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Bayesian modelling of a diagnostic helium beam ADAS workshop, Armagh Observatory, October 4th, 2010 Maciej Krychowiak M. Brix, D. Dodt, R. König, O. Schmitz,

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Presentation on theme: "Bayesian modelling of a diagnostic helium beam ADAS workshop, Armagh Observatory, October 4th, 2010 Maciej Krychowiak M. Brix, D. Dodt, R. König, O. Schmitz,"— Presentation transcript:

1 Bayesian modelling of a diagnostic helium beam ADAS workshop, Armagh Observatory, October 4th, 2010 Maciej Krychowiak M. Brix, D. Dodt, R. König, O. Schmitz, J. Svensson, R. Wolf

2 2 Helium beam diagnostic  Radial profiles of n e and T e at the plasma edge n e : 10 12... 10 13 m -3 T e : 10... 200 eV   r  1 mm,  t  1 ms plasma line of sight helium beam nozzle  Measure three spectral lines of atomic helium (typically 667, 706, 728 nm)  Compare two line ratios with CR model  T e : triplet/singlet  n e : singlet/singlet singlettriplet

3 3 direction of the gas flow beam relaxation (steady-state solution) no beam relaxation (time dependent solution) nozzle =0 (stationary beam) electron (de)excitationradiationtransport ionisation charge exchange  Beam atoms penetrate the plasma, radiate, get ionised, leave the observation volume  Movement in one direction → 1-dim transport equation: CR modelling of helium beams  ~ 200 uncertain rate coefficients for electron collisions, known only from calculations  Collisions with protons, neutrals

4 4 Comparisons to other diagnostics  Comparisons to TS and lithium beam (Schmitz et al. 2008):   n e 10%,  T e 30%  Observed beam penetration smaller than model by 30% Comparative measurements on TEXTOR (Schmitz, et al., Plasma Phys. Control. Fusion 50 (2008) 115004)

5 5  CR model of the helium beam is a complex system with many uncertain parameters  Quantitative errors in n e /T e  Probabilistic approach provides: Diagnostic design study: application of helium beam in the high density divertor plasma of the stellarator W7-X Statements on atomic data (correction factors, uncertainties) by analysis of (uncertain) experimental data. Why probabilistic CR model for helium beam

6 prior knowledge likelihood Bayesian CR modelling of (relaxed) helium beam posterior marginalised posterior  Take n e /T e, simulate line ratios, D 2-dim posterior (parameters of interest) further marginalise 1-dim posteriors 6

7 7 Model assumptions  Steady state solution (transport neglected, n e > 2×10 12 cm -3 )  Collisional processes included: electronic (de)excitation and ionization, no charge exchange  n = 1-5 included (29 levels)  n = 1-4: „helike_hps02he_t3.adf”, n = 5: compilation by Brix (phd)  High density, low temperature W7-X divertor plasma: n e = 10 14 cm -3, T e = 5 eV

8 9%9% 4.7% 3.2% 15% 21% 31% 25% n=3-4 30% 45% 8 ADAS dataset „helike_hps02he_t3.adf”: uncertainties 5%5% 20% n=3-4 50%

9 Measure 2 line ratios  Relatively large n e /T e errors  Diagnostic design study 9  n e =128%  T e =45%

10 Measure 3 absolute line intensities beam density (attenuation) uncertain: +/- 50%  Strongly reduced n e /T e errors 10  n e =66% Te=8%Te=8%

11 Fit 3 line intensities Measurement error: 5%  n e = 66%  T e = 8% Enlarge signal noise Increase number of spectral lines Measurement errors 5 → 10%  T e : 8.7% 11 Fit one additional line (501.6 nm)  T e : 8.5% Fit two more lines (492.2, 504.8 nm)  T e : 7.8% n e [cm -3 ]  n e = 122%  n e = 103%  n e = 107%

12 12  n e =50%  T e =26%  Use comparisons to other diagnostics at TEXTOR:  n e = 10%,  T e = 30%  T e = 32 eV, n e = 4×10 12 cm -3  Run Bayesian analysis using RCs and their uncertainties from „helike_hps02he_t3.adf” Refining the beam excitation model  Some RC uncertainties in „helike_hps02he_t3.adf” are overestimated !

13 13 Refining the beam excitation model  Priors: RCs from „helike_hps02he_t3.adf” as before New: n e, T e : Gauss profile, width of 10% and 30% respectively (observation)  Marginalise over n e, T e and all rate coefficients except for the ones of interest prior knowledge likelihood posterior marginalised posterior  Result:  RC (1 1 S-3 1 S) 9.9% (11% in ADAS)  RC (3 1 S-3 1 P) 18.2% (30% in ADAS)  But: The model is not complete  Principle suitability of Bayesian analysis for judging atomic data

14 Thank you for your attention


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