Search NASA⌕ Search

SEARCH · Search NASA

Results for “MELCOR Code”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

An Assessment of MELCOR 2.1: Containment Thermal-Hydraulic Tests in the Heissdampfreaktor (HDR) Facility

MELCOR is being developed at Sandia National Laboratories for the U.S. Nuclear Regulatory Commission. MELCOR is a fully integrated code (encompassing the reactor coolant system and the containment building) that models the progression of postulated accidents in light water reactor power plants. It provides a capability for independently auditing analyses submitted by reactor manufacturers and utilities. In order to assess the adequacy of containment thermal - hydraulic modeling incorporated in the MELCOR code, a key containment test facility was analyzed. This report documents MELCOR code calculations for simulating steam - water blowdown tests performed in the Heissdampfreaktor ( HDR) de-commissioned containment facility located near Frankfurt , Germany . These tests are a series of blowdown experiments in a large scaled test facility ; including some tests with the addition of hydrogen release which are intended to simulate a variety of postulated break s inside large containment buildings. The key objectives of this MELCOR assessment are to study: (1) the expansion and transport of high energy steam - water releases, (2) heat and mass transfer to structural passive heat sinks, and (3) containment gas mixing and stratification. Moreover, MELCOR results are compared to the CONTAIN code for the same tests.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Development of a CRAB-MELCOR Framework for Utilization in Support of Estimating a Realistic Mechanistic Source Term for Microreactors

Research and development activities are being performed to link important advanced non-light-water microreactor technology research and development activities sponsored by the U.S. Department of Energy’s Office of Nuclear Energy with regulatory requirements and critical licensing needs likely to impact the deployment of a domestic commercial microreactor fleet. This report presents the progress of ongoing work to perform a gap analysis of the coupling of the Nuclear Regulatory Commission’s Comprehensive Reactor Analysis Bundle code suite and MELCOR code. This key Fiscal Year 2023 research reflects microreactor regulatory needs and challenges noted by industry, Department of Energy, and Nuclear Regulatory Commission stakeholders.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

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↗
DOE OSTI2012

The Fukushima Daiichi Accident Study Information Portal

This paper presents a description of The Fukushima Daiichi Accident Study Information Portal. The Information Portal was created by the Idaho National Laboratory as part of joint NRC and DOE project to assess the severe accident modeling capability of the MELCOR analysis code. The Fukushima Daiichi Accident Study Information Portal was created to collect, store, retrieve and validate information and data for use in reconstructing the Fukushima Daiichi accident. In addition to supporting the MELCOR simulations, the Portal will be the main DOE repository for all data, studies and reports related to the accident at the Fukushima Daiichi nuclear power station. The data is stored in a secured (password protected and encrypted) repository that is searchable and accessible to researchers at diverse locations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Identification and Resolution of Gaps in Mechanistic Source Term and Consequence Analysis Modeling for Molten Salt Reactors Salt Spill Scenarios

This report represents an assessment of the gaps in Mechanistic Source Term (MST) and consequence assessment modeling for Molten Salt Reactors (MSRs). The current capabilities for MELCOR and the MELCOR Accident Code System (MACCS) are discussed, along with updates needed in order to address specific needs for MSRs. A test plan developed by Argonne National Laboratories is discussed as addressing some of these gaps, while some will require additional attention. Further recommendations are made on addressing these gaps. This report satisfies the DOE NE Milestone M2RD-21SN0601061 to leverage MELCOR and MACCS to identify parameters of importance for source term assessments for salt spill experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

SOFE2023 Presentation: "Tritium Safety and Sensitivity Analysis of Tritium Extraction eXperiment (TEX) PbLi Loop Using MELCOR-TMAP"

The efficient extraction of tritium from the breeder blanket (BB) in a fusion reactor is vital for maintaining the tritium economy for a sustainable and self-sufficient fusion power plant. The vacuum permeator (VP) design is one of several promising technology platforms for extracting tritium from the BB with the advantages of being capable of operating continuously at high temperatures with the aim of achieving high tritium extraction efficiencies. The Tritium Extraction eXperiment (TEX), under construction at the Safety and Tritium Applied Research (STAR) Facility at Idaho National Laboratory (INL), is designed to test the viability of VP technology by introducing atomic hydrogen (H, D, and T) from a source permeator (SP) into a forced convection lead lithium eutectic (PbLi) loop and determining the hydrogen extraction rates from the vanadium VP. Presented here is a computational analysis of the hydrogen inventory and permeation behavior in TEX using the hydrogen transport and accident analysis code MELCOR-TMAP developed at INL. The results of a sensitivity analysis based on MELCOR-TMAP simulations of hydrogen extraction efficiencies from the TEX test section using varying PbLi flow rates, hydrogen source rates from the SP, and material property uncertainties are also reported. Operation scenarios for TEX in consideration of the analyses based on results from MELCOR-TMAP are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Fukushima Daiichi Unit 1 Ex-Vessel Prediction: Core Concrete Interaction

Lower head failure and corium concrete interaction were predicted to occur at Fukushima Daiichi Unit 1 (1F1) by several different system-level code analyses, including MELCOR v2.1 and MAAP5. Although these codes capture a wide range of accident phenomena, they do not contain detailed models for ex-vessel core melt behavior. However, specialized codes exist for analysis of ex-vessel melt spreading (e.g., MELTSPREAD) and long-term debris coolability (e.g., CORQUENCH). On this basis, an analysis was carried out to further evaluate ex-vessel behavior for 1F1 using MELTSPREAD and CORQUENCH. Best-estimate melt pour conditions predicted by MELCOR v2.1 and MAAP5 were used as input. MELTSPREAD was then used to predict the spatially dependent melt conditions and extent of spreading during relocation from the vessel. The results of the MELTSPREAD analysis are reported in a companion paper. This information was used as input for the long-term debris coolability analysis with CORQUENCH.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Fukushima Daiichi Unit 1 ex-vessel prediction: Core melt spreading

Lower head failure and corium-concrete interaction were predicted to occur at Fukushima Daiichi Unit 1 (1F1) by several different system-level code analyses, including MELCOR v2.1 and MAAP5. Although these codes capture a wide range of accident phenomena, they do not contain detailed models for ex-vessel core melt behavior. However, specialized codes exist for analysis of ex-vessel melt spreading (e.g., MELTSPREAD) and long-term debris coolability (e.g., CORQUENCH). On this basis, an analysis has been carried out to further evaluate ex-vessel behavior for 1F1 using MELTSPREAD and CORQUENCH. Best-estimate melt pour conditions predicted by MELCOR v2.1 and MAAP5 were used as input. MELTSPREAD was then used to predict the spatially-dependent melt conditions and extent of spreading during relocation from the vessel. Lastly, this information was then used as input for the long-term debris coolability analysis with CORQUENCH that is reported in a companion paper.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Fukushima Daiichi Unit 1 Ex-Vessel Prediction: Core-Concrete Interaction

Lower head failure and corium-concrete interaction were predicted to occur at Fukushima Daiichi Unit 1 (1F1) by several different system-level code analyses, including MELCOR v2.1 and MAAP5. Although these codes capture a wide range of accident phenomena, they do not contain detailed models for ex-vessel core melt behavior. However, specialized codes exist for the analysis of ex-vessel melt spreading (e.g., MELTSPREAD) and long-term debris coolability (e.g., CORQUENCH). On this basis, in this paper an analysis was carried out to further evaluate ex-vessel behavior for 1F1 using MELTSPREAD and CORQUENCH. Best-estimate melt pour conditions predicted by MELCOR v2.1 and MAAP5 were used as input. MELTSPREAD was then used to predict the spatially dependent melt conditions and extent of spreading during relocation from the vessel. The results of the MELTSPREAD analysis are reported in a companion paper. This information was used as input for the long-term debris coolability analysis with CORQUENCH. For the MELCOR-based melt pour scenario, CORQUENCH predicted the melt would readily cool within 2.5 h after the pour, and the sumps would experience limited ablation (approximately 18 cm) under water-flooded conditions. Finally, for the MAAP-based melt pour scenarios, CORQUENCH predicted that the melt would cool in approximately 22.5 h, and the sumps would experience approximately 65 cm of concrete ablation under water-flooded conditions.

42 ENGINEERING↗
DOE OSTI2015

Analyzing simulation-based PRA data through traditional and topological clustering: A BWR station blackout case study

Here, dynamic probabilistic risk assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP and MELCOR) with simulation controller codes (e.g., RAVEN and ADAPT). Whereas system simulator codes model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic and operating procedures) and stochastic (e.g., component failures and parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by sampling values of a set of parameters and simulating the system behavior for that specific set of parameter values. For complex systems, a major challenge in using DPRA methodologies is to analyze the large number of scenarios generated, where clustering techniques are typically employed to better organize and interpret the data. In this paper, we focus on the analysis of two nuclear simulation datasets that are part of the risk-informed safety margin characterization (RISMC) boiling water reactor (BWR) station blackout (SBO) case study. We provide the domain experts a software tool that encodes traditional and topological clustering techniques within an interactive analysis and visualization environment, for understanding the structures of such high-dimensional nuclear simulation datasets. We demonstrate through our case study that both types of clustering techniques complement each other for enhanced structural understanding of the data.

97 MATHEMATICS AND COMPUTING↗