Fukushima Daiichi accident study : status as of April 2012.
Author(s) -
Randall O. Gauntt,
Donald A. Kalinich,
Jeffrey N Cardoni,
Jesse Phillips,
Andrew Goldmann,
Susan Y. Pickering,
Matthew W. Francis,
Kevin Robb,
L.J. Ott,
Dean Wang,
Curtis Smith,
Shawn W St Germain,
David Schwieder,
Cherie Phelan
Publication year - 2012
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/1055601
Subject(s) - nuclear decommissioning , nuclear engineering , environmental science , nuclear power plant , core (optical fiber) , range (aeronautics) , engineering , nuclear physics , physics , aerospace engineering , telecommunications
In response to the accident at the Fukushima Daiichi nuclear power station in Japan, the U.S. Nuclear Regulatory Commission (NRC) and Department of Energy agreed to jointly sponsor an accident reconstruction study as a means of assessing severe accident modeling capability of the MELCOR code. MELCOR is the state-of-the-art system-level severe accident analysis code used by the NRC to provide information for its decision-making process in this area. The objectives of the project were: (1) collect, verify, and document data on the accidents by developing an information portal system; (2) reconstruct the accident progressions using computer models and accident data; and (3) validate the MELCOR code and the Fukushima models, and suggest potential future data needs. Idaho National Laboratory (INL) developed an information portal for the Fukushima Daiichi accident information. Sandia National Laboratories (SNL) developed MELCOR 2.1 models of the Fukushima Daiichi Units 1, 2, and 3 reactors and the Unit 4 spent fuel pool. Oak Ridge National Laboratory (ORNL) developed a MELCOR 1.8.5 model of the Unit 3 reactor and a TRACE model of the Unit 4 spent fuel pool. The good correlation of the results from the SNL models with the data from the plants and with the ORNL model results provides additional confidence in the MELCOR code. The modeling effort has also provided insights into future data needs for both model development and validation.
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