Use of massively parallel computing to improve modelling accuracy within the nuclear sector

The extreme environments found within the nuclear sector impose large safety factors on modelling analyses to ensure components operate in their desired manner. Improving analysis accuracy has clear value of increasing the design space that could lead to greater efficiency and reliability. Novel materials for new reactor designs often exhibit non-linear behaviour; additionally material properties evolve due to in-service damage a combination that is difficult to model accurately. To better describe these complex behaviours a range of modelling techniques previously under-pursued due to computational expense are being developed. This work presents recent advancements in three techniques: Uncertainty quantification (UQ); Cellular automata finite element (CAFE); Image based finite element methods (IBFEM). Case studies are presented demonstrating their suitability for use in nuclear engineering made possible by advancements in parallel computing hardware that is projected to be available for industry within the next decade costing of the order of $100k.

[1]  B Notarberardino,et al.  An efficient approach to converting three-dimensional image data into highly accurate computational models , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[2]  Timothy D. Burchell,et al.  Strength of Neutron-Irradiated High-Quality 3D Carbon Fiber Composite , 2003 .

[3]  D. V. Griffiths,et al.  Risk Assessment in Geotechnical Engineering , 2008 .

[4]  Dierk Raabe,et al.  Cellular Automata in Materials Science with Particular Reference to Recrystallization Simulation , 2002 .

[5]  Anton Shterenlikht,et al.  CELLULAR AUTOMATA MODELLING OF NANOCRYSTALLINE INSTABILITY * , 2012 .

[6]  J. West,et al.  Challenges of Open Innovation: The Paradox of Firm Investment in Open-Source Software , 2006 .

[7]  Andrey P. Jivkov,et al.  Multi-scale modelling of nuclear graphite tensile strength using the site-bond lattice model , 2016 .

[8]  P. Rebut,et al.  The ITER divertor , 1993, 15th IEEE/NPSS Symposium. Fusion Engineering.

[9]  Blas P. Uberuaga,et al.  Radiation damage tolerant nanomaterials , 2013 .

[10]  Philip J. Withers,et al.  In situ 3D X‐ray microtomography study comparing auxetic and non‐auxetic polymeric foams under tension , 2011 .

[11]  Lee Margetts.  Parallel finite element analysis , 2002 .

[12]  Liviu Popa-Simil,et al.  Using High Performance Scientific Computing to Accelerate the Discovery and Design of Nuclear Power Applications , 2015 .

[13]  Edoardo Patelli,et al.  General purpose software for efficient uncertainty management of large finite element models , 2012, Finite elements in analysis and design : the international journal of applied finite elements and computer aided engineering.

[14]  Canqun Yang,et al.  MilkyWay-2 supercomputer: system and application , 2014, Frontiers of Computer Science.

[15]  John M. Boone,et al.  Development of a micromechanical finite element model from computed tomography images for shear modulus simulation of asphalt mixtures , 2012 .

[16]  J. Bourgat.  Numerical experiments of the homogenization method , 1979 .

[17]  Mu Xiaying,et al.  A finite element elastic-plastic-creep analysis of materials with temperature dependent properties , 1988 .

[18]  W. J. Hall,et al.  Seismic Design Criteria for Nuclear Reactor Facilities , 1973 .

[19]  Lee Margetts,et al.  Transient Thermal Finite Element Analysis of CFC-Cu ITER Monoblock Using X-ray Tomography Data , 2015 .

[20]  Lee Margetts,et al.  Practical Application of the Stochastic Finite Element Method , 2016 .

[21]  D. V. Griffiths,et al.  Spatial variability in the coefficient of thermal expansion induces pre-service stresses in computer models of virgin Gilsocarbon bricks , 2015 .

[22]  G. Matthews,et al.  Characterisation of the porous structure of Gilsocarbon graphite using pycnometry, cyclic porosimetry and void-network modeling , 2014 .

[23]  Lee Margetts,et al.  The convergence variability of parallel iterative solvers , 2006 .

[24]  J. Yeh.  Recent progress in high-entropy alloys , 2006 .

[25]  P. Withers,et al.  Three-dimensional observation and image-based modelling of thermal strains in polycrystalline alumina , 2013 .

[26]  A. M. Yamileva,et al.  Comparison of the Parallelization Efficiency of a Thermo - Structural Problem Simulated in SIMULIA Abaqus and ANSYS Mechanical , 2012 .

[27]  R. Raffray,et al.  ITER Divertor, Design Issues and Research and Development , 1999 .

[28]  Lee Margetts,et al.  Three-dimensional cellular automata modelling of cleavage propagation across crystal boundaries in polycrystalline microstructures , 2015, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[29]  Erich Strohmaier,et al.  The TOP500 List and Progress in High-Performance Computing , 2015, Computer.

[30]  Paul Bowen,et al.  Size effects on the microscopic cleavage fracture stress, σF*, in martensitic microstructures , 1986 .

[31]  H. Bolt,et al.  Self passivating W-based alloys as plasma-facing material , 2009 .

[32]  S. Zinkle,et al.  Structural materials for fission & fusion energy , 2009 .

[33]  Michael Gschwind,et al.  The IBM Blue Gene/Q Compute Chip , 2012, IEEE Micro.

[34]  Robert Strzodka,et al.  Parallel computing on graphics processing units and heterogeneous platforms , 2015, Concurr. Comput. Pract. Exp..

[35]  B. Riccardi,et al.  High heat flux testing of EU tungsten monoblock mock-ups for the ITER divertor , 2015 .

[36]  Lee Margetts,et al.  Thermal characterisation of ceramic/metal joining techniques for fusion applications using X-ray tomography , 2014 .

[37]  Indrajit Charit,et al.  Structural materials for Gen-IV nuclear reactors: Challenges and opportunities , 2008 .

[38]  M. F. Smith,et al.  Development and Testing of the ITER Divertor Monoblock Braze Design , 1991 .

[39]  Satoshi Nishio,et al.  Fracture mechanics evaluation of a crack generated in SiC/SiC composite first wall , 2001 .

[40]  Adisa Azapagic,et al.  Sustainability indicators for the assessment of nuclear power , 2011 .

[41]  D. V. Griffiths,et al.  Programming the finite element method , 1982 .

[42]  P. Barabaschi,et al.  Structural analysis of the JT-60SA cryostat base , 2011 .

[43]  J. Mackenzie,et al.  SECOND PAPER ON STATISTICS ASSOCIATED WITH THE RANDOM DISORIENTATION OF CUBES , 1958 .

[44]  Karl S. Hemmert.  Green HPC: From Nice to Necessity , 2010, Comput. Sci. Eng..

[45]  Lee Margetts,et al.  Parallel Processing for Time-Dependent Heat Flow Problems , 2013 .

[46]  Pawel Gepner,et al.  Multi-Core Processors: New Way to Achieve High System Performance , 2006, PARELEC.

[47]  J. N. Reddy,et al.  Nonlinear transient thermoelastic analysis of functionally graded ceramic-metal plates , 1998 .