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We have modelled self-consistently how to most efficiently fuel ITER hydrogen (H), helium (He) and deuterium–tritium (DT) plasmas with gas and/or pellets with the integrated core and 2D SOL/divertor suite of codes JINTRAC. This paper presents the first overview of full integrated simulations from core to divertor of ITER scenarios following their evolution from X-point formation, through L-mode, L–H transition, steady-state H-mode, H–L transition and current ramp-down. Our simulations respect all ITER operational limits, maintaining the target power loads below 10 MW m−2 by timely gas fuelling or Ne seeding. For the pre-fusion plasma operation (PFPO) phase our aim was to develop robust scenarios and our simulations show that commissioning and operation of the ITER neutral beam (NB) to full power should be possible in 15 MA/5.3 T L-mode H plasmas with pellet fuelling and 20 MW of ECRH. For He plasmas gas fuelling alone allows access to H-mode at 7.5 MA/2.65 T with 53–73 MW of additional heating, since after application of NB and during the L–H transition, the modelled density build-up quickly reduces the NB shine-through losses to acceptable levels. This should allow the characterisation of ITER H-mode plasmas and the demonstration of ELM control schemes in PFPO-2. In ITER DT plasmas we varied the fuelling and heating schemes to achieve a target fusion gain of Q = 10 and to exit the plasma from such conditions with acceptable divertor loads. The use of pellets in DT can provide a faster increase of the density in L-modes, but it is not essential for unrestricted NB operation due to the lower shine-through losses compared to H. During the H–L transition and current ramp-down, gas fuelling and Ne seeding are required to keep the divertor power loads under the engineering limits but accurate control over radiation is crucial to prevent the plasma becoming thermally unstable.

ELM mitigation to avoid melting of the tungsten (W) divertor is one of the main factors affecting plasma fuelling and detachment control at full current for high Q operation in ITER. Here we derive the ITER operational space, where ELM mitigation to avoid melting of the W divertor monoblocks top surface is not required and appropriate control of W sources and radiation in the main plasma can be ensured through ELM control by pellet pacing. We apply the experimental scaling that relates the maximum ELM energy density deposited at the divertor with the pedestal parameters and this eliminates the uncertainty related with the ELM wetted area for energy deposition at the divertor and enables the definition of the ITER operating space through global plasma parameters. Our evaluation is thus based on this empirical scaling for ELM power loads together with the scaling for the pedestal pressure limit based on predictions from stability codes. In particular, our analysis has revealed that for the pedestal pressure predicted by the EPED1 + SOLPS scaling, ELM mitigation to avoid melting of the W divertor monoblocks top surface may not be required for 2.65 T H-modes with normalized pedestal densities (to the Greenwald limit) larger than 0.5 to a level of current of 6.5–7.5 MA, which depends on assumptions on the divertor power flux during ELMs and between ELMs that expand the range of experimental uncertainties. The pellet and gas fuelling requirements compatible with control of plasma detachment, core plasma tungsten accumulation and H-mode operation (including post-ELM W transient radiation) have been assessed by 1.5D transport simulations for a range of assumptions regarding W re-deposition at the divertor including the most conservative assumption of zero prompt re-deposition. With such conservative assumptions, the post-ELM W transient radiation imposes a very stringent limit on ELM energy losses and the associated minimum required ELM frequency. Depending on W transport assumptions during the ELM, a maximum ELM frequency is also identified above which core tungsten accumulation takes place.

In the four-stage approach of the new ITER Research Plan, the first pre-fusion power operation (PFPO) phase will only have limited power available from external heating and current drive (H&CD) systems: 20-30 MW provided by the electron cyclotron resonance heating (ECRH) system. Accessing the H-mode confinement regime at such low auxiliary power requires operating at low magnetic field, plasma current and density, i.e. 1.8 T and 5 MA for a density between 40% and 50% of the Greenwald density. II-mode plasmas at 5 MA/1.8 T will also be investigated in the second PFPO phase when ITER will have its full complement of H&CD capabilities installed, i.e. 20-30 MW of ECRH, 20 MW of ion cyclotron resonance heating and 33 MW of neutral beam injection. This paper describes the operational constraints and the II&CD capabilities for such scenarios in hydrogen and helium plasmas, to assess their viability and the issues it will be possible to address with them. The modelling results show that 5 MA/1.8 T scenarios are viable and will allow the exploration of the H-mode physics and control issues foreseen in the ITER Research Programme in the PFPO phases.

Content: EU DEMO studies for pulsed (DEMO1) and steady-state (DEMO2) concepts are currently in the pre-conceptual phase [1]. DEMO1 aims at producing about 2GW of fusion power with a burn time of approximately 2 hours. Within EUROfusion Power Plant Physics and Technology department, DEMO scenario modelling is carried out as part of the validation of feasibility and performance of DEMO designs. One of the most challenging activities deals with numerical investigations of DEMO1 transient phases including ramp-up and ramp-down, which exhibit peculiar issues with respect to existing devices. Studies on ramp-up have been carried out to highlight the effects of different ramp-up options in terms of robustness of the access to the desired flattop scenario. A heating power during ramp-up, additional to the one required during flattop, appears to be necessary for plasma burn initiation and access to H-mode, with Paux,RU50MW depending on the uncertainties on L-H transition scaling. Current ramp-rate and heating power influence also plasma position controllability, and results are presented in terms of the achieved li(3) and bp. Additional power requirements and integration of different systems which are relevant for DEMO heating mix assessment are here discussed. Ramp-down phase in DEMO poses specific issues on vertical stability given the distance of control actuators from the plasma. Ramp-down trajectories with controllable plasma boundaries have been coupled to transport studies showing the necessity of additional ramp-down heating power to avoid radiative plasma collapses. Off-axis power deposition helps plasma controllability, together with a current ramp-rate100kA/s. Plasma radiation also dominates the H-L transition, which is investigated and appears to be a critical step in terms of plasma control. DEMO performance is strongly linked to the maximum plasma elongation, which has to be assessed comparing different ramp-down trajectories. [1] G. Federici et. al, Fus. Eng. Des. 89, 882-889 (2014)

The Demonstration Fusion Power Reactor DEMO is the step foreseen to bridge the gap between ITER and the first commercial fusion power plant. One key element in the European work plan for DEMO is the elaboration of a conceptual design for a suitable core particle fuelling system. First considerations for such a system are presented in this contribution. Following the well-considered ITER solution, most analysis performed in this study assumes conventional pellet technology will be used for the fuelling system. However, taking advantage of the less compressed time frame for the DEMO project, several other techniques thought to bear potential for advanced fuelling performance are considered as well. In a first, basic analysis all actuation parameters at hand and their implications on the fuelling performance were considered. Tentative transport modeling of a reference scenario strongly indicates only particles deposited inside the plasma pedestal allow for efficient fuelling. Shallow edge fuelling results in an unbearable burden on the fuel cycle. Sufficiently deep particle deposition seems technically achievable, provided pellets are launched from the torus inboard at sufficient speed. All components required for a DEMO pellet system capable for high speed inboard pellet launch are already available or can be developed in due time with reasonable efforts. Furthermore, steps to integrate this solution into the EU DEMO model are taken.

The XGC1 edge gyrokinetic code is used for a high fidelity prediction for the width of the heat-flux to divertor plates in attached plasma condition. The simulation results are validated against the empirical scaling $\lambda_q \propto B_P^{-\gamma}$ obtained from present tokamak devices, where $\lambda_q$ is the divertor heat-flux width mapped to the outboard midplane and $\gamma_q=1.19$ as defined by T. Eich et al. [Nucl. Fusion 53 (2013) 093031], and $B_P$ is the magnitude of the poloidal magnetic field at outboard midplane separatrix surface. This empirical scaling predicts $\lambda_q \leq 1mm$ when extrapolated to ITER, which would require operation with very high separatrix densities $(n_{sep}/n_{Greenwald} > 0.6)$ in the Q=10 scenario to achieve semi-detached plasma operation and high radiative fractions leading to acceptable divertor power fluxes. XGC1 predicts, however, that $\lambda_q$ for ITER is over 5 mm, suggesting that operation in the ITER Q=10 scenario with acceptable divertor power loads could be obtained over a wider range of plasma separatrix densities and radiative fractions. The physics reason behind this difference is, according to the XGC1 results, that while the ion magnetic drift contribution to the divertor heat-flux width is wider in the present tokamaks, the turbulent electron contribution is wider in ITER. A high current C-Mod discharge is found to be in a mixed regime: While the heat-flux width by the ion neoclassical magnetic drift is still wider than the turbulent electron heat-flux width, the heat-flux magnitude is dominated by the narrower electron heat-flux., Comment: Submitted to Nuclear Fusion

The ExB shear stabilisation of anomalous transport in JET hybrid discharges is studied via selfconsistent predictive modelling of electron and ion temperature, ion density and toroidal rotation velocity performed with the GLF23 model. The ExB shear stabilisation factor (parameter aE in the GLF23 model) is adjusted to predict accurately the four simulated quantities under different experimental conditions, and the uncertainty in aE determined by 15% deviation between simulated and measured quantities is estimated. A correlation of aE with toroidal rotation velocity and ExB shearing rate is found in the low density plasmas, suggesting that the turbulence quench rule may be more complicated than assumed in the GLF23 model with constant aE. For the selected discharges the best predictive accuracy is obtained by using weak/no ExB shear stabilisation (i.e. aE 0) at low toroidal angular frequency (W < 60krad/s), even in the scenarios with the current overshoot, and aE = 0.9 at high frequency (W > 100krad/s). Interestingly, a weak ExB shear stabilisation of anomalous transport is found in the medium density strongly rotating discharge. An importance of linear be stabilisation in this discharge is estimated and compared to the low density discharge with equally high be. The toroidal rotation velocity is well predicted here by assuming that the momentum diffusion coefficient is a fraction of thermal ion diffusivity. Taking into account the aE and Prandtl number with their uncertainties determined in the modelling of JET hybrid discharges, the performance of ITER hybrid scenario with optimised heat mix (33MW of NBI and 20MW of ECCD) is estimated showing the importance of toroidal rotation for achieving Q > 5.

D. Kalupin, I. Ivanova-Stanik, I. Voitsekhovitch, J. Ferreira, D. Coster, L.L. Alves, Th. Aniel, J.F Artaud, V. Basiuk, J.P.S. Bizarro, R. Coelho, A. Czarnecka, Ph. Huynh, A. Figueiredo, J. Garcia, L. Garzotti, F. Imbeaux, F. Köchl, M.F. Nave, G. Pereverzev, O. Sauter, B.D. Scott, R. Stankiewicz, P. Strand, ITM-TF contributors and JET EFDA contributors The "European Transport Simulator" (ETS) is the new modular package for 1-D discharge evolution developed within the EFDA Integrated Tokamak Modelling (ITM) Task Force. It consists of precompiled physics modules combined into a workflow through standardized input/ output data-structures. Ultimately, the ETS will allow for an entire discharge simulation from the start up until the current termination phase, including controllers and sub-systems. The paper presents the current status of the ETS towards this ultimate goal. It discusses the design of the workflow, and presents the first physics applications of the ETS for the analysis of JET tokamak discharges.

The empirical Bohm-gyro-Bohm (BgB) transport model implemented in the JETTO code is used to predictively simulate the purely Ohmic (OH), L-mode current-ramp-down phase of three JET hybrid pulses, which combine two different ramp rates with two different electron densities (at the beginning of the ramp). The modelling is discussed, namely the strategy to reduce as much as possible the number of free parameters used to benchmark the model predictions against the experimental results. Hence, by keeping the gas puffing rate as measured whilst tuning the line-araverage electron density via the recycling coefficient (which in the modelling is taken at the separatrix instead of the wall), it is shown that the BgB model reproduces well the experimental data, as far as both average quantities (plasma internal inductance, linear-average electron density and volume average electron temperature) and profiles (electron density and temperature) are concerned, with relative errors remaining mostly below 20%. The sensitiveness with respect to the recycling coefficient, the ion effective charge and the energy of neutrals entering the plasma through the separatrix are assessed, being also shown the need for a proper sawtooth model if experimental results are to be reproduced. The strong non-linear coupling in a OH plasma between density, temperature and current (essentially via interplay between the power-balance equation, Joule's heating with a temperaturedependent resistivity and the dependence of BgB transport coefficients on profile gradients) is put in evidence and analyzed in light of modelling results. It is still inferred from the modelling that the real value of the recycling coefficient at the separatrix (basically, the so-called fuelling efficiency times the actual recycling coefficient at the wall) must become close to one in the final stages of the discharges, when the gas puffing is switched off and so recycling comes to be the only source of particles. If the wall recycling remains close to one (as standard for tokamaks), this may indicate that the fuelling efficiency also approaches unity, apparently consistent with the observed fact that the plasma is pushed towards the machine wall at the end of the current ramps.

Fuelling requirements for ITER are analysed in relation to pellet fuelling and ELM pacing, and a divertor power load control consistent with the ITER pumping and fuel throughput capabilities. The plasma parameters at the separatrix and the particle sources are derived from scalings based on SOLPS simulations. Effective transport coefficients in the H-mode pedestal are derived from EPED1 + SOLPS scalings for the pedestal height and width. 1.5D transport is simulated in the ASTRA framework. The operating window for ITER DT plasmas with the required fusion performance and level of ELM, and divertor power load control compatible with ITER fuelling and pumping capabilities, is determined. It is shown that the flexibility of the ITER fuelling systems, comprising pellet and gas injection systems, enables operation with Q = 10, which was found to be marginal in previous studies following a similar approach but with different assumptions. The present assessment shows that a reduction of 〈 n e 〉 by a factor ~2 (from 9 to 5 × 1019 m−3) in 15 MA H-mode plasmas leads to a reduction in the required pellet fuelling rate by a factor of four. Results of the analysis of the fuelling requirements for a range of ITER scenarios are found to be similar to those obtained with the JINTRAC code that included 2D modelling of the edge plasma.

Plasma current density simulations of JET and JT-60U shots in reverse-q advanced scenarios based on the previous data analysis of the identity plasma experiments have been performed. The effects of the main differences between the shots (neutral beam current density (jnbi), electron density and geometry) have been studied. The reversed q-profile (which was the target in this identity experiment and is observed at the beginning of each shot) was sustained in JT-60U while it became flat in JET towards the end of the shot. In JET, jnbi is peaked on-axis whereas in JT-60U it is peaked off-axis (at ρ = 0.5) while the NBI fraction of the selected shots is the same (22-24%). A strong density ITB appeared (at ρ = 0.5) in JT-60U but not in JET. The plasma geometry was mainly set to match but it was not identical. In addition, the extrapolation to JET steady-state operation has been done by testing the sensitivity of q to different externally driven currents, electron density and geometry in predictive current diffusion simulations. Moreover, critical bootstrap current density has been analysed. The reasons for the different time evolution of q-profile have been studied with predictive current simulations with the 1.5D transport code JETTO. The current diffusion model was validated against reverse-q shots, and simulations were performed with experimental data profiles, jNBI given by ASCOT and neoclassical resistivity and bootstrap current calculated by NCLASS. Bootstrap current density was the most efficient way to sustain the beneficial reverse shape of q-profile. Replacing the JET ne profile with one from JT-60U leads to an increase of 0.2-0.3 MA in the bootstrap current (f bs increases from 15% to 30%). However, sustaining the stationary reverse q is not achieved in JET with bootstrap current induced by the density gradient of JT-60U. Even 10 times larger gradient than in JT-60U helps to sustain the shape of the q-profile longer than the experimentally observed density profile in JET but the minimum value of q moves closer to central plasma and the shape of q is not stationary in a 10 s simulation. The effect of different shape of NBI current density profile is negligible due to quite small fraction. Sustaining the reverse q requires 45% or larger added off-axis fraction. However, increasing the inverse aspect ratio increases bootstrap current and decreases the critical bootstrap current more effectively than increasing the density gradient: two times larger inverse aspect ratio produces almost three times larger bootstrap fraction but ten times larger density gradient only two times larger bootstrap fraction. The conclusions based on these simulations indicate that the need for bootstrap current is larger in JET and the same conditions cause smaller bootstrap fraction, which suggests that achieving steady-state operation in JET under these conditions is unlikely.

Experiments in Alcator C-Mod tokamak plasmas in the Enhanced D-alpha H-mode regime with ITER-like mid-radius plasma density peaking and Ion Cyclotron Resonant heating, in which tungsten is introduced by the laser blow-off technique, have demonstrated that accumulation of tungsten in the central region of the plasma does not take place in these conditions. The measurements obtained are consistent with anomalous transport dominating tungsten transport except in the central region of the plasma where tungsten transport is neoclassical, as previously observed in other devices with dominant neutral beam injection heating, such as JET and ASDEX Upgrade. In contrast to such results, however, the measured scale lengths for plasma temperature and density in the central region of these Alcator C-Mod plasmas, with density profiles relatively flat in the core region due to the lack of core fuelling, are favourable to prevent inter and intra sawtooth tungsten accumulation in this region under dominance of neoclassical...

For investigating the damping effect of low-order rational surfaces on the drift of pellet deposited plasmoids, a safety factor (q) profile scan experiment was performed in Tore Supra, on a series of discharges with identical temperature and density profiles. Fast time-resolved density measurements show that the position of the deposition peak does not move smoothly during the ablation/homogenization phase but changes step by step, each step being located close to an integer or half-integer q value. This behaviour is well reproduced by time-dependent simulations with the pellet ablation/deposition code HPI2, which takes into account the braking of the plasmoid drift by external currents flowing along field lines in the background plasma. The key feature of this damping mechanism is a modulation as a function of the local safety factor, the braking being more effective in the vicinity of simple rational q values. The overall agreement between measurements and code predictions for a significant range of edge safety factors is fully consistent with the fact that the limitation of the plasmoid polarization by parallel currents is the dominant damping process of the ∇B-induced drift in tokamaks. (Some figures may appear in colour only in the online journal)

The paper presents the results of 1.5-dimensional simulations of density profiles and pellet fuelling for the ITER baseline scenario performed with the ASTRA and JETTO transport codes by the ITER Scenario Modelling working group within the European Task Force on Integrated Tokamak Modelling. The first part of the paper describes the physics of the problem and how it is implemented in the different codes available to the working group. The second part presents the results of the simulations. Results obtained with the GLF23 physics based transport model and a simplified description of the pellet particle source are described alongside results obtained with the simpler Bohm/gyro-Bohm semi-empirical transport model and a more sophisticated pellet ablation/deposition code providing a completely self-consistent description of the pellet source. A parametric study has been performed to assess the effect of varying parameters independently, the values of which in ITER are either uncertain or not easily controllable (such as particle diffusivity, edge stability, wall recycling and boundary conditions), on the target plasma density, temperature, Q and pellet frequency required to achieve a certain degree of density control. To this end the edge particle diffusivity was increased by a factor of three, the pedestal normalized critical pressure gradient for ballooning stability was decreased by 20%, the boundary conditions on density and temperature were modified by 30–40% and the wall recycling particle source was increased from zero to 20% of the particle outflux. The results show that variations in the order of 15% for density and temperature, 40% for Q and 100% for the pellet frequency can be expected. Open problems and modelling needs are also discussed in the paper.

The current ramp-up phase of ITER demonstration discharges, performed at JET, is analysed and the capability of the empirical L-mode Bohm–gyroBohm and Coppi–Tang transport models as well as the theory-based GLF23 model to predict the temperature evolution in these discharges is examined. The analysed database includes ohmic (OH) plasmas with various current ramp rates and plasma densities and the L-mode plasmas with the ion cyclotron radio frequency (ICRF) and neutral beam injection (NBI) heating performed at various ICRF resonance positions and NBI heating powers. The emphasis of this analysis is a data consistency test, which is particularly important here because some parameters, useful for the transport model validation, are not measured in OH and ICRF heated plasmas (e.g. ion temperature, effective charge). The sensitivity of the predictive accuracy of the transport models to the unmeasured data is estimated. It is found that the Bohm–gyroBohm model satisfactorily predicts the temperature evolution in discharges with central heating (the rms deviation between the simulated and measured temperature is within 15%), but underestimates the thermal electron transport in the OH and off-axis ICRF heated discharges. The Coppi–Tang model strongly underestimates the thermal transport in all discharges considered. A re-normalization of these empirical models for improving their predictive capability is proposed. The GLF23 model, strongly dependent on the ion temperature gradient and tested only for NBI heated discharges with measured ion temperatures, predicts accurately the temperature in the low power NBI heated discharge (rms < 10%) while the discrepancy with the data increases at high power. Based on the analysis of the JET discharges, the modelling of the current ramp-up phase for the H-mode ITER scenario is performed with particular emphasis on the sensitivity of the sawtooth-free duration of this phase to transport model.

Pellet material deposited in a tokamak plasma experiences a drift towards the low field side of the torus induced by the magnetic field gradient. Plasma fuelling in ITER relies on the beneficial effect of this drift to increase the pellet deposition depth and fuelling efficiency. It is therefore important to analyse this phenomenon in present machines to improve the understanding of the ∇B induced drift and the accuracy of the predictions for ITER. This paper presents a detailed analysis of pellet material drift in MAST pellet injection experiments based on the unique diagnostic capabilities available on this machine and compares the observations with predictions of state-of-the-art ablation and deposition codes.

Pellet injection is planned to be the main fuelling method on ITER. The high temperature of the plasma during a fusion burn will limit the penetration of the pellet to the outer third of the minor radius. This limited penetration is expected to be compensated by a polarization drift, which will deposit the particles deeper in the plasma for the pellets injected from the high field side. In order to evaluate the expected depth of the fuelling on ITER, a good understanding of this drift effect is important. Experimental data acquired on the DIII-D (USA) and Tore Supra (France) tokamaks show that the polarization drift is influenced by the low order rational q surfaces. These surfaces appear to attenuate the polarization mechanism as the drifting particles cross them. In this paper, a correlation between the maximum of the pellet mass deposition profile and the positions of the q = 2 and q = 3 surfaces on DIII-D and Tore Supra is shown for high field side and low field side injection. A model is proposed to explain this effect and compared with the experimental results. To conclude, the possible consequences of this phenomenon on the fuelling in ITER are described.

In the last few decades, pellet injection has become an important tool of discharge operation and control. In ITER, plasma fuelling and edge localized mode (ELM) pacemaking will rely mainly on pellet injection (other applications will be impurity injection for diagnostic purposes and disruption mitigation). This paper describes our present understanding of the physics of ablation and ∇B-induced displacement of the pellet material, presents last experimental results on discharge fuelling and ELM pacemaking by pellet injection and discusses—on the basis of simulation results—how the experiments performed in present day machines can be extrapolated to ITER.

Key parts of the ITER scenarios are determined by the capability of the proposed poloidal field (PF) coil set. They include the plasma breakdown at low loop voltage, the current rise phase, the performance during the flat top (FT) phase and a ramp down of the plasma. The ITER discharge evolution has been verified in dedicated experiments. New data are obtained from C-Mod, ASDEX Upgrade, DIII-D, JT-60U and JET. Results show that breakdown for E axis < 0.23–0.33 V m−1 is possible unassisted (ohmic) for large devices like JET and attainable in devices with a capability of using ECRH assist. For the current ramp up, good control of the plasma inductance is obtained using a full bore plasma shape with early X-point formation. This allows optimization of the flux usage from the PF set. Additional heating keeps l i(3) < 0.85 during the ramp up to q 95 = 3. A rise phase with an H-mode transition is capable of achieving l i(3) < 0.7 at the start of the FT. Operation of the H-mode reference scenario at q 95 ∼ 3 and the hybrid scenario at q 95 = 4–4.5 during the FT phase is documented, providing data for the l i (3) evolution after the H-mode transition and the l i (3) evolution after a back-transition to L-mode. During the ITER ramp down it is important to remain diverted and to reduce the elongation. The inductance could be kept ⩽1.2 during the first half of the current decay, using a slow I p ramp down, but still consuming flux from the transformer. Alternatively, the discharges can be kept in H-mode during most of the ramp down, requiring significant amounts of additional heating.

The ITER Scenario Modelling Working Group (ISM WG) is organized within the European Task Force on Integrated Tokamak Modelling (ITM-TF). The main responsibility of the WG is to advance a pan-European approach to integrated predictive modelling of ITER plasmas with the emphasis on urgent issues, identified during the ITER Design Review. Three major topics are discussed, which are considered as urgent and where the WG has the best possible expertize. These are modelling of current profile control, modelling of density control and impurity control in ITER (the last two topics involve modelling of both core and SOL plasma). Different methods of heating and current drive are tested as controllers for the current profile tailoring during the current ramp-up in ITER. These include Ohmic, NBI, ECRH and LHCD methods. Simulation results elucidate the available operational margins and rank different methods according to their ability to meet different requirements. A range of 'ITER-relevant' plasmas from existing tokamaks were modelled. Simulations confirmed that the theory-based transport model, GLF23, reproduces the density profile reasonably well and can be used to assess ITER profiles with both pellet injection and gas puffing. In addition, simulations of the SOL plasma were launched using both H-mode and L-mode models for perpendicular transport within the edge barrier and in the SOL. Finally, an integrated approach was also used for the predictive modelling of impurity accumulation in ITER. This includes helium ash, extrinsic impurities (such as argon) and impurities coming from the wall (including tungsten). The relative importance of anomalous and neo-classical pinch contributions towards impurity penetration through the edge transport barrier and further accumulation in the core was assessed.

CRONOS is a suite of numerical codes for the predictive/interpretative simulation of a full tokamak discharge. It integrates, in a modular structure, a 1D transport solver with general 2D magnetic equilibria, several heat, particle and impurities transport models, as well as heat, particle and momentum sources. This paper gives a first comprehensive description of the CRONOS suite: overall structure of the code, main available models, details on the simulation workflow and numerical implementation. Some examples of applications to the analysis of experimental discharges and the predictions of ITER scenarios are also given.

The JET 2019–2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019–2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (a) physics in the coming D–T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D–T benefited from the highest D–D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 and 2019–2020 under Grant Agreement No. 633053. Peer Reviewed Article signat per 1223 autors/autores: J. Mailloux1, N. Abid1, K. Abraham1, P. Abreu2, O. Adabonyan1, P. Adrich3, V. Afanasev4, M. Afzal1, T. Ahlgren5, L. Aho-Mantila6, N. Aiba7, M. Airila6, M. Akhtar1, R. 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Belonohy1, M. Ben Yaala33, J. Benayas1, J. Bentley1, H. Bergsåker34, J. Bernardo2, M. Bernert18, M. Berry1, L. Bertalot13, H. Betar35, M. Beurskens36, S. Bickerton1, B. Bieg37, J. Bielecki38, A. Bierwage7, T. Biewer29, R. Bilato18, P. Bílková39, G. Birkenmeier18, H. Bishop1, J.P.S. Bizarro2, J. Blackburn1, P. Blanchard40, P. Blatchford1, V. Bobkov18, A. Boboc1, P. Bohm39, T. Bohm41, I. Bolshakova42, T. Bolzonella23, N. Bonanomi18, D. Bonfiglio23, X. Bonnin13, P. Bonofiglo43, S. Boocock1, A. Booth1, J. Booth1, D. Borba2,30, D. Borodin44, I. Borodkina39,44, C. Boulbe45, C. Bourdelle27, M. Bowden1, K. Boyd1, I.Bozicevic Mihalic46, S.C. Bradnam1, V. Braic47, L. Brandt48, R. Bravanec49, B. Breizman50, A. Brett1, S. Brezinsek44, M. Brix1, K. Bromley1, B. Brown1, D. Brunetti1,12, R. Buckingham1, M. Buckley1, R. Budny, J. Buermans51, H. Bufferand27, P. Buratti17, A. Burgess1, A. Buscarino28, A. Busse1, D. Butcher1, E.de la Cal9, G. Calabrò52, L. Calacci53, R. Calado2, Y. Camenen54, G. 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Zychor3 // 1 United Kingdom Atomic Energy Authority, Culham Science Centre, Abingdon, Oxon, OX14 3DB, United Kingdom of Great Britain and Northern Ireland 2 Instituto de Plasmas e Fusao Nuclear, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisboa, Portugal 3 National Centre for Nuclear Research (NCBJ), 05-400 Otwock-Swierk, Poland 4 Ioffe Physico-Technical Institute, 26 Politekhnicheskaya, St Petersburg 194021, Russia 5 University of Helsinki, PO Box 43, FI-00014 University of Helsinki, Finland 6 VTT Technical Research Centre of Finland, PO Box 1000, FIN-02044 VTT, Finland 7 National Institutes for Quantum and Radiological Science and Technology, Naka, Ibaraki 311-0193, Japan 8 Consorzio CREATE, Via Claudio 21, 80125 Napoli, Italy 9 Laboratorio Nacional de Fusión, CIEMAT, Madrid, Spain 10 NCSR ‘Demokritos’ 153 10, Agia Paraskevi Attikis, Greece 11 NRC Kurchatov Institute, 1 Kurchatov Square, Moscow 123182, Russia 12 Institute for Plasma Science and Technology, CNR, via R. Cozzi 53, 20125 Milano, Italy 13 ITER Organization, Route de Vinon-sur-Verdon, CS 90 046, 13067 Saint Paul Lez Durance Cedex, France 14 Universidad Nacional de Educacion a Distancia, Dept Ingn Energet, Calle Juan del Rosal 12, E-28040 Madrid, Spain 15 Troitsk Insitute of Innovating and Thermonuclear Research (TRINITI), Troitsk 142190, Moscow Region, Russia 16 Department of Physics and Astronomy, Uppsala University, SE-75120 Uppsala, Sweden 17 Dip.to Fusione e Tecnologie per la Sicurezza Nucleare, ENEA C. R. Frascati, via E. Fermi 45, 00044 Frascati (Roma), Italy 18 Max-Planck-Institut für Plasmaphysik, D-85748 Garching, Germany 19 National Institute for Fusion Science, Oroshi, Toki, Gifu 509-5292, Japan 20 MIT Plasma Science and Fusion Center, Cambridge, MA 02139, United States of America 21 Universidad Politécnica de Madrid, Grupo I2A2, Madrid, Spain 22 Centre for Energy Research, POB 49, H-1525 Budapest, Hungary 23 Consorzio RFX, Corso Stati Uniti 4, 35127 Padova, Italy 24 University of Latvia, 19 Raina Blvd., Riga, LV 1586, Latvia 25 Department of Electrical and Electronic Engineering, University of Cagliari, Piazza d’Armi 09123 Cagliari, Italy 26 National Technical University of Athens, Iroon Politechniou 9, 157 73 Zografou, Athens, Greece 27 CEA, IRFM, F-13108 Saint Paul Lez Durance, France 28 Dipartimento di Ingegneria Elettrica Elettronica e Informatica, Università degli Studi di Catania, 95125 Catania, Italy 29 Oak Ridge National Laboratory, Oak Ridge, TN 37831, TN, United States of America 30 EUROfusion Programme Management Unit, Culham Science Centre, Culham, OX14 3DB, United Kingdom of Great Britain and Northern Ireland 31 Karlsruhe Institute of Technology, PO Box 3640, D-76021 Karlsruhe, Germany 32 General Atomics, PO Box 85608, San Diego, CA 92186-5608, United States of America 33 Department of Physics, University of Basel, Switzerland 34 Fusion Plasma Physics, EECS, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden 35 Institut Jean Lamour, UMR 7198, CNRS-Université de Lorraine, 54500 Vandoeuvre-lès-Nancy, France 36 Max-Planck-Institut für Plasmaphysik, Teilinsitut Greifswald, D-17491 Greifswald, Germany 37 Maritime University of Szczecin Faculty of Marine Engineering, Waly Chrobrego 1-2, 70-500 Szczecin, Poland 38 Institute of Nuclear Physics, Radzikowskiego 152, 31-342 Kraków, Poland 39 Institute of Plasma Physics of the CAS, Za Slovankou 1782/3, 182 00 Praha 8, Czech Republic 40 Ecole Polytechnique Fédérale de Lausanne (EPFL), Swiss Plasma Center (SPC), CH-1015 Lausanne, Switzerland 41 University of Wisconsin-Madison, Madison, WI 53706, United States of America 42 Magnetic Sensor Laboratory, Lviv Polytechnic National University, Lviv, Ukraine 43 Princeton Plasma Physics Laboratory, James Forrestal Campus, Princeton, NJ 08543, NJ, United States of America 44 Forschungszentrum Jülich GmbH, Institut für Energie- und Klimaforschung, Plasmaphysik, 52425 Jülich, Germany 45 Université Cote d’Azur, CNRS, Inria, LJAD, Parc Valrose, 06108 Nice Cedex 02, France 46 Ruder Boskovic Institute, Bijenicka 54, 10000 Zagreb, Croatia 47 The National Institute for Optoelectronics, Magurele-Bucharest, Romania 48 Mechanics, SCI, KTH SE-100 44 Stockholm, Sweden 49 Fourth State Research, 503 Lockhart Dr, Austin, TX, United States of America 50 University of Texas at Austin, Institute for Fusion Studies, Austin, TX 78712, United States of America 51 Laboratory for Plasma Physics LPP-ERM/KMS, B-1000 Brussels, Belgium 52 University of Tuscia, DEIM, Via del Paradiso 47, 01100 Viterbo, Italy 53 Università di Roma Tor Vergata, Via del Politecnico 1, Roma, Italy 54 Aix-Marseille University, CNRS, PIIM, UMR 7345, 13013 Marseille, France 55 Instituto de Física, Universidade de Sao Paulo, Rua do Mat˜ao Travessa R Nr.187, CEP 05508-090 Cidade Universitária, Sao Paulo, Brasil 56 University of Milano-Bicocca, Piazza della Scienza 3, 20126 Milano, Italy 57 Centre for Fusion, Space and Astrophysics, University of Warwick, Coventry, CV4 7AL, United Kingdom of Great Britain and Northern Ireland 58 Institute of Plasma Physics and Laser Microfusion, Hery 23, 01-497 Warsaw, Poland 59 Aalto University, PO Box 14100, FIN-00076 Aalto, Finland 60 FOM Institute DIFFER, Eindhoven, The Netherlands 61 Warsaw University of Technology, 02-507 Warsaw, Poland 62 Astrophysics Research Centre, School of Mathematics and Physics, Queen’s University, Belfast, BT7 1NN, United Kingdom of Great Britain and Northern Ireland 63 The National Institute for Laser, Plasma and Radiation Physics, Magurele-Bucharest, Romania 64 Department of Applied Physics, Ghent University, 9000 Ghent, Belgium 65 Slovenian Fusion Association (SFA), Jozef Stefan Institute, Jamova 39, SI-1000 Ljubljana, Slovenia 66 The National Institute for Cryogenics and Isotopic Technology, Ramnicu Valcea, Romania 67 Dublin City University (DCU), Dublin, Ireland 68 University of California at San Diego, La Jolla, CA 92093, United States of America 69 EUROfusion Programme Management Unit, Boltzmannstr. 2, 85748 Garching, Germany 70 UNED, Dpto. Informática y Automática, Madrid, Spain 71 National Science Center ‘Kharkov Institute of Physics and Technology’, Akademichna 1, Kharkiv 61108, Ukraine 72 York Plasma Institute, Department of Physics, University of York, York, YO10 5DD, United Kingdom of Great Britain and Northern Ireland 73 Department of Physics, Chalmers University of Technology, SE-41296 Gothenburg, Sweden 74 Department of Space, Earth and Environment, Chalmers University of Technology, SE-41296 Gothenburg, Sweden 75 European Commission, B-1049 Brussels, Belgium 76 University of Tennessee, Knoxville, TN 37996, TN, United States of America 77 Universitat Politècnica de Catalunya, Barcelona, Spain 78 Barcelona Supercomputing Center, Barcelona, Spain 79 Universidad de Sevilla, Sevilla, Spain 80 Aix-Marseille University, CNRS, IUSTI, UMR 7343, 13013 Marseille, France 81 Dipartimento di Ingegneria Astronautica, Elettrica ed Energetica, SAPIENZA Università di Roma, Via Eudossiana 18, 00184 Roma, Italy 82 Institute for Nuclear Research, Prospekt Nauky 47, Kyiv 03680, Ukraine 83 Studiecentrum voor Kernenergie—Centre d’Etude de l’Energie Nucléaire, Boeretang 200, 2400 Mol, Belgium 84 University of Toyama, Toyama, 930-8555, Japan 85 University of California, Irvine, Irvine, California 92697, United States of America 86 Department of Physics, Technical University of Denmark, Bldg 309, DK-2800 Kgs Lyngby, Denmark 87 Institution ‘Project Center ITER’, Moscow, 123182, Russia 88 Faculty of Mathematics, Department of Experimental Physics, Physics and Informatics Comenius University Mlynska dolina F2, 84248 Bratislava, Slovakia 89 University College Cork (UCC), Cork, Ireland 90 Institute of Physics, Opole University, Oleska 48, 45-052 Opole, Poland 91 Daegu University, Jillyang, Gyeongsan, Gyeongbuk 712-174, Republic of Korea 92 Department of Nuclear Engineering, Seoul National University, Seoul, Republic of Korea 93 Fusion for Energy Joint Undertaking, Josep Pl. 2, Torres Diagonal Litoral B3, 08019, Barcelona, Spain 94 PELIN LLC, 27a, Gzhatskaya Ulitsa, Saint Petersburg, 195220, Russia 95 Arizona State University, Tempe, AZ, United States of America 96 Politecnico di Torino, Corso Duca degli Abruzzi 24, I-10129 Torino, Italy 97 ICREA and Barcelona Supercomputing Center, Barcelona, Spain 98 Universidad Complutense de Madrid, Madrid, Spain 99 Istituto dei Sistemi Complessi—CNR and Dipartimento di Energia—Politecnico di Torino, C.so Duca degli Abruzzi 24, 10129 Torino, Italy 100 Eindhoven University of Technology, The Netherlands 101 Purdue University, 610 Purdue Mall, West Lafayette, IN 47907, United States of America 102 Department of Material Science, Shimane University, 1060 Nishikawatsu, Matsue, 690-8504, Japan 103 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Brehová 78/7, 115 19 Praha 1, Czech Republic 104 College of William and Mary, Williamsburg, VA 23185, United States of America 105 University of California, 1111 Franklin St., Oakland, CA 94607, United States of America 106 University of Strathclyde, Glasgow, G4 0NG, United Kingdom of Great Britain and Northern Ireland 107 Kindai University, Higashi-Osaka, 577-8502, Japan 108 Shizuoka University, Shizuoka, 422-8529, Japan 109 Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford OX1 3PU, United Kingdom of Great Britain and Northern Ireland 110 Columbia University, New York, NY 10027, United States of America 111 Dipartimento di Fisica ‘G. Galilei’, Universita’ degli Studi di Padova, Padova, Italy 112 Space and Plasma Physics, EECS, KTH SE-100 44 Stockholm, Sweden 113 University of Ioannina, Panepistimioupoli Ioanninon, PO Box 1186, 45110 Ioannina, Greece 114 Universidade do Porto, Faculdade de Engenharia, 4200-465 Porto, Portugal 115 The University of Tokyo, Kashiwa, Chiba, 277-0882, Japan 116 Lithuanian Energy Institute, Breslaujos g. 3, LT-44403, Kaunas, Lithuania 117 HRS Fusion, West Orange, NJ, United States of America 118 Ibaraki University Graduate School of Science and Engineering, Mito, Ibaraki 310-8512, Japan 119 Technische Universität Wien, Fusion@ÖAW Österreichische Akademie der Wissenschaften (ÖAW), Austria