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The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated. In order to evaluate the impact of these two factors on the safety of the plant, the Risk Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This report focuses, in particular, on the impact of power uprate on the safety of a boiled water reactor system. The case study considered is a loss of off-site power followed by the loss of diesel generators, i.e., a station black out (SBO) event. Analysis is performed by using a thermo-hydraulic code, i.e. RELAP-5, and a stochastic analysis tool currently under development at INL, i.e. RAVEN. Starting from the event tree models contained in SAPHIRE, we built the input file for RELAP-5 that models in great detail system dynamics under SBO conditions. We also interfaced RAVEN with RELAP-5 so that it would be possible to run multiple RELAP-5 simulation runs by changing specific keywords of the input file. We both employed classical statistical tools, i.e. Monte-Carlo, and more advanced machine learning based algorithms to perform uncertainty quantification in order to quantify changes in system performance and limitations as a consequence of power uprate. We also employed advanced data analysis and visualization tools that helped us to correlate simulation outcome such as maximum core temperature with a set of input uncertain parameters. Results obtained gave a detailed overview of the issues associated to power uprate for a SBO accident scenario. We were able to quantify how timing of safety related events were impacted by a higher reactor core power. Such insights can provide useful material to the decision makers to perform risk-infomed safety margins management.
The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impact of these factors on the safety of the plant, the Risk Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This report focuses, in particular, on the application of a RISMC detailed demonstration case study for an emergent issue using the RAVEN and RELAP-7 tools. This case study looks at the impact of a couple of challenges to a hypothetical pressurized water reactor, including: (1) a power uprate, (2) a potential loss of off-site power followed by the possible loss of all diesel generators (i.e., a station black-out event), (3) and earthquake induces station-blackout, and (4) a potential earthquake induced tsunami flood. The analysis is performed by using a set of codes: a thermal-hydraulic code (RELAP-7), a flooding simulation tool (NEUTRINO) and a stochastic analysis tool (RAVEN) - these are currently under development at the Idaho National Laboratory.
The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates and improved operations. In order to evaluate the impact of these factors on the safety of the plant, the Risk-Informed Safety Margin Characterization (RISMC) project aims to provide insights to decision makers through a series of simulations of the plant dynamics for different initial conditions and accident scenarios. This paper presents a case study in order to show the capabilities of the RISMC methodology to assess impact of power uprate of a Boiling Water Reactor system during a Station Black-Out accident scenario. We employ a system simulator code, RELAP5-3D, coupled with RAVEN which perform the stochastic analysis. Lastly, our analysis is performed by: 1) sampling values from a set of parameters from the uncertainty space of interest, 2) simulating the system behavior for that specific set of parameter values and 3) analyzing the outcomes from the set of simulation runs.
This is a DOE milestone report to demonstrate refined BWR SBO simulations with the RELAP-7 code.
In the Risk Informed Safety Margin Characterization (RISMC) approach we want to understand not just the frequency of an event like core damage, but how close we are (or are not) to key safety-related events and how might we increase our safety margins. The RISMC Pathway uses the probabilistic margin approach to quantify impacts to reliability and safety by coupling both probabilistic (via stochastic simulation) and mechanistic (via physics models) approaches. This coupling takes place through the interchange of physical parameters and operational or accident scenarios. In this paper we apply the RISMC approach to evaluate the impact of a power uprate on a pressurized water reactor (PWR) for a tsunami-induced flooding test case. This analysis is performed using the RISMC toolkit: RELAP-7 and RAVEN codes. RELAP-7 is the new generation of system analysis codes that is responsible for simulating the thermal-hydraulic dynamics of PWR and boiling water reactor systems. RAVEN has two capabilities: to act as a controller of the RELAP-7 simulation (e.g., system activation) and to perform statistical analyses (e.g., run multiple RELAP-7 simulations where sequencing/timing of events have been changed according to a set of stochastic distributions). By using the RISMC toolkit, we can evaluate how power uprate affects the system recovery measures needed to avoid core damage after the PWR lost all available AC power by a tsunami induced flooding. The simulation of the actual flooding is performed by using a smooth particle hydrodynamics code: NEUTRINO.
In this paper we evaluate the impact of a power uprate on a pressurized water reactor (PWR) for a tsunami-induced flooding test case. This analysis is performed using the RISMC toolkit: the RELAP-7 and RAVEN codes. RELAP-7 is the new generation of system analysis codes that is responsible for simulating the thermal-hydraulic dynamics of PWR and boiling water reactor systems. RAVEN has two capabilities: to act as a controller of the RELAP-7 simulation (e.g., component/system activation) and to perform statistical analyses. In our case, the simulation of the flooding is performed by using an advanced smooth particle hydrodynamics code called NEUTRINO. The obtained results allow the user to investigate and quantify the impact of timing and sequencing of events on system safety. The impact of power uprate is determined in terms of both core damage probability and safety margins.
The Department of Energy’s (DOE’s) Light Water Reactor Sustainability Program aims to develop and deploy technologies that will make the existing U.S. nuclear fleet more efficient and competitive. The program has developed a standard methodology for determining the impact of new technologies in order to assist nuclear power plant (NPP) operators in building sound business cases. The Advanced Instrumentation, Information, and Control (II&C) Systems Technologies Pathway is part of the DOE’s Light Water Reactor Sustainability (LWRS) Program. It conducts targeted research and development (R&D) to address aging and reliability concerns with the legacy instrumentation and control and related information systems of the U.S. operating light water reactor (LWR) fleet. This work involves two major goals: (1) to ensure that legacy analog II&C systems are not life-limiting issues for the LWR fleet and (2) to implement digital II&C technology in a manner that enables broad innovation and business improvement in the NPP operating model. Resolving long-term operational concerns with the II&C systems contributes to the long-term sustainability of the LWR fleet, which is vital to the nation’s energy and environmental security. The II&C Pathway is conducting a series of pilot projects that enable the development and deployment of new II&C technologies in existing nuclear plants. Through the LWRS program, individual utilities and plants are able to participate in these projects or otherwise leverage the results of projects conducted at demonstration plants. Performance advantages of the new pilot project technologies are widely acknowledged, but it has proven difficult for utilities to derive business cases for justifying investment in these new capabilities. Lack of a business case is often cited by utilities as a barrier to pursuing wide-scale application of digital technologies to nuclear plant work activities. The decision to move forward with funding usually hinges on demonstrating actual cost reductions that can be credited to budgets and thereby truly reduce O&M or capital costs. Technology enhancements, while enhancing work methods and making work more efficient, often fail to eliminate workload such that it changes overall staffing and material cost requirements. It is critical to demonstrate cost reductions or impacts on non-cost performance objectives in order for the business case to justify investment by nuclear operators. The Business Case Methodology (BCM) addresses the ?benefit? side of the analysis—as opposed to the cost side—and how the organization evaluates discretionary projects (net present value (NPV), accounting effects of taxes, discount rates, et cetera). The cost and analysis side is not particularly difficult for the organization and can usually be determined with a fair amount of precision (not withstanding implementation project cost overruns). It is in determining the "benefits" side of the analysis that utilities have more difficulty in technology projects and that is the focus of this methodology.
The fatal event occurred in Fukushima Daiichi NPP, focused the e orts of many R&D organiza- tions towards the comprehensive study of the accident sequence, in order to better understand the phenomenology which took place throughout the whole accident. The development of powerful analytical tools and advanced plant models, underwent a surge since the event occurred in Three Mile Island NPP. From Fukushima Daiichi accident on, plant modeling has been notably enhanced, and furthermore it has pointed out the necessity of having tools capable to provide emergency preparedness and emergency response against this kind of events. This necessity has given rise to the creation of the European FASTNET project, within the Horizon 2020. Nowadays, advanced plant modeling combined with powerful analytical tools, have allowed to obtain more accurate results of severe accident at nuclear power reactors than at any time in the past. FASTNET gathers all these previous e orts, in order to develop tools capable to obtain fast response concerning source term evolution which eventually reaches the environment. The foundation of FASTNET is a large database of accident scenarios. This project is enclosed in the creation of the mentioned database for a Station Blackout scenario in a GE BWR 3 Mark 1 reactor design, by means of the analytical code MELCOR 2.1. Given the fact that source term evolution cannot be conceived without thermal-hydraulic evolution, present work focuses on both elds of study, and attempts to provide a comprehensive analysis of the accident for a reactor technology quite similar as the one of the Unit 1 in Fukushima Daiichi.