This paper gives an overview of OpenMC, an open source Monte Carlo particle transport code recently developed at the Massachusetts Institute of Technology. OpenMC uses continuous-energy cross sections and a constructive solid geometry representation, enabling high-fidelity modeling of nuclear reactors and other systems. Modern, portable input/output file formats are used in OpenMC: XML for input, and HDF5 for output. High performance parallel algorithms in OpenMC have demonstrated near-linear scaling to over 100,000 processors on modern supercomputers. Other topics discussed in this paper include plotting, CMFD acceleration, variance reduction, eigenvalue calculations, and software development processes.

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The method of characteristics (MOC) is a numerical integration technique for partial differential equations, and has seen widespread use for reactor physics lattice calculations. The exponential growth in computing power has finally brought the possibility for high-fidelity full core MOC calculations within reach. The OpenMOC code is being developed at the Massachusetts Institute of Technology to investigate algorithmic acceleration techniques and parallel algorithms for MOC. OpenMOC is a free, open source code written using modern software languages such as C/C++ and CUDA with an emphasis on extensible design principles for code developers and an easy to use Python interface for code users. The present work describes the OpenMOC code and illustrates its ability to model large problems accurately and efficiently.

A new approach for direct Doppler broadening of nuclear data in Monte Carlo simulations is proposed based on the multipole representation. The multipole representation transforms resonance parameters into a set of poles and residues only some of which exhibit a resonant behavior. A method is introduced to approximate the contribution to the background cross section in an effort to reduce the number of poles needing to be broadened. The multipole representation results in memory savings of 1-2 orders of magnitude over comparable techniques. This approach provides a simple way of computing nuclear data at any temperature which is essential for multi-physics calculations, while having a minimal memory footprint which is essential for scalable high performance computing. The concept is demonstrated on two major isotopes of uranium (U-235 and U-238) and implemented in the OpenMC code. Two LEU critical experiments were solved and showed great accuracy with a small loss of efficiency (10-30%) over a single-temperature pointwise library.

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