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NASA NTRS2020

MSL Telecom Automated Anomaly Detection

The Mars Science Laboratory (MSL) Telecom Operations Team at the Jet Propulsion Laboratory (JPL) has implemented a machine learning system in order to automate the anomaly detection process as a part of daily operations. Machine learning enables reliable detection of anomalies in Telecom-related telemetry and automated reporting of Telecom subsystem status, resulting in an 90% reduction in team workload and improved anomaly detection reliability. At present, machine learning methods are used to detect: 1. Anomalous long-term trends in telemetry data 2. Anomalous time-domain evolution of telemetry values Both types of anomalies pose their own unique challenges that are addressed in different ways. In the first case, long term trending of daily minima, maximum, and mean telemetry values in temperatures, currents, voltages, and radio frequency (RF) power levels is used in addition to hard threshold safety checks to look for changes in long-term equipment health and performance. Long-term trending methods allow for ordinary seasonal variations in these quantities caused by temperature changes over the course of the Martian year while allowing operators to determine whether current performance remains in line with historical values from previous years. Changes in long-term trends can provide important insights into the health and status of the rover's on-board systems as well as valuable early warning if subtle degradation begins to take hold. But while trending of daily statistics is valuable, it does not detect anomalies in the short-term time evolution of data over the course of minutes or hours during a day, and this task is handled with short-term shape analysis. Principal components analysis (PCA) has been found to provide robust detection of short-term anomalies, and several examples of the use of PCA to detect actual anomalous events will be provided here. In using PCA, we use both the percentage of explained variance and also a log likelihood test on the PCA expansion coefficients to flag telemetry data for human review. Previous work in the field of spacecraft anomaly detection includes [1] for MSL and [2] for some other JPL missions.

Mukai, Ryan↗

DOE OSTI2023

Enhanced Component Performance Study: Motor Operated Valves 1998–2022

This report presents an enhanced performance evaluation of motor-operated valves (MOVs) 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 MOV failure modes considered are fail to open or close (FTOC), fail to operate or control (FTOP), and spurious operation (SO). 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 trend was identified for MOVs for the most recent 10-year period: • Low-demand MOV frequency of FTOC demands (demands per reactor year). The following decreasing trends were identified for MOVs for the most recent 10-year period: • Low-demand MOV FTOC failure probability • Low-demand MOV frequency of FTOC events (failures per reactor year).

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1986

Space station Ada runtime support for nested atomic transactions

The Space Station Data Management System (DMS), associated computing subsystems, and applications have varying degrees of reliability associated with their operation. A model has been developed (McKay '86) which allows the DMS runtime environment to appear as an Ada virtual machine to applications executing within it. This model is modular, flexible, and dynamically configurable to allow for evolution and growth over time. Support for Fault-tolerant computing is included within this model. The basic primitive involved in this support is based on atomic actions (Grey '78). An atomic action possesses two fundamental properties: (1) it is indivisible with respect to concurrent actions, and (2) it is indivisible with respect to failure. A transaction is a collection of atomic actions which collectively appear to be one action. Transactions may be nested, providing even more powerful support for reliability. A proposed approach is described for providing support for nested atomic transactions within the Ada runtime model developed for the Space Station environment. The level of support is modular, flexible and dynamically configurable just like the overall runtime support environment.

Monteiro, Edward J.↗

DOE OSTI2022

Enhanced Component Performance Study: Motor-Operated Valves 1998-2020

This report presents an enhanced performance evaluation of motor-operated valves (MOVs) 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 MOV failure modes considered are fail to open or close (FTOC), fail to operate or control (FTOP), and spurious operation (SO). 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 trend was identified for MOVs for the most recent 10-year period: • Low-demand MOV frequency of FTOC demands (demands per reactor year). The following increasing trends were identified for MOVs for the most recent 10-year period: • Low-demand MOV FTOC failure probability • Low-demand MOV frequency of FTOC events (failures per reactor year).

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2007

Propulsion Controls and Diagnostics Research at NASA Glenn Research Center

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. Also the propulsion systems required to enable the National Aeronautics and Space Administration (NASA) Vision for Space Exploration in an affordable manner will need to have high reliability, safety and autonomous operation capability. The Controls and Dynamics Branch (CDB) at NASA Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. This paper describes the current activities of the CDB under the NASA Aeronautics Research and Exploration Systems Missions. The programmatic structure of the CDB activities is described along with a brief overview of each of the CDB tasks including research objectives, technical challenges, and recent accomplishments. These tasks include active control of propulsion system components, intelligent propulsion diagnostics and control for reliable fault identification and accommodation, distributed engine control, and investigations into unsteady propulsion systems.

Garg, Sanjay↗

DOE OSTI2019

An Introduction to Grid Services: Concepts, Technical Requirements, and Provision from Wind

As the role of wind energy grows in the U.S. power grid, there is increased interest and requirements for it to provide 'essential reliability' services (historically often referred to as 'ancillary' services). These services are critical to maintaining the reliability and stability of the grid, and historically were provided by large 'synchronous' generators, mainly fossil-fueled and hydroelectric generators. To help evaluate the potential role of wind in providing these services, this report provides an overview of services provided to the grid, including their technical requirements, quantities currently procured, and some estimates of costs. The report also summarizes the technical and regulatory issues around wind providing these services.

17 WIND ENERGY↗

DOE OSTI2019

An Introduction to Grid Services: Concepts, Technical Requirements, and Provision from Wind

17 WIND ENERGY↗

DOE OSTI2023

Enhanced Component Performance Study: Air Operated Valves 1998–2022

This report presents an enhanced performance evaluation of air operated valves (AOVs) 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 AOV failure modes considered are fail to open or close (FTOC), fail to operate or control (FTOP), and spurious operation (SO). 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 AOVs for the most recent 10 year period: • Low demand AOV frequency of FTOC demands (demands per reactor year) • High demand AOV frequency of FTOC demands. The following decreasing trends were identified for AOVs for the most recent 10 year period: • Low demand AOV FTOC failure probability • Low demand AOV FTOP failure rate • Low demand AOV frequency of FTOC events (failures per reactor year) • Low demand AOV frequency of FTOP events.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Evaluation of Concentrated Piperazine for CO 2 Capture from Coal-Fired Flue Gas (Final Report, REV0)

Concentrated piperazine (PZ) is a novel solvent being developed by the University of Texas at Austin (UT) for CO 2 capture from coal-fired power plants. The high thermal stability of PZ permits solvent regeneration at higher temperature (150 °C) and pressure, reducing compression capital and operating costs. The purpose of Cooperative Agreement DE-FE0005654, Evaluation of Concentrated Piperazine for CO 2 Capture from Coal-Fired Flue Gas , was to gain operational experience using PZ solvent to absorb CO 2 and explore novel, high-temperature processes for solvent regeneration. The pilot-scale test campaigns funded under this project have resulted in the continual improvement in the heat duty of the regeneration systems and solvent and equipment optimization. This document summarizes the results from the Phase 1 (2011, 2013 and 2015) and Phase 2 (2018) test campaigns. In Phase 1, the campaign was conducted on synthetic flue gas at the University of Texas’ Separations Research Program (SRP) facility to investigate CO 2 capture with 5 and 8 molal (5$m$ and 8$m$) PZ and two-stage flash (2SF) and advanced flash stripper (AFS) regeneration designs. Phase 1 testing also investigated techniques for measuring amine aerosol that can be generated during operation, and the effect of absorber operating conditions and sulfur containing compounds in the flue gas on aerosol generation. This testing showed that the AFS represents an optimized amine regeneration system with superior energy performance and simple operability over the 2SF or a simple stripper (SS), that 5$m$ PZ provides an economic and operability advantage over 8$m$ PZ, and that phase doppler interferometry (PDI) can provide useful particle size information on amine aerosol. In Phase 2, the campaign was conducted on coal-fired flue gas at the National Carbon Capture Center (NCCC) to investigate CO 2 capture with 5$m$ PZ and the AFS. The PZ solvent was also used with an existing SS at the NCCC to provide comparison with the AFS performance. Additionally, the campaign investigated the effect of flue gas SO 3 on amine aerosol from the CO 2 absorber. The NCCC pilot plant testing demonstrated the robustness of the PZ solvent and the high energy performance of the AFS provided significant improvements in energy performance over the conventional SS for PZ and other solvents, and approached the DOE’s economic targets for second generation carbon capture technologies. Extended testing allowed the project team to demonstrate reliable long-term operation of this novel regeneration technology and solvent combination. EPRI, Luminant, B&W, LG&E, Chevron, Southern Company, and UT are project co-funders. UT and Trimeric were project team members. URS Group was the prime contractor.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Wireless Sensor Modalities at a Nuclear Plant Site to Collect Vibration Data

One of the major contributors to the total operating costs of domestic nuclear fleet of reactors today is the operation and maintenance (O&M) costs. These include labor-intense preventive maintenance programs involving manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets at periodic frequency, irrespective of their conditions. This has resulted in a labor-centric business model to achieve high capacity factors. To build an optimal maintenance program, it’s time to transition from this labor-centric business model to a technology-centric business model. Fortunately, there are technologies (advanced sensor, data analytics, and risk assessment methodologies) that will support this transition. The technology-centric business model will result in significant plant life extension and reduction of time-based maintenance activities. This will drive down O&M costs as labor is a rising cost and technology is a declining cost. This approach will lay the foundation for real-time condition assessment of plant assets, allowing condition-based maintenance to enhance plant safety, reliability, and economics of operation. The goal of this project is to address challenges in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and science-based data analytic capabilities to advance online monitoring and predictive maintenance in nuclear plants to improve plant performance (efficiency gain and economic competitiveness). To achieve the project goal, in partnership with Exelon Generating Company (Exelon), researchers from Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) are performing research and development (R&D) to demonstrate application of wireless sensors using the distributed antenna system and advanced data analytics to achieve predictive maintenance. In the report, wireless vibration sensors, vibration data and its indicator are described. The wireless vibration sensors presented in this report support three types of wireless communication, namely, Wi-Fi, cellular, and 900 MHz. These wireless vibration sensors are considered by partner plant site for installation on plant asset to enable online vibration monitoring to replace periodic measurements. These vibration data along with other plant process data will be utilized to develop diagnostic and prognostic models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Validation of Microgrid Algorithms using At-Scale Simulation and Emulation Real-Time (ASSERT) Framework

This paper presents a novel framework for validating microgrid algorithms using a At-Scale Simulation and Emulation Real-Time (ASSERT) setup. The proposed universal microgrid validation framework was developed at Advanced Research on Integrated Energy Systems (ARIES) platform at National Renewable Energy Laboratory in Golden, Colorado, USA. As the number of intercommunicating devices grow in power systems, along with more integration of inverter-based resources, developing and validating microgrid operation and control algorithms is becoming complex and time-consuming task. The ASSERT framework is designed to provide a comprehensive, accurate, and efficient solution for validating microgrid algorithms. It combines at-scale simulations and real-time emulation to create a virtual environment that closely mimics the behavior of a physical microgrids which are characteristic of future smart distribution systems, such as: (1) increasing variability in the physical size of new energy technologies; (2) requiring control large numbers of interconnected devices, and (3) integrating diverse technologies that have not previously worked together. The paper describes the technical details of the ASSERT framework, its validation process, and its benefits over traditional validation methods. The framework's ability to validate the performance of various algorithms is demonstrated through a case study, which shows that it can effectively identify the weaknesses of an algorithm and optimize its performance. Overall, the ASSERT framework is a promising tool that can significantly enhance the development and validation of microgrid algorithms, leading to more reliable and efficient microgrid operation.

at-scale↗

DOE OSTI2025

Numerical Analysis of High-Order Modes in SRF Resonators for Particle Accelerators

Over the past decades, superconducting technology has rapidly evolved towards high accelerating gradients and low surface resistance, making it possible to operate particle accelerators with high average beam currents and large duty factors. However, RF losses due to coherent excitation of the HOM become the limiting factor for these regimes. Unlike the cavity operating mode, which is tuned separately, the HOM parameters can significantly vary from one cavity to another due to finite mechanical tolerances during the manufacturing process. Thus, it is of utmost importance to know the HOM parameter spread in advance in order to predict unexpected cryogenic losses, overheating of beam line components and maintain stable beam dynamics. In this paper, we present a method for generating cavity geometry with an arbitrary spread of mechanical imperfections and numerically evaluating HOM statistics. Knowing the spread of HOM parameters, we calculated the probability of resonant HOM losses in SRF accelerating cavities used in CW beam current machines such as the PIP-II and LCLS-II linacs, as well as for the SRF crab-cavity for the ILC project. Finally, we present experimental results of HOM spectra measurements in hundreds of 1.3 GHz cavities installed in LCLS-II cryomodules. Studying the effects of HOM excitation results in specifications of the SRF cavity and cryomodule and can significantly impact the efficiency and reliability of the machine operation.

Lunin, Andrei [Fermilab] (ORCID:0000000290096792)↗

DOE OSTI2022

Transient Stability Study of a Real-World Microgrid with 100% Renewables

This paper performs a transient stability study of a real-world microgrid that can operate with 100% renewables to better understand the stability and reliability of the microgrid under various dynamic scenarios. In particular, the operation of multiple grid-forming (GFM) and grid-following (GFL) inverters in such a power system is not well understood under dynamic operation conditions, such as islanding and black start; therefore, in this paper, an electromagnetic transient model of the microgrid is developed to investigate the stability of the system under various dynamic operating conditions and to identify potential reliability risks. The PSCAD/EMTDC simulation with the high-fidelity model provides helpful insights into the optimal operation modes of GFM and GFL inverters as well as the stability and reliability of the microgrid. It can also inform field deployment in terms of inverter control parameters and coordination as well as the expected performance of black start and unplanned islanding.

black start↗

DOE OSTI2022

Transient Stability Study of a Real-World Microgrid with 100% Renewables

black start↗

DOE OSTI2019

Identification of Balance of Plant Asset and Wireless Instrumentation to Enable Predictive Maintenance

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2009

Unified Communications for Space Inventory Management

To help assure mission success for long-duration exploration activities, NASA is actively pursuing wireless technologies that promote situational awareness and autonomy. Wireless technologies are typically extensible, offer freedom from wire tethers, readily support redundancy, offer potential for decreased wire weight, and can represent dissimilar implementation for increased reliability. In addition, wireless technologies can enable additional situational awareness that otherwise would be infeasible. For example, addition of wired sensors, the need for which might not have been apparent at the outset of a program, night be extremely costly due in part to the necessary routing of cables through the vehicle. RFID, or radio frequency identification, is a wireless technology with the potential for significant savings and increased reliability and safety in space operations. Perhaps the most obvious savings relate to the application of inventory management. A fully automated inventory management system is highly desirable for long-term sustaining operations in space environments. This assertion is evidenced by inventory activities on the International Space Station, which represents the most extensive inventory tracking experience base in the history of space operations. In the short tern, handheld RFID readers offer substantial savings owing to reduced crew time for inventory audits. Over the long term, a combination of improved RFID technology and operational concepts modified to fully utilize the technology should result in space based inventory management that is highly reliable and requires very little crew time. In addition to inventory management, RFID is likely to find space applications in real-time location and tracking systems. These could vary from coarse-resolution RFID portals to the high resolution afforded by ultra-wideband (UWB) RFID. Longer range RFID technologies that leverage passive surface acoustic wave (SAW) devices are being investigated to track assets on a lunar or planetary surface.

Gifford, Kevin K.↗

DOE OSTI2026

Evaluating multistation phase picking algorithm phase neural operator (PhaseNO) on local seismic networks

Reliable automatic phase picking is important for many seismic applications. With the development of machine learning approaches, many algorithms are proposed, evaluated and applied to different areas. Many of these algorithms are single station based, while recent proposed methods start to combine surrounding stations into consideration in the problem of phase picking. Among these algorithms, the phase neural operator (PhaseNO) shows promising results on regional data sets comparing to existing algorithms. But there are many use cases for the local seismic networks in our community, therefore in this paper we evaluate the performance of PhaseNO on four different local data sets and compare the results to PhaseNet and EQTransformer. We used both individual phase picking metrics as well as association metrics to illustrate the performance of PhaseNO. By manually reviewing the newly detected events, we find that the PhaseNO model outperforms the single station-based approaches in the local-scale use cases due to its consideration of coherent signals from multiple stations. We also explored PhaseNO’s behaviours when only using one station, as well as gradually increasing the number of stations in the seismic network to better understand its behaviour. Overall, using the off-the-shelf machine learning based phase pickers, PhaseNO demonstrated its good performance on local-scale seismic networks.

58 GEOSCIENCES↗

DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗