1. 7th Workshop on Fusion Data Proc. Validation and Analysis 1 Conference name, data and Presenter Synthetic diagnostics in the EU-ITM simulation platform R. Coelho [1], S. Äkäslompolo [2], A. Dinklage [3], A. Kus [3], E. Sundén [4], S. Conroy [4] E. Blanco [5], G. Conway [6], S. Hacquin [7], S. Heuraux [7b], C. Lechte [8], F. Silva [1], A. Sirinelli [7] and ITM-TF contributors* [1] Associação EURATOM/IST, Instituto de Plasmas e Fusão Nuclear – Laboratório Associado, Instituto Superior Técnico, Universidade Técnica de Lisboa, P-1049-001 Lisboa, Portugal [2] Aalto University, Euratom-Tekes Association, P.O. Box 14100, FI-00076 AALTO, Finland [3] Max-Planck-Institut für Plasmaphysik, EURATOM-Association, Wendelsteinstr. 1, Greifswald, Germany [4] Uppsala University, VR-Euratom Association, Box 516, 751 20 Uppsala, Sweden [5] Asociación EURATOM-CIEMAT para Fusión, CIEMAT, Madrid, Spain Association [6] Max-Planck-Institut für Plasmaphysik, EURATOM-IPP Association, Garching, Germany [7] CEA, IRFM, F-13108 Saint-Paul-lez-Durance, France. [7b] IJL, UMR CNRS 7198 U. Lorraine Faculty of Sciences BP 70239, F-54506 Cedex, France [8] Institute for Plasma Research, University of Stuttgart, 70569 Stuttgart, Germany 7th Workshop on Fusion Data Processing Validation and Analysis March 26 th- 28 th 2012

2. 7th Workshop on Fusion Data Proc. Validation and Analysis 2 Outline of the talk Rationale for synthetic diagnostics in ITM ITM software environment and selected tools Ongoing efforts in synthetic diagnostics integration in ITM Spectral MSE 3D Reflectometry Neutron Diagnostics Neutral Particle Analyser / Fast Ion Loss Detector Conclusions and perspectives

3. 7th Workshop on Fusion Data Proc. Validation and Analysis 3 The ITM-TF in short… Co-ordinate the development of a coherent set of validated simulation tools for ITER exploitation Benchmark these tools on existing tokamak experiments Provide a comprehensive simulation package for ITER and DEMO plasmas. Coordinate the European Software developments in view of increasing quality and reducing parallel efforts. ITM-TF charge Development of the necessary standardized software tools for interfacing code modules and accessing experimental data. ITM-TF Remit from EFDA SC (03)-21/4.9.2 (June 24th, 2003) 3 Courtesy of P.Strand

4. 7th Workshop on Fusion Data Proc. Validation and Analysis 4 Outline of the talk Rationale for synthetic diagnostics in ITM ITM software environment and selected tools Ongoing efforts in synthetic diagnostics integration in ITM Spectral MSE 3D Reflectometry Neutron Diagnostics Neutral Particle Analyser / Fast Ion Loss Detector Conclusions and perspectives

5. 7th Workshop on Fusion Data Proc. Validation and Analysis 5 Rationale for SD in ITM In a nut shell…synthetic diagnostic integration in ITM is needed for : Integrated data analysis : feed the best experimental data in interpretative Tokamak simulations Plasma Control : build diagnostic signals for feedback plasma control emulation. Code Validation : essential when multiscale complex physics is involved, e.g. turbulence (reflectometry, PCI, CECE, BES)

6. 7th Workshop on Fusion Data Proc. Validation and Analysis 6 Code Validation in ITM Long-term effort with guidelines since ITM-TF inception Qualification Verification Validation Computational model Conceptual model Plasma Data Validity Qualification: Is the physics description adequate? Verification: Are the equations implemented and solved for correctly? Validation: Do we have a reliable and sufficiently accurate description of the plasma? Data Validity: Is our measured data a sufficient representation of reality? Code benchmarking: (C2C) A tool in both V&V and physics exploration P. Strand

7. 7th Workshop on Fusion Data Proc. Validation and Analysis 7 Plasma Control System : ITER view Controlling a full tokamak simulation IMAS requirements towards Plant system integration, O. Sauter, IM Design Team, ITER IM Technology Workshop, Cadarache, France Raw (e.g [V], [A] units) or post- processed (e.g. T e, j, v) data (depends on controller design and processing latency  Diagnostic Division)

8. 7th Workshop on Fusion Data Proc. Validation and Analysis 8 Outline of the talk Rationale for synthetic diagnostics in ITM ITM software environment and selected tools Ongoing efforts in synthetic diagnostics integration in ITM Spectral MSE 3D Reflectometry Neutron Diagnostics Neutral Particle Analyser / Fast Ion Loss Detector Conclusions and perspectives

9. 7th Workshop on Fusion Data Proc. Validation and Analysis 9 ITM Software Environment

10. 7th Workshop on Fusion Data Proc. Validation and Analysis 10 Consistent Physical Objects (1) Dedicated derived types that describe -diagnostic / hardware describing a fusion device -physics elements of multi-scale plasma simulation Bookkeeping Diagnostic Setting (time independent) Time-dependent measurements

11. 7th Workshop on Fusion Data Proc. Validation and Analysis 11 Consistent Physical Objects (2) An Ontology of CPOs to cover all system requirements New diagnostic CPOs or revision of CPO Ontology is welcome

12. 7th Workshop on Fusion Data Proc. Validation and Analysis 12 Workflow Engine – KEPLER (1)  The UAL libraries provide CPO awareness to KEPLER Eq. Reconstruction Actor kepler-project.org CPOs_in CPO_out Ellaborated from C. Konz / W. Zingmann

13. 7th Workshop on Fusion Data Proc. Validation and Analysis 13 Workflow Engine – KEPLER (2) Conceptual Kepler design for a synthetic diagnostic module (e.g. MSE) with Input and Output CPOs

14. 7th Workshop on Fusion Data Proc. Validation and Analysis 14 Outline of the talk Rationale for synthetic diagnostics in ITM ITM software environment and selected tools Ongoing efforts in synthetic diagnostics integration in ITM Spectral MSE 3D Reflectometry Neutron Diagnostics Neutral Particle Analyser / Fast Ion Loss Detector Conclusions and perspectives

15. 7th Workshop on Fusion Data Proc. Validation and Analysis 15 Spectral MSE Forward model for emissivity and radiance spectra (MSE, CX, BS, edge,…) Focus on MSE (π,σ ± ) + CX (beam attenuation) Total E in moving frame L - Radiant flux over l.o.s. A. Dinklage et al. FST 59

16. 7th Workshop on Fusion Data Proc. Validation and Analysis 16 Emissivity model Emissivity model follows from collisional radiative model for beam and plasma neutrals Emissivity Detector signal E, E/2 and E/3 beam components Included in the model

17. 7th Workshop on Fusion Data Proc. Validation and Analysis 17 Spectral MSE - Results Spectral MSE at ASDEX Upgrade and MSE spectrum from #25827 (R. Reimer et al Cont. Plasma Phys. 50) Full integration in ITM is ongoing (module tested, workflow under development, validation on other discharges by end 2012)

18. 7th Workshop on Fusion Data Proc. Validation and Analysis 18 Outline of the talk Rationale for synthetic diagnostics in ITM ITM software environment and selected tools Ongoing efforts in synthetic diagnostics integration in ITM Spectral MSE 3D Reflectometry Neutron Diagnostics Neutral Particle Analyser / Fast Ion Loss Detector Conclusions and perspectives

19. 7th Workshop on Fusion Data Proc. Validation and Analysis 19 3D Reflectometer (1) 3D kernel is integrated in ITM, reads CPOs (includes turbulence CPO). Testing of dedicating datastructure ongoing this week. V&V initiates in 2012 (2d codes and exp.data). Strong effort on 2D benchmarking is ongoing. erc3D workflow

20. 7th Workshop on Fusion Data Proc. Validation and Analysis 20 3D Reflectometer (2) top side

21. 7th Workshop on Fusion Data Proc. Validation and Analysis 21 3D Reflectometer (3) First results of erc3d

22. 7th Workshop on Fusion Data Proc. Validation and Analysis 22 Outline of the talk Rationale for synthetic diagnostics in ITM ITM software environment and selected tools Ongoing efforts in synthetic diagnostics integration in ITM Spectral MSE 3D Reflectometry Neutron Diagnostics Neutral Particle Analyser / Fast Ion Loss Detector Conclusions and perspectives

23. 7th Workshop on Fusion Data Proc. Validation and Analysis 23 The synthetic neutron diagnostic handles two kinds of diagnostics: Proportional counters (neutron camera) Energy resolving neutron spectrometers (TOFOR and MPRu)  fusiondiag CPO for diagnostic settings and exp. Data First module : the Directional RElativistic Spectrum Simulator (DRESS) MC code, specifically developed for ITM. Calculates the energy spectra and source rates of particles created in fusion reactions (alpha particles and neutrons) Only source particles going in the direction of the detector are considered by DRESS (pick from differential cross section in CM !)  coreprof or distribution (non-Maxwellian) for diff.cross section and kinematics, equilibrium for ψ  (R,Z) mapping Neutron diagnostics (1)

24. 7th Workshop on Fusion Data Proc. Validation and Analysis 24 Neutron diagnostics (2) Neutrons are transported towards the neutron diagnostic as described by fusiondiag (collimator) Fraction of solid angle of neutron source distribution seen by detector (LINE21). Encapsulated in 3D “Voxels” Each voxel has associated direction to detector (approx. valid for small volume voxels) Poloidal projection of the fractional solid angles seen by the horizontal neutron camera at JET using the DT settings 10 -9

25. 7th Workshop on Fusion Data Proc. Validation and Analysis 25 Neutron diagnostics (3) Secondary particle interactions from neutron projectile are detected. The JET camera detectors measure recoil protons’ deposited energies TOFOR measures the time-of-flight of neutrons. MPRu measures recoil proton track deviation in a magnetic field. A Detector Response Function in fusiondiag maps the neutron energy to the actual measurement. Detector response function of the MPRu X – detector cell En – neutron energy Z-axis – counts (monenergetic highlighted)

26. 7th Workshop on Fusion Data Proc. Validation and Analysis 26 Neutron diagnostics (4) Synthetic detector measurements  Stored in fusiondiag CPO Example : synthetic measurement of a 14MeV mono-energetic beam impinging on a 14-MeV dedicated time-of-flight spectrometer using two different settings (blue and red for different electronics setup emulation) synthetic counts for a 14- MeV time-of-flight spectrometer

27. 7th Workshop on Fusion Data Proc. Validation and Analysis 27 Outline of the talk Rationale for synthetic diagnostics in ITM ITM software environment and selected tools Ongoing efforts in synthetic diagnostics integration in ITM Spectral MSE 3D Reflectometry Neutron Diagnostics Neutral Particle Analyser / Fast Ion Loss Detector Conclusions and perspectives

28. 7th Workshop on Fusion Data Proc. Validation and Analysis 28 NPA diagnostic (1) Based on the ASCOT kernel and tools. Test ions that fall on NPA cone of sight and that can reach detector (neutralization and re-ionization included) Cone of sight of NPA detector (red – wall blocked; black – port blocked) Use : 3dwall, fusiondiag CPOs Distribution of ASCOT “test particles” inside 3D ASDEX Upgrade wall Use : 3dwall, distribution CPOs Neutral source from mass-m ion

29. 7th Workshop on Fusion Data Proc. Validation and Analysis 29 NPA diagnostic (2) Velocity pitch (V // / V Tot ) dependence  unknown Larmor phase lead to “cone of flight” (c.o.f) Use : equilibrium, distribution CPOs Z=0 in Pol.plane

30. 7th Workshop on Fusion Data Proc. Validation and Analysis 30 NPA diagnostic (3) Fraction of c.o.f intersect with collimator effective area  scale factor on flux count Use : fusiondiag (collimator)

31. 7th Workshop on Fusion Data Proc. Validation and Analysis 31 NPA diagnostic (4) Re-ionization along flight path  scale factor on flux count Use : coreprof, coreneutrals CPOs Number of mean free paths Flux Calculated neutral flux attenuation due to re- ionization.

32. 7th Workshop on Fusion Data Proc. Validation and Analysis 32 NPA diagnostic (5) Final goal  Neutral flux as function of energy Stored in : fusiondiag CPO Calculated neutral flux as a function of energy  ion distribution source : 60keV NBI pini, E ion >20keV

33. 7th Workshop on Fusion Data Proc. Validation and Analysis 33 Conclusions and Perspectives ITM-TF is conscious of the relevance of SD and integration work is in progress (Spectral MSE, 3d Reflectometer, NPA and neutron camera) ITM modelling platform : why exp./diag./control community should use it –ITM datastructure is flexible : CPO can evolve to fit your needs. –Kepler orchestrator : user friendly workflow design, independent of the device. –Useful platform for diagnostic and control R&D ITM envisages integration of further SD from community to assist code validation, e.g. 3D cameras, Soft/hard X-rays, PCI, BES.