Exponential Convergence Rates for Reduced-Source Monte Carlo Transport in [x,μ] Geometry

摘要

An adaptive reduced-soruce approach is utlizied for a Monte Carlo transport solution for the one-speed finite slab problem in [x,μ] gep,eru/ Although a solution of the underlying problem has been available to arbitrary precision for some tiem, the purpose here is to demsontrate how the convergence afforded by traditional (nonadaptive) Monte Carlo can be improved signficantly, without compromising its precision. It is demonstrated that the reduced-soruce Monte Carlo technique obtains multiple-orcers-of-magnitude improvement over traditional Monte Carlo convergence for the two-dimensional transport problem treated. The goal is that ongoing research will obtain exponential convergence for practical applications thawt are not tractable with methodoogy currently available.