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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Risk-Informed Safety Analysis for Accident Tolerant Fuels

Accident Tolerant Fuels (ATF) are being tested by different nuclear vendors and research organization and their introduction in light water reactors fleet is planned for the second half of the 2020`s. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Safety Analysis pathway (LWRS-RISA), research activities are being conducted at the Idaho National Laboratory (INL) for developing tools and methods that can help the industry in quantifying the ATF introduction benefits. In this paper we describe the developed risk-informed methodology, the codes improvements and we present some results for selected accidental conditions. The developed methodology combines INL state-of-the-art deterministic Best Estimate tools like RELAP5-3D code, and Probabilistic Risk Analysis tools like RAVEN and SAPHIRE codes. The analyses are performed on a three-loops pressurized water reactor (PWR) simulating accidental conditions like Station Blackout and LB-LOCA and considering near-term ATF (FeCrAl and Chromium-coated clads). Finally, we show, through our methodologies, how the delta-Core Damage Frequency can be assessed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

West Valley Demonstration Project (WVDP) Annual Site Environmental Report (ASER) for Calendar Year 2018

The report, prepared for the U.S. Department of Energy West Valley Demonstration Project office (DOE-WVDP), summarizes the environmental protection program at the WVDP for calendar year (CY) 2018. Monitoring and surveillance of the facilities used by the DOE are conducted to verify protection of public health and safety and the environment. The report is a key component of DOE’s effort to keep the public informed of environmental conditions at the WVDP. The quality assurance protocols applied to the environmental monitoring program ensure the validity and accuracy of the monitoring data. In addition to demonstrating compliance with environmental laws, regulations, and directives, evaluation of data collected in 2018 continued to indicate that WVDP activities pose no threat to public health or safety, or to the environment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Industry Fire Modeling Enhancement Tools and Methods. Light Water Reactor Sustainability Program report

Modeling and implementing fire safety for nuclear power plants is a costly activity. Because of the complexity of fire phenomenon and multiple operational procedures, it is difficult to computationally provide assurance that the mitigation methods are adequate for critical areas using current analysis methods. An economical method to provide more accurate modeling and optimize mitigation methods is needed to improve nuclear power viability. This report describes the background of current fire model strategy; the first stage of a tool to help reduce resources needed in fire analysis and the plan for the next step in advancing fire. The report lays out the path decided upon by Idaho National Laboratory and Industry representatives to best help reduce costs and improve realism in Fire Probabilistic Risk Analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗
DOE OSTI2016

INL Seismic Monitoring Annual Report: January 1, 2013 to December 31, 2013

During 2013, the Idaho National Laboratory (INL) recorded 14,011 independent triggers and 7,355 triggers were manmade blasts and distant, regional, and local earthquakes. Within the region, the INL Seismic Monitoring program located 2,085 earthquakes and 150 man-made blasts. Near and within the 161-km radius of INL, 38 of these earthquakes had small to moderate size magnitudes that ranged from 3.0 to 4.2. Residents near 19 of the M>3.0 earthquakes reported ground shaking affects of these earthquakes to the U.S. Geological Survey. Also, five new seismic stations with broadband seismometers and accelerometers were installed near INL facility areas. These new stations were installed to collect earthquake data that can be used in future INL probabilistic seismic hazard analyses to reduce uncertainties of ground motion models. In 2013, 1,013 earthquakes were located within the 161-km radius of INL and three occurred within the eastern Snake River Plain (ESRP). The earthquakes included three swarms and a mainshock-aftershock sequence. The earthquakes were located northwest of the INL in the Basin and Range regions of Idaho and Montana and southeast of the ESRP in the Basin and Range region along the Idaho-Wyoming border. A swarm of >180 earthquakes occurred at Driggs, Idaho; the largest events had local magnitudes (ML) of 2.8 and 3.1 and were felt by residents. A less intense swarm of 64 earthquakes was located west of Jackson, Wyoming along the Idaho-Wyoming border. The largest event was a MW 3.8 that was felt by local residents. Southeast of Pocatello, Idaho an earthquake of ML 4.2 was followed by 18 aftershocks that included a ML 3.6. Both earthquakes were felt by residents near to the epicenters. Three earthquakes occurred within the ESRP and three other earthquakes were located at the northwest edge of the ESRP. The coda magnitude (Mc) 1.3 earthquake was located in the center of ESRP north of the Great Rift and at a depth of 45 km. To the west, an earthquake of Mc 0.7 was located at a depth of 37 km and at the northwestern end of the Great Rift. Four earthquakes, Mc 0.0, Mc 1.3, Mc 1.8, and Mc 1.1 were located north of the INL along the edge of the ESRP. The Mc 0.0 and 1.1 earthquakes were located just within the ESRP at depths less than 6 km.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Probabalistic Modeling of Minibangs and Megabands (Final Report)

This project was original proposed as a fundamental advance in the treatment of probabilistic modeling as it applies to nuclear fission calculations of nuclear database inputs and produced particle distributions in heavy-ion collisions. However, funding decisions made within LLNL and the DOE Office of Science led to the project proceeding through three distinct stages. The first two, probabilistic calculations of the fission and jet energy loss relate follow directly from the proposed research. The fission task led to the development of a proof-of-principle Gaussian Process Emulator for time-dependent generator coordinate method (TDGCM) calculation for the fission of Pu-240. To study energy loss in heavy-ion collisions with a probabilistic model, we generated a training data set using the Pythia event generator superimposed on a heavy-ion background with a single quench-factor parameter. We then used kernel density estimation (KDE) to recover the distribution of quench-factors for a calibration data set. In the third stage, we proceeded to work through collaborations, collecting new data within the ATLAS experiment at the Large Hadron Collider (LHC), and further developing bayesian methodology within the Jet Energy-loss Tomography with a Statistically and Computationally Advanced Program Envelope (JETSCAPE) Collaboration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Variation-Resilient FeFET-Based In-Memory Computing Leveraging Probabilistic Deep Learning

Reliability issues stemming from device level nonidealities of nonvolatile emerging technologies like ferroelectric field-effect transistors (FeFETs), especially at scaled dimensions, cause substantial degradation in the accuracy of in-memory crossbar-based AI systems. Here, in this work, we present a variation-aware design technique to characterize the device level variations and to mitigate their impact on hardware accuracy employing a Bayesian neural network (BNN) approach. An effective conductance variation model is derived from the experimental measurements of cycle-to-cycle (C2C) and device-to-device (D2D) variations performed on FeFET devices fabricated using 28 nm high-k metal gate technology. The variations were found to be a function of different conductance states within the given programming range, which sharply contrasts earlier efforts where a fixed variation dispersion was considered for all conductance values. Such variation characteristics formulated for three different device sizes at different read voltages were provided as prior variation information to the BNN to yield a more exact and reliable inference. Near-ideal accuracy for shallow networks (MLP5 and LeNet models) on the MNIST dataset and limited accuracy decline by ~3.8%–16.1% for deeper AlexNet models on CIFAR10 dataset under a wide range of variations corresponding to different device sizes and read voltages, demonstrates the efficacy of our proposed device-algorithm co-design technique.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Advanced Shuttle Strategies for Parallel QCCD Architectures

Trapped ions (TIs) are at the forefront of quantum computing implementation, offering unparalleled coherence, fidelity, and connectivity. However, the scalability of TI systems is hampered by the limited capacity of individual ion traps, necessitating intricate ion shuttling for advanced computational tasks. The quantum charge-coupled device (QCCD) framework has emerged as a promising solution, facilitating ion mobility for universal quantum computation. Current QCCD architectures predominantly feature a linear topology, which is increasingly recognized as inefficient for complex quantum operations. Anticipating the shift toward more efficacious designs, this article introduces an innovative quantum scheduling strategy optimized for parallel QCCD topologies. Our strategy proposes a probabilistic formula for ion movement, alongside ingenious methods for local layer generation and layer compression, yielding a significant reduction in ion shuttle times. Through simulations, we demonstrate that our strategy not only substantially outstrips the linear model but also exhibits better performance over other parallel strategies that employ greedy algorithms. This is achieved through our nuanced resolution of complexities, such as traffic blocks and trap capacity limitations. The consequent reduction in shuttle operations leads to lower energy consumption and an enhancement in the quantum computer's fidelity, ultimately accelerating program execution times.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Advancing Risk‐Informed Decision Making in Managing Defense Nuclear Waste in the United States: Opportunities and Challenges for Risk Analysis

Abstract An omnibus spending bill in 2014 directed the Department of Energy to analyze how effectively Department of Energy (DOE) identifies, programs, and executes its plans to address public health and safety risks that remain as part of DOE's remaining environmental cleanup liabilities. A committee identified two dozen issues and associated recommendations for the DOE, other federal agencies, and the U.S. Congress to consider, as well as other stakeholders such as states and tribal nations. In regard to risk assessment, the committee described a risk review process that uses available data, expert experience, identifies major data gaps, permits input from key stakeholders, and creates an ordered set of risks based on what is known. Probabilistic risk assessments could be a follow‐up from these risk reviews. In regard to risk management, the states, in particular, have become major drivers of how resources are driven. States use different laws, different priorities, and challenge DOE's policies in different ways. Land use decisions vary, technology choices are different, and other notable variations are apparent. The cost differences associated with these differences are marked. The net result is that resources do not necessarily go to the most prominent human health and safety risks, as seen from the national level.

Greenberg, Michael R.↗
DOE OSTI2022

Human Performance Analysis Depending on Operator Expertise (Student vs. Operator) and Simulator Complexity (Rancor Microworld vs. Compact Nuclear Simulator)

Human reliability analysis (HRA) evaluates human errors and provides human error probabilities (HEPs) for application in probabilistic safety assessment (PSA), which is a comprehensive safety assessment method for nuclear power plants (NPPs). Generally, HRA methods estimate HEPs based on human reliability data collected from actual historical measurement, simulator experiments, or expert judgement. Most recent HRA data collection studies focus on collecting data via full-scope main control room (MCR) simulators with actual licensed reactor operators. Contrary to this, Idaho National Laboratory (INL) has adopted a different approach, which attempts to collect HRA data based on experiment using simplified simulators and student participants by following the Simplified Human Error Experimental Program (SHEEP). This approach has a couple of advantages compared to full-scope data collection. Representatively, it has relatively low entry point for collecting HRA data, and secures large sample sizes with reasonable cost and labor. In the previous studies, we developed the SHEEP framework, then verified whether the data collected through the framework could support a representative full-scope data collection study, i.e., the Human Reliability Data Extraction (HuREX) study. Also, we analyzed human performance measurements depending on participant type (i.e., student vs. operator). In this paper, we analyze human performance data collected from an experiment comparing operator expertise and simulator complexity when using the more simplified simulator developed by INL, i.e., Rancor Microworld and the less simplified simulator, i.e., Compact Nuclear Simulator (CNS) developed by Korea Atomic Energy Research Institute (KAERI). Analysis of variance (ANOVA) tests and correlation analysis are used for analyzing the experimental data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Report on High Energy Arcing Fault Experiments: Experimental Results from Open Box Enclosures

This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena. The experiments focus on providing data to better characterize the arc to improve the prediction of arc energy emitted during a HEAF event. An open box experiment allow for direct observation of the arc, which allows diagnostic instrumentation to record the phenomenological data needed for better characterization of the arc energy source term. The data collected supports characterization of the arc and arc jet, enclosure breach, material loss, and electrical properties. These results will be used to better characterizing the hazard for improvements in fire probabilistic risk assessment (PRA) realism. The experiments were performed at KEMA Labs located in Chalfont, Pennsylvania. The experimental design, setup, and execution were completed by staff from the NRC, the National Institute of Standards and Technology (NIST), Sandia National Laboratories (SNL) and KEMA Labs. In addition, representatives from the Electric Power Research Institute (EPRI) observed some of the experimental setup and execution. The HEAF experiments were performed between August 22, 2020 and September 18, 2020 on near-identical 51 cm (20 in) cube metal boxes suspended from a Unistrut support structure. The three-phase arcing fault was initiated at the ends of the conductors oriented vertically and located at the center of the box. Either aluminum or copper conductors were used for the conductors. The low-voltage experiments used 1 000 volts AC, while the medium-voltage experiments used 6 900 volts AC consistent with other recently completed experiments. Durations of the experiment ranged from 1 s to 5 s with fault currents ranging from 1 kA to 30 kA. Real-time electrical operating conditions, including voltage, current and frequency, were measured during the experiments. Heat fluxes and incident energies were measured with plate thermometers, radiometers, and slug calorimeters at various locations around the electrical enclosures. The experiments were documented with normal and high-speed videography, infrared imaging and photography.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Report on High Energy Arcing Fault Experiments: Experimental Results from Low-Voltage Switchgear Enclosures

This report documents an experimental program designed to investigate High Energy Arcing Fault (HEAF) phenomena for low-voltage metal enclosed switchgear containing aluminum conductors. This report covers full-scale laboratory experiments using representative nuclear power plant (NPP) three-phase electrical equipment. Electrical, thermal, and pressure data were recorded for each experiment and documented in this report. This report covers experiments performed on two low-voltage switchgear units with each unit consisting of two vertical sections. The data collected supports characterization of the low-voltage HEAF hazard and these results will be used to support potential improvements in fire probabilistic risk assessment (PRA) methods. The experiments were performed at KEMA Labs located in Chalfont, Pennsylvania. The experimental design, setup, and execution were completed by staff from the NRC, the National Institute of Standards and Technology (NIST), Sandia National Laboratories (SNL) and KEMA. In addition, representatives from the Electric Power Research Institute (EPRI) observed some of the experimental setup and execution. The HEAF experiments were performed between August 26 and Augsut 29, 2019 on nearidentical Westinghouse Type DS low-voltage metal-enclosed indoor switchgear. The threephase arcing fault was initiated on the aluminum main bus or in select cases on the copper bus stabs near the breaker. These experiments used either nominal 480 volts AC or 600 volts AC. Durations of the experiments ranged from approximately 0.4 s to 8.3 s with fault currents ranging from approximately 9.2 kA to 19.3 kA. Real-time electrical operating conditions, including voltage, current and frequency, were measured during the experiments. Heat fluxes and incident energies were measured with plate thermometers, radiometers, and slug calorimeters at various locations around the electrical enclosures. Environmental measurements of breakdown, conductivity and electromagnetics were also taken. The experiments were documented with normal and high-speed videography, infrared imaging and photography. The results, while limited, indicated the difficulty in maintaining and sustaining low-voltage arcs on aluminum components of sufficient duration and at a single point as observed operating experience.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Probabilistic Modeling of Commercial Building Occupancy Patterns Using Location-Based Map Data: Preprint

Considering occupancy patterns is crucial to simulate buildings' energy use. Current energy models use inputs that simplify the actual diversity in occupancy into static occupancy patterns and are not able to represent the numerous variations in occupancy patterns between buildings and across different locations. Recently, inferring occupancy schedules from metered electricity consumption data was used to model occupancy in commercial buildings. However, the translation from metered data to occupancy schedules requires many assumptions that might not capture the reality, and the process is hindered by the availability of data from advanced metering infrastructure. With the development of information technologies, occupancy modeling should not be limited to traditional approaches. The prevalence of social networks and location services with real-time user feedback provides publicly accessible data via Maps Application Programming Interfaces (APIs) such as Google Maps, SafeGraph, Mapbox, Foursquare, etc. This paper presents an automated framework for modeling parametric occupancy patterns using such APIs to calibrate commercial district buildings' energy models. This process includes three main steps: data extraction and processing, parametric schedules generation, and schedules integration. We demonstrated this framework in districts where we used maps API to generate more accurate behavioral patterns for operations and electric vehicle charging events. We used these patterns to determine differences in energy use across key sociodemographic and spatial parameters. The presented method has the potential for worldwide applications. Users can utilize this framework to extract data for selected locations of interest to create more realistic behavioral patterns for commercial facilities across different districts.

building energy modeling↗
DOE OSTI2018

Utilization of Renewable Energy to Meet New National Challenges in Energy and Climate Change

The project aims to design a microgrid system to promote utilization of renewable energy resources such as wind and solar to address the national challenges in energy and climate change. Different optimization techniques and simulation software are used to study the performance of the renewable energy system under study. A series of research works performed under the grant Department of Energy (DOE) is presented. This grant opportunity affords Howard faculty, students, graduates, undergraduates, K-12, postdocs and visiting scholars to benefit state of the art research work. The research work has led to improve or advance understanding of new hardware technologies, software development and engineering optimization methods necessary and sufficient for handling probabilistic models and real-time computation and functions necessary for development of microgrid system. Consistent with State of Project Objective Howard University has partitioned the task into the following integrated activities: 1. Stochastic Model for RER and Load • Development of modeling Renewable Energy Resources (RER) and load which is used to perform distribution power flow study which leads to publication in refereed journals and conferences. The work was also published at the IEEE conference. 2. Stochastic optimization for voltage/Var • The development of voltage VAr optimization based on a review of existing knowledge in optimization led to the use of stochastic program and evolution of programming optimization method for V/VAr optimization. Papers were presented at the North America Power Systems Conference and the IEEE PES general meeting. 3. Modeling RER and Storage • Extending the concept of optimization method an RER with storage, such as the development of microgrid V/VAr and storage is performed. Several papers were published at the North America Power Systems Conference and the IEEE PES general meeting. 4. Power Game • Development of power game experiment using Labvolt to allow for hands on understanding of design and development of microgrid functions is performed. Publication were done by students at the end of their summer program. 5. Designing Microgrid Testbed • Example microgrid test bed is developed. In addition, function of the test bed are developed. The papers were presented at the North America Power Systems Conference and the IEEE general meeting. 6. Outreach Program • From the outreach program, topics from the project have been included in the revision of courses at Howard University, new book called Energy Processing and Smartgrid has being developed. • Hosted masters students from University of Denver to complete their projects with us. • Hosted high school students for early exposure for careers in STEM • Representations made in IEEE conferences to share the lessons learned in the use of micro grid to expose students to STEM education and research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evolution of Scenario Generation Capabilities in the ExaSGD Project

High-fidelity renewable energy scenarios and rare-event high-impact contingencies are essential for modeling operations and infrastructure expansion of the next generation power grids using exascale computing resources. As the ExaSGD project progressed, our capabilities for generating scenarios for modeling wind power output at multiple wind farms significantly improved, evolving from the use of independent random perturbations to importance sampling-based techniques capturing representative spatial-temporal relations. Contingency generation also improved, evolving from standard N-1 techniques to probabilistic models of infrastructure damage resulting from extreme weather events. We review the developments in the realistic intermittent-energy scenario forecasting and extreme-event contingency creation as the ExaSGD project progressed and discuss the future work in these areas.

economic dispatch↗
DOE OSTI2018

IAEA Initiatives that Integrate Stakeholders, Models and Decision Making - 18646

The International Atomic Energy Agency (IAEA) has initiated an effort to provide stakeholder support services as part of Phase II of the Constraints to Implementing Decommissioning and Environmental Remediation (CIDER II) programs. The intent of this sub-group of CIDER II is to provide members states support in areas of stakeholder communication, engagement and participation, with the goal of building trust in decommissioning and environmental remediation (D and ER) decisions for radioactive contamination and facilities. IAEA has also initiated a follow-on effort to address Modeling and Data for Radiological Impact Assessments (MODARIA II), which is aimed at enhancing the capabilities of Member States to simulate radionuclide transfer in the environment, and to ensure appropriate levels of protection from ionizing radiation. Working Group 1 of MODARIA II is focused on the integration of modeling and decision analysis. These two groups have complementary and supporting objectives, which provides an opportunity for collaboration and mutual benefit. The technical integrator is the approach of structured decision making, which follows a five-step process that combines stakeholder values with models through a technically defensible decision analysis. Briefly, the steps are: 1. Provide the context and decision context for the problem; 2. Obtain costs, values and concerns from stakeholders, to develop objectives that need to be achieved (e.g., improve human health, minimize costs, increase jobs); 3. Identify options that might achieve the objectives (e.g., cleanup, institutional controls, education); 4. Develop probabilistic models that connect options to objectives so that the objectives can be evaluated collectively (e.g., a fate and transport and risk model to address the objective of reducing human health risk, a cost model to address costs of taking action); and, 5. Model evaluation, including sensitivity analysis, to determine if an action can be taken with sufficient certainty, or if collection of more data is needed to decrease uncertainty before a decision is made. This approach also supports adaptive management as new data are collected. This approach clarifies the roles of stakeholders and subject matter experts in the decision-making process, where stakeholders specify values, and subject matter experts focus on the models that are needed to evaluate the options. It also provides a technically defensible, reproducible, transparent and traceable approach to all of the components necessary to properly solve the types of complex decision problems that plague radioactive waste management, decommissioning and environmental remediation. This paper introduces the major challenges to implementing such a broad scale of decision analysis, and approaches to overcoming those challenges, which include not only the technical challenges, but also the need to develop capacity in a range of skills not usually accommodated in environmental modeling and includes the need for the IAEA to address decision making in different countries, and with different cultures, religions, political affiliations, and languages. This paper explores the potential for IAEA to benefit from both the CIDER II and MODARIA II programs, and hence to develop a fully integrated approach to effective decision making for radioactive waste management and environmental remediation. Note that there are many people involved in these efforts at the IAEA, and credit belongs to those people for the progress that has been made to date. Our intent here is simply to introduce these IAEA programs at the WM2018 Symposium to provide our perspective and some awareness of some of the directions in which IAEA appears to be headed regarding stakeholder engagement, environmental and risk modeling, data science, and decision analysis. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Prototype System for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed by In-Use Procedures

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and extension of their current operating licenses. The Outage Risk Management Improvement Pilot Project seeks to improve the management of nuclear power plant outages through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and equipment out of service would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify the incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment that is being relied on to meet the requirements of the nuclear safety plan. In addition, Operations and the Outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently in outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This project will develop tools and strategies to minimize these interactions. This report describes a prototype tool designed to support plant personnel in controlling work during NPP outages to prevent unintended interactions. A software application was created to manage and display important configuration information and utilize natural language processing to access the impacts of upcoming procedures and work orders. Initial industry feedback is also presented.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Technical Maturity Assessment of Risk-Informed Safety Analysis Tools

Ensuring maximum safety while enhancing economic benefit is one of most important goal of In the of US Light Water Reactor Sustainability (LWRS) program. Optimization of the safety margins will provide best practice to achieve this goal which can also lead to cost reduction. Under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway has been focusing on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. One of the important activities of the pathway is to deploy risk-informed analysis tools to related nuclear industry to support precise representation of safety margins and factors that contribute to cost and safety. The tools therefore need highest technical maturity so that industry can use immediately with strong credibility. The tools should have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway, therefore, have been performing a comprehensive assessment of technical maturity and verification and validation (V&V) status of selected tools to improve adaptability to the industry. The technical maturity assessment includes three work scope: (a) define requirements based on risk-informed concept; (b) investigate and review development and V&V status for technical maturity assessment; and (c) identify technical gap and propose improvement to meet RISA toolkit requirements. The Requirement Traceability Matrix (RTM) concept was used to capture the requirements from user and developer of the project and/or software. The importance of each requirements was evaluated by Phenomena Identification and Ranking Technology (PIRT) which systematically gathers information and ranks the importance of the information. Finally, degree of the maturity was measured by Technology Readiness Level (TRL) for estimating the maturity of the technologies during the development and acquisition phase of certain technology. This paper summarizes development of assessment method and technical maturity evaluation of multi-purpose probabilistic risk analysis tool RAVEN.

, PIRT↗