Hitoshi Tamaki

Estimation of Source Term Uncertainty in a Severe Accident With Correlated Variables

The quantitative evaluation of the fission product release to the environment during a severe accident is of great importance. In the present analysis, integral severe accident code MELCOR 1.8.5 has been applied to estimating uncertainty of source term for the accident at Unit 2 of the Fukushima Daiichi nuclear power plant (NPP) as an example and to discussing important models or parameters influential to the source term. Forty-two parameters associated with models for the transportation of radioactive materials were chosen and narrowed down to 18 through a set of screening analysis. These 18 parameters in addition to 9 parameters relevant to in-vessel melt progression obtained by the preceding uncertainty study were input to the subsequent sensitivity analysis by Morris method. This one-factor-at-a-time approach can preliminarily identify inputs which have important effects on an output, and 17 important parameters were selected from the total of 27 parameters through this approach. The selected parameters have been integrated into uncertainty analysis by means of Latin Hypercube Sampling technique and Iman-Conover method, taking into account correlation between parameters. Cumulative distribution functions of representative source terms were obtained through the present uncertainty analysis assuming the failure of suppression chamber. Correlation coefficients between the outputs and uncertain input parameters have been calculated to identify parameters of great influences on source terms, which include parameters related to models on core components failure, models of aerosol dynamic process and pool scrubbing.Copyright

Application of Bayesian nonparametric models to the uncertainty and sensitivity analysis of source term in a BWR severe accident

A full-scope method is constructed to reveal source term uncertainties and to identify influential inputs during a severe accident at a nuclear power plant (NPP). An integrated severe accident code, MELCOR Ver. 1.8.5, is used as a tool to simulate the accident similar to that occurred at Unit 2 of the Fukushima Daiichi NPP. In order to figure out how much radioactive materials are released from the containment to the environment during the accident, Monte Carlo based uncertainty analysis is performed. Generally, in order to evaluate the influence of uncertain inputs on the output, a large number of code runs are required in the global sensitivity analysis. To avoid the laborious computational cost for the global sensitivity analysis via MELCOR, a surrogate stochastic model is built using a Bayesian nonparametric approach, Dirichlet process. Probability distributions derived from uncertainty analysis using MELCOR and the stochastic model show good agreement. The appropriateness of the stochastic model is cross-validated through the comparison with MELCOR results. The importance measure of uncertain input variables are calculated according to their influences on the uncertainty distribution as first-order effect and total effect. The validity of the present methodology is demonstrated through an example with three uncertain input variables.

An integrated approach to source term uncertainty and sensitivity analyses for nuclear reactor severe accidents

Large-scale computer programs simulate severe accident phenomena and often have a moderate-to-large number of models and input variables. Analytical solutions to uncertainty distributions of interested source terms are impractical, and influential inputs on outputs are hard to discover. Runs of such integral codes for complex severe accidents are generally time-consuming and hence computationally expensive. This article presents an integrated approach to uncertainty and sensitivity analyses for nuclear reactor severe accident source terms, with an example which simulates an accident sequence similar to that occurred at Unit 2 of the Fukushima Daiichi Nuclear Power Plant using an integral code, MELCOR. Monte-Carlo-based uncertainty analysis has been elaborated to investigate the released fractions of representative radionuclides, Cs and CsI. In order to estimate the sensitivity of inputs, which have a substantial influence on the core melt progression and the transportation process of radionuclides, a variance decomposition method is applied. Stochastic process, specifically a Dirichlet process, is applied to construct a surrogate model in sensitivity analysis as a substitute of the code. The surrogate model is cross-validated by comparing with corresponding results of MELCOR. The analysis with the simpler model avoids laborious computational cost/load, so that the importance measures for input factors are obtained successfully.

Review of five investigation committees’ reports on the Fukushima Dai-ichi nuclear power plant severe accident: focusing on accident progression and causes1

On March 11, 2011, the Tohoku District-off the Pacific Ocean Earthquake and the subsequent tsunami resulted in the severe core damage at TEPCOs Fukushima Dai-ichi Nuclear Power Plant Units 1–3, involving hydrogen explosions at Units 1, 3, and 4 and the large release of radioactive materials to the environment. Four independent committees were established by the Japanese government, the Diet of Japan, the Rebuild Japan Initiative Foundation, and TEPCO to investigate the accident and published their respective reports. Also, the Nuclear and Industrial Safety Agency carried out an analysis of accident causes to obtain the lessons learned from the accident and made its report public. This article reviews the reports and clarifies the differences in their positions, from the technological point of view, focusing on the accident progression and causes. Moreover, the undiscussed issues are identified to provide insights useful for the near-term regulatory activities including accident investigation by the Nuclear Regulation Authority.

Influence of In-Vessel Melt Progression on Uncertainty of Source Term During a Severe Accident

The influence of the in-vessel melt progression on the uncertainty of source terms was examined in the uncertainty analysis with integral severe accident analysis code MELCOR (Ver. 1.8.5), taking the accident at Unit 2 of the Fukushima Daiichi nuclear power plant as an example. The 32 parameters selected from the rough screening analysis were sampled by Latin hypercube sampling technique in accordance with the uncertainty distributions specified for each parameter. The uncertainty distributions of the outputs, including the source terms of the representative radioactive materials (Cs, CsI, Te and Ba), the total mass of in-vessel H2 generation and the total debris mass released from the reactor pressure vessel to the drywell, were obtained through the uncertainty analysis with an assumption of the failure of drywell. Based on various types of correlation coefficient for each parameter, 9 significant uncertain parameters potentially dominating the source terms were identified. These 9 parameters were transferred to the subsequent sensitivity and uncertainty analyses, in which the influence of the transportation of radioactive materials was taken into account.Copyright