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DOE OSTI2020

Retail Hydrogen Station Reliability Status and Advances

One of the most vital emerging commercial markets for hydrogen is fuel cell-powered mobility including cars, trucks, and buses. These vehicles are refueled via a network of hydrogen fueling stations, with the highest number of U.S. stations being in California. The numbers of both fuel cell electric vehicles (FCEVs) and hydrogen stations have increased in the last two years, with anecdotal information from FCEV drivers indicating that station reliability is hurting the consumer acceptability of FCEV technologies. Therefore, this study benchmarks the current state of hydrogen station reliability in practice and presents on-going research that is investigating the failures that are contribute to hydrogen station reliability issues. This is accomplished with an analysis of operation, safety, and maintenance data from hydrogen stations and fuel cell electric vehicles to benchmark the maintenance and failure of hydrogen stations and their components. This analysis, of over 5,000 station maintenance events, presents the leading maintenance categories and failure rates, and is a prerequisite to the development of data-driven reliability improvement plans. We present a reliability growth analysis and on-going research into the root causes of failure for dispensers, a particularly failure-prone subsystem.

08 HYDROGEN↗

DOE OSTI2026

Overview of NLR Automated Mobility District Implementation Research - Phases I, II, and III. The Convergence of Automation, Electrification, and On-Demand Services: Enabling Resilient Automated Mobility Districts

A research program by the National Renewable Energy Laboratory has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings, referred to as Automated Mobility Districts (AMDs). An AMD emphasizes the deployment of automated vehicles (AV) passenger transport services within a dense urban setting and other major activity centers with intense passenger origin-destination demand patterns, such as those found in large business districts, airports, and university and medical campuses. Phase I and II surveyed 10 early deployment sites and subsequently collected and evaluated the lessons learned from these early deployment sites, with particular attention to fleet operations, impacts of service reliability, and vehicle technology evolution as the field of companies was being progressively winnowed by the challenges of full automation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

Analysis of Electric Power Board of Chattanooga Smart Grid Investment

The deployment of a Smart Grid within the EPB electrical system has brought significant value to EPB customers and to EPB operations. The Smart Grid implementation has permitted the capability to automate many of the existing systems, increasing the overall efficiency and decreasing round trip time for many required operation functions. This has both reduced the cost of operations and increased the reliability of customer service. This boost in performance can be primarily linked to two main components: the communication network and the availability of data. The existence of a fiber communication backbone has opened numerous opportunities for EPB. Large data sets from remote devices can be continuously polled and used to compute numerous metrics. The speed of communication has provided a pathway to sophisticated distribution automation that would not otherwise be possible. The data have been shown to provide a much broader view of the actual electrical system that was not previously available, opening many new opportunities in data analytics. This report documents many of the existing systems and operational features of the EPB system. Many of these systems have seen significant improvement with the deployment of Smart Grid technologies. The research behind this report found that in some cases, the value was directly computable or estimable for these enhancements. Currently, several ongoing research topics are under investigation within EPB. Through a grant from TVA, EPB is currently installing a 1.3MW solar photovoltaic system, which will be the first-generation asset owned by EPB.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

A Testbed Environment for Buildings-to-Grid Cyber Resilience Research and Development

The Smart Grid is characterized by the proliferation of advanced digital controllers at all levels of its operational hierarchy from generation to end consumption. Such controllers within modern residential and commercial buildings enable grid operators to exercise fine-grained control over energy consumption through several emerging Buildings-to-Grid (B2G) applications. Though this capability promises significant benefits in terms of operational economics and improved reliability, cybersecurity weaknesses in the supporting infrastructure could be exploited to cause a detrimental effect and this necessitates focused research efforts on two fronts. First, the understanding of how cyber attacks in the B2G space could impact grid reliability and to what extent. Second, the development and validation of cyber-physical application-specific countermeasures that are complementary to traditional infrastructure cybersecurity mechanisms for enhanced cyber attack detection and mitigation. The PNNL B2G testbed is currently being developed to address these core research needs. Specifically, the B2G testbed combines high-fidelity buildings+grid simulators, industry-grade building automation and Supervisory Control and Data Acquisition (SCADA) systems in an integrated, realistic, and reconfigurable environment capable of supporting attack-impact-detection-mitigation experimentation. In this paper, we articulate the need for research testbeds to model various B2G applications broadly by looking at the end-to-end operational hierarchy of the Smart Grid. Finally, the paper not only describes the architecture of the B2G testbed in detail, but also addresses the broad spectrum of B2G resilience research it is capable of supporting based on the smart grid operational hierarchy identified earlier.

Sridhar, Siddharth↗

NASA NTRS2008

Performance of MEMS Silicon Oscillator, ASFLM1, under Wide Operating Temperature Range

Over the last few years, MEMS (Micro-Electro-Mechanical Systems) resonator-based oscillators began to be offered as commercial-off-the-shelf (COTS) parts by a few companies [1-2]. These quartz-free, miniature silicon devices could compete with the traditional crystal oscillators in providing the timing (clock function) for many digital and analog electronic circuits. They provide stable output frequency, offer great tolerance to shock and vibration, and are immune to electro-static discharge [1-2]. In addition, they are encapsulated in compact lead-free packages, cover a wide frequency range (1 MHz to 125 MHz), and are specified, depending on the grade, for extended temperature operation from -40 C to +85 C. The small size of the MEMS oscillators along with their reliability and thermal stability make them candidates for use in space exploration missions. Limited data, however, exist on the performance and reliability of these devices under operation in applications where extreme temperatures or thermal cycling swings, which are typical of space missions, are encountered. This report presents the results of the work obtained on the evaluation of an ABRACON Corporation MEMS silicon oscillator chip, type ASFLM1, under extreme temperatures.

Patterson, Richard L.↗

DOE OSTI2019

Technology-Enabled Risk-Informed Maintenance Strategy to Minimize Operation and Maintenance Costs

The domestic fleet of nuclear power plants (NPPs) is facing a unique economic sustainability challenge in today’s energy market due to high total operating costs. One of the major contributors to the total operating cost of an NPP is the operations and maintenance (O&M) budget, which includes labor-intense preventive maintenance (PM) programs. PM programs involve manually performing inspection, calibration, testing, and maintenance of plant assets at periodic frequencies, as well as time-based replacement of assets, irrespective of individual asset condition. This approach, combined with the push to achieve high capacity factors, has resulted in a labor-centric business model. It is time to transition from this labor-centric business model to a technology-centric business model that will enable an optimal maintenance strategy by eliminating unnecessary costs associated with time-based PM activities. To enable this transition, the commercial nuclear industries are utilizing and developing reliable methodologies, based on available state of the art technologies, which facilitate assessing equipment condition and the dynamic risk of failure. The U.S. Department of Energy’s Idaho National Laboratory (INL) under the Light Water Reactor Sustainability (LWRS) Program is partnering with PKMJ Technical Services and Public Service Enterprise Group (PSEG) Nuclear, LLC to develop and demonstrate a deployable risk-informed predictive maintenance strategy to eliminate unnecessary O&M costs for an identified plant system, laying the foundation for scale-up to the entire plant. Recently developed technologies such as advanced wireless and wired sensors, data analytics, and risk assessment methodologies will support this transition. The technology-centric O&M model will result in significant automation and lay the foundation for real-time condition assessment of plant assets, thus enabling condition-based maintenance and enhancing plant safety, reliability, and economics of operation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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)↗