D. S. Darrow Princeton Plasma Physics Laboratory

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Presentation transcript:

Neutral beam ion loss simu-lation and scintillator-based loss diagnostic for NSTX D. S. Darrow Princeton Plasma Physics Laboratory 8th IAEA TCM on Energetic Particles in Magnetic Confinement Systems San Diego, CA, October 6-8, 2003 This work supported by US DoE contract number DE-AC02-76CH03073

ST fast ion confinement could differ from conventional tokamak m not necessarily conserved (LB~rfi) MHD-induced fast ion radial transport may be stronger in absence of m conservation Losses due to large rfi may generate significant Er and plasma flows (MA~0.25 seen in NSTX)

Several approaches to evaluate beam ion confinement Energetic Neutral Particle Analyzer (Medley P12) Neutron collimator diagnostic (Roquemore P9) Multi-sightline solid state NPA (Shinohara) New scintillator fast ion loss probe Detailed modeling of loss probe signals

New beam ion loss probe being installed in NSTX Enhances substantially existing Faraday cup probe Scintillator-based, so will resolve energy and pitch angle of lost beam ions Scintillator detector: principle of operation

Scintillator probe assembly Aperture Light shield Graphite armor Base & Heat sink Scintillator (inside) Plasma Vacuum window Bay J Incident ions

Apertures designed to resolve all 3 energy components of beam 80 keV D NBI => components at 80, 40, & 27 keV Probe can resolve components even at maximum BT (0.6 T): r=9.6, 6.8, & 5.6 cm Also covers ~20°-90° in pitch angle with 5° resolution Gyroradius distributions on scintillator plate at 0.3 T

Scintillator plate also contains embedded Faraday cups Cups formed by undercoated aluminum layer Allows rapid absolute calibration & gives fast time response Cups matched to ~10° bins in pitch angle

Want to calculate classical beam ion loss rate to detector at wall Comparison of calculation with measurement should allow determination of which components of loss are new features of spherical tokamak geometry vs classically-expected losses

Faraday cup loss probe sees signals from NBI

Detailed model needed since loss varies strongly with outer gap Outer gap is distance from separatrix to limiter at outer midplane

Detector signal calculation (isotropic source) Follow full gyro-orbit backward from detector through plasma; integrate source strength along orbit path & normalize by total source rate*: TFTR For isotropically-emitted fast ions (e.g. as), integral over W is trivial (S(W) = constant) *Follows Chrien ‘80, Heidbrink ‘84

Detector signal calculation (directional source) For neutral beam ions, use S(x, W) = Sx(x)Sv(W), with Sv(W) = exp(-q2/qb2), q=angle between particle velocity vector & beam injection direction, qb=beam divergence angle q=1.5° for NSTX beams, so contributing portion of velocity space is quite small (0.002 sr)

Spatial part of beam source function is also well localized 1/e width of beam: 12 cm horizontal 42 cm vertical

Typical orbit to detector Commonly, only a few steps contribute in each orbit

Difference between TFTR & NSTX geometries vastly changes model gaper Lorbit Dg Lsource Aperture Source TFTR: La ~10 cm, Lorb~1000 cm, so can resolve a source profile with Dg~0.01 rads. Aperture extent is 1-D, so need only compute gaper/Dg~100 orbits NSTX: LNB~6 cm, Lorb~10,000 cm => need Dg~0.0006 rads. Aperture extent is 2-D, so need to follow (gaper/Dg)2~2,800,000 orbits to resolve source distribution accurately(!) 0.1 x 1.3 cm 0.6 cm diam

Finely-resolved sampling confirms extremely localized source Aperture y Aperture x Aperture divided into 1000 x 1000 This level of resolution clearly insufficient

Further developments required Confirm that integration error remains small enough to not affect modeled signal Parallelize calculation Apply adaptive mesh to focus computation on regions where signal contribution is most significant

Summary New fast ion loss detector will be available on NSTX for coming experimental campaigns Resolves E & c of loss Developing model to compute classical orbit loss to detectors in NSTX Geometry & beam localization in v-space make this computationally much more intensive than previous similar models