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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

System Study: High-Pressure Coolant Injection 1998-2022

This report presents an unreliability evaluation of the high-pressure coolant injection (HPCI) system at 22 U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCI results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

System Study: High-Pressure Coolant Injection 1998-2020

This report presents an unreliability evaluation of the high-pressure coolant injection system (HPCI) at 25 U.S. commercial boiling water reactors. Demand, run hour, and failure data from 1998–2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCI results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

System Study: High-Pressure Core Spray 1998-2020

This report presents an unreliability evaluation of the high-pressure core spray (HPCS) at eight U.S. commercial boiling water reactors. Demand, run hour, and failure data from 1998–2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCS results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

System Study: High-Pressure Safety Injection 1998-2020

This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 69 U.S. commercial nuclear reactors. Demand, run hours, and failure data from calendar years 1998–2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPSI results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

System Study: Isolation Condenser 1998-2020

This report presents an unreliability evaluation of the isolation condenser (ISO) system at four U.S. boiling water reactors. Demand, run hours, and failure data from calendar year 1998 through 2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the ISO results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

System Study: Reactor Core Isolation Cooling 1998-2020

This report presents an unreliability evaluation of the reactor core isolation cooling (RCIC) system at 31 U.S. commercial boiling water reactors. Demand, run hours, and failure data from calendar years 1998 through 2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the RCIC results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

System Study: Residual Heat Removal 1998-2020

This report presents an unreliability evaluation of the residual heat removal (RHR) system in two modes of operation (low-pressure injection in response to a large loss-of-coolant accident and in response to post-trip shutdown cooling) at 104 U.S. commercial nuclear reactors. Demand, run hour, and failure data from 1998–2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the RHR results.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Enhanced Component Performance Study: Motor Driven Pumps 1998–2022

This report presents an enhanced performance evaluation of motor-driven pumps (MDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2022 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR=1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trends were identified for MDPs for the most recent 10-year period: (1) Standby MDP frequency of start demands (demands per reactor year), (2) Standby MDP frequency of FTR=1H hours (hours per reactor year), (3) Standby MDP frequency of FTR>1H hours, and (4) Normally running MDP frequency of run hours. The following decreasing trends were identified for MDPs for the most recent 10-year period: (1) Standby MDP FTR=1H failure probability, (2) Normally running MDP FTR failure rate, (3) Standby MDP unavailability, (4) Standby MDP total unreliability (8-hour mission), and (5) Normally running MDP total unreliability (8-hour mission).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

System Study: Reactor Core Isolation Cooling 1998-2024

This report presents an unreliability evaluation of the reactor core isolation cooling (RCIC) system at 28 U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from calendar years 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period and yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the RCIC results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

System Study: High-Pressure Coolant Injection 1998-2024

This report presents an unreliability evaluation of the high-pressure coolant injection (HPCI) system at 22 U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period and yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCI results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

System Study: High-Pressure Core Spray 1998-2024

This report presents an unreliability evaluation of the high-pressure core spray (HPCS) at eight U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period and yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCS results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A catalogue of white dwarfs in Gaia EDR3

ABSTRACT We present a catalogue of white dwarf candidates selected from Gaia Early Data Release 3 (EDR3). We applied several selection criteria in absolute magnitude, colour, and Gaia quality flags to remove objects with unreliable measurements while preserving most stars compatible with the white dwarf locus in the Hertzsprung–Russell diagram. We then used a sample of over 30 000 spectroscopically confirmed white dwarfs and contaminants from the Sloan Digital Sky Survey (SDSS) to map the distribution of these objects in the Gaia absolute magnitude–colour space. Finally, we adopt the same method presented in our previous work on Gaia Data Release 2 (DR2) to calculate a probability of being a white dwarf (PWD) for ≃1.3 million sources that passed our quality selection. The PWD values can be used to select a sample of ${\simeq} 359\,000$ high-confidence white dwarf candidates. We calculated stellar parameters (effective temperature, surface gravity, and mass) for all these stars by fitting Gaia astrometry and photometry with synthetic pure-H, pure-He, and mixed H–He atmospheric models. We estimate an upper limit of 93 per cent for the overall completeness of our catalogue for white dwarfs with G ≤ 20 mag and effective temperature (Teff) > 7000 K, at high Galactic latitudes (|b| > 20°). Alongside the main catalogue we include a reduced proper motion extension containing ${\simeq} 10\,200$ white dwarf candidates with unreliable parallax measurements that could, however, be identified on the basis of their proper motion. We also performed a cross-match of our catalogues with SDSS Data Release 16 (DR16) spectroscopy and provide spectral classification based on visual inspection for all resulting matches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Enhanced Component Performance Study: Turbine-Driven Pumps 1998-2020

This report presents an enhanced performance evaluation of turbine-driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The TDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR≤1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. No increasing trends were identified for TDPs for the most recent 10-year period: The following decreasing trends were identified for TDPs for the most recent 10-year period: • Standby TDP FTR>1H failure rate • Standby TDP unavailability • Standby MDP total unreliability (8-hour mission) • Standby TDP frequency of FTR>1H events (failures per reactor year) • Normally running TDP frequency of start demands (demands per reactor year) • Normally running TDP frequency of run hours (hours per reactor year).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Enhanced Component Performance Study: Motor-Driven Pumps 1998-2020

This report presents an enhanced performance evaluation of motor-driven pumps (MDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR≤1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP frequency of start demands (demands per reactor year) • Standby MDP frequency of FTR≤1H hours (hours per reactor year) • Standby MDP frequency of FTR>1H hours • Normally running MDP frequency of run hours. The following decreasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP FTR≤1H failure probability • Normally running MDP FTR failure rate • Standby MDP unavailability • Normally running MDP total unreliability (8-hour mission) • Standby MDP frequency of FTR≤1H events (failures per reactor year) • Normally running MDP frequency of FTR events.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Enhanced Component Performance Study: Turbine Driven Pumps 1998–2022

This report presents an enhanced performance evaluation of turbine driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2022 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The TDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR=1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10 year period while yearly estimates for reliability are provided for the entire study period. No increasing trends were identified for TDPs for the most recent 10 year period: The following decreasing trends were identified for TDPs for the most recent 10 year period: • Standby TDP FTR>1H failure rate • Normally running TDP FTR failure rate • Standby TDP unavailability • Standby MDP total unreliability (8-hour mission) • Standby TDP frequency of start demands (demands per reactor year) • Standby TDP frequency of FTR=1H hours (hours per reactor year) • Standby TDP frequency of FTR>1H events (failures per reactor year) • Normally running TDP frequency of start demands • Normally running TDP frequency of run hours • Normally running TDP frequency of FTR events.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Advanced Semi-Supervised Learning with Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Advanced Semi-Supervised Learning With Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay

Despite state-of-the-art technologies like artificial intelligence, human judgment is critically essential in cooperative systems, such as the multi-agent system (MAS), which collect information among agents based on multiple-cue judgment. Human agents can prevent impaired situational awareness of automated agents by confirming situations under environmental uncertainty. System error caused by uncertainty can result in an unreliable system environment, and this environment affects the human agent, resulting in non-optimal decision-making in MAS. Thus, it is necessary to know how human behavior is changed to capture system reliability under uncertainty. Another issue affecting MAS is time delay, which can delay agent information transfer, resulting in low performance and instability. However, it is difficult to find studies on the influence of time delay on human agents. This study is about understanding the human decision-making process under a specific system reliability environment by uncertainty with time delay. We used concepts of expected and unexpected uncertainty to implement reliability of the system usage environment with three types of time delay conditions: no time delay, regular time delay, and irregular time delay conditions. We used electroencephalogram (EEG) for human cognitive neural mechanisms in multiple-cue judgment systems to understand human decision-making. In the reliability of system usage environment, the unreliable system environment significantly creates less memory load by less utilization of system rules for decision-making. In terms of time delay, delayed information delivery does not significantly affect memory load for decision-making.

cognitive process↗