Research Papers

Backbone: A Multiphysics Framework for Coupling Nuclear Codes Based on CORBA and MPI

[+] Author and Article Information
Yu Liu

Fuel and Fuel Channel Safety Branch,
Canadian Nuclear Laboratories,
Chalk River, ON, Canada K0J 1J0
e-mail: yu.liu@cnl.ca

Michael Nishimura

Department of Computer Science,
University of Waterloo,
Waterloo, ON, Canada N2L 3G1
e-mail: mjnishim@uwaterloo.ca

Marat Seydaliev

Fuel and Fuel Channel Safety Branch,
Canadian Nuclear Laboratories,
Chalk River, ON, Canada K0J 1J0
e-mail: marat.seydaliev@cnl.ca

Markus Piro

Fuel and Fuel Channel Safety Branch,
Canadian Nuclear Laboratories,
Chalk River, ON, Canada K0J 1J0
e-mail: markus.piro@cnl.ca

Manuscript received January 5, 2016; final manuscript received May 10, 2016; published online December 20, 2016. Assoc. Editor: Juan-Luis Francois.This work was prepared while under employment by the Government of Canada as part of the official duties of the author(s) indicated above, as such copyright is owned by that Government, which reserves its own copyright under national law.

ASME J of Nuclear Rad Sci 3(1), 011020 (Dec 20, 2016) (10 pages) Paper No: NERS-16-1002; doi: 10.1115/1.4034061 History: Received January 05, 2016; Accepted May 12, 2016

Recent trends in nuclear reactor performance and safety analyses increasingly rely on multiscale multiphysics computer simulations to enhance predictive capabilities by replacing conventional methods that are largely empirically based with a more scientifically based methodology. Through this approach, one addresses the issue of traditionally employing a suite of stand-alone codes that independently simulate various physical phenomena that were previously disconnected. Multiple computer simulations of different phenomena must exchange data during runtime to address these interdependencies. Previously, recommendations have been made regarding various approaches for piloting different design options of data coupling for multiphysics systems (Seydaliev and Caswell, 2014, “CORBA and MPI Based “Backbone” for Coupling Advanced Simulation Tools,” AECL Nucl. Rev., 3(2), pp. 83–90). This paper describes progress since the initial pilot study that outlined the implementation and execution of a new distribution framework, referred to as “Backbone,” to provide the necessary runtime exchange of data between different codes. The Backbone, currently under development at the Canadian Nuclear Laboratories (CNL), is a hybrid design using both common object request broker architecture (CORBA) and message passing interface (MPI) systems. This paper also presents two preliminary cases for coupling existing nuclear performance and safety analysis codes used for simulating fuel behavior, fission product release, thermal hydraulics, and neutron transport through the Backbone. Additionally, a pilot study presents a few strategies of a new time step controller (TSC) to synchronize the codes coupled through the Backbone. A performance and fidelity comparison is presented between a simple heuristic method for determining time step length and a more advanced third-order method, which was selected to maximize configurability and effectiveness of temporal integration, saving time steps and reducing wasted computation. The net effect of the foregoing features of the Backbone is to provide a practical toolset to couple existing and newly developed codes—which may be written in different programming languages and used on different operating systems—with minimal programming effort to enhance predictions of nuclear reactor performance and safety.

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Ivanov, K., and Avramova, M., 2007, “Progress and Challenges in the Development and Qualification of Multi-Level Multi-Physics Coupled Methodologies for Reactor Analysis,” Proceedings of the International Congress on Advances in Nuclear Power Plants (ICAP 2007), Nice, France, May 13–18, .
Seydaliev, M., and Caswell, D., 2014, “CORBA and MPI-Based “Backbone” for Coupling Advanced Simulation Tools,” AECL Nucl. Rev., 3(2), pp. 83–90. 10.12943/ANR.2014.00036
The Consortium for Advanced Simulation or LWRs (CASL), 2016, http://www.casl.gov/ (accessed July 13, 2016).
Kim, M., Kim, H.-K., Kim, H.-J., Hwang, S. H., Hong, I. S., and Kim, C. H., 2006, “Enhancement of Safety Analysis Capability for a CANDU-6 Reactor Using RELAP-CANDU/SCAN Coupled Code System,” Nucl. Technol., 156(2), pp. 159–167.
Dupleac, D., Prisecaru, I., Ghitescu, P., and Negut, G., 2007, “Effect of CANDU 6 Core Modeling on Large Break LOCA Analysis,” Proceedings of the 12th International Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-12), Pittsburgh, PA, Sept. 30–Oct. 4, .
Szabo, T., Kretzschmar, F., and Schulenberg, T., 2014, “Obtaining a More Realistic Hydrogen Distribution in the Containment by Coupling MELCOR With GASFLOW,” Nucl. Eng. Des., 269, pp. 330–339. 0029-5493 10.1016/j.nucengdes.2013.07.009
Gouja, I., Avramova, M., and Rubin, A., 2010, “Development and Optimization of Coupling Interfaces Between Reactor Core Neutronics and Thermal-Hydraulic Codes,” Proceedings of the International Conference on Advances in Reactor Physics to Power the Nuclear Renaissance (PHYSOR 2010), Pittsburgh, PA, May 9–14.
Gomez-Torres, A. M., Sanchez-Espinoza, V., Ivanov, K., and Macian-Juan, R., 2012, “DYNSUB: A High Fidelity Coupled Code System for the Evaluation of Local Safety Parameters—Part I: Development, Implementation and Verification,” Ann. Nucl. Energy, 48, pp. 108–122. 0306-4549 10.1016/j.anucene.2012.05.011
Sanchez, V., and Al-Hamry, A., 2009, “Development of a Coupling Scheme Between MCNP and COBRA-TF for the Prediction of the Pin Power of a PWR Fuel Assembly,” Proceedings of the International Conference on Mathematics, Computational Methods and Reactor Physics (M&C2009), Saratoga Springs, NY, May 3–7.
Chen, Z., Chen, X.-N., Rineiski, A., Zhao, P., and Chen, H., 2015, “Coupling a CFD Code With Neutron Kinetics and Pin Thermal Models for Nuclear Reactor Safety Analyses,” Ann. Nucl. Energy, 83, pp. 41–49. 0306-4549 10.1016/j.anucene.2015.03.023
Gaston, D., Newman, C., Hansen, G., and Lebrun-Grandie, D., 2009, “MOOSE: A Parallel Computational Framework for Coupled Systems of Nonlinear Equations,” Nucl. Eng. Des., 239(10), pp. 1768–1778. 0029-5493 10.1016/j.nucengdes.2009.05.021
Chauliac, C., Aragones, J.-M., Bestion, D., Cacuci, D. G., Crouzet, N., Weiss, F.-P., and Zimmermann, M. A., 2011, “NURESIM—A European Simulation Platform for Nuclear Reactor Safety: Multi-Scale and Multi-Physics Calculations, Sensitivity and Uncertainty Analysis,” Nucl. Eng. Des., 241(9), pp. 3416–3426. 0029-5493 10.1016/j.nucengdes.2010.09.040
Baudron, A.-M., Crouzet, N., Doderlein, C., Geay, A., Lautard, J.-J., Richebois, E., Royer, E., and Sireta, P., 2008, “Unstructured 3D MINOS/FLICA4 Coupling in SALOME Application to JHR Transient Analysis,” International Conference on the Physics of Reactors (PHYSOR’08), Interlake, Switzerland, Sept. 14–19.
Baviere, R., Tauveron, N., Perdu, F., Garre, E., and Li, S., 2014, “A First System/CFD Coupled Simulation of a Complete Nuclear Reactor Transient Using CATHARE2 and TRIO_U. Preliminary Validation on the Phénix Reactor Natural Circulation Test,” Nucl. Eng. Des., 277, pp. 124–137. 10.1016/j.nucengdes.2014.05.031
Schmidt, R., Belcourt, N., Hooper, R., and Pawlowski, R., 2011, “An Introduction to LIME 1.0 and Its Use in Coupling Codes for Multiphysics Simulations,” Sandia National Laboratories, Albuquerque, NM, .
SALOME, 2016, SALOME: The Open Source Integration Platform for Numerical Simulation, http://www.salome-platform.org/ (accessed July 13, 2016).
Denis, A., Perez, C., and Priol, T., 2004, “Network Communications in Grid Computing: At a Crossroads Between Parallel and Distributed Worlds,” Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS’04), Sante Fe, NM, Apr. 26–30.
Message Passing Interface Forum, 2009, MPI: A Message-Passing Interface Standard Version 2.2, Message Passing Interface Forum, High Performance Computing Center, Stuttgart, Germany.
OMG—Object Management Group, 2016, OMG, http://www.omg.org (accessed July 13, 2016).
Shim, C. B., Jung, Y. S., Yoon, J. I., and Joo, H. G., 2011, “Application of Backward Differentiation Formula to Spatial Reactor Kinetics Calculation With Adaptive Time Step Control,” Nucl. Eng. Technol., 43(6), 531–546. 10.5516/NET.2011.43.6.531
Soderlind, G., 2003, “Digital Filters in Adaptive Time-Stepping,” ACM Trans. Math. Software, 29(1), pp. 1–26. 0098-3500 10.1145/641876
omniORB: Free CORBA ORB, http://omniorb.sourceforge.net/index.html (accessed July 13, 2016).
Suresh, A., and Townsend, S. E., 2007, “Coupling of Computational Fluid Dynamic (CFD) Codes for Steady and Unsteady Simulations,” 43rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, Cincinnati, OH, July 8–11, Paper AIAA 2007-5044.
Michaelsen, P. M., Pritz, B., and Gabi, M., 2013, “A Fluid Structure Interaction Tool by Coupling of Existing Codes,” Proceedings of the 20th European MPI Users’ Group Meeting (EuroMPI’13), Madrid, Spain, Sept. 15–18, pp. 157–162.
Message Passing Interface Forum, 1997, MPI-2: Extensions to the Message-Passing Interface, http://www.mpi-forum.org/docs/mpi-2.0/mpi-20-html/mpi2-report.html (accessed July 13, 2016).
Kopysov, S. P., Krasnopyorov, I. V., and Rychkov, V. N., 2006, “CORBA and MPI Code Coupling,” Programm. Comput. Software, 32(5), pp. 276–283. 0361-7688 10.1134/S0361768806050045
QT Company, 2016, QT, qt-project.org (accessed July 13, 2016).
OpenPBS, 2004, OpenPBS, http://www.mcs.anl.gov/research/projects/openpbs/ (accessed July 13, 2016).
IBM Spectrum LSF, http://www-03.ibm.com/systems/platformcomputing/products/lsf/ (accessed July 13, 2016).
Williams, A. F., 2005, “The Eloca Fuel Modelling Code: Past, Present and Future,” Proceedings of the 9th International CNS Conference on CANDU Fuel, Belleville, ON, Sept. 18–21.
Brito, A. C., Iglesias, F. C., Liu, Y., Petrilli, M. A., Richards, M. J., Gibb, R. A., and Reid, P. J., 1995, “Source 2.0: A Computer Program to Calculate Fission Product Release From Multiple Fuel Elements for Accident Scenarios,” Proceedings of the 4th International Conference on CANDU Fuel, Pembroke, ON, Oct. 1–4, Vol. 2, pp. 5B-45–5B-56.
CATHENA, 2015, CATHENA, 2015, CATHENA, https://www.cathena.aecl.ca/index.htm (accessed July 13, 2016).
Yukalov, V. I., Yukalova, E. P., and Sornette, D., 2009, “Punctuated Evolution due to Delayed Carrying Capacity,” , Swiss Federal Institute of Technology Zurich, Zurich, Switzerland.


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Fig. 1

Reactor performance and safety analysis codes [3]

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Fig. 2

Infrastructure of the Backbone for coupling advanced nuclear codes

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Fig. 3

Data package format of the Backbone communication protocol

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Fig. 4

Solution of integrating the Backbone with a cluster

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Fig. 5

Simulation results comparison between the coupling case and the ELOCA only case

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Fig. 6

Evolution of sheath and coolant temperatures at the simulated fuel bundle, bundle power from 3D-Solver

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Fig. 7

Sinusoidal function (Eq. (2)) against time, and the size of time step against time, using third-order controller 1 (H312b configuration, 0.05 tolerance, 1/18 error weight, 1/9 last error weight, and 1/18 second last error weight)

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Fig. 8

Sinusoidal function against time, and the size of time step against time, over 50 points

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Fig. 9

Delayed logistic function f against time, as output by the simulation, and the time step size against time, with steps selected using simple strategy (1.01 step-up, 0.9 step-down); 116 time steps, 9 rejections

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Fig. 10

Delayed logistic function f against time, as output by the simulation, and the time step size against time, with steps selected using the elementary controller (0.05 tolerance, 0.2 error weight); 93 time steps, 12 rejections

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Fig. 11

Delayed logistic function f against time, as output by the simulation, and the time step size against time, with steps selected using third-order controller (H312b configuration, 0.05 tolerance, 1/18 error weight, 1/9 last error weight, and 1/18 second last error weight); 121 time steps, 20 rejections




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