Analysis of disruption and RE proposals for MST Piero Martin on behalf of MST1 TFLs

Proposed experiments (clusters) 1)Disruption mitigation via Massive Gas Injection 2)Disruption avoidance 3)Runaway Electrons: scenario, physics and mitigation via MGI 4)Runaway Electrons: decorrelation via applied magnetic perturbation P. Martin| GPM 2015 | Lausanne | | Page 2

Disruption mitigation via Massive Gas Injection A joint AUG/TCV/modeling experiment Background proposals: H1.3_MST_D_2, Disruption mitigation with MGI, Pautasso H1.3_MST_D_14 Model MGI-mitigated disruptions with JOREK, Nardon H1.3_MST_D_16, Assessment of thermal load mitigation during MGI, Lehnen P. Martin| GPM 2015 | Lausanne | | Page 3

MGI experiment deliverables 1) Define the role of injected gas quantity (AUG, TCV) -How does heat load on the divertor plate depend on the quantity/flow rate/type of injected impurities ? o AUG used the amount of gas equivalent to that foreseen on ITER, but…the amount of gas that will be absorbed by the ITER plasma will be 1-2 order of magnitude lower due to the distance of the valve from the plasma. -Identify minimum quantity required for mitigation 2) Define the role of the number and position of valves (AUG & TCV) –How it affects fuelling efficiency and redistribution.asymmetry of radiated power? –Assess the role of plasma-valve gap (gap scan) P. Martin| GPM 2015 | Lausanne | | Page 4

MGI experiment deliverables - 2 3) Describe the role of MHD (AUG &TCV) -Test MGI with q 0 >1 and q 0 < 1, to check impact of m=1, n=1 -Test MGI in locked plasmas 4) Assess the role of e-i equipartition in limited radiation fraction (TCV) -Change T e /T i variation (ECRH/NBI) to test impact of e-i equipartition on E rad /E th 5) Describe the role of intrinsic impurities (AUG) –How they influence disruption dynamics at low amounts of injected impurities? P. Martin| GPM 2015 | Lausanne | | Page 5

MGI modeling SOLPS to reproduce experimental observations for gas quantity JOREK: complete work with D2 (preliminary MGI simulation in 2014), extend to other gases, benchmark against data Gas penetration physics is being studied with the 1D code IMAGINE Fil, ITPA MHD Padova,(2014) P. Martin| GPM 2015 | Lausanne | | Page 6

Disruption avoidance: via applied magnetic perturbation via ECCD at high beta and close to density limit via model based plasma supervision A joint AUG/TCV/modeling experiment P. Martin| GPM 2015 | Lausanne | | Page 7

Supporting proposals Disruption avoidance: via applied magnetic perturbation H1.3_MST_D_7, Control of the locking position of locked modes near disruptions, Maraschek H1.3_MST_D_9, Determination and correction of the static intrinsic error field, Maraschek H1.3_MST_D_13, 2/1 NTM wall-locking avoidance by forced rotation through external magnetic perturbations, Zanca Via ECCD at high beta and close to density limit H1.3_MST_D_6, Disruption control in high beta_N and high density scenarios with ECCD/ECRH, Esposito&Maraschek H1.3_MST_D_8, Application of disruption avoidance techniques (ECCD/ECRH) in accessible scenarios, Maraschek via model based plasma supervision H1.3_MST_D_5, Model-based plasma supervision and disruption avoidance, Felici P. Martin| GPM 2015 | Lausanne | | Page 8

Disruption avoidance: via applied magnetic perturbation via ECCD at high beta and close to density limit via model based plasma supervision P. Martin| GPM 2015 | Lausanne | | Page 9

Controlling the locked mode Magnetic forces can be exerted by coils to drag the island in the optimum position for ECCD illumination. Volpe et al PoP 16 (2009) P. Martin| GPM 2015 | Lausanne | | Page 10

M. Okabayashi P. Zanca et al, IAEA 2014 P. Martin| GPM 2015 | Lausanne | | Page 11

HL1.1 evaluation | Page 12

1) Reliable active control of the mode locking position, for efficient ECRH/ECCD stabilizing action or to gain time for soft-landing Static: apply external perturbation to control locking position on a shot-by-shot basis Dynamic: lock mode entrainment to the rotating applied perturbation Disruption avoidance via magnetic perturbation deliverables P. Martin| GPM 2015 | Lausanne | | Page 13

At low density intrinsic error field can penetrate the plasma and cause disruption Issue for ITER ramp-up “dirty” solution: gas puff during ramp-up, but limits op-space 2) Determine error field during low density Ip ramp Compensate intrinsic error field with B-coils Disruption avoidance via magnetic perturbation deliverables P. Martin| GPM 2015 | Lausanne | | Page 14

Disruption avoidance: via applied magnetic perturbation via ECCD at high beta and close to density limit via model based plasma supervision A joint AUG/TCV/modeling experiment P. Martin| GPM 2015 | Lausanne | | Page 15

Experiment rationale Combination of disruption precursor signals to trigger in real time EC that targets a rational surface to: o reducing or suppressing the main MHD mode leading to the disruption o delaying or even avoiding the current quench. Accuracy in EC power deposition location and the timing of the intervention, key elements for a successful avoidance P. Martin| GPM 2015 | Lausanne | | Page 16

Disruption avoidance via ECCD Esposito, Maraschek, MST review meeting (2014) P. Martin| GPM 2015 | Lausanne | | Page 17

Disruption avoidance via ECCD deliverables 1Establish the required steering precision and the tracking strategy on q=2 surface 2Deploy new precursor signals in RT: Singular Value Decomposition disruption prediction algorithm (based on Mirnov coils, porting from FTU) 3Determine the ECCD power threshold required for disruption avoidance 4Perform density limit disruption avoidance in H-mode scenarios 5Develop overall strategy for disruption avoidance including discharge soft shut down 6Develop new strategy based on two gyrotrons on 3/2 and 2/1 resonant surfaces 7Once succesfull, move towards routine application Could be performed also in TCV ? Not foreseen in original proposal P. Martin| GPM 2015 | Lausanne | | Page 18

Disruption avoidance: via applied magnetic perturbation via ECCD at high beta and close to density limit via model based plasma supervision A joint AUG/TCV/modeling experiment P. Martin| GPM 2015 | Lausanne | | Page 19

State observer At each step, a model of the physical system generate a predicted state estimate, from which a set of predicted measurements is computed. State estimate then improved based on the discrepancy between predicted measurements and actual measurements, yielding an updated state estimate. Felici, MST review meeting (2014) P. Martin| GPM 2015 | Lausanne | | Page 20

Disruption avoidance via model-based plasma supervision deliverables 1) Implement a model-based plasma scenario supervision system based on RAPTOR that compares the physics expectation for the evolution of the plasma with diagnostic measurements state of the plasma with known limiits..and flags when thresholds are exceeded. 2)Implement and test safe ramp-down strategies to actuate a soft-stop if threshold violations are detected Development of real-time algorithms, mostly piggy-back Application to specific high-performance shots when ready. Machine-independent, test same algorithms on TCV and AUG P. Martin| GPM 2015 | Lausanne | | Page 21

Runaway Electrons: Scenario, physics and mitigation via MGI A joint AUG/TCV/modeling experiment Background proposals: H1.3_MST_D_3, Runaway electron generation and dissipation, Papp H1.3_MST_D_10 Runaway electrons and disruption physics, Decker H1.3_MST_D_11, Effect of MGI asymmetry on generation and suppression of runaway electrons, Plyusnin H1.3_MST_D_15a, Model runaway electrons as test particles in JOREK, Nardon H1.3_MST_D_15b, Effect of plasma shaping on runaway electrons generation/loss, Reux P. Martin| GPM 2015 | Lausanne | | Page 22

Runaway scenario available in AUG and TCV Reliable, efficient and safe scenario was developed for RE generation at AUG in 2014 (circular IWL, 2.5*10 19, 2.5 T, 0.8 MA, w/ ECRH) Disruption and RE induced with #1 Ar puff REs can be suppressed with #2 Ar puff Pautasso, MST review meeting (2014) P. Martin| GPM 2015 | Lausanne | | Page 23

Granetz, IAEA FEC (2014) P. Martin| GPM 2015 | Lausanne | | Page 24

Runaway electron deliverables 1) RE generation characterization (AUG&TCV) Describe RE seed intensity (pre-existing fast electrons) with different mix of NBI/ECRH Assess RE generation scenario (current, Bt, MGI dependencies) Determination of the critical field Describe effect of shaping (aspect ratio/elongation) 2) RE losses (AUG&TCV) Characterize the effect of MHD instabilities on runaway electron confinement Shaping (does elongation suppress runaways?) 3) RE mitigation (AUG&TCV) Assess mitigation with Ne (ITER relevant) Compare MGI effect from close and distant injection P. Martin| GPM 2015 | Lausanne | | Page 25

RE modeling CLISTE time dependent solution of Grad Shafranov Equation to improve modeling of beam evolution JOREK: runaway electrons as test particles In simulations of MGI-mitigated disruptions Deconfinement by MHD turbulence Limited vs. diverted plasmas AUG vs. JET LUKE: kinetic modelling (3d Fokker Planck) of runaway formation P. Martin| GPM 2015 | Lausanne | | Page 26

Runaway Electrons: Decorrelation via applied magnetic perturbation Background proposals: H1.3_MST_D_17 Decorrelation of runaway electrons by magnetic perturbations and role of 3D plasma response, Gobbin H1.3_MST_D_3, Runaway electron generation and dissipation, Papp H1.3_MST_D_19, Runaway electron position control and current ramp-down, Carnevale P. Martin| GPM 2015 | Lausanne | | Page 27

Runaway losses and magnetic stochasticity Izzo IAEA FEC 2010 Nimrod P. Martin| GPM 2015 | Lausanne | | Page 28

Runaway losses and magnetic stochasticity Enhanced losses with externally applied magnetic perturbation Piero Martin| 2015 GPM | Lausanne | | Page 29 DIII-D TEXTOR RFX tok ITER Papp PPCF 2012 Lehnen PRL 2008 Hollmann PoP 2010 Gobbin ITPA 2014

RE decorrelation deliverables 1.Assess role of spontaneous MHD instabilities in enhancing RE decorrelation (e.g. kink, tearing) o occurring during the thermal quench or when the RE beam is fully formed. 2.Impact of 3D helical deformations on RE decorrelation in response to RMPs. o Check if beam unstable/marginally unstable to n=1 modes like external kink/tearing o coupling RMPs to such modes may produce resonant field amplification. 3.Effects on MHD stability/3D helical distortions of RE mitigation methods like MGI. P. Martin| GPM 2015 | Lausanne | | Page 30

Modeling of RE beam decorrelation 3d equilibrium that forms after application of RMPs using various codes: MARS-F (linear) M3D (nonlinear), PIXIE3D, V3FIT/VMEC,… Simulations compared with measurements of 3D distortions by various diagnostics (e.g. magnetics, SXR, HXR,...). Effects of eddy-currents induced in 3D wall structures modeled with CARIDDI and CAFÉ RE transport and decorrelation: ANTS, Hamiltonian guiding center code ORBIT ….. P. Martin| GPM 2015 | Lausanne | | Page 31

Runaway electron position control and current ramp-down deliverables Get in AUG RE beam position control and current ramp-down dissipation as in FTU Obtain a reliable scenario for runaway suppression studies in AUG integrating also the MGI Develop a RE dynamic model to improve control algorithms Extension to TCV proposed as first priority I p [A] R ext [m] FC [#] time [s] P. Martin| GPM 2015 | Lausanne | | Page 32

Prediction modeling tasks Cross-machine analysis for JET and AUG disruptions (linked to JET1) - H1.3_MST_D_1 Cross-disruption predictors between AUG and JET (with link to WPJET1) - H1.3_MST_D_4 Development of a disruption precursor based on rotating MHD instabilities - H1.3_MST_D_12 Physics-based real-time identification of disruptions and their causes (with link to JET1) H1.3_MST_D_18 P. Martin| GPM 2015 | Lausanne | | Page 33

Proposed by JT-60 SA team H1.3_MST_D_20: An experimental investigation of dependence of VDE on plasma elongation and internal inductance in the TCV Tokamak Need for experiments to be defined (perhaps data mining sufficient) P. Martin| GPM 2015 | Lausanne | | Page 34

Tentative shot allocation for proposed experiments 1)Disruption mitigation via Massive Gas Injection o 20# AUG, 26# TCV 2)Disruption avoidance o Magnetic Perturb. 16# AUG o beta and close to density limit 24# AUG, 26# TCV o Model Based Plasma supervision 3# AUG, 10# TCV 3)Runaway Electrons: scenario, physics and mitigation via MGI o 24# AUG, 52# TCV 4)Runaway Electrons: decorrelation via applied magnetic perturbation o 16# AUG, 13# TCV Shot numbers are PRELIMINARY P. Martin| GPM 2015 | Lausanne | | Page 35