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Source term uncertainty analysis; Probabilistic approaches and applications to a BWR severe accident

Zheng, X.; Ito, Hiroto; Tamaki, Hitoshi; Maruyama, Yu

A suite of methods has been established to quantitatively estimate uncertainties in source term analysis during a nuclear reactor severe accident. The accident sequence occurred at Unit 2 of the Fukushima Daiichi Nuclear Power Plant is taken as an example. The approach mainly consists of four steps: screening analysis, random sampling, numerical computation and verification of uncertainty distributions. First, by using an individually randomized one-factor-at-a-time screening method, a group of variables are preliminarily determined as uncertain inputs. Second, appropriate probability distributions are assigned to input variables. Random samples are generated using Latin Hypercube sampling with the consideration of rank correlation. Third, random samples of variables are inputted into MELCOR 1.8.5. Numerical simulation with multiple code runs is implemented. Finally, uncertainty distributions for representative source terms are obtained and verified. The technique of Bayesian nonparametric density estimation is applied to obtain probability density functions of source terms. The difference of probability density functions is evaluated through the comparison based on the Kullback-Leibler (KL) divergence. With the subjective judgment of small enough KL divergence, after a certain number of numerical computations, the uncertainty distributions of representative source terms are considered as stable enough as reliable results.



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