The OpenMC Monte Carlo particle transport code

Romano, Paul K.; Forget, Benoit

doi:10.1016/j.anucene.2012.06.040

Cited by 316 publications

(121 citation statements)

References 5 publications

Supporting

Mentioning

116

Contrasting

Unclassified

Order By: Relevance

“…This is consistent with the scaling study in [14], which demonstrates excellent parallel efficiency for particle transport in OpenMC using domain replication. Figure 6 shows results for ∆ as the domain mesh was refined.…”

Section: Domain Decomposition Performancesupporting

confidence: 79%

“…These results motivated the present work, where we implement domain decomposition in a full-physics MC code (OpenMC, [14]) and explore the full-size reactor problem for both tally and particle communication performance characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, traditional parallel MC codes employ full domain replication to take advantage of the embarrassingly-parallel nature of neutral particle tracking. With this scheme, all material and tally data is allocated on each distributed computational node ( [13,14]) and synchronized between fission source iterations: a relatively inexpensive operation ( [15]). Given on-node memory constraints, it is clear that this parallelization scheme is not capable of tackling reactor problems on its own.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Monte Carlo domain decomposition for robust nuclear reactor analysis

et al. 2014

Self Cite

View full text Add to dashboard Cite

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 2.39TB 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 coarse domain meshes.

show abstract

Section: Domain Decomposition Performancesupporting

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Monte Carlo domain decomposition for robust nuclear reactor analysis

et al. 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…This approach has been shown to be highly scalable, (1) but does not lend itself to problems where the memory requirements exceed that of a single node. For the realistic analysis of light-water reactors (LWRs), the memory requirements can be quite severe.…”

Section: Introductionmentioning

confidence: 99%

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

Romano

Forget

Smith

et al. 2014

SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…For the analyses presented in this work, the OpenMC Monte Carlo code is used (Romano and Forget, 2013). Section 2 provides a background of how Monte Carlo methods are used for analyzing reactors.…”

Section: Introductionmentioning

confidence: 99%

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

Herman

Forget

Smith

2015

Annals of Nuclear Energy

Self Cite

View full text Add to dashboard Cite

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 average 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 * Corresponding author Email addresses: bherman@mit.edu (Bryan R. Herman), bforget@mit.edu (Benoit Forget), kord@mit.edu (Kord Smith) Preprint submitted to Annals of Nuclear Energy January 26, 2017 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.

show abstract

The OpenMC Monte Carlo particle transport code

Cited by 316 publications

References 5 publications

Monte Carlo domain decomposition for robust nuclear reactor analysis

Monte Carlo domain decomposition for robust nuclear reactor analysis

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

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

Contact Info

Product

Resources

About