The OpenMC Monte Carlo particle transport code

A new Monte Carlo code called OpenMC is currently under development at the Massachusetts Institute of Technology as a tool for simulation on high-performance computing platforms. Given that many legacy codes do not scale well on existing and future parallel computer architectures, OpenMC has been developed from scratch with a focus on high performance scalable algorithms as well as modern software design practices. The present work describes the methods used in the OpenMC code and demonstrates the performance and accuracy of the code on a variety of problems.United States. Department of Energy (DE-AC05-00OR22725

Progress and Status of the Openmc Monte Carlo Code

The present work describes the latest advances and progress in the development of the OpenMC Monte Carlo code, an open-source code originating from the Massachusetts Institute of Technology. First, an overview of the development workflow of OpenMC is given. Various enhancements to the code such as real-time XML input validation, state points, plotting, OpenMP threading, and coarse mesh finite difference acceleration are described.United States. Department of Energy. Naval Reactors Division (Rickover Fellowship Program in Nuclear Engineering)United States. Department of Energy (Consortium for Advanced Simulation of Light Water Reactors. Contract DE-AC05-00OR22725)United States. Department of Energy. Office of Advanced Scientific Computing Research (Contract DE-AC02-06CH11357

A Cumulative migration method for computing rigorous transport cross sections and diffusion coefficients for LWR lattices with Monte Carlo

A new method for computing homogenized assembly neutron transport cross sections and diffusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations performed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices. Comparisons of several common transport cross section approximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.Idaho National Laboratory (Contract DE-AC07-05ID14517

Accelerated sampling of the free gas resonance elastic scattering kernel

In this work, we present the derivation and investigation of a new Doppler broadening rejection sampling approach for the exact treatment of resonance elastic scattering in Monte Carlo neutron transport codes. Implemented in OpenMC, this method correctly accounts for the energy dependence of cross sections when treating the thermal motion of target nuclei in elastic scattering events. The method is verified against both stochastic and deterministic reference results in the literature for ²³⁸U resonance scattering. Upscatter percentages and mean scattered energies calculated with the method are shown to agree well with the reference scattering kernel results. Additionally, pin cell and full core k[subscript eff] results calculated with this implementation of the exact resonance scattering kernel are shown to be in close agreement with those in the literature. The attractiveness of the method stems from its improvement upon a computationally expensive rejection sampling procedure employed by an earlier stochastic resonance scattering treatment. With no loss in accuracy, the accelerated sampling algorithm is shown to reduce overall runtime by 3–5% relative to the Doppler broadening rejection correction method for both pin cell and full core benchmark problems. This translates to a 30–40% reduction in runtime overhead.United States. Department of Energy (DE-AC05-00OR22725

Multi-core performance studies of a Monte Carlo neutron transport code

Performance results are presented for a multi-threaded version of the OpenMC Monte Carlo neutronics code using OpenMP in the context of nuclear reactor criticality calculations. Our main interest is production computing, and thus we limit our approach to threading strategies that both require reasonable levels of development effort and preserve the code features necessary for robust application to real-world reactor problems. Several approaches are developed and the results compared on several multi-core platforms using a popular reactor physics benchmark. A broad range of performance studies are distilled into a simple, consistent picture of the empirical performance characteristics of reactor Monte Carlo algorithms on current multi-core architectures.United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Contract DEAC02-06CH11357

Data decomposition of Monte Carlo particle transport simulations via tally servers

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithm in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.United States. Dept. of Energy. Naval Reactors Division. Rickover Fellowship Program in Nuclear EngineeringUnited States. Dept. of Energy. Office of Advanced Scientific Computing Research (Contract DE-AC02-06CH11357)United States. Dept. of Energy (Consortium for Advanced Simulation of Light Water Reactors. Contract DE-AC05-00OR22725

On the use of tally servers in Monte Carlo simulations of light-water reactors

An algorithm for decomposing tally data in Monte Carlo simulations using servers has recently been proposed and analyzed. In the present work, we make a number of refinements to a theoretical performance model of the tally server algorithm to better predict the performance of a realistic reactor simulation using Monte Carlo. The impact of subdividing fuel into annular segments on parameters of the performance model is evaluated and shown to result in a predicted overhead of less than 20% for a PWR benchmark on the Mira Blue Gene/Q supercomputer. Additionally, a parameter space study is performed comparing tally server implementations using blocking and non-blocking communication. Non-blocking communication is shown to reduce the communication overhead relative to blocking communication, in some cases resulting in negative overhead.United States. Dept. of Energy. Office of Advanced Scientific Computing Research (Contract DE-AC02-06CH11357

Monte Carlo domain decomposition for robust nuclear reactor analysis

Monte Carlo (MC) neutral particle transport codes are considered the gold-standard for nuclear simulations, but they cannot be robustly applied to high-fidelity nuclear reactor analysis without accommodating several terabytes of materials and tally data. While this is not a large amount of aggregate data for a typical high performance computer, MC methods are only embarrassingly parallel when the key data structures are replicated for each processing element, an approach which is likely infeasible on future machines. The present work explores the use of spatial domain decomposition to make full-scale nuclear reactor simulations tractable with Monte Carlo methods, presenting a simple implementation in a production-scale code. Good performance is achieved for mesh-tallies of up to 2.39 TB distributed across 512 compute nodes while running a full-core reactor benchmark on the Mira Blue Gene/Q supercomputer at the Argonne National Laboratory. In addition, the effects of load imbalances are explored with an updated performance model that is empirically validated against observed timing results. Several load balancing techniques are also implemented to demonstrate that imbalances can be largely mitigated, including a new and efficient way to distribute extra compute resources across finer domain meshes.United States. Dept. of Energy. Center for Exascale Simulation of Advanced Reactor

Progress toward Monte Carlo–thermal hydraulic coupling using low-order nonlinear diffusion acceleration methods

A new approach for coupled Monte Carlo (MC) and thermal hydraulics (TH) simulations is proposed using low-order nonlinear diffusion acceleration methods. This approach uses new features such as coarse mesh finite difference diffusion (CMFD), multipole representation for fuel temperature feedback on microscopic cross sections, and support vector machine learning algorithms (SVM) for iterations between CMFD and TH equations. The multipole representation method showed small differences of about 0.3% root mean square (RMS) error in converged assembly source distribution compared to a conventional MC simulation with ACE data at the same temperature. This is within two standard deviations of the real uncertainty. Eigenvalue differences were on the order of 10 pcm. Support vector machine regression was performed on-the-fly during MC simulations. Regression results of macroscopic cross sections parametrized by coolant density and fuel temperature were successful and eliminated the need of partial derivative tables generated from lattice codes. All of these new tools were integrated together to perform MC-CMFD-TH-SVM iterations. Results showed that inner iterations between CMFD-TH-SVM are needed to obtain a stable solution