illustrated by two simple examples: one, of multidimensional integration involving two independent variables, and the other, of computing the second order scattering contribution to the sky radiance.

Deepak, A.↗

NASA NTRS1982

Analysis of backward error recovery for concurrent processes with recovery blocks

Three different methods of implementing recovery blocks (RB's). These are the asynchronous, synchronous, and the pseudo recovery point implementations. Pseudo recovery points so that unbounded rollback may be avoided while maintaining process autonomy are proposed. Probabilistic models for analyzing these three methods under standard assumptions in computer performance analysis, i.e., exponential distributions for related random variables were developed. The interval between two successive recovery lines for asynchronous RB's mean loss in computation power for the synchronized method, and additional overhead and rollback distance in case PRP's are used were estimated.

Shin, K. G.↗

NASA NTRS1988

Creep life prediction based on stochastic model of microstructurally short crack growth

A nondimensional model of microstructurally short crack growth in creep is developed based on a detailed observation of the creep fracture process of 304 stainless steel. In order to deal with the scatter of small crack growth rate data caused by microstructural inhomogeneity, a random variable technique is used in the model. A cumulative probability of the crack length at an arbitary time, G(bar a, bar t), and that of the time when a crack reaches an arbitary length, F(bar t, bar a), are obtained numerically by means of a Monte Carlo method. G(bar a, bar t), and F(bar t, bar a) are the probabilities for a single crack. However, multiple cracks generally initiate on the surface of a smooth specimen from the early stage of creep life to the final stage. TAking into account the multiple crack initiations, the actual crack length distribution observed on the surface of a specimen is predicted by the combination of probabilities for a single crack. The prediction shows a fairly good agreement with the experimental result for creep of 304 stainless steel at 923 K. The probability of creep life is obtained from an assumption that creep fracture takes place when the longest crack reaches a critical length. The observed and predicted scatter of the life is fairly small for the specimens tested.

Kitamura, Takayuki↗

NASA NTRS1988

Atmospheric Electrical Modeling in Support of the NASA F-106 Storm Hazards Project

A recently developed storm electrification model (SEM) is used to investigate the operating environment of the F-106 airplane during the NASA Storm Hazards Project. The model is 2-D, time dependent and uses a bulkwater microphysical parameterization scheme. Electric charges and fields are included, and the model is fully coupled dynamically, microphysically and electrically. One flight showed that a high electric field was developed at the aircraft's operating altitude (28 kft) and that a strong electric field would also be found below 20 kft; however, this low-altitude, high-field region was associated with the presence of small hail, posing a hazard to the aircraft. An operational procedure to increase the frequency of low-altitude lightning strikes was suggested. To further the understanding of lightning within the cloud environment, a parameterization of the lightning process was included in the SEM. It accounted for the initiation, propagation, termination, and charge redistribution associated with an intracloud discharge. Finally, a randomized lightning propagation scheme was developed, and the effects of cloud particles on the initiation of lightning investigated.

Helsdon, John H., Jr.↗

NASA NTRS1989

Creep life prediction based on stochastic model of microstructurally short crack growth

A nondimensional model of microstructurally short crack growth in creep is developed based on a detailed observation of the creep fracture process of 304 stainless steel. In order to deal with the scatter of small crack growth rate data caused by microstructural inhomogeneity, a random variable technique is used in the model. A cumulative probability of the crack length at an arbitrary time, G(bar a, bar t), and that of the time when a crack reaches an arbitrary length, F(bar t, bar a), are obtained numerically by means of a Monte Carlo method. G(bar a, bar t), and F(bar t, bar a) are the probabilities for a single crack. However, multiple cracks generally initiate on the surface of a smooth specimen from the early stage of creep life to the final stage. Taking into account the multiple crack initiations, the actual crack length distribution observed on the surface of a specimen is predicted by the combination of probabilities for a single crack. The prediction shows a fairly good agreement with the experimental result for creep of 304 stainless steel at 923 K. The probability of creep life is obtained from an assumption that creep fracture takes place when the longest crack reaches a critical length. The observed and predicted scatter of the life is fairly small for the specimens tested.

Kitamura, Takayuki↗

NASA NTRS2017

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, approximately 70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

MAIAC AO↗

DOE OSTI2014

Study of Nonlinear Dynamics of Intense Charged Particle Beams in the Paul Trap Simulator Experiment

The Paul Trap Simulator Experiment (PTSX) is a compact laboratory device that simulates the nonlinear dynamics of intense charged particle beams propagating over a large distance in an alternating-gradient magnetic transport system. The radial quadrupole electric eld forces on the charged particles in the Paul Trap are analogous to the radial forces on the charged particles in the quadrupole magnetic transport system. The amplitude of oscillating voltage applied to the cylindrical electrodes in PTSX is equivalent to the quadrupole magnetic eld gradient in accelerators. The temporal periodicity in PTSX corresponds to the spatial periodicity in magnetic transport system. This thesis focuses on investigations of envelope instabilities and collective mode excitations, properties of high-intensity beams with significant space-charge effects, random noise-induced beam degradation and a laser-induced-fluorescence diagnostic. To better understand the nonlinear dynamics of the charged particle beams, it is critical to understand the collective processes of the charged particles. Charged particle beams support a variety of collective modes, among which the quadrupole mode and the dipole mode are of the greatest interest. We used quadrupole and dipole perturbations to excite the quadrupole and dipole mode respectively and study the effects of those collective modes on the charge bunch. The experimental and particle-in-cell (PIC) simulation results both show that when the frequency and the spatial structure of the external perturbation are matched with the corresponding collective mode, that mode will be excited to a large amplitude and resonates strongly with the external perturbation, usually causing expansion of the charge bunch and loss of particles. Machine imperfections are inevitable for accelerator systems, and we use random noise to simulate the effects of machine imperfection on the charged particle beams. The random noise can be Fourier decomposed into various frequency components and experimental results show that when the random noise has a large frequency component that matches a certain collective mode, the mode will also be excited and cause heating of the charge bunch. It is also noted that by rearranging the order of the random noise, the adverse effects of the random noise may be eliminated. As a non-destructive diagnostic method, a laser-induced- fluorescence (LIF) diagnostic is developed to study the transverse dynamics of the charged particle beams. The accompanying barium ion source and dye laser system are developed and tested.

LIF↗

NASA NTRS1982

A unified method for evaluating real-time computer controllers: A case study

A real time control system consists of a synergistic pair, that is, a controlled process and a controller computer. Performance measures for real time controller computers are defined on the basis of the nature of this synergistic pair. A case study of a typical critical controlled process is presented in the context of new performance measures that express the performance of both controlled processes and real time controllers (taken as a unit) on the basis of a single variable: controller response time. Controller response time is a function of current system state, system failure rate, electrical and/or magnetic interference, etc., and is therefore a random variable. Control overhead is expressed as a monotonically nondecreasing function of the response time and the system suffers catastrophic failure, or dynamic failure, if the response time for a control task exceeds the corresponding system hard deadline, if any. A rigorous probabilistic approach is used to estimate the performance measures. The controlled process chosen for study is an aircraft in the final stages of descent, just prior to landing. First, the performance measures for the controller are presented. Secondly, control algorithms for solving the landing problem are discussed and finally the impact of the performance measures on the problem is analyzed.

Shin, K. G.↗

NASA NTRS1985

A unified method for evaluating real-time computer controllers and its application

Shin, K. G.↗

DOE OSTI2014

DEVELOPMENT OF AN ANTIFOAM TRACKING SYSTEM AS AN OPTION TO SUPPORT THE MELTER OFF-GAS FLAMMABILITY CONTROL STRATEGY AT THE DWPF

The Savannah River National Laboratory (SRNL) has been working with the Savannah River Remediation (SRR) Defense Waste Processing Facility (DWPF) in the development and implementation of an additional strategy for confidently satisfying the flammability controls for DWPF’s melter operation. An initial strategy for implementing the operational constraints associated with flammability control in DWPF was based upon an analytically determined carbon concentration from antifoam. Due to the conservative error structure associated with the analytical approach, its implementation has significantly reduced the operating window for processing and has led to recurrent Slurry Mix Evaporator (SME) and Melter Feed Tank (MFT) remediation. To address the adverse operating impact of the current implementation strategy, SRR issued a Technical Task Request (TTR) to SRNL requesting the development and documentation of an alternate strategy for evaluating the carbon contribution from antifoam. The proposed strategy presented in this report was developed under the guidance of a Task Technical and Quality Assurance Plan (TTQAP) and involves calculating the carbon concentration from antifoam based upon the actual mass of antifoam added to the process assuming 100% retention. The mass of antifoam in the Additive Mix Feed Tank (AMFT), in the Sludge Receipt and Adjustment Tank (SRAT), and in the SME is tracked by mass balance as part of this strategy. As these quantities are monitored, the random and bias uncertainties affecting their values are also maintained and accounted for. This report documents: 1) the development of an alternate implementation strategy and associated equations describing the carbon concentration from antifoam in each SME batch derived from the actual amount of antifoam introduced into the AMFT, SRAT, and SME during the processing of the batch. 2) the equations and error structure for incorporating the proposed strategy into melter off-gas flammability assessments. Sample calculations of the system are also included in this report. Please note that the system developed and documented in this report is intended as an alternative to the current, analytically-driven system being utilized by DWPF; the proposed system is not intended to eliminate the current system. Also note that the system developed in this report to track antifoam mass in the AMFT, SRAT, and SME will be applicable beyond just Sludge Batch 8. While the model used to determine acceptability of the SME product with respect to melter off-gas flammability controls must be reassessed for each change in sludge batch, the antifoam mass tracking methodology is independent of sludge batch composition and as such will be transferable to future sludge batches.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Efficient computation of N -point correlation functions in D dimensions

We present efficient algorithms for computing the N-point correlation functions (NPCFs) of random fields in arbitrary D-dimensional homogeneous and isotropic spaces. Such statistics appear throughout the physical sciences and provide a natural tool to describe stochastic processes. Typically, algorithms for computing the NPCF components have $\mathscr O$(n N ) complexity (for a dataset containing n particles); their application is thus computationally infeasible unless N is small. By projecting the statistic onto a suitably defined angular basis, we show that the estimators can be written in a separable form, with complexity $\mathscr O$(n 2 ) or $\mathscr O$(n g log n g ) if evaluated using a Fast Fourier Transform on a grid of size n g . Our decomposition is built upon the D-dimensional hyperspherical harmonics; these form a complete basis on the (D – 1) sphere and are intrinsically related to angular momentum operators. Concatenation of (N – 1) such harmonics gives states of definite combined angular momentum, forming a natural separable basis for the NPCF. As N and D grow, the number of basis components quickly becomes large, providing a practical limitation to this (and all other) approaches: However, the dimensionality is greatly reduced in the presence of symmetries; for example, isotropic correlation functions require only states of zero combined angular momentum. We provide a Julia package implementing our estimators and show how they can be applied to a variety of scenarios within cosmology and fluid dynamics. The efficiency of such estimators will allow higher-order correlators to become a standard tool in the analysis of random fields.

97 MATHEMATICS AND COMPUTING↗