FY2010 - Oak Ridge National Laboratory

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Director’s R&D Fund— Ultrascale Computing and Data Science 05294 Denovo: The Next-Generation HPC Solver for Multiscale Nuclear Energy Transport Kevin T. Clarno, Thomas M. Evans, Gokhan Yesilyurt, Mark L. Williams, and John A. Turner Project Description Nuclear technology now permeates virtually all aspects of the American economy and is a necessary part of any U.S. energy security strategy. Predictive nuclear energy simulations will involve the modeling of the many physical phenomena that are inherently coupled, including Boltzmann radiation transport, and will require tremendous computational resources. Experiences in many fields have demonstrated that in coupled-physics calculations, a three-dimensional Boltzmann transport solver requires most of the computational resources because of its seven-dimensional phase space. We will extend an existing production-quality parallel transport solver to develop a first-of-a-kind capability that creates a mathematically consistent two-level approach to addressing the significant multiscale (in phase space) challenges associated with predictive simulation of novel reactor concepts. Through hierarchical domain decomposition in full phase space, we will amortize the inherent spatial sweep scaling limitation of traditional transport solvers to fully utilize the multicore architectures in present and future leadershipclass computing platforms. We will advance the next-generation high-performance computing (HPC) nuclear reactor transport solver to establish ORNL as the sole source for massively parallel multiscale neutronics codes by incorporating a scalable algorithm that provides a consistent multilevel approach to the multiscale problem in a coupled-physics environment. Mission Relevance The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program within the DOE Office of Nuclear Energy (NE) is evolving into an application-oriented software development program that will establish several nuclear reactor and fuel, separations and safeguards, and waste repository simulation code teams. The completion of this project in 2011 will demonstrate the highly scalable integrated solver capability of Denovo for massively parallel multiscale nuclear energy radiation transport solvers. The benefits of parallel multiscale Boltzmann transport solvers extend well beyond the present focus of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. Nuclear nonproliferation, security, and safeguards in the <strong>National</strong> Nuclear Security Administration and the Department of Homeland Security, under programs related to special nuclear material production and protection, and radiological dispersion devices, require high-fidelity transport solvers with tremendous computational requirements. Advanced DOE NE reactors, fuel fabrication facilities, and separations facilities will require extensive analyses of potential criticality excursions to demonstrate the safe operation and material accountability, some of which are coupled-physics challenges such as modeling a fissile material in solution within a separations facility. Results and Accomplishments This project has exceeded several exceptional technical achievements and was a major component in the winning Consortium for Advanced LWR Simulation (CASL) DOE Energy Innovation Hub proposal, which will revolutionize advanced modeling and simulation for nuclear reactor analysis. Through the LDRD funding, the Denovo transport code has been enhanced to include an efficient massively parallel space-energy decomposed eigenvalue solver, which is required for nuclear reactor physics, and has efficiently utilized up to 200,000 cores of Jaguar for solving several large-scale nuclear reactor analysis benchmark problems. The primary technical achievements include (1) porting Denovo to the Jaguar hardware and demonstrating scalability to 200,000 cores; (2) developing of an eigenvalue transport solver 82
Director’s R&D Fund— Ultrascale Computing and Data Science for reactor simulation applications; (3) demonstrating fidelity for several target nuclear energy benchmark simulations; (4) developing a novel space-energy domain decomposition algorithm for eigenvalue transport problems; and (5) demonstrating the use of Denovo in multiscale nuclear energy applications, including both fuels and reactors, with resolved materials. The CASL project has provided follow-on funding that will enable the tight-coupling of Denovo with many other physics packages, and the distribution of Denovo to a broad spectrum of expert reactor analysts in the commercial nuclear industry to provide a far-reaching impact for the nuclear energy community. In terms of quantifiable milestone accomplishments, Denovo has met the 2010 DOE Joule program milestone for demonstrated scalability on Jaguar; met the OLCF-3 requirements as a Tier 1 application for the next-generation HPC hardware bid; and been part of a winning the INCITE proposal, Uncertainty Quantification for Three-Dimensional Reactor Assembly Simulations, with a successful renewal spanning 2010–2011 for over 26 million CPU-hours. Additionally, Denovo-related work has contributed to two PhD dissertations, currently in candidacy, by Rachel Slaybaugh, University of Wisconsin, and Steven Hamilton, Emory University. Information Shared Evans, T. M., K. T. Clarno, and J. E. Morel. 2010. “A transport acceleration scheme for multigroup discrete ordinates with upscattering.” Nucl. Sci. Eng. 165, 292–301. Evans, T. M., A. Stafford, and K. T. Clarno. 2010. “Denovo—A new three-dimensional parallel discrete ordinates code in SCALE.” Nucl. Technol. 171, 171–200 (2010). 05384 Scalable, Fully Implicit Algorithms for First-Principles Kinetic Simulations at the Ultrascale Luis Chacón , Diego del-Castillo-Negrete, Raúl Sánchez , and Daniel C. Barnes Project Description This project aims at developing a novel, scalable kinetic algorithmic strategy based on fully implicit nonlinear methods. The approach will be able to exploit ORNL's ultrascale computing capabilities to enable a first-of-a-kind future predictive thermonuclear plasma modeling capability. Plasmas in the regimes of interest for nuclear fusion feature extremely disparate time and length scales. Current firstprinciples kinetic algorithms are explicit, needing to resolve the fastest time scales and the smallest length scales in the model for numerical stability, and are therefore extremely inefficient. The fully implicit character of our approach will eliminate numerical stability constraints (thus enhancing efficiency possibly by orders of magnitude). Its nonlinear character will deliver enhanced accuracy and nonlinear stability. Our approach will be particle based and thus naturally suitable for parallel supercomputers. If successful, this research will enable simulations that are presently unattainable with current algorithms even with ultrascale computing and will have direct implications for first-tier DOE projects such as ITER. Mission Relevance The project has strong relevance to two DOE missions: energy security and scientific discovery and innovation. Relevance to energy security stems from this project’s connection to magnetic fusion energy 83
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NEUTRON SCIENCES ..................
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NATIONAL SECURITY SCIENCE AND TECHN
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05887 Controlling the Catalytic Pro
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Introduction INTRODUCTION The Labor
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Index of Project Numbers 05501 ....
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FY2010 - Oak Ridge National Laboratory

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