Regular Articles

Full Text / References

Integrated Modeling of Tokamak Experiments with OMFIT

Orso MENEGHINI and Lang LAO¹⁾

Oak Ridge Associated Universities, Oak Ridge, Tennessee, USA

1)

General Atomics, San Diego, California, USA

(Received 8 December 2012 / Accepted 11 January 2013 / Published 23 April 2013)

Abstract

One Modeling Framework for Integrated Tasks (OMFIT) is a framework that allows data to be easily exchanged among different codes by providing a unifying data structure. The main idea at the base of OMFIT is to treat files, data and scripts as a uniform collection of objects organized into a tree structure, which provides a consistent way to access and manipulate such collection of heterogeneous objects, independent of their origin. Within the OMFIT tree, data can be copied/referred from one node to another and tasks can call each other allowing for complex compound task to be built. A top-level Graphical User Interface (GUI) allowing users to manage tree objects, carry out simulations and analyze the data either interactively or in batch. OMFIT supports many scientific data formats and when a file is loaded into the framework, its data populates the tree structure, automatically endowing it with many potential uses. Furthermore, seamless integration with experimental management systems allows direct manipulation of their data. In OMFIT modeling tasks are organized into modules, which can be easily combined to create arbitrarily-large multi-physics simulations. Modules inter-dependencies are seamlessly defined by variables referencing tree locations among them. Creation of new modules and customization of existing ones is encouraged by graphical tools for their management and an online repository. High level Application Programmer Interfaces (APIs) enable users to execute their codes on remote servers and creation application-specific GUIs. Finally, within OMFIT it is possible to visualize experimental and modeling data for both quick analysis and publication purposes. Examples of application to the DIII-D tokamak are presented.

Copyright (c) 2013 The Japan Society of Plasma Science and Nuclear Fusion Research

Keywords

simulation, plasma, transport, workflow

DOI: 10.1585/pfr.8.2403009

Full Text

PDF format (1.2Mbytes)

References

• [1] W.W. Pfeiffer et al., “ONETWO: A computer code for modeling plasma transport in tokamaks” Nuclear Fusion 1 (1980).
• [2] H. St John et al., Presented at the 15th International Conf. on Plasma Physics and Controlled Nuclear Fusion Research, Seville, Spain, 1994, 1 (1994).
• [3] integrated modeling code, http://w3.pppl.gov/transp/
• [4] H. Shirai et al., Plasma Phys. Control. Fusion 42, 1193 (2000).
• [5] G. Pereverzev and P.N. Yushmanov, “ASTRA automated system for transport analysis in a tokamak” Max-Planck-Institut fuer Plasmaphysik, Garching, Germany (2002).
• [6] J.F. Artaud et al., Nucl. Fusion 50, 043001 (2010).
• [7] J.A. Crotinger, L. LoDestro, L.D. Pearlstein, A. Tarditi, T.A. Casper and E.B. Hooper, “Corsica: A comprehensive simulation of toroidal magnetic-fusion devices,” Lawrence Livermore National Laboratory Report, Livermore, CA USA (1997).
• [8] M. Murakami et al., Nucl. Fusion 51, 103006 (2011).
• [9] J.R. Cary et al., J. Physics: Conference Series 78, 012086 (2007).
• [10] A. Bécoulet et al., Comput. Phys. Comm. 177, 55 (2007).
• [11] B. Ludäscher et al., Concurrency and Computation: Practice and Experience 18, 1039 (2006).
• [12] Jill Dahlburg et al., J. Fusion Energy 20, 135 (2001).
• [13] W.R. Elwasif et al., in Parallel, Distributed and Network-Based Processing (PDP), 2010 18th Euromicro International Conf. on, Institute of Electrical and Electronics Engineers (IEEE), pages 419427 (2010).
• [14] A. Fukuyama et al., in Proc. 20th Fusion Energy Conf., Villamoura, Portugal (2004).
• [15] B. Guillerminet et al., Fusion Eng. Des. 83, 442 (2008).
• [16] R. Rew and G. Davis, IEEE Comput. Graph. Appl. 10, 76 (1990).
• [17] EXELIS, “DL. Exelis Visual Information Solutions,” Boulder, Colorado.
• [18] MATLAB, The MathWorks Inc., Natick, Massachusetts.
• [19] J.A. Stillerman et al., Rev. Sci. Instrum. 68, 939 (1997).
• [20] L.L. Lao et al., Nucl. Fusion 25, 1611 (1985).
• [21] M.F. Sanner et al., J. Mol. Graph. Model. 17, 57 (1999).
• [22] J.D. Hunter, Comput. in Science & Engineering (IEEE Computer Soc., 2007) pp.90-95.
• [23] T.E. Oliphant, A Guide to NumPy 1 (Trelgol Publishing USA, 2006).
• [24] E. Jones, T. Oliphant and P. Peterson, “SciPy: Open source scientic tools for Python,” http://www.scipy.org/ (2001).
• [25] F. Lundh, “An introduction to tkinter,” URL: www.pythonware.com/library/tkinter/introduction/index.htm (1999).
• [26] L.C. Bernard, F.J. Helton and R.W. Moore, Comput. Phys. Comm. 24, 377 (1981).
• [27] A. Pletzer, A. Bondeson and R.L. Dewar, J. Comput. Phys. 115, 530 (1994).
• [28] Holger St John, “Globally Convergent Newton Method Parallel (GCNMP) solver,” under development, private communication.
• [29] A.P. Smirnov and R.W. Harvey, “The GENRAY ray tracing code,” CompX Report CompX-2000-01 (2001).
• [30] Mike Kotschenreuther, G. Rewoldt and W.M. Tang, Comput. Phys. Comm. 88, 128 (1995).
• [31] G.M. Staebler, J.E. Kinsey and R.E. Waltz, Phys. Plasmas 14, 055909 (2007).
• [32] J.D. Callen, A.J. Cole and C.C. Hegna, Phys. Plasmas 19, 112505 (2012).
• [33] N.M. Ferraro, Phys. Plasmas 19, 056105 (2012).
• [34] V.S. Chan et al., Nucl. Fusion 51, 083019 (2011).

This paper may be cited as follows:

Orso MENEGHINI and Lang LAO, Plasma Fusion Res. 8, 2403009 (2013).