title: Performance of the improved version of monte Carlo code A3MCNP for large-scale shielding problems.
abstract: A3MCNP (Automatic Adjoint Accelerated MCNP) is a revised version of the MCNP Monte Carlo code, which automatically prepares variance reduction parameters for the CADIS (Consistent Adjoint Driven Importance Sampling) methodology. Using a deterministic 'importance' (or adjoint) function, CADIS performs source and transport biasing within the weight-window technique. The current version of A3MCNP uses the three-dimensional (3-D) Sn transport TORT code to determine a 3-D importance function distribution. Based on simulation of several real-life problems, it is demonstrated that A3MCNP provides precise calculation results with a remarkably short computation time by using the proper and objective variance reduction parameters. However, since the first version of A3MCNP provided only a point source configuration option for large-scale shielding problems, such as spent-fuel transport casks, a large amount of memory may be necessary to store enough points to properly represent the source. Hence, we have developed an improved version of A3MCNP (referred to as A3MCNPV) which has a volumetric source configuration option. This paper describes the successful use of A3MCNPV for a concrete cask neutron and gamma-ray shielding problem, and a PWR dosimetry problem.
authors.affiliation: Mitsubishi Heavy Industries, Yokohama 220-8401, Japan. masaki_omura@mhi.co.jp
authors.forename: M
authors.initials: M
authors.lastname: Omura
authors.forename: Y
authors.initials: Y
authors.lastname: Miyake
authors.forename: T
authors.initials: T
authors.lastname: Hasegawa
authors.forename: K
authors.initials: K
authors.lastname: Ueki
authors.forename: O
authors.initials: O
authors.lastname: Sato
authors.forename: A
authors.initials: A
authors.lastname: Haghighat
authors.forename: G E
authors.initials: GE
authors.lastname: Sjoden
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017076:Computer-Aided Design; D003252:Construction Materials / Q000032:analysis*; D004867:Equipment Design; D019544:Equipment Failure Analysis / Q000379:methods; D015233:Models, Statistical; D009010:Monte Carlo Method; D009716:Numerical Analysis, Computer-Assisted; D011829:Radiation Dosage; D011835:Radiation Protection / Q000295:instrumentation* / Q000379:methods; D011874:Radiometry / Q000379:methods*; D012542:Scattering, Radiation; D012984:Software