Monte Carlo Alpha Iteration Algorithm for a Subcritical System Analysis. (3rd September 2015)

• Record Type: Journal Article
• Authors: Shim, Hyung Jin; Jang, Sang Hoon; Kang, Soo Min
• Other Names: Giusti Valerio Academic Editor.
• Is Part Of: Science and technology of nuclear installations. Volume 2015(2015)
• Publication Date: 2015-09-03
• Subjects: Nuclear engineering -- Periodicals; Nuclear facilities -- Periodicals; Nuclear engineering; Nuclear facilities; Electronic journals; Periodicals; 621.48
• DOI: 10.1155/2015/859242
• Languages: English
• ISSNs: 1687-6075

Abstract

Abstract : The α - k iteration method which searches the fundamental mode alpha-eigenvalue via iterative updates of the fission source distribution has been successfully used for the Monte Carlo (MC) alpha-static calculations of supercritical systems. However, the α - k iteration method for the deep subcritical system analysis suffers from a gigantic number of neutron generations or a huge neutron weight, which leads to an abnormal termination of the MC calculations. In order to stably estimate the prompt neutron decay constant ( α ) of prompt subcritical systems regardless of subcriticality, we propose a new MC alpha-static calculation method named as the α iteration algorithm. The new method is derived by directly applying the power method for the α -mode eigenvalue equation and its calculation stability is achieved by controlling the number of time source neutrons which are generated in proportion to α divided by neutron speed in MC neutron transport simulations. The effectiveness of the α iteration algorithm is demonstrated for two-group homogeneous problems with varying the subcriticality by comparisons with analytic solutions. The applicability of the proposed method is evaluated for an experimental benchmark of the thorium-loaded accelerator-driven system.