Perturbation based Monte Carlo criticality search in density, enrichment and concentration
2015
Abstract Criticality search is a very important aspect in reactor physics analysis. Due to the advantages of Monte Carlo method and the development of computer technologies, Monte Carlo criticality search is becoming more and more necessary and feasible. Existing Monte Carlo criticality search methods need large amount of individual criticality runs and may have unstable results because of the uncertainties of criticality results. In this paper, a new perturbation based Monte Carlo criticality search method is proposed and discussed. This method only needs one individual criticality calculation with perturbation tallies to estimate k eff changing function using initial k eff and differential coefficients results, and solves polynomial equations to get the criticality search results. The new perturbation based Monte Carlo criticality search method is implemented in the Monte Carlo code RMC, and criticality search problems in density, enrichment and concentration are taken out. Results show that this method is quite inspiring in accuracy and efficiency, and has advantages compared with other criticality search methods.
Keywords:
- Dynamic Monte Carlo method
- Mathematical optimization
- Kinetic Monte Carlo
- Monte Carlo molecular modeling
- Quantum Monte Carlo
- Computational physics
- Monte Carlo method
- Mathematics
- Hybrid Monte Carlo
- Monte Carlo method in statistical physics
- Quasi-Monte Carlo method
- Criticality
- Statistical physics
- Monte Carlo integration
- Correction
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