Particles WG Summary ITPA CDBM, Lausanne

Main results 1.H-mode profile database JET & AUG databases united, eff and  main governing parameters for density peaking. Strong correlation with N G., little evidence for curvature pinch and thermodiffusion. C-MOD joined with recent experiments, lifting any doubt on possible role of N G in favor of eff Prediction of moderately peaked density profile ~1.5 for ITER in inductive and hybrid scenarios TCV (2 groups of peaking for same eff ) and JT-60U (more peaked) disturb the cosy JET-AUG-C-MOD picture and suggest additional physics governs particle convection. C-MOD, JT-60U and TCV have negligible core sources. Strong electron heating and ripple effects, rotation and uncertaintenties may be some clues as to where to look. 2.L-modes TCV and JET database shows clear dominance of TEP or curvature type pinch in Ohmic plasmas (TCV) and JET (all plasmas). Core ECH leads to partial flattening in TCV qualitatively consistently with TEM thermodiffusion. L-mode peaking is not or weakly susceptible to changes in eff. Difference in l i may be a clue to difference with H-modes. (H: l i 1)

3.Non-axisymetrical confinement LHD shows competition of outward neoclassical convection and anomalous transport. Behaviour tokamak-like (moderate peaking) with low ripple configuration at all collisionalities explored, implying the existence of an anomalous inward pinch. High ripple => hollow profiles. Convection close to neoclassical. Diffusion ~10 times above NC Anomalous effects modelled qualitatively by ITG/TEM drift turbulence Demonstrates interest of low ripple stellarator configurations TCV plasmas with broken axisymetry (due to 1,1 mode) and core electron heating also develop hollow profiles in core.

4.Impurity transport Overwhelming evidence for anomalous transport collected over many years, shown once more at this meeting with recent work. JET: steady-state impurity profiles typically less peaked than n e (r), even flat to hollow (C, He) TCV: n c profiles more peaked than n e in Ohmic. Become similar (flatter) with ECH. Transport close to NC only in core (AUG,JET), prone to high Z accumulation. Core becomes anomalous with ‘modest’ amount of core electron heating (Q: what is ‘modest’ in ITER? Role of heating/equipartition?). Core ECH/ICRH established tools to reduce core n z, even when n z peaking not ascribed to NC effect (carbon in TCV L-mode). Theory explains anomalous impurity convection by combination of curvature pinch, thermodiffusion and effect of // velocity fluctations. Latter two are of opposite sign and sign of thermodiffusion switches inward/outward for TEM/ITG. Effect of fuel density peaking of 1.46 (ITER extrapolation) leads to 30% extra fusion power (Q~30) at given volume average density and beta, assuming Ti profile such as in simulations (Polelevoi 2003) and no change in inpurity, He concentration. This advantage is only lost if V He /D He >2V D /D D and n He (a)=4e18m -3 for pumping the He produced by 400MW of fusion power. (Lousy pumping, reference is n He (a)=1e18m -3 ) Observations in JET show V He /D He <0, i.e. main plasma contributes to He compression, alleviating pumping requirements.

Joint work 1.Previous recommendations Scan towards low eff did not get time at participating labs. Recent C-mod data, just like JET and AUG are data scavenging from other experiments. 2.Database extensions 1.More devices: Add TCV, JT-60U. Contact person for DIII-D, NSTX, MAST, HL-2A etc, new machines when running 2.Database extensions : impurities Add as new impurities enter (sparse data) Steady state nz(r), Vz,Dz, error bars, profiles, tauz Participants: JET TCV C-MOD AUG JT-60U …Check what is available first. Most interesting at low nueff or scan 3.Database format: how to share Central database with web interface, MDS, structured data, same names and quantities as profile db where defs coincide, extendable, interfaceable with profile db: Martin Greenwald Nodes to contain data plus any relevant info (errors, type of diagnostic…) 2nd step: Raw data with location also? Psi(R,Z)? Shape of VV. 4.Theory (de)validation: participants Par Strand, Clemente Angioni, David Mikkelsen, Emiliano Fable, ? Files format for exchange with theory. Gyro input format? Public documentation of codeinput and results, to be stored in database too.

2.bis) Code validations. Can codes reproduce observed behaviour at least where experimental behaviour is robust? (->ITER) Ne profiles / GLF23 does good job in H-mode (state where  =  _fuelling). Systematic runs to check dependencies done, comparison with experimental db should be easy E.Fable/HWeisen (TGLF should be much better, to be checked). Same for P.Strand /HWeisen with Weiland model. Export representative experimental samples showing documented dependencies to theorists using same data structure. Same for impurity profiles: can be included in GLF23 & Weiland, Multispecies quasilinear and nonlinear GK runs (C Angioni, D Mikkelsen) Z scaling. JET data in 1 year? 3.Relation between heat and particle/impurity transport coefficients Evidence for D~chi, except ITB’s and near axis. Long history. Collect/review data? 4. Gas fuelling efficiency scaling with plasma opacity (C-MOD data up to half ITER opacity, no sign that it becomes unfuellable)

Impact of Particle group ITER modeling should include peaked profiles as expected from recent results ~1.5. Major change to operating point. Impact on divertor and pumping. Lower edge n e if kept at nominal values. Ways out: raise edge n e, at constant . This only slightly reduced gain from peaked profile. Issue with burn control? Also more power to divertor and walls, influence on ELMs etc Pressure profiles may be more peaked->stability, more bootstrap, Less consolidated, but potentially very important: impurity profiles, esp. hollow n c, n He profiles, good for He pumping. Wayne to communicate to coordinating council?

Meeting,Publications Only some members can come to ITPA in Japan september Specific work session tbd? Meet in US spring 2008 with lots done! Letter comparing C-MOD with JET/AUG Medium term: –Plan code/experiment comparison when done –Documentation of multi-machine behaviour when more machines in DB