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Title: Biases in Monte Carlo eigenvalue calculations

Conference ·
OSTI ID:6880662

The Monte Carlo method has been used for many years to analyze the neutronics of nuclear reactors. In fact, as the power of computers has increased the importance of Monte Carlo in neutronics has also increased, until today this method plays a central role in reactor analysis and design. Monte Carlo is used in neutronics for two somewhat different purposes, i.e., (a) to compute the distribution of neutrons in a given medium when the neutron source-density is specified, and (b) to compute the neutron distribution in a self-sustaining chain reaction, in which case the source is determined as the eigenvector of a certain linear operator. In (b), then, the source is not given, but must be computed. In the first case (the fixed-source'' case) the Monte Carlo calculation is unbiased. That is to say that, if the calculation is repeated ( replicated'') over and over, with independent random number sequences for each replica, then averages over all replicas will approach the correct neutron distribution as the number of replicas goes to infinity. Unfortunately, the computation is not unbiased in the second case, which we discuss here.

Research Organization:
Argonne National Lab., IL (United States)
Sponsoring Organization:
USDOE; USDOE, Washington, DC (United States)
DOE Contract Number:
W-31109-ENG-38
OSTI ID:
6880662
Report Number(s):
ANL/CP-75373; CONF-921209-3; ON: DE93004189
Resource Relation:
Conference: International Association Mathematics and Computers Simulation (IMACS) international symposium on mathematical modelling and computer simulation, Bangalore (India), 7-11 Dec 1992
Country of Publication:
United States
Language:
English