Monte Carlo perturbation algorithms exploit new computer architecturesFunded under: JRC-REACTSAFE 6C
Fundamental aspects of correlated sampling and differential operator procedures applied to systems of linear equations modelling Markov processes are investigated. Algorithms providing sensitivities (gradients, Jacobians) and perturbation estimates obtained by a single simulation experiment are described in detail. In this context it becomes evident that the algorithm for calculating the Jacobians may benefit considerably from the use of vector processors. Mathematical proofs are provided which show that under most conditions a finite relative variance can be obtained for arbitrarily small parameter variations.
Bibliographic Reference: Paper presented: Mathematical Methods and Supercomputing in Nuclear Applications, Karlsruhe (DE), April 19-23, 1993
Availability: Available from (1) as Paper EN 37356 ORA
Record Number: 199310492 / Last updated on: 1994-11-29
Original language: en
Available languages: en