Download or read book Domain Decomposition for Monte Carlo Particle Transport Simulations of Nuclear Reactors written by Nicholas Edward Horelik and published by . This book was released on 2015 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo (MC) neutral particle transport methods have long been considered the gold-standard for nuclear simulations, but high computational cost has limited their use significantly. However, as we move towards higher-fidelity nuclear reactor analyses the method has become competitive with traditional deterministic transport algorithms for the same level of accuracy, especially considering the inherent parallelism of the method and the ever-increasing concurrency of modern high performance computers. Yet before such analysis can be practical, several algorithmic challenges must be addressed, particularly in regards to the memory requirements of the method. In this thesis, a robust domain decomposition algorithm is proposed to alleviate this, along with models and analysis to support its use for full-scale reactor analysis. Algorithms were implemented in the full-physics Monte Carlo code OpenMC, and tested for a highly-detailed PWR benchmark: BEAVRS. The proposed domain decomposition implementation incorporates efficient algorithms for scalable inter-domain particle communication in a manner that is reproducible with any pseudo-random number seed. Algorithms are also proposed to scalably manage material and tally data with on-the-fly allocation during simulation, along with numerous optimizations required for scalability as the domain mesh is refined and divided among thousands of compute processes. The algorithms were tested on two supercomputers, namely the Mira Blue Gene/Q and the Titan XK7, demonstrating good performance with realistic tallies and materials requiring over a terabyte of aggregate memory. Performance models were also developed to more accurately predict the network and load imbalance penalties that arise from communicating particles between distributed compute nodes tracking different spatial domains. These were evaluated using machine properties and tallied particle movement characteristics, and empirically validated with observed timing results from the new implementation. Network penalties were shown to be almost negligible with per-process particle counts as low as 1000, and load imbalance penalties higher than a factor of four were not observed or predicted for finer domain meshes relevant to reactor analysis. Load balancing strategies were also explored, and intra-domain replication was shown to be very effective at improving parallel efficiencies without adding significant complexity to the algorithm or burden to the user. Performance of the strategy was quantified with a performance model, and shown to agree well with observed timings. Imbalances were shown to be almost completely removed for the finest domain meshes. Finally, full-core studies were carried out to demonstrate the efficacy of domain-decomposed Monte Carlo in tackling the full scope of the problem. A detailed mesh required for a robust depletion treatment was used, and good performance was demonstrated for depletion tallies with 206 nuclides. The largest runs scored six reaction rates for each nuclide in 51M regions for a total aggregate memory requirement of 1.4TB, and particle tracking rates were consistent with those observed for smaller non-domain- decomposed runs with equivalent tally complexity. These types of runs were previously not achievable with traditional Monte Carlo methods, and can be accomplished with domain decomposition with between 1.4x and 1.75x overhead with simple load balancing.

Download or read book Parallel Algorithms for Monte Carlo Particle Transport Simulation on Exascale Computing Architectures written by Paul Kollath Romano and published by . This book was released on 2013 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo particle transport methods are being considered as a viable option for high-fidelity simulation of nuclear reactors. While Monte Carlo methods offer several potential advantages over deterministic methods, there are a number of algorithmic shortcomings that would prevent their immediate adoption for full-core analyses. In this thesis, algorithms are proposed both to ameliorate the degradation in parallal efficiency typically observed for large numbers of processors and to offer a means of decomposing large tally data that will be needed for reactor analysis. A nearest-neighbor fission bank algorithm was proposed and subsequently implemented in the OpenMC Monte Carlo code. A theoretical analysis of the communication pattern shows that the expected cost is O([square root]N) whereas traditional fission bank algorithms are O(N) at best. The algorithm was tested on two supercomputers, the Intrepid Blue Gene/P and the Titan Cray XK7, and demonstrated nearly linear parallel scaling up to 163,840 processor cores on a full-core benchmark problem. An algorithm for reducing network communication arising from tally reduction was analyzed and implemented in OpenMC. The proposed algorithm groups only particle histories on a single processor into batches for tally purposes - in doing so it prevents all network communication for tallies until the very end of the simulation. The algorithm was tested, again on a full-core benchmark, and shown to reduce network communication substantially. A model was developed to predict the impact of load imbalances on the performance of domain decomposed simulations. The analysis demonstrated that load imbalances in domain decomposed simulations arise from two distinct phenomena: non-uniform particle densities and non-uniform spatial leakage. The dominant performance penalty for domain decomposition was shown to come from these physical effects rather than insufficient network bandwidth or high latency. The model predictions were verified with measured data from simulations in OpenMC on a full-core benchmark problem. Finally, a novel algorithm for decomposing large tally data was proposed, analyzed, and implemented/tested in OpenMC. The algorithm relies on disjoint sets of compute processes and tally servers. The analysis showed that for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead. Tests were performed on Intrepid and Titan and demonstrated that the algorithm did indeed perform well over a wide range of parameters.

Download or read book Scalable Domain Decomposed Monte Carlo Particle Transport written by Matthew Joseph O'Brien and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present the parallel algorithms necessary to run domain decomposedMonte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costlythan the numerical simulation. The main algorithms we consider are:* Domain decomposition of constructive solid geometry: enables extremely largecalculations in which the background geometry is too large to fit in the memory of asingle computational node.* Load Balancing: keeps the workload per processor as even as possible so the calculationruns efficiently.* Global Particle Find: if particles are on the wrong processor, globally resolve theirlocations to the correct processor based on particle coordinate and background domain.* Visualizing constructive solid geometry, sourcing particles, deciding that particlestreaming communication is completed and spatial redecomposition.These algorithms are some of the most important parallel algorithms required for domaindecomposed Monte Carlo particle transport. We demonstrate that our previous algorithmswere not scalable, prove that our new algorithms are scalable, and run some of the algorithmsup to 2 million MPI processes on the Sequoia supercomputer.

Download or read book Monte Carlo Methods for Particle Transport written by Alireza Haghighat and published by CRC Press. This book was released on 2020-08-09 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully updated with the latest developments in the eigenvalue Monte Carlo calculations and automatic variance reduction techniques and containing an entirely new chapter on fission matrix and alternative hybrid techniques. This second edition explores the uses of the Monte Carlo method for real-world applications, explaining its concepts and limitations. Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, it is an ideal textbook and practical guide for nuclear engineers and scientists looking into the applications of the Monte Carlo method, in addition to students in physics and engineering, and those engaged in the advancement of the Monte Carlo methods. Describes general and particle-transport-specific automated variance reduction techniques Presents Monte Carlo particle transport eigenvalue issues and methodologies to address these issues Presents detailed derivation of existing and advanced formulations and algorithms with real-world examples from the author’s research activities

Download or read book Scalable Domain Decomposed Monte Carlo Particle Transport written by and published by . This book was released on 2013 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.

Download or read book Fifth World Congress Quebec Canada 1954 written by and published by . This book was released on 1955 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Monte Carlo Particle Transport Methods written by I. Lux and published by CRC Press. This book was released on 2018-05-04 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this book we try to reach several more-or-less unattainable goals namely: To compromise in a single book all the most important achievements of Monte Carlo calculations for solving neutron and photon transport problems. To present a book which discusses the same topics in the three levels known from the literature and gives us useful information for both beginners and experienced readers. It lists both well-established old techniques and also newest findings.

Download or read book Particle Transport Simulation with the Monte Carlo Method written by Leland Lavele Carter and published by . This book was released on 1975 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Efficient Robust Domain decomposition Algorithm for Particle Monte Carlo written by and published by . This book was released on 2007 with total page 3 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Monte Carlo N Particle Simulations for Nuclear Detection and Safeguards written by John S. Hendricks and published by Springer Nature. This book was released on 2022-09-27 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is a pedagogical, examples-based guide to using the Monte Carlo N-Particle (MCNP®) code for nuclear safeguards and non-proliferation applications. The MCNP code, general-purpose software for particle transport simulations, is widely used in the field of nuclear safeguards and non-proliferation for numerous applications including detector design and calibration, and the study of scenarios such as measurement of fresh and spent fuel. This book fills a gap in the existing MCNP software literature by teaching MCNP software usage through detailed examples that were selected based on both student feedback and the real-world experience of the nuclear safeguards group at Los Alamos National Laboratory. MCNP input and output files are explained, and the technical details used in MCNP input file preparation are linked to the MCNP code manual. Benefiting from the authors’ decades of experience in MCNP simulation, this book is essential reading for students, academic researchers, and practitioners whose work in nuclear physics or nuclear engineering is related to non-proliferation or nuclear safeguards. Each chapter comes with downloadable input files for the user to easily reproduce the examples in the text.

Download or read book Advanced Monte Carlo for Radiation Physics Particle Transport Simulation and Applications written by Andreas Kling and published by Springer Science & Business Media. This book was released on 2014-02-22 with total page 1200 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the state of the art of Monte Carlo methods in radiation physics and particle transport simulation and applications. Special attention is paid to algorithm development for modeling, and the analysis of experiments and measurements in a variety of fields.

Download or read book Hybrid and Parallel Domain Decomposition Methods Development to Enable Monte Carlo for Reactor Analyses written by and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper describes code and methods development at the Oak Ridge National Laboratory focused on enabling high-fidelity, large-scale reactor analyses with Monte Carlo (MC). Current state-of-the-art tools and methods used to perform ''real'' commercial reactor analyses have several undesirable features, the most significant of which is the non-rigorous spatial decomposition scheme. Monte Carlo methods, which allow detailed and accurate modeling of the full geometry and are considered the ''gold standard'' for radiation transport solutions, are playing an ever-increasing role in correcting and/or verifying the deterministic, multi-level spatial decomposition methodology in current practice. However, the prohibitive computational requirements associated with obtaining fully converged, system-wide solutions restrict the role of MC to benchmarking deterministic results at a limited number of state-points for a limited number of relevant quantities. The goal of this research is to change this paradigm by enabling direct use of MC for full-core reactor analyses. The most significant of the many technical challenges that must be overcome are the slow, non-uniform convergence of system-wide MC estimates and the memory requirements associated with detailed solutions throughout a reactor (problems involving hundreds of millions of different material and tally regions due to fuel irradiation, temperature distributions, and the needs associated with multi-physics code coupling). To address these challenges, our research has focused on the development and implementation of (1) a novel hybrid deterministic/MC method for determining high-precision fluxes throughout the problem space in k-eigenvalue problems and (2) an efficient MC domain-decomposition (DD) algorithm that partitions the problem phase space onto multiple processors for massively parallel systems, with statistical uncertainty estimation. The hybrid method development is based on an extension of the FW-CADIS method, which attempts to achieve uniform statistical uncertainty throughout a designated problem space. The MC DD development is being implemented in conjunction with the Denovo deterministic radiation transport package to have direct access to the 3-D, massively parallel discrete-ordinates solver (to support the hybrid method) and the associated parallel routines and structure. This paper describes the hybrid method, its implementation, and initial testing results for a realistic 2-D quarter core pressurized-water reactor model and also describes the MC DD algorithm and its implementation.

Download or read book Monte Carlo Particle Transport Capability for Inertial Confinement Fusion Applications written by L. M. Stuart and published by . This book was released on 2006 with total page 7 pages. Available in PDF, EPUB and Kindle. Book excerpt: A time-dependent massively-parallel Monte Carlo particle transport calculational module (ParticleMC) for inertial confinement fusion (ICF) applications is described. The ParticleMC package is designed with the long-term goal of transporting neutrons, charged particles, and gamma rays created during the simulation of ICF targets and surrounding materials, although currently the package treats neutrons and gamma rays. Neutrons created during thermonuclear burn provide a source of neutrons to the ParticleMC package. Other user-defined sources of particles are also available. The module is used within the context of a hydrodynamics client code, and the particle tracking is performed on the same computational mesh as used in the broader simulation. The module uses domain-decomposition and the MPI message passing interface to achieve parallel scaling for large numbers of computational cells. The Doppler effects of bulk hydrodynamic motion and the thermal effects due to the high temperatures encountered in ICF plasmas are directly included in the simulation. Numerical results for a three-dimensional benchmark test problem are presented in 3D XYZ geometry as a verification of the basic transport capability. In the full paper, additional numerical results including a prototype ICF simulation will be presented.

Download or read book Particle Communication and Domain Neighbor Coupling written by and published by . This book was released on 2015 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 221 = 2,097,152 MPI processes on the IBM BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain's replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.

Download or read book Particle transport simulation with the Monte Carlo method written by Leland L. Carter and published by . This book was released on 1975 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of the Random Ray Method of Neutral Particle Transport for High fidelity Nuclear Reactor Simulation written by John Robert Tramm and published by . This book was released on 2018 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: A central goal in computational nuclear engineering is the high-fidelity simulation of a full nuclear reactor core by way of a general simulation method. General full core simulations can potentially reduce design and construction costs, increase reactor performance and safety, reduce the amount of nuclear waste generated, and allow for much more complex and novel designs. To date, however, the time to solution and memory requirements for a general full core high fidelity 3D simulation have rendered such calculations impractical, even using leadership class supercomputers. Reactor designers have instead relied on calibrated methods that are accurate only within a narrow design space, greatly limiting the exploration of innovative concepts. One numerical simulation approach, the Method of Characteristics (MOC), has the potential for fast and efficient performance on a variety of next generation computing systems, including CPU, GPU, and Intel Xeon Phi architectures. While 2D MOC has long been used in reactor design and engineering as an efficient simulation method for smaller problems, the transition to 3D has only begun recently, and to our knowledge no 3D MOC based codes are currently used in industry. The delay of the onset of full 3D MOC codes can be attributed to the impossibility of “naively” scaling current 2D codes into 3D due to prohibitively high memory requirements. To facilitate transition of MOC based methods to 3D, we have developed a fundamentally new computational algorithm. This new algorithm, known as The Random Ray Method (TRRM), can be viewed as a hybrid between the Monte Carlo (MC) and MOC methods. Its three largest advantages compared to MOC are that it can handle arbitrary 3D geometries, it offers extreme improvements in memory efficiency, and it allows for significant reductions in algorithmic complexity on some simulation problems. It also offers a much lower time to solution as compared to MC methods. In this thesis, we will introduce the TRRM algorithm and a parallel implementation of it known as the Advanced Random Ray Code (ARRC). Then, we will evaluate its capabilities using a series of benchmark problems and compare the results to traditional deterministic MOC methods. A full core simulation will be run to assess the performance characteristics of the algorithm at massive scale. We will also discuss the various methods to parallelize the algorithm, including domain decomposition, and will investigate the new method’s scaling characteristics on two current supercomputers, the IBM Blue Gene/Q Mira and the Cray XC40 Theta. The results of these studies show that TRRM is capable of breakthrough performance and accuracy gains compared to existing methods which we demonstrate to enable general, full core 3D high-fidelity simulations that were previously out of reach.

Download or read book Resonance Self Shielding Calculation Methods in Nuclear Reactors written by Liangzhi Cao and published by Woodhead Publishing. This book was released on 2022-10-01 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Resonance Self-Shielding Calculation Methods in Nuclear Reactors presents the latest progress in resonance self-shielding methods for both deterministic and Mote Carlo methods, including key advances over the last decade such as high-fidelity resonance treatment, resonance interference effect and multi-group equivalence. As the demand for high-fidelity resonance self-shielding treatment is increasing due to the rapid development of advanced nuclear reactor concepts and progression in high performance computational technologies, this practical book guides students and professionals in nuclear engineering and technology through various methods with proven high precision and efficiency. Presents a collection of resonance self-shielding methods, as well as numerical methods and numerical results Includes new topics in resonance self-shielding treatment Provides source codes of key calculations presented