7th Workshop on Fusion Data Proc. Validation and Analysis1

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 26th-28th 2012

7th Workshop on Fusion Data Proc. Validation and Analysis2

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

7th Workshop on Fusion Data Proc. Validation and Analysis3

The ITM-TF in short…

from EFDA SC (03)-21/4.9.2 (June 24th, 2003)3

Courtesy of P.Strand

7th Workshop on Fusion Data Proc. Validation and Analysis4

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

7th Workshop on Fusion Data Proc. Validation and Analysis5

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)

7th Workshop on Fusion Data Proc. Validation and Analysis6

Code Validation in ITM

Long-term effort with guidelines since ITM-TF inception

Qualification

Verification

Val

idat

ion

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 asufficient representation of reality?

Code benchmarking: (C2C)A tool in both V&V and physics exploration

P. Strand

7th Workshop on Fusion Data Proc. Validation and Analysis7

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. Te, j, v) data

(depends on controller design and processing latency Diagnostic Division)

7th Workshop on Fusion Data Proc. Validation and Analysis8

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

7th Workshop on Fusion Data Proc. Validation and Analysis9

ITM Software Environment

7th Workshop on Fusion Data Proc. Validation and Analysis10

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

7th Workshop on Fusion Data Proc. Validation and Analysis11

Consistent Physical Objects (2)

• An Ontology of CPOs to cover all system requirements

New diagnostic CPOs or revision of CPO Ontology is welcome

7th Workshop on Fusion Data Proc. Validation and Analysis12

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

7th Workshop on Fusion Data Proc. Validation and Analysis13

Workflow Engine – KEPLER (2)

• Conceptual Kepler design for a synthetic diagnostic module (e.g. MSE) with Input and Output CPOs

7th Workshop on Fusion Data Proc. Validation and Analysis14

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

7th Workshop on Fusion Data Proc. Validation and Analysis15

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

7th Workshop on Fusion Data Proc. Validation and Analysis16

Emissivity model

• Emissivity model follows from collisional radiative model for beam and plasma neutrals

Emissivity

Detector signal

E, E/2 and E/3 beam componentsIncluded in the model

7th Workshop on Fusion Data Proc. Validation and Analysis17

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)

7th Workshop on Fusion Data Proc. Validation and Analysis18

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

7th Workshop on Fusion Data Proc. Validation and Analysis19

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.

erc3Dworkflow

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3D Reflectometer (2)

top

side

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3D Reflectometer (3)

First results of erc3d

7th Workshop on Fusion Data Proc. Validation and Analysis22

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

7th Workshop on Fusion Data Proc. Validation and Analysis23

• 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)

7th Workshop on Fusion Data Proc. Validation and Analysis24

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

7th Workshop on Fusion Data Proc. Validation and Analysis25

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)

7th Workshop on Fusion Data Proc. Validation and Analysis26

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

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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

7th Workshop on Fusion Data Proc. Validation and Analysis28

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 wallUse : 3dwall, distribution CPOs

Neutral source from mass-m ion

7th Workshop on Fusion Data Proc. Validation and Analysis29

NPA diagnostic (2)

• Velocity pitch (V// / VTot) dependence

unknown Larmor phase lead to “cone of flight” (c.o.f)Use : equilibrium, distribution CPOs

Z=0 inPol.plane

7th Workshop on Fusion Data Proc. Validation and Analysis30

NPA diagnostic (3)

• Fraction of c.o.f intersect with collimator effective area

scale factor on flux countUse : fusiondiag (collimator)

7th Workshop on Fusion Data Proc. Validation and Analysis31

NPA diagnostic (4)

• Re-ionization along flight path scale factor on flux countUse : coreprof, coreneutrals CPOs

Number of mean free paths

Flux

Calculated neutral flux attenuation due to re-ionization.

7th Workshop on Fusion Data Proc. Validation and Analysis32

NPA diagnostic (5)

• Final goal Neutral flux as function of energyStored in : fusiondiag CPO

Calculated neutral flux as a function of energy

ion distribution source : 60keV NBI pini, Eion>20keV

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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.