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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Laboratory Evaluation and Field Demonstration of High Rotor Switched Reluctance Motor (HRSRM) Technology

In this project, a new motor technology based on a novel design called a High Rotor Pole Switched Reluctance Motor (HRSRM) was demonstrated and evaluated. The HRSRM system combines an innovative electric motor design with a programmable variable-speed drive and a controller that provides real time monitoring and cloud-based connectivity. Unlike induction or permanent-magnet motor designs, this motor uses a switched reluctance (SR) design that purports to be simpler to manufacture and more reliable and efficient to operate. Several of the stated benefits of the HRSRM system were evaluated as part of this project. First, the technology is claimed to offer greater energy efficiency than any motor currently on the market. Second, according to the manufacturer, the motor can be dropped into an existing pump or heating, ventilation, and air-conditioning application in less than 30 minutes, and has controls that can be pre-programmed to interact with the application’s existing control structure. Third, the control system allows the HRSRM to replace a constant-speed motor with one that provides variable-speed capabilities without requiring the installation of a variable-speed drive. The evaluation of a 10 hp HRSRM system was conducted in two parts. One portion of the evaluation consisted of performance tests conducted in a tightly controlled laboratory environment in which the performance of the HRSRM system was compared with that of a premium efficiency induction motor with a variable-frequency drive. The other portion of the evaluation was conducted at a field location within a General Services Administration facility in which the HRSRM system replaced an existing motor system in a 10 hp chilled water pump. The performance of the HRSRM system was compared with that of the incumbent motor system that was supplied with the pump from the manufacturer. The overall project and performance objectives for this motor evaluation are defined in Table ES.1.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

MEPHESTO: Modeling Energy-Performance in Heterogeneous SoCs and Their Trade-Offs

Integrated shared memory heterogeneous architectures are pervasive because they satisfy the diverse needs of mobile, autonomous, and edge computing platforms. Although specialized processing units (PUs) that share a unified system memory improve performance and energy efficiency by reducing data movement, they also increase contention for this memory since the PUs interact with each other. Prior work has investigated performance degradation due to memory contention, but few have studied the relationship of power and energy to memory contention. Moreover, a comprehensive solution that models memory contention for kernel placement on contemporary heterogeneous systems on chip (SoCs) in response to energy and performance has been largely unaddressed.This paper presents MEPHESTO, a novel and holistic approach for managing this balance. The authors characterize applications and PUs in terms of two memory contention factors - time factors and power factors - to achieve the desired trade-off between energy and performance for collocated kernel execution on heterogeneous systems. The authors believe that this investigation is the first to combine all of these factors and present a simple knob-based approach that expresses the target trade-off. The approach is evaluated on a diverse integrated shared memory heterogeneous system with a CPU, GPU, and programmable vision accelerator. By using an empirical model for memory contention that provides up to 92% accuracy, the kernel collocation approach can provide a near-optimal ordering and placement based on the user-defined, energy-performance trade-off parameter. Moreover, the dynamic programming-based heuristics provide up to 30% better energy or 20% performance benefits when compared with the greedy approaches commonly employed by previous studies.

Alaul haque monil, Mohammad↗
DOE OSTI2022

WinnowML: Stable feature selection for maximizing prediction accuracy of time-based system modeling

Online deep learning (ODL) has become an important methodology for modeling time-based performance of computer systems. An open problem is the intelligent selection of features from raw workload traces of computer systems. The best methods are overly sensitive to noisy data, causing frequent feature changes and re-training. Using all available features inflates training time and introduces model artifacts if some features should have been dropped. We present WinnowML, a method for automatically determining the most relevant feature subset for a predictive time-series model. WinnowML combines existing feature ranking algorithms and a history of each feature's ranking to iteratively rank a feature set to lower prediction error and maximize long term relevance. From this ranked feature set, the most relevant and stable subset is selected to train a model. Experimentally, we show how WinnowML can lower a model's mean absolute relative error up to 42% on average compared to the closest performing approach. Additionally, we lower the fluctuation in feature ranking and selection up to 65%. We also demonstrate how to combine WinnowML and a model search tool to provide improvements in performance of up to 14.5% when compared to using all the feature available.

Bel, Oceane MS↗
DOE OSTI2025

Artificial Intelligence and Machine Learning Applications in Modern Power Systems

Machine learning (ML) and artificial intelligence (AI) algorithms offer valuable tools for the analysis and interpretation of large datasets. These tools have the capability to uncover insights that may not be readily apparent within these datasets. In recent years, the integration of ML and AI has become increasingly prevalent in various applications within the power system domain. One of the earliest instances of machine learning in power systems can be traced back to demand forecasting, where artificial neural networks were employed for short-term load forecasting. In contemporary power systems, an abundance of high-resolution geospatial and temporal data is generated at various time intervals, ranging from sub-seconds (Phasor Measurement Units or PMUs) to seconds (Supervisory Control and Data Acquisition or SCADA), minutes (Process Information or PI), and extending to days, months, and years. These datasets contain valuable information concerning system reliability and performance. This information holds the potential to offer critical insights into system operations, as well as solutions for predicting and mitigating contingencies to prevent cascading outages. Despite the immense power of machine learning tools, system operators, planners, and utilities often exhibit hesitancy in fully embracing AI-enabled system operations and planning. This cautious approach persists, even as numerous diverse applications of machine learning continue to emerge in the realm of power systems. In this chapter, our focus will delve deep into ML and AI applications tailored for power systems. These applications aim to furnish system operators with enhanced situational awareness and augment their decision-making capabilities, especially during challenging operating conditions. Specific areas of interest encompass root cause analyses of electricity market datasets and the strategic selection of representative samples from vast power system databases for training ML/AI models. Finally, the chapter will conclude with a short discussion on the future of ML/AI in power systems and possible directions that the industry is moving towards.

power system applications, machine learning (ML), ↗
DOE OSTI2021

Transportation Energy Analytics Dashboard (TEAD)

The investment decisions within the nation’s transportation sector have traditionally been prioritized and measured against safety and travel efficiency goals. Increasingly, federal, state, and local policies are requiring consideration of energy use and emissions in the design of our transportation infrastructure. Yet the processes, analytics, and knowledge to include these new metrics into transportation decisions are lacking. Although targeted studies and before and after analysis are performed from time to time, no comprehensive real-time monitoring systems provide energy and emissions to the same level as congestion and safety. To address this gap, the Center for Advanced Transportation Technology (CATT Lab) and the Maryland Transportation Institute (MTI) at the University of Maryland (UMD), in partnership with the National Renewable Energy Laboratory (NREL), have developed a Transportation Energy Analytics Dashboard, or TEAD, to raise awareness of the energy and emission impacts to the same level of observability as that of safety and mobility concerns. The overall goal of this project was to develop and demonstrate an online tool to monitor transportation energy use and emissions in real-time and to archive this data for retrospective analysis. By combining surface transportation energy and emissions evaluation capability with more traditional safety, mobility and reliability system evaluation, our goal is for TEAD to create a dynamic new paradigm in transportation systems management and performance analyses, for both real-time traffic operations, and longer-term planning for project and program investment decision-making.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Regulatory Mechanisms to Enable Investments in Electric Utility Resilience

In 2019, Sandia National Laboratories contracted Synapse Energy Economics (Synapse) to research the integration of community and electric utility resilience investment planning as part of the Designing Resilient Communities: A Consequence-Based Approach for Grid Investment (DRC) project. Synapse produced a series of reports to explore the challenges and opportunities in several key areas, including benefit-cost analysis, performance metrics, microgrids, and regulatory mechanisms to promote investments in electric system resilience. This report focuses on regulatory mechanisms to improve resilience. Regulatory mechanisms that improve resilience are approaches that electric utility regulators can use to align utility, customer, and third-party investments with regulatory, ratepayer, community, and other important stakeholder interests and priorities for resilience. Cost-of-service regulation may fail to provide utilities with adequate guidance or incentives regarding community priorities for infrastructure hardening and disaster recovery. The application of other types of regulatory mechanisms to resilience investments can help. This report: characterizes regulatory objective as they apply to resilience; identifies several regulatory mechanisms that are used or can be adapted to improve the resilience of the electric system--including performance-based regulation, integrated planning, tariffs and programs to leverage private investment, alternative lines of business for utilities, enhanced cost recovery, and securitization; provides a case study of each regulatory mechanism; summarizes findings across the case studies; and suggests how these regulatory mechanisms might be improved and applied to resilience moving forward. In this report, we assess the effectiveness of a range of utility regulatory mechanisms at evaluating and prioritizing utility investments in grid resilience. First, we characterize regulatory objectives which underly all regulatory mechanisms. We then describe seven types of regulatory mechanisms that can be used to improve resilience--including performance-based regulation, integrated planning, tariffs and programs to leverage private investment, alternative lines of business for utilities, enhanced cost recovery, and securitization--and provide a case study for each one. We summarize our findings on the extent to which these regulatory mechanisms have supported resilience to date. We conclude with suggestions on how these regulatory mechanisms might be improved and applied to resilience moving forward.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Simulation Results of a Thermal Power Dispatch System from a Generic Pressurized Water Reactor in Normal and Abnormal Operating Conditions

Amid economic pressures in the U.S. electricity market, nuclear utilities are exploring new revenue streams, including hydrogen production. A generic pressurized water reactor simulator was modified to incorporate a novel design for a TPD system coupled to a hydrogen production plant. Standard malfunctions were included in the simulation design, including steam line breaks at various system locations and flow interruptions in the hydrogen plant due to multiple faults, reflecting anticipated operational challenges. It is imperative that the TPD system operation has a minimal effect on the reactor power, primary coolant system, and turbine system operation and performance. Due to the specific design and application of this TPD system, with the proposed turbine control system changes, the overall impact on the existing plant systems is low. Normal TPD operating scenarios resulted in minor effects on the existing plant systems: reactor power changes by at most 0.2%, and gross generator output changes by 20.5 MWe from 100 MWt of TPD. The most severe malfunction analyzed in this work is a full TPD steam line break downstream of the extraction location, which results in an increase in reactor power of about 0.5%. The gross generator output decreases by 36 MWe, a total decrease of 60 MWe from the full power steady state (FPSS) condition. These results indicate that an industrial hydrogen production plant could be coupled thermally to a nuclear power plant with limited effects on the existing system operation and safety.

08 HYDROGEN↗
DOE OSTI2026

Technoeconomic Opportunity Analysis for Local Power Generation in Falls City, Nebraska

Falls City is a small community in Nebraska interested in understanding how energy from local energy systems could support the community's economic development planning. To address the current community needs and address the future energy demand technical assistance conducted through the Communities Local Energy Action Program (Communities LEAP) assessed the technical and economic opportunities of adding energy technologies to Falls City's municipally owned and operated electric utility system. The modeling performed considered the technical and economic feasibility of technologies using the System Advisor Model (SAM). The modeling explored three technology configurations using multiple years of historical weather and wholesale cost data (2015-2022 & a typical meteorological year), and two different wholesale escalation rates (0.3% and 2.5%). Wholesale energy prices were based on the Southwest Power Pool's (SPP) real-time energy market and the annual escalation rates of these rates based on historical SPP wholesale and national retail electricity price trends. Results from the modeling showed that at current CAPEX costs and SPP wholesale electricity costs no technology combination averaged across the scenarios run provide a positive net present value (NPV). External financial support, changes in market conditions, and additional revenue streams would help create more economically favorable projects. As conditions change re-evaluation may be necessary.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A computational modeling framework for pre-clinical evaluation of cardiac mapping systems

There are a variety of difficulties in evaluating clinical cardiac mapping systems, most notably the inability to record the transmembrane potential throughout the entire heart during patient procedures which prevents the comparison to a relevant “gold standard”. Cardiac mapping systems are comprised of hardware and software elements including sophisticated mathematical algorithms, both of which continue to undergo rapid innovation. The purpose of this study is to develop a computational modeling framework to evaluate the performance of cardiac mapping systems. The framework enables rigorous evaluation of a mapping system’s ability to localize and characterize (i.e., focal or reentrant) arrhythmogenic sources in the heart. The main component of our tool is a library of computer simulations of various dynamic patterns throughout the entire heart in which the type and location of the arrhythmogenic sources are known. Our framework allows for performance evaluation for various electrode configurations, heart geometries, arrhythmias, and electrogram noise levels and involves blind comparison of mapping systems against a “silver standard” comprised of computer simulations in which the precise transmembrane potential patterns throughout the heart are known. A feasibility study was performed using simulations of patterns in the human left atria and three hypothetical virtual catheter electrode arrays. Activation times (AcT) and patterns (AcP) were computed for three virtual electrode arrays: two basket arrays with good and poor contact and one high-resolution grid with uniform spacing. The average root mean squared difference of AcTs of electrograms and those of the nearest endocardial action potential was less than 1 ms and therefore appears to be a poor performance metric. In an effort to standardize performance evaluation of mapping systems a novel performance metric is introduced based on the number of AcPs identified correctly and those considered spurious as well as misclassifications of arrhythmia type; spatial and temporal localization accuracy of correctly identified patterns was also quantified. This approach provides a rigorous quantitative analysis of cardiac mapping system performance. Proof of concept of this computational evaluation framework suggests that it could help safeguard that mapping systems perform as expected as well as provide estimates of system accuracy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Multipole Expansion of Atomic Electron Density Fluctuation Interactions in the Density-Functional Tight-Binding Method

The accuracy of the density-functional tight-binding (DFTB) method in describing noncovalent interactions is limited due to its reliance on monopole-based spherical charge densities. In this study, we present a multipole-extended second-order DFTB (mDFTB2) method that takes into account atomic dipole and quadrupole interactions. Furthermore, we combine the multipole expansion with the monopole-based third-order contribution, resulting in the mDFTB3 method. To assess the accuracy of mDFTB2 and mDFTB3, we evaluate their performance in describing noncovalent interactions, proton transfer barriers, and dipole moments. Here, our benchmark results show promising improvements even when using the existing electronic parameters optimized for the original DFTB3 model. Both mDFTB2 and mDFTB3 outperform their monopole-based counterparts, DFTB2 and DFTB3, in terms of accuracy. While mDFTB2 and mDFTB3 perform comparably for neutral and positively charged systems, mDFTB3 exhibits superior performance over mDFTB2 when dealing with negatively charged systems and proton transfers. Overall, the incorporation of the multipole expansion significantly enhances the accuracy of the DFTB method in describing noncovalent interactions and proton transfers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Re-Designing the CSP Thermal Energy Storage System to Enable Higher-Temperature Performance at Reduced Cost (Final Technical Report)

Current commercial concentrating solar power (CSP) plants distinguish themselves from ordinary photovoltaic (PV) power plants by storing enough collected energy to enable generation for several hours after the sun goes down. CSP plants store this energy in the sensible heat of nitrate salts in large metallic storage tanks. Stainless-steel AISI 347H (SS347H) is needed for the hot tank operating at about 565 degrees C whereas carbon steel is sufficient for the cold-tank materials. Two-tank nitrate-salt thermal energy storage (TES) is presently in use in several trough-based CSP plants in Europe and in the U.S., operating up to about 390 degrees C. Three commercially operating tower-based CSP plants - Gemasolar in Spain, Crescent Dunes in Nevada, and Noor III in Morocco - use the same approach, storing nitrate salts at temperatures up to 580 degrees C. SS347H is many times more expensive than carbon steel and constitutes a significant cost element in today's CSP plants. Hence, CSP developers need to close the cost gap with PV-based solar plants by making cost reductions in every system of the plant. Redesigning the TES tanks is one opportunity for cost reduction.

14 SOLAR ENERGY↗
DOE OSTI2026

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity)

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity) project aims to demonstrate a novel, scalable method for removing carbon dioxide (CO 2 ) directly from ambient air and delivering it to cyanobacterial cultures to produce commodity biofuel, mid-value protein for supplements, and high value phycocyanin (PC), a natural blue colorant (Figure A). This approach uses low-cost, reusable anion exchange polymers embedded in modular mesh packets, which capture CO 2 during drying cycles when exposed to ambient air, and release concentrated CO 2 into aqueous cultivation systems. The project addresses a critical challenge in energy research needed for developing sustainable, economically viable methods of Direct Air Capture (DAC) that can be integrated with bio-based systems for fuel and chemical production. AUDACity contributes to scientific understanding by integrating materials chemistry, cyanobacterial biology, and system engineering to create a distributed CO 2 delivery platform. Key insights have emerged around the design of biocompatible sorbents, optimization of CO 2 capture-release cycles, and durability of packet-based delivery systems under outdoor conditions. Notably, the team has synthesized and tested a range of polymer sorbents, identified mechanisms of material degradation and fouling, and advanced both lab- and pilot-scale cultivation systems to evaluate performance. From a technical and economic standpoint, AUDACity shows promise for achieving cost-effective CO 2 capture and delivery into aqueous media and biofuel production. Preliminary techno-economic analysis (TEA) indicates that the DAC system based on current performance can reach $\$$680/tonne CO 2 delivered into aqueous solution; with reasonable improvements to sorbent lifetime, sorbent capacity, reducing water uptake the approach could reach $\$$66/tonne by avoiding the need for energy-intensive sorbent regeneration and CO 2 compression, making it more feasible for decentralized deployment. With these costs for CO 2 and by extracting and selling high-value PC ($\$$50/kg) and mid-value protein supplement ($\$$6/kg), the remaining biomass can be hydrothermally treated into biofuel for $\$$2.50/gallon, and would support a small first-of-a-kind biorefinery capable of producing 500 barrels per day of biofuel. The project offers meaningful public benefits by advancing carbon removal technologies that are low-energy, modular, and adaptable to non-arable land and brackish water use. It aligns with national goals to develop advanced biotechnology and supports future pathways for bio-based fuels and products. By enabling direct coupling of CO 2 transfer into aqueous medium and biological carbon utilization, AUDACity lays the groundwork for effective algae cultivation without wasteful CO 2 delivery and is a promising and innovative solution for low-carbon fuel and bioproduct generation contributing to a vigorous bioeconomy.

09 BIOMASS FUELS↗
DOE OSTI2023

Development of an Unmanned Mobile Current Turbine Platform: Preprint

The design and development of a prototype unmanned mobile floating platform, equipped with a custom low-flow marine current turbine for autonomously seeking and harnessing tidal/coastal currents is described. The platform is an unmanned surface vehicle in the form of a catamaran with two electric outboard motors and capabilities for autonomous navigation. An undershot water wheel, aided by a custom flow concentrator, has been selected as the basic design for the marine current turbine, which is mounted on the stern of the unmanned surface vehicle platform. The concept of operation is that the platform would navigate to a designated marine current resource, autonomously anchor at the location, align itself in the current and deploy the current turbine using a custom cable-lift deployment mechanism. As the turbine harnesses the local current, an onboard power-take-off device converts the harnessed mechanical energy to electricity which is stored in onboard batteries. Considerations of deployment in tidal and coastal waters required obtaining the necessary environmental permits for conducting in-water testing; developing required mitigation measures in protecting local wildlife and their habitats; and identifying potential in-water test sites and surveying them for their suitability in terms of the current resource, bottom type, water depth, and local boat traffic. The design and development of the turbine and the results of initial in-water testing are discussed. The potential for scaling up the system for extended capacity is presented.

ENGINEERING,TIDAL AND WAVE POWER↗
DOE OSTI2023

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

Addressing performance portability across diverse accelerator architectures has emerged as a major challenge in the development of application and programming systems for high-performance computing environments. Although recent programming systems that focus on performance portability have significantly improved productivity in an effort to meet this challenge, the problem becomes notably more complex when compute nodes are equipped with multiple accelerator types—each with unique performance attributes, optimal data layout, and binary formats. To navigate the intricacies of multi-accelerator programming, we propose CHARM-SYCL as an extension of our CHARM multi-accelerator execution environment [27]. This environment will combine our SYCL-based performance-portability programming front end with a back end for extremely heterogeneous architectures as implemented with the IRIS runtime from Oak Ridge National Laboratory. Our preliminary evaluation indicates potential productivity boost and reasonable performance compared to vendor-specific programming system and runtimes.

Fujita, Norihisa↗
DOE OSTI2019

Effect of Torque-Tube Parameters on Rear-Irradiance and Rear-Shading Loss for Bifacial PV Performance on Single-Axis Tracking Systems: Preprint

The emergence of cost-competitive bifacial PV modules has raised the question of the additional value of bifacial modules in 1-axis tracking arrays, in particular when considering rear-irradiance losses from the tracker system itself. In this work, the effect of different geometries and materials of torque tubes is evaluated and found to reduce rear-irradiance averages without any torque-tube shading by 0.1 to 12% for metallic and black absorptive torque tubes respectively for a clear-sky day. This paper will compare modeled to measured rear-irradiance profiles, and propose a recommended range of rear-shading loss factors for different geometry conditions. The effect of rear-irradiance distribution into electrical mismatch loss will also be explored.

14 SOLAR ENERGY↗
DOE OSTI2019

Influence of commercial refrigeration system design and refrigerant options on life cycle climate performance

Ongoing efforts to reduce direct and indirect emissions of commercial refrigeration systems include using leak reduction measures, refrigerant charge minimization, low global warming potential (GWP) refrigerants and energy efficiency measures. In this paper, Life Cycle Climate Performance (LCCP) analysis is used to estimate the lifetime carbon dioxide equivalent emissions of commercial refrigeration system designs and refrigerant options. Commercial refrigeration systems investigated in this study include the centralized direct expansion (DX) system with hydrofluorocarbon (HFC) and hydrofluoroolefin (HFO) refrigerant blends, the transcritical R-744 booster system, and self-contained systems using R-290. The results of the LCCP analysis are presented for a variety of cities around the world, and recommended systems and refrigerant options are provided based on direct and indirect carbon emissions.

Petersen, Michael↗
DOE OSTI2024

High-bandwidth Dynamic Load Emulation of Mechanical Systems using Electric Drives

Machine drives are versatile systems that can be programmed to emulate a variety of mechanical loads. In this paper, we walk through the modeling and control framework of a shaft-coupled dual-motor drive system that is programmed to emulate a fictitious mechanical system. We quantitatively evaluate the control performance of such a system and derive a theoretical limit that explains its inaccuracy at high operating frequencies. To overcome this problem, we propose an alternate control structure that achieves the same control objective at high frequencies as well. After suitable adjustments are made to the controller, we validate its performance using simulation results.

machine drives ,load emulation, speed-torque chara↗
DOE OSTI2022

Enhanced Component Performance Study: Emergency Diesel Generators 1998-2020

This report presents an enhanced performance evaluation of emergency power system (EPS) and high-pressure core spray (HPCS) emergency diesel generators (EDGs) at U.S. commercial nuclear power plants. This report evaluates component performance over time using (1) Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS) data from 1998 through 2020 and (2) maintenance unavailability performance data from Mitigating Systems Performance Index (MSPI) Basis Document data from 2002 through 2020. The objective is to show estimates of current failure probabilities and rates related to EDGs, trend these data on an annual basis, determine if the current data are consistent with the probability distributions currently recommended for use in NRC probabilistic risk assessments, show how the reliability data differ for different EDG manufacturers and for EDGs with different ratings; and summarize the subcomponents, causes, detection methods, and recovery associated with each EDG failure mode. The EDG failure modes considered are fail to start (FTS), fail to load and run (FTLR), and fail to run after one hour of operation (FTR>1H). Engineering analyses were performed with respect to time period and failure mode without regard to the actual number of EDGs at each plant. The factors analyzed are: subcomponent, failure cause, detection method, recovery, manufacturer, and EDG rating. The following increasing trends were identified for EDGs for the most recent 10-year period: • HPCS EDG FTS failure probability • EPS and HPCS EDG frequency of start demands (demands per reactor year) • EPS and HPCS EDG frequency of FTLR demands. The following decreasing trends were identified for EDGs for the most recent 10-year period: • EPS EDG FTS failure probability • EPS EDG FTLR failure probability • EPS EDG unavailability • EPS and HPCS EDG frequency of FTLR events (failures per reactor year).

99 GENERAL AND MISCELLANEOUS↗