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Prediction of particle transport and density profiles in ITER

Prediction of particle transport and density profiles in ITER. I. Voitsekhovitch, C. Kessel. Action from IOS ITPA April 2013 : to present a detailed plan on the modelling of density profile for ITER H-mode scenario. Objectives:

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Prediction of particle transport and density profiles in ITER

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  1. Prediction of particle transport and density profiles in ITER I. Voitsekhovitch, C. Kessel Action from IOS ITPA April 2013: to present a detailed plan on the modelling of density profile for ITER H-mode scenario • Objectives: • Improvement of density prediction (main ions, impurities) for different phases of ITER scenarios based on particle transport and source models validated on existing experiments • Estimation of uncertainties of ITER predictions based on experimental uncertainties. Requirements to fuelling. • (iii) Optimisation of density evolution in ITER operational scenarios, density control There are many examples of particle transport modelling for existing experiments and ITER. The goal is to summarise the existing results and identify the missing issues

  2. Proposals include: • Assessment of the IOS modelling capabilities (modellers input is needed to complete the Code Summary Table (page 3)) • Description of general approach to ITER H-mode scenario modelling • Present status of density modelling (very brief summary) and actions for: - current ramp up - L-H transition and density build up - main heating phase - discharge termination • Approximate schedule

  3. Code Summary Table: transport codes used within IOS for scenario development (based on IOS presentations) - Other codes or characteristics to be added? - More detailed description of modules may be documented separately

  4. General approach to development of ITER operational scenarios: main steps Step 1. Collection of experimental multi-machine database Deliverables: data delivered to modellers Step 2. Model validation on existing experiments Deliverables: (1) statistical estimations of model’s accuracy (2) well documented adjustable parameters Step 3. Modelling of ITER scenarios Modelling/optimisation of ITER scenario (fast ‘core+pedestal’ simulations) Intermediate deliverables: reference scenarios with uncertainties to investigate with more sophisticated and time consuming packages Free boundary equilibrium Core and edge MHD Integrated core-SOL-divertor-impurity (SS) Integrated core-SOL-divertor-impurity (transients) Final deliverables: - reference scenarios with uncertainties - identification of most sensitive issues at different operational phases IO: IMAS validation, PCS This approach is proposed for density prediction during different phases of H-mode scenario

  5. Particle transport during current ramp up – present status • Step 1. Current ramp up database: collected within ISM and IOS groups (JET, DIII-D, AUG, C-mod) • Step 2. Validation for particle transport & sources models - main ion density: usually prescribed (Hogeweij et al, NF 2013, Voitsekhovitch et al PPCF 2010, …) - core impurity: ad hoc profiles constrained by Zeff or time of the first sawtooth, scan in W concentration (G.M.D. Hogeweij IOS 2013) - core main ions + impurity: Bohm-gyroBohm (BgB) + NCLASS + GLF23-like pinch, scan in W concentration (F. Koechl, IOS 2013) • Step 3. Projection to ITER: - prescribed density (or Greenwald fraction) + sensitivity studies (usual assumption) - ad hoc D, V and edge source (C. Kessel IOS 2013) - BgB model, fuelling adjusted to get prescribed Greenwald fraction (F. Koechl et al EPS 2012) - prescribed impurity concentration (explicitly or via influx controlling concentration), scan in impurity (C. Kessel IOS 2013, V Leonov, IOS 2013, F. Koechl et al EPS 2012)

  6. Particle transport during current ramp up – proposed actions • Step 1. Multi-machine database available. JET ILW discharges? • Step 2. Model validation: - JET and DIII-D data are in ASTRA and CRONOS, BgB and GLF23 models for main ions can be tested. Cmod modelling with TSC? - Current ramp up data can be provided for impurity simulations (ZIMPUR?) - Contribution from other codes? Issues to be addressed: • What neutral influx is needed to maintain given fGw? Is it consistent with edge simulations? • Effect of NBI fuelling and density peaking on current diffusion? • Effect of impurities? Deliverables: - documented modelling assumptions (transport, fuelling) and adjustable parameters - predictive capabilities of the models (rms, offset) - effect of transport and fuelling on q, li, flux consumption and sawtooth onset • Step 3. Projection to ITER with uncertainties (same issues + optimisation of fuelling): Deliverables: ITER ramp up scenarios with main ion and impurity density evolution computed with validated models.

  7. L-H transition and density build up – present status • Step 1. No L-H transition and access to type III and type I data collected within IOS (task for PEP group?). Dataset for density build up can be the same as for the main heating phase (discussed on page 9) • Step 2. Model validation: - usually Martin, sometimes Fundamenski scaling for L-H transition - power (fraction of PLH) to access type III and type I ELMy H-mode - set of models validated in coupled core-SOL simulations + N seeding for JET discharge (L-H threshold, BgB, NCLASS, Martin scaling etc.) (V. Parail et al, IOS 2013]) - few density build up simulations (Loarte et al IAEA 2012, Willensdorfer et al, NF 2013) – low particle pinch across ETB • Step 3.Projection to ITER: - usually Martin scaling is used - relatively slow pedestal rise to avoid numerical problems, arbitrary evolution of pedestal ne, Te and Ti - access to burn with ad hoc transport (prescribed D and V) and neutral source, pellet fuelling (C. Kessel, IOS 2013)

  8. L-H transition and density build up – proposed actions • Step 1. Multi-machine database: - pedestal and L-H power threshold database (PEP group?) - database for density build up (NBI, pellets) and impurity behaviour during the L-H transition (same as for the main heating phase, page 9)? • Step 2. Model validation. Issues to be addressed: - what models predict accurately the plasma dynamics? - conditions for impurity accumulation during transition? - other? Should these issues be addressed by PEP ITPA group and reported to IOS? • Step 3. Projection to ITER. Issues to be addressed: - how important is plasma dynamic during the L-H transition for access to burn? For example, characteristic time scale for density and temperature rise? - how to build the pedestal by avoiding W accumulation (increase of T with respect to n)? - how to provide the 50:50 DT fraction with D NBI fuelling and T pellets? - other?

  9. Particle transport during main heating phase – present status Step 1. 0D H-mode database collected by IOS (demonstration of ITER baseline at q95=3, fGw~0.85) (Sips et al, IAEA 2012, Stober, IOS 2013, Hubbard IOS 2013) – it can be used for particle transport study: - Large variety of heating parameters: 100% NBI (JET)  100% RF (Cmod) - NBI (JET, AUG) and edge fuelling (wall, gas puff). Pulses with pellets? - Different divertor and wall materials: CFC (JET), W (AUG), Mo (Cmod) - Need density peaking, collisionality, radiation fraction for selecting the minimal subset of discharges for main species and impurity study Sips et al, IAEA 2012

  10. Particle transport during main heating phase – present status • Step 2. Model validation: - core deuterium transport: BgB and GLF23 (but on limited database) (Garzotti et al, NF 2006 and 2012, Garcia et al, ISM 2013) - core tritium transport: MMM95 (G. Bateman), semi-empirical for tracer (Voitsekhovitch et al PoP 1995) - pedestal height: peeling-ballooning (PB) / empirical scalings / EPED - pedestal transport: ~ neoclassical or ad hoc - boundary density consistent with SOL/divertor: Kukushkin et al, JNM 2011 - but for C wall - pellets: NGPS (OK for ablation), re-deposition models do not always agree with experiments (T&C 2013 talk by M. Valovic) - core-SOL-divertor-impurities: COREDIV validated on AUG & JET, JINTRAC validated on JET shot • Step 3. Projection to ITER: • - main ions: same validated core and pedestal transport models are usually applied (Koechl et al, EPS 2012, Garzotti et al, NF 2012) • - core impurity – critical W concentration is estimated (C. Kessel IOS 2013, V. Leonov IOS 2013) • - coupled core-SOL-divertor-impurity – marginal H-mode performance at medium density with W impurity (Ivanova-Stanik et al, PET 2013, to be presented at this IOS)

  11. Particle transport during main heating phase – proposed actions Angioni et al, PPCF 2009 Step 1. Subset of IOS H-mode database to address: - effect of collisionality on density peaking - effect of central fuelling on density peaking at similar eff - impurity accumulation under different conditions Deliverables: discharges with good profile data quality for these studies Step 2. Model validation: - core + pedestal transport models at different  and central fuelling - core impurity modelling at low and high radiation - coupled core-SOL-divertor-impurity simulations Deliverables: - predictive accuracy for main ion transport models, documented assumptions and adjustable parameters - sensitivity to main ion edge source (neutral influx, energy of incoming neutrals, …) Step 3. Projection to ITER: - estimation of fusion performance with uncertainties based on model validation (core + pedestal). Is it possible to maintain equal D&T density with D NBI and T pellets? - core impurity simulations for reference cases - core-SOL-divertor-impurity simulations for reference cases - MHD analysis for reference cases • What models can predict reliably the eff dependence of density peaking? • Importance of central fuelling for density peaking at low eff? • Separation the collisionality and central fuelllng effects on density peaking Deliverables: reference scenarios with estimated uncertainties. Operational space for these scenarios

  12. Particle transport during discharge termination • Step 1. No database collected within IOS • Model validation - ohmic current ramp down (BgB, gas puff, adjusted recycling): Bizarro et al, paper on the JET Pinboard - NBI, H-L transition during the ramp down (BgB + PB + L-H threshold): Belo et al, EPS 2012, Koechl / Litaudon et al NF 2013 - measured impurities are assumed • Projection to ITER - BgB (L-mode) transport, fuelling adjusted to get prescribed Greenwald fraction (Koechl et al EPS 2012) Long-term action to be addressed after the main heating phase?

  13. Schedule and tasks depend on modellers availability. Can be something like this Current ramp up (draft schedule)

  14. Main heating phase (draft schedule) Joint modelling sessions (for example, ISM-like working sessions) would be very beneficial for modelling work

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