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Optimal Batch Size Growth for Wielandt Method and Superhistory Method
Nuclear Science and Engineering  (IF1.381),  Pub Date : 2021-09-23, DOI: 10.1080/00295639.2021.1968223
Qingquan Pan, Tengfei Zhang, Xiaojing Liu, Yun Cai, Lianjie Wang, Kan Wang

Abstract

In a high dominance ratio system, the problem of slow fission source convergence is faced during the Monte Carlo criticality calculation. The Wielandt method and the Superhistory method have been proven to reduce the dominance ratio. Still, the Wielandt method and the Superhistory method have also proven to be unable to accelerate the convergence of the fission source. With the estimation of errors in the cumulative fission source and the batch size optimization methodology, the optimal batch size growth for the Wielandt method and the Superhistory method is proposed. Compared with the direct simulation with the optimal batch size growth, the Wielandt simulation and the Superhistory simulation better use the optimal batch size growth. A single fuel rod model was tested, and the results show that the new method is helpful for the acceleration of fission source convergence.