UWFDM-1323 Monte Carlo Isotopic Inventory Analysis for Complex Nuclear Systems
نویسنده
چکیده
Monte Carlo Inventory Simulation Engine or MCise is a newly developed method for calculating isotopic inventory of materials. The method offers the promise of modeling materials with complex processes and irradiation histories, which pose challenges for current deterministic tools. Monte Carlo techniques based on following the history of individual atoms allows those atoms to follow randomly determined flow paths, enter or leave the system at arbitrary locations, and be subjected to radiation or chemical processes at different points in the flow path. The method has strong analogies to Monte Carlo neutral particle transport. The fundamental of analog method is fully developed, including considerations for simple, complex and loop flows. The validity of the analog method is demonstrated with test problems under various flow conditions. The method reproduces the results of a deterministic inventory code for comparable problems. While a successful and efficient parallel implementation has permitted an inexpensive way to improve statistical precision by increasing the number of sampled atoms, this approach does not always provide the most efficient avenue for improvement. Therefore, six variance reduction tools are implemented as alternatives to improve precision of Monte Carlo simulations. Forced Reaction is designed to force an atom to undergo a predefined number of reactions in a given irradiation environment. Biased Reaction Branching is primarily focused on improving statistical results of the isotopes that are produced from rare reaction pathways. Biased Source Sampling is aimed at increasing frequencies of sampling rare initial isotopes as the starting particles. Reaction Path Splitting increases the population by splitting the atom at each reaction point, creating one new atom for each decay or transmutation product. Delta Tracking is recommended for a high-frequency pulsing
منابع مشابه
UWFDM-1282 Monte Carlo Techniques for the Comprehensive Modeling of Isotopic Inventories in Future Nuclear Systems and Fuel Cycles
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