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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Measuring orbit responses with oscillating trajectories in the Fermilab Linac

Recording changes in beam transverse positions and longitudinal phase reported by Beam Position Monitors (BPMs) in response to a beam deflection by an upstream dipole corrector or RF cavity phase (orbit response) is a powerful tool for analysis of accelerator optics and assisting with machine tuning. In Fermilab Linac, orbit responses were recorded by oscillating the corrector currents and cavity phases in a sinusoidal manner parasitically during regular operation, simultaneously oscillating up to 19 correctors and 7 cavities at distinct frequencies, providing faster, drift-resistant measurements through frequency-domain analysis. This report describes the technique, including error estimations and consistency checks and shows examples of the measurements.

Shemyakin, Alexander [Fermilab] (ORCID:00000001501↗
DOE OSTI2021

Extracting Material Property Measurement Data from Scientific Articles

Machine learning-based prediction of material properties is often hampered by the lack of sufficiently large training datasets. The majority of such measurement data is embedded in scientific literature and the ability to automatically extract these data is essential to support the development of reliable property prediction methods. In this work, we describe a methodology for an automatic property extraction framework using material solubility as the target property. We create an annotated dataset containing tags for solubility-related entities using a combination of regular expressions and manual tagging. We then compare five entity recognition models leveraging both token-level and span-level architectures on the task of classifying solute names, solubility values, and solubility units. Additionally, we explore a novel pretraining approach that leverages automated chemical name and quantity extraction tools to generate large datasets that do not rely on intensive manual effort. Finally, we perform an analysis to identify the causes of classification errors.

Panapitiya, Gihan U.↗
DOE OSTI2016

Analysis of Loss-of-Offsite-Power Events 1997-2015

Loss of offsite power (LOOP) can have a major negative impact on a power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience during calendar years 1997 through 2015. LOOP events during critical operation that do not result in a reactor trip, are not included. Frequencies and durations were determined for four event categories: plant-centered, switchyard-centered, grid-related, and weather-related. Emergency diesel generator reliability is also considered (failure to start, failure to load and run, and failure to run more than 1 hour). There is an adverse trend in LOOP durations. The previously reported adverse trend in LOOP frequency was not statistically significant for 2006-2015. Grid-related LOOPs happen predominantly in the summer. Switchyard-centered LOOPs happen predominantly in winter and spring. Plant-centered and weather-related LOOPs do not show statistically significant seasonality. The engineering analysis of LOOP data shows that human errors have been much less frequent since 1997 than in the 1986 -1996 time period.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Analysis of Loss-of-Offsite-Power Events: 1987-2016

Loss of offsite power (LOOP) can have a major negative impact on a power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience during calendar years 1987 through 2016. LOOP events during critical operation that do not result in a reactor trip are not included. Frequencies and durations were determined for four event categories: plant-centered, switchyard-centered, grid-related, and weather-related. Emergency diesel generator reliability is also considered (failure to start, failure to load and run, and failure to run more than 1 hour). An adverse trend in overall LOOP frequency is identified. An adverse trend in LOOP durations is identified. Plant-centered and weather-related LOOP events do not show statistically significant seasonality. The engineering analysis of LOOP data shows that human errors have been much less frequent since 1997 than in the 1986–1996 time period.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Analysis of Loss-of-Offsite-Power Events 1987-2018

Loss of offsite power (LOOP) can have a major negative impact on a power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience during calendar years 1987 through 2018. LOOP events during critical operation that do not result in a reactor trip are not included. Frequencies and durations were determined for four event categories: plant-centered, switchyard-centered, grid-related, and weather-related. No significant trends in critical operation LOOP frequencies over the most recent 10-year period are identified. Adverse trends in LOOP durations are identified for switchyard-centered and grid-related LOOPs, as well as overall LOOPs during critical operation and overall LOOPs during shutdown operation. Both grid-related and weather-related LOOP events are found to show statistically significant seasonality. The engineering analysis of LOOP data shows that human errors have been much less frequent since 1997 than in the 1987–1996 time period.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Exactly and Easily Applying Experimental Boundary Conditions in Computational Structural Dynamics

Most experimental setups and environment specifications define acceleration loads on the component. However, Sierra Structural Dynamics cannot apply acceleration boundary conditions in modal transient analysis. Modal analysis of these systems and environments must be done through the application of a huge artificial force to a large fictitious point mass. Introducing a large mass into the analysis is a common source of numerical error. In this report we detail a mathematical procedure to directly apply acceleration boundary conditions in modal analyses without the requirement of adding a non-physical mass to the system. We prototype and demonstrate this procedure in Matlab and scope the work required to integrate this procedure into Sierra Structural Dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

“Shoulda, Coulda, Woulda”: Conceptualizing the Differences in Trust Between Human-Human Teaming and Human-Machine Teaming

Intelligent decision support systems (IDSSs) are machine teammates designed to facilitate better human decision-making in high-consequence domains such as health care, power grid operations, and fraud detection. IDSSs identify patterns in datasets and provide intelligent decision-making recommendations to human teammates. However, previous research indicates that humans often trust IDSS recommendations less than the recommendations from their human teammates, even when the machine teammate is more accurate. To conceptualize why trust differs, we review the literature surrounding trust, error, and predictability. Then, we compile and compare participant trust ratings and decision-making in an abridged systematic review of previous studies manipulating teammate type, error rate, and error type. Finally, we conduct a content analysis of participants’ qualitative responses to trust queries from a survey on generative language models. Results suggest that humans may trust IDSS teammates less than other human teammates because of differences in (1) interaction complexity, (2) blame attribution, and (3) swift trust. We conclude that human factors practitioners should collaborate with data scientists and domain experts to build and maintain trust in IDSSs by anthropomorphizing algorithms, matching mental models, and considering individual differences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Measuring Orbit Responses with Oscillating Trajectories in the Fermilab Linac

Recording changes in beam transverse positions re-ported by Beam Position Monitors (BPMs) in response to a beam deflection by an upstream dipole corrector (orbit response) is a powerful tool for analysis of accelerator optics and assisting with machine tuning. In the Fermilab Linac, orbit responses are recorded by oscillating the currents of up to 19 correctors, providing faster, drift-resistant measurements through frequency-domain analysis. This report describes the technique, including error estimations and consistency checks and shows an example of the measurements.

Shemyakin, Alexander V. [Fermilab] (ORCID:00000001↗
DOE OSTI2022

Intracardiac Electrical Imaging using the 12-lead ECG: A Machine Learning Approach using Synthetic Data

Current state-of-the-art techniques for non-invasive imaging of cardiac electrical phenomena require voltage recordings from dozens of different torso locations and anatomical models built from expensive medical diagnostic imaging procedures. Here this study aimed to assess if recent machine learning advances could alternatively reconstruct electroanatomical maps at clinically relevant resolutions using only the standard 12-lead electrocardiogram (ECG) as input. To that end, a computational study was conducted to generate a dataset of over 16000 detailed cardiac simulations, which was then used to train neural network (NN) architectures designed to exploit both spatial and temporal correlations in the ECG signal. Analysis over a validation set showed average errors in activation map reconstruction below 1.7 msec over 75 intracardiac locations. Furthermore, phenotypical patterns of activation and the morphology of the activation potential were correctly reconstructed. The approach offers opportunities to stratify patients non-invasively, both retrospectively and prospectively, using metrics otherwise only available through invasive clinical procedures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Modeling Toolkit for Comparing AC and DC Electrical Distribution Efficiency in Buildings

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.

DC distribution↗
DOE OSTI2016

Minimizing Grating Slope Errors in the IEX Monochromato at the Advanced Photon Source

The IEX beamline at the APS is currently in the commissioning phase. The energy resolution of the beamline was not meeting original specifications by several orders of magnitude. The monochromator, an in-focus VLS-PGM, is currently configured with a high and a medium-line-density grating. Experimental results indicated that both gratings were contributing to the poor energy resolution and this led to venting the monochromator to investigate. The initial suspicion was that a systematic error had occurred in the ruling process on the VLS gratings, but that proved to not be the case. Instead the problem was isolated to mechanical constraints used to mount the gratings into their respective side-cooled holders. Modifications were made to the holders to eliminate problematic constraints without compromising the rest of the design. Metrology performed on the gratings in the original and modified holders demonstrated a 20-fold improvement in the surface profile error which was consistent with finite element analysis performed in support of the modifications. Two gratings were successfully reinstalled and subsequent measurements with beam show a dramatic improvement in energy resolution.

Fisher, M. V.↗
DOE OSTI2015

Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

14 SOLAR ENERGY↗
DOE OSTI2024

SNL Human Reliability Analysis (Capstone Final Report)

Sandia National Laboratories (SNL) requested a measure of possible human error for each state verification method for a safety mechanism performed at partnering production agencies. A team of three human factors individuals were tasked with conducting observations during site visits of both production agencies in order to complete a Human Reliability Analysis (HRA). A HRA will be used because it provides both qualitative and quantitative reports of human error. This report is the first phase of that effort, which will describe the methods which occur at one of the production agencies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Comparative Study of Finite Element Methods Using the Time-Accuracy-Size(TAS) Spectrum Analysis

We present a performance analysis appropriate for comparing algorithms using different numerical discretizations. By taking into account the total time-to-solution, numerical accuracy with respect to an error norm, and the computation rate, a cost-benefit analysis can be performed to determine which algorithm and discretization are particularly suited for an application. This work extends the performance spectrum model in for interpretation of hardware and algorithmic tradeoffs in numerical PDE simulation. As a proof-of-concept, popular finite element software packages are used to illustrate this analysis for Poisson’s equation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Analyzing a Five-Year Failure Record of a Leadership-Class Supercomputer

Extreme-scale computing systems are required to solve some of the grand challenges in science and technology. From astrophysics to molecular biology, supercomputers are an essential tool to accelerate scientific discovery. However, large computing systems are prone to failures due to their complexity. It is crucial to develop an understanding of how these systems fail to design reliable supercomputing platforms for the future. This paper examines a five-year failure and workload record of a leadership-class supercomputer. To the best of our knowledge, five years represents the vast majority of the lifespan of a supercomputer. This is the first time such analysis is performed on a top 10 modern supercomputer. We performed a failure categorization and found out that: i) most errors are GPU-related, with roughly 37% of them being double-bit errors on the cards; ii) failures are not evenly spread across the physical machine, with room temperature presumably playing a major role; and iii) software errors of the system bring down several nodes concurrently. Our failure rate analysis unveils that: i) the system consistently degrades, being at least twice as reliable at the beginning, compared to the end of the period; ii) Weibull distribution closely fits the mean-time-between-failure data; and iii) hardware and software errors show a markedly different pattern. Finally, we correlated failure and workload records to reveal that: i) failure and workload records are weakly correlated, except for certain types of failures when segmented by the hours of the day; ii) several categories of failures make jobs crash within the first minutes of execution; and iii) a significant fraction of failed jobs exhaust the requested time with a disregard of when the failure occurred during execution.

Rojas, Elvis↗
DOE OSTI2024

Estimating the Contributions to Human Error Probability from the Convolution of the Distribution of Time Available and Time Required

As part of their duties, Human Reliability Analysis must often evaluate if crews in nuclear power plants (NPPs) can complete tasks associated with a human-failure event within time limits. For example, the time required in NPP scenarios is determined by systematic and structured walkthroughs, feasibility studies, recorded times from training exercises, and interviews with experienced operators and experts. Typically, a point estimate is derived for the estimate (mean, maximum, or 95th percentile of time required). Using point-estimate values can mask the risk associated with variability among crews, plant conditions and set-up, environmental conditions, and other impact factors under which these actions are executed. While point estimates for time required and time available have served the industry well, without considering the uncertainty they could lead to biased understanding about the risk. The Integrated Human Event Analysis System - General Methodology (IDHEAS-G) model (developed by the US Nuclear Regulatory Commission, NRC) for human error probability calculates human error probability by summing two probabilities: insufficient time and cognitive error. As such, the model takes a more holistic approach by considering the full distributions for time required and time available to calculate the human error probability because the time available to complete the task is insufficient. In this study, we expand on the work of the NRC and discuss methods for estimating these time considerations. For example, for the time required, the impact of Performance Influencing Factors (PIFs) on the distribution was divided into impacts that are aleatory in nature, such as crew-to-crew variability, and those that are epistemic (i.e., the PIFs). Starting with the factors that introduce aleatory uncertainty, a first-order distribution was developed from a large set of time required (i.e., NPP task completion times) data for the range of operator actions that occur in the NPP control room under simulated accident conditions. The first-order distribution can then be adjusted to account for epistemic uncertainty using research associated with the impact of applicable PIFs on the time required. We also develop guidance for analysts to address the probability distributions for the time available. The guidance we developed on how to estimate time required and time available distributions is based on the identification of pertinent research and data, data analyses, and expert knowledge elicitation.

human error probability, human performance, time e↗
DOE OSTI2025

Getting brighter: Impacts of improved day-ahead solar forecasts in high-solar, high-storage electricity systems

This paper analyzes the impacts of improved day-ahead solar forecasts on costs and dispatch in the solar-rich Southeast U.S. It uses an optimized high-solar, high-storage resource portfolio in which solar generation capacity accounts for 45 % of total installed capacity (34 %–36 % of generation) and energy storage capacity (43 GW) is equivalent to 33 % of peak demand. In a base scenario, improved day-ahead solar forecasts reduce production costs by $\$87$ million per year ($\$0.13$ per MWh load, $2023$$). This level of savings is within the range or lower than earlier studies of solar forecast improvements at lower levels of solar generation (<25 % of total generation). In this study, solar expansion was accompanied by two important sources of flexibility for managing solar forecast error: energy storage and day-ahead solar curtailment. Furthermore, the analysis finds that regional coordination complements day-ahead solar forecast improvements while natural gas commitment flexibility is a substitute for forecast improvements, as the improved solar forecast leads to sub-optimal commitment of thermal units. Day-ahead solar forecast improvements reduce reserves required to manage forecast error by 30 %. Fewer reserves to manage large, infrequent solar forecast errors could be an important benefit of improved solar forecasts.

14 SOLAR ENERGY↗
DOE OSTI2013

An Evaluation of Departmental Radiation Oncology Incident Reports: Anticipating a National Reporting System

Purpose: Systems to ensure patient safety are of critical importance. The electronic incident reporting systems (IRS) of 2 large academic radiation oncology departments were evaluated for events that may be suitable for submission to a national reporting system (NRS). Methods and Materials: All events recorded in the combined IRS were evaluated from 2007 through 2010. Incidents were graded for potential severity using the validated French Nuclear Safety Authority (ASN) 5-point scale. These incidents were categorized into 7 groups: (1) human error, (2) software error, (3) hardware error, (4) error in communication between 2 humans, (5) error at the human-software interface, (6) error at the software-hardware interface, and (7) error at the human-hardware interface. Results: Between the 2 systems, 4407 incidents were reported. Of these events, 1507 (34%) were considered to have the potential for clinical consequences. Of these 1507 events, 149 (10%) were rated as having a potential severity of ≥2. Of these 149 events, the committee determined that 79 (53%) of these events would be submittable to a NRS of which the majority was related to human error or to the human-software interface. Conclusions: A significant number of incidents were identified in this analysis. The majority of events in this study were related to human error and to the human-software interface, further supporting the need for a NRS to facilitate field-wide learning and system improvement.

62 RADIOLOGY AND NUCLEAR MEDICINE↗