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At least 91 records · Page 5

RELAP-7 User's Guide

The document contains a user's guide on how to run the RELAP-7 code. The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory. RELAP-7 will become the main reactor systems simulation toolkit for the LWRS (Light Water Reactor Sustainability) program’s RISMC (Risk Informed Safety Margin Characterization) effort and the next generation tool in the RELAP reactor safety/systems analysis application series. RELAP-7 is written with object oriented programming language C++. A number of example problems and their associated input files are presented in this document to guide users to run the RELAP-7 code starting with simple pipe problems to problems with increasing complexity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Flooding Capability for River-based Scenarios

This report describes the initial investigation into modeling and simulation tools for application of riverine flooding representation as part of the Risk-Informed Safety Margin Characterization (RISMC) Pathway external hazards evaluations. The report provides examples of different flooding conditions and scenarios that could impact river and watershed systems. Both 2D and 3D modeling approaches are described.

97 MATHEMATICS AND COMPUTING↗

Flooding Fragility Experiments and Prediction

This report describes the work that has been performed on flooding fragility, both the experimental tests being carried out and the probabilistic fragility predictive models being produced in order to use the text results. Flooding experiments involving full-scale doors have commenced in the Portal Evaluation Tank. The goal of these experiments is to develop a full-scale component flooding experiment protocol and to acquire data that can be used to create Bayesian regression models representing the fragility of these components. This work is in support of the Risk-Informed Safety Margin Characterization (RISMC) Pathway external hazards evaluation research and development.

54 ENVIRONMENTAL SCIENCES↗

Smooth Particle Hydrodynamics-based Wind Representation

As a result of the 2011 accident at the Fukushima Dai-ichi NPP and other operational NPP experience, there is an identified need to better characterize and evaluate the potential impacts of externally generated hazards on NPP safety. Due to the ubiquitous occurrence of high winds around the world and the possible extreme magnitude of the hazard that has been observed, the assessment of the impact of the high-winds hazard has been identified as an important activity by both NPP owner-operators and regulatory authorities. However, recent experience obtained from the conduct of high-winds risk assessments indicates that such activities have been both labor-intensive and expensive to perform. Additionally, the existing suite of methods and tools to conduct such assessments (which were developed decades ago) do not make use of modern computational architectures (e.g., parallel processing, object-oriented programming techniques, or simple user interfaces) or methods (e.g., efficient and robust numerical-solution schemes). As a result, the current suite of methods and tools will rapidly become obsolete. Physics-based 3D simulation methods can provide information to assist in the RISMC PRA methodology. This research is intended to determine what benefits SPH methods could bring to high-winds simulations for the purposes of assessing their potential impact on NPP safety. The initial investigation has determined that SPH can simulate key areas of high-wind events with reasonable accuracy, compared to other methods. Some problems, such as simulation voids, need to be addressed, but possible solutions have been identified and will be tested with continued work. This work also demonstrated that SPH simulations can provide a means for simulating debris movement; however, further investigations into the capability to determine the impact of high winds and the impacts of wind-driven debris that lead to SSC failures need to be done. SPH simulations alone would be limited in size and computation time. An advanced method of combing results from grid-based methods with SPH through a data-driven model is proposed. This method could allow for more accurate simulation of particle movement near rigid bodies even with larger SPH particle sizes. If successful, the data-driven model would eliminate the need for a SPH turbulence model and increase the simulation domain size. Continued research beyond the scope of this project will be needed in order to determine the viability of a data-driven model.

17 WIND ENERGY↗

Enhancements to the RAVEN code in FY16

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN has currently reached a good level of maturity in terms of deployed state-of-art and advanced capabilities. The main subject of this report is to show the activities that have been recently accomplished: • Implementation of ensemble modeling for time-series, and • initial implementation of model validation for surrogate models, and • advanced visualization capability for topology based data analysis The development of ensemble modeling for time-series has been performed in order to begin tackling the needs of those RISMC applications that need to communicate 1-Dimensional information (e.g. power histories, etc.) among different models. In this document the implementation details and an application example is reported. The second subject of this report is about the initial development of methods, within the RAVEN framework, to assess the validity of the predictive capabilities of surrogate models. Indeed, after the construction of a surrogate tight to a certain physical model, it is crucial to assess the goodness of its representation, in order to be confident with its prediction. In this initial activity, a cross-validation technique has been employed. This report will highlight the implementation details and proof its correct implementation by an application example. The final subject of this report is about the implementation of advanced visualization capability in RAVEN, for interactive data analysis. Indeed, RAVEN offers several post-processing capabilities that can structurally decompose data extracted from experimental results offering both data clustering/partitioning and dimensionality reduction techniques. A disadvantage of the workflow available in RAVEN is that it treats these as black box operations and the user is expected to know specific information about their data including the number of partitions to expect in some cases or the “correct” parameter settings for a particular algorithm. In order to overcome this limitation, it has been added an interactive user interface that can be run in RAVEN to explore different parameter settings on the fly specifically for the topological post-processor and allows the user to explore the data interactively. The design of this user interface is generalizable to other algorithms and can be used as a model to generate more dynamic and user-friendly visualization capabilities within RAVEN.

97 MATHEMATICS AND COMPUTING↗

Risk-Informed External Hazards Analysis for Seismic and Flooding Phenomena for a Generic PWR

This report describes the activities performed during the FY2017 for the US-DOE Light Water Reactor Sustainability Risk-Informed Safety Margin Characterization (LWRS-RISMC), Industry Application #2. The scope of Industry Application #2 is to deliver a risk-informed external hazards safety analysis for a representative nuclear power plant. Following the advancements occurred during the previous FYs (toolkits identification, models development), FY2017 focused on: increasing the level of realism of the analysis; improving the tools and the coupling methodologies. In particular the following objectives were achieved: calculation of buildings pounding and their effects on components seismic fragility; development of a SAPHIRE code PRA models for 3-loops Westinghouse PWR; set-up of a methodology for performing static-dynamic PRA coupling between SAPHIRE and EMRALD codes; coupling RELAP5-3D/RAVEN for performing Best-Estimate Plus Uncertainty analysis and automatic limit surface search; and execute sample calculations for demonstrating the capabilities of the toolkit in performing a risk-informed external hazards safety analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Improved Safety Margin Characterization of Risk from Loss of Offsite Power

Original intent: The original intent of this task was “support of the Risk-Informed Safety Margin Characteristic (RISMC) methodology in order” “to address … efficiency of computation so that more accurate and cost-effective techniques can be used to address safety margin characterizations” (S. M. Hess et al., “Risk-Informed Safety Margin Characterization,” Procs. ICONE17, Brussels, July 2009, CD format). It was intended that “in Task 1 itself this improvement will be directed toward upon the very important issue of Loss of Offsite Power (LOOP) events,” more specifically toward the challenge of efficient computation of the multidimensional nonrecovery integral that has been discussed by many previous contributors to the theory of nuclear safety. It was further envisioned that “three different computational approaches will be explored,” corresponding to the three subtasks listed below; deliverables were tied to the individual subtasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Risk-Informed Systems Analysis (RISA) Dynamic Fire PRA Roadmap

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 initial investigation into modeling and simulation tools for application of fire as part of the Risk-Informed Systems Analysis (RISA), formerly Risk-Informed Safety Margin Characterization (RISMC). The report provides a framework of how 3D modeling and simulation techniques could be combined with a dynamic Probabilistic Risk Analysis (PRA) to reduce compounding conservatism present in current Fire PRA methods. Electrical Power Research Institute has analyzed current Fire PRA practices and identified the most significant contributors to risk and areas for improving analysis. This framework describes how to apply dynamic PRA and simulation methods for key contributors/scenarios, credit missing factors of manual fire suppression, and applying conditional probabilities.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Probabilistic Economic Valuation of Safety Margin Management

The goal of this project was to explore a new methodology for evaluation of potential safety margin upgrades to add a new instrument to the Risk Informed Safety Margin Characterization (RISMC) toolkit. To this end, the RAVEN code developed by the Idaho National Laboratory was used to perform a cost-benefit analysis of several potential power plant safety upgrades to compare the material cost of the upgrades with the probabilistic benefit of avoiding accident scenario consequences to find the most cost-effective safety upgrades. By coupling RAVEN to MELCOR to drive Monte-Carlo method stochastic parameter analysis and using data from existing nuclear codes, as well as MELCOR’s radionuclide relocation tracking capabilities, the radionuclide release source term activity in a severe accident scenario can be estimated. Severe Accident Mitigation upgrades were benchmarked against the Hardened Containment Ventilation upgrade mandated by the USNRC for Mk1 BWRs using dollars spent per Curie of release prevented as a metric by which to evaluate the economic efficacy of the upgrades. Additionally, Fault Tree/Event Tree-based analyses were performed to compare older methods of evaluation to the methodology pioneered in this work, and Monthly Operating Report (MORP) outage data was analyzed for insights into power plant outage optimization and reduction.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A risk-informed approach to safety margins analysis

The Risk Informed Safety Margins Characterization (RISMC) Pathway is a systematic approach developed to characterize and quantify safety margins of nuclear power plant structures, systems and components. The model has been tested on the Advanced Test Reactor (ATR) at Idaho National Lab.

99 GENERAL AND MISCELLANEOUS↗

Risk Informed Margins Management as part of Risk Informed Safety Margin Characterization

The ability to better characterize and quantify safety margin is important to improved decision making about Light Water Reactor (LWR) design, operation, and plant life extension. A systematic approach to characterization of safety margins and the subsequent margin management options represents a vital input to the licensee and regulatory analysis and decision making that will be involved. In addition, as research and development in the LWR Sustainability (LWRS) Program and other collaborative efforts yield new data, sensors, and improved scientific understanding of physical processes that govern the aging and degradation of plant SSCs needs and opportunities to better optimize plant safety and performance will become known. To support decision making related to economics, readability, and safety, the Risk Informed Safety Margin Characterization (RISMC) Pathway provides methods and tools that enable mitigation options known as risk informed margins management (RIMM) strategies.

97 MATHEMATICS AND COMPUTING↗

Overview of New Tools to Perform Safety Analysis: BWR Station Black Out Test Case

Dynamic Probabilistic Risk Assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP, MELCOR) with simulation controller codes (e.g., RAVEN, ADAPT). While system simulator codes accurately model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic, operating procedures) and stochastic (e.g., component failures, parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by: 1) sampling values of a set of parameters from the uncertainty space of interest (using the simulation controller codes), and 2) simulating the system behavior for that specific set of parameter values (using the system simulator codes). For complex systems, one of the major challenges in using DPRA methodologies is to analyze the large amount of information (i.e., large number of scenarios ) generated, where clustering techniques are typically employed to allow users to better organize and interpret the data. In this paper, we focus on the analysis of a nuclear simulation dataset that is part of the Risk Informed Safety Margin Characterization (RISMC) Boiling Water Reactor (BWR) station blackout (SBO) case study. We apply a software tool that provides the domain experts with an interactive analysis and visualization environment for understanding the structures of such high-dimensional nuclear simulation datasets. Our tool encodes traditional and topology-based clustering techniques, where the latter partitions the data points into clusters based on their uniform gradient flow behavior. We demonstrate through our case study that both types of clustering techniques complement each other in bringing enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗

Results of a Demonstration Assessment of Passive System Reliability Utilizing the Reliability Method for Passive Systems (RMPS)

Advanced small modular reactor designs include many advantageous design features such as passively driven safety systems that are arguably more reliable and cost effective relative to conventional active systems. Despite their attractiveness, a reliability assessment of passive systems can be difficult using conventional reliability methods due to the nature of passive systems. Simple deviations in boundary conditions can induce functional failures in a passive system, and intermediate or unexpected operating modes can also occur. As part of an ongoing project, Argonne National Laboratory is investigating various methodologies to address passive system reliability. The Reliability Method for Passive Systems (RMPS), a systematic approach for examining reliability, is one technique chosen for this analysis. This methodology is combined with the Risk-Informed Safety Margin Characterization (RISMC) approach to assess the reliability of a passive system and the impact of its associated uncertainties. For this demonstration problem, an integrated plant model of an advanced small modular pool-type sodium fast reactor with a passive reactor cavity cooling system is subjected to a station blackout using RELAP5-3D. This paper discusses important aspects of the reliability assessment, including deployment of the methodology, the uncertainty identification and quantification process, and identification of key risk metrics.

Bucknor, Matthew↗

Study of Data-Driven Mesh-Model Optimization in System Thermal-Hydraulic Simulation

Quantification of nuclear power plant safety risk requires a systematic and yet practical approach to identification of accident scenarios, assessment of their likelihood and consequences. Instrumental to this goal is risk-informed safety margin characterization (RISMC) framework, whose realization requires computationally robust and affordable methods for sufficiently accurate simulation of complex multi-dimensional physical phenomena, such as turbulent and multi-phase flow. The CFD-like correlation-based codes with 3D simulation capability (e.g., GOTHIC) ensure computational efficiency using coarse mesh size and the sub-grid phenomena in the boundary layer that can be captured by adequate constitutive correlations. However, the error sources and user effects on the selection of mesh size and models lead to unpredictable simulation error, while rich High-Fidelity (HF) data from experiments and numerical simulation using validated code or DNS are not fully explored. It would be useful to have a “smart” data-driven multi-scale framework in which the low-resolution models can be “taught” to emulate high-resolution models. The objective of this work is to develop and evaluate a physical-based data-driven mesh-model optimization approach (Optimized Mesh/Model Information System, OMIS) to estimate the simulation error and give advice on the optimized selection of coarse mesh size and Low-Fidelity (LF) models for System Thermal Hydraulic (STH) simulation to achieve accuracy comparable to that of HF models. This approach takes advantages of computational efficiency of coarse-mesh simulation and application of Machine Learning (ML) algorithms.

97 MATHEMATICS AND COMPUTING↗

RISK-INFORMED EXTERNAL HAZARDS ANALYSIS BY EEVE TOOLKIT

Introducing risk-informed safety analyses for external events can bring sensible benefits to the nuclear power industry easing the regulatory burden introduced in the aftermath of the Fukushima accident. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Margin Characterization project (LWRS-RISMC), research activities were conducted at INL for developing and applying a toolkit for performing risk-informed external hazards analysis. The “EEVE” (External EVEnts) toolkit, a chain of INL and state-of-the-art codes, was set-up and applied for simulating earthquake-induced transients with internal flooding in a PWR. This was done using methodology set-up for evaluating new data and determining critical areas that would benefit most from advanced analysis methods. The methodology is agnostic and it can be applied to other external hazards than just seismic and flooding (e.g., high winds, intense precipitation, etc.). The first step was the deterministic calculations for evaluating the propagation of a set of earthquakes and for determining the effects on a fire suppression system in an auxiliary building. These deterministic calculations were performed using the LS-DYNA and the OPENSEE structural mechanics codes. Probability failures and event trees of a generic 3-loops Westinghouse PWR were derived from a generic SAPHIRE model. Seismically induced Loss of Offsite Power, Station Blackout, and fire suppression piping failure events were considered. SAPHIRE code allowed a pre-screening of all possible branches of the event tree and a selection of those with the largest Core Damage Frequency increase for further analysis using dynamic PRA methods. INL's EMRALD code performed dynamic PRA calculations of the identified sequences, integrating risk analysis with on-line deterministic safety analysis results (seismically-induced internal flooding calculations by NEUTRINO code and system analysis by RELAP5-3D code). RELAP5-3D Best-Estimate calculations coupled with RAVEN statistical code were used for deriving limit surfaces as function of relevant transient parameters. This data was used by EMRALD for determining the final core status (core damage/core safe). Finally, the coupling of seismic, flooding, system thermal-hydraulic, uncertainty quantification and probabilistic risk analysis for an advanced risk-informed external hazards analysis was demonstrated. Results showed the sensible decrease in the level of conservatism achieved using the developed risk-informed methodology, which allowed also improving the evaluation of the failure modes and failure probabilities of different components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Advanced Computational Accident Scenario Modeling for Safety Margin Economic Analysis

The intent of this research is to establish a new tool in the Risk Informed Safety Margin Characterization (RISMC) tool-kit for the fiscal analysis of potential power plant upgrades. This is being done by providing proof-of-concept of the Safety Margin Economic Evaluation (SMEE) methodology of performing cost-benefit analyses of potential Nuclear Power Plant (NPP) upgrades to allow for more data-driven decision making with regards to nuclear safety. To this end, the RAVEN code developed by the Idaho National Laboratory is being used to perform a cost-benefit analysis of several potential power plant safety upgrades to compare the material cost of the upgrades with the probabilistic benefit of avoiding accident scenario consequences to find the most cost effective safety upgrades. Additionally, the MELCOR and MACCS2 codes developed by the Sandia National Laboratory are being used for accident scenario modeling. Evaluating potential NPP upgrades is concluded by doing a detailed cost-benefit analysis of the upgrades. The cost of the upgrade is the direct material cost of implementing, maintaining, and operating the upgrade at an NPP for the projected duration of its lifetime. The benefit of the upgrade is more complex, and is essentially the Risk avoided, where Risk is defined as Consequences multiplied by Probability. Here, Consequences is the economic impact of a severe accident and/or nuclear release and Probability is the likelihood that an NPP upgrade will prevent or mitigate a severe accident, reducing or even eliminating its Consequences. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Demonstration of NonLinear Seismic Soil Structure Interaction and Applicability to New System Fragility Seismic Curves

Risk calculations should focus on providing best estimate results, and associated insights, for evaluation and decision-making. Specifically, seismic probabilistic risk assessments (SPRAs) are intended to provide best estimates of the various combinations of structural and equipment failures that can lead to a seismic induced core damage event. However, in general this approach has been conservative, and potentially masks other important events (for instance, it was not the seismic motions that caused the Fukushima core melt events, but the tsunami ingress into the facility). SPRAs are performed by convolving the seismic hazard (the frequency of certain magnitude events) with the seismic fragility (the conditional probability of failure of a structure, system, or component given the occurrence of earthquake ground motion). In this calculation, there are three main pieces to seismic risk quantification, 1) seismic hazard and nuclear power plants (NPPs) response to the hazard, fragility or capacity of structures, systems and components (SSC), and systems analysis. Figure 1 provides a high level overview of the risk quantification process. The focus of this research is on understanding and removing conservatism (when possible) in the quantification of seismic risk at NPPs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Seismic Isolation Working Meeting Gap Analysis Report

The ultimate goal in nuclear facility and nuclear power plant operations is operating safety during normal operations and maintaining core cooling capabilities during off-normal events including external hazards. Understanding the impact external hazards, such as flooding and earthquakes, have on nuclear facilities and NPPs is critical to deciding how to manage these hazards to expectable levels of risk. From a seismic risk perspective the goal is to manage seismic risk. Seismic risk is determined by convolving the seismic hazard with seismic fragilities (capacity of systems, structures, and components (SSCs)). There are large uncertainties associated with evolving nature of the seismic hazard curves. Additionally there are requirements within DOE and potential requirements within NRC to reconsider updated seismic hazard curves every 10 years. Therefore opportunity exists for engineered solutions to manage this seismic uncertainty. One engineered solution is seismic isolation. Current seismic isolation (SI) designs (used in commercial industry) reduce horizontal earthquake loads and protect critical infrastructure from the potentially destructive effects of large earthquakes. The benefit of SI application in the nuclear industry is being recognized and SI systems have been proposed, in the American Society of Civil Engineers (ASCE) 4 standard, to be released in 2014, for Light Water Reactors (LWR) facilities using commercially available technology. However, there is a lack of industry application to the nuclear industry and uncertainty with implementing the procedures outlined in ASCE-4. Opportunity exists to determine barriers associated with implementation of current ASCE-4 standard language.

99 GENERAL AND MISCELLANEOUS↗