Joint International Conference on Supercomputing in Nuclear Applications and Monte Carlo 2013 (SNA + MC 2013) La Cité des Sciences et de l’Industrie, Paris, France, October 27–31, 2013 Accelerated equilibrium core composition search using a new MCNP-based simulator Jeffrey E. Seifried 1 , Phillip M. Gorman 1 , Jasmina L. Vujic 1 , and Ehud Greenspan 1 1 University of California, Berkeley, Department of Nuclear Engineering, MC 1730, Berkeley, CA 94720 MocDown is a new Monte Carlo depletion and recycling simulator which couples neutron transport with MCNP and transmutation with ORIGEN. This modular approach to depletion allows for flexible operation by incorporating the accelerated progression of a complex fuel processing scheme towards equilibrium and by allowing for the online coupling of thermo-fluids feedback. MocDown also accounts for the variation of decay heat with fuel isotopics evolution. In typical cases, MocDown requires just over a day to find the equilibrium core composition for a multi-recycling fuel cycle, with a self-consistent thermo-fluids solution–a task that required between one and two weeks using previous Monte Carlo-based approaches. KEYWORDS: Monte Carlo neutron transport, depletion, recycling, parallel, decay heat, conversion, thermo-fluids, coupled neutronics thermo-fluids I. Introduction Existing core simulation codes are either insufficiently accurate or computationally inefficient in the search for the equilibrium composition of recently proposed reduced-moderation boiling water reactor designs. (1, 2) The cores of such reactors feature a strongly varying axial coolant density distribution, hard and axially varying neutron spectra, and large axially varying flux gradients, which together mandate the use of continuous-energy three-dimensional Monte Carlo neutron transport. Tight physi- cal coupling between the spatial variation of the fission power density and coolant density require tight numerical coupling between neutron transport and thermo-fluids models. Interest in, primarily, the equilibrium cycle necessitates an efficient means of finding the equilibrium core composition. This paper describes a new tool named MocDown which meets these and other needs. In section II, the general design and programming approaches which were taken in developing MocDown are discussed. Then, in section III, the RBWR- Th core design, which serves for numerical illustrations of MocDown’s utility, is briefly described. Next, section IV de- scribes and demonstrates the accelerated recycling scheme that MocDown takes in seeking equilibrium core compositions for multi-recycling fuel cycles. Section V shows an example of the online thermo-fluids coupling. Finally, in section VI, Moc- Down’s simple approach for source rate scaling, which accounts for isotopic composition-dependent decay heat, is described. II. MocDown general programming characteristics MocDown is an advanced Monte Carlo depletion simula- tor. Just as MOCUP, (3) MONTEBURNS, (4) IMOCUP, (5) Mocup.py, (6) VESTA, (7) and countless other codes do, Moc- Down simulates the depletion of nuclear reactor cores by cou- pling neutron transport with MCNP (8) and transmutation with ORIGEN2.2. (9) In addition, it facilitates the search for the equilibrium composition of multi-recycling fuel cycles in an efficient manner, enables online coupling of thermo-fluids mod- els, and employs a simple approach towards neutron source rate scaling. MocDown also incorporates many other programming best practices which provide for a robust, reliable experience for users. MocDown is written in object-oriented Python 3. Auxil- iary operations, like thermo-fluids models and fuel processing, are completely customizable in external modules. These mod- ules take advantage of interface methods (e.g., GetBurnCells or GetIsDecayStep), which pass all data in memory and eliminate error prone I/O and file parsing. For example, a Python 3 library, which offers IAPWS-IF97 steam table prop- erty lookups within Python, (10) was readily found and integrated into a simple thermo-fluids model. This modular approach also allows MocDown to remain separate and intact for a number of projects, greatly simplifying version control and software verification. Execution of ORIGEN2.2 is concurrently threaded using standard Python 3 libraries, enabling the depletion of twenty regions in parallel (although this number depends upon the hardware, it is thought to be a typical number). When depleting large systems in parallel, runtime speedups of 6-7× have been observed over serial execution. Transmutation constants (region-wise total flux magnitudes and region-, isotope-, and reaction-wise one-group cross- sections) are extracted with a single MCNP tally which is dy- namically generated. This removes restraints upon the number of regions or isotopes that can be depleted. In contrast, MON- TEBURNS and MOCUP use one tally per depletion region and can tolerate only a certain number of regions, based upon their configuration and the version of MCNP. The isotopes