Asunta, O.

Coelho, R.

Coster, D.

Ferreira, J.

Figueiredo, A.

Gal, K.

Ivanova-Stanik, I.

Jonnson, T.

Kalupin, D.

Owsiak, M.

Palak, B.

Schneider, M.

Stankiewicz, R.

Strand, P.

English

MPG.PuRe

 Predictive simulations of reactor-scale plasmas fuelled with multiple pellets with the European Transport Simulator  D. Kalupin [1], O.Asunta[2], R. Coelho[3], D. Coster [4], J. Ferreira[3], A. Figueiredo[3], K.Gal[5], I.Ivanova-Stanik[6],T. Jonnson[7], M. Owsiak[8], B. Palak[8], M.Schneider[9], R.Stankiewicz[6], P.Strand[10]  and the EU-IM team*  [1]  EUROfusion Consortium Programme Management Unit, Boltzmannstr. 2, D-85748, Garching, Germany [2]      Department of Applied Physics, Aalto University, P.O. Box 14100, FI-00076 AALTO, Finland [3]  Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa 1049-001 Lisboa, Portugal [4]  Max-Planck-Institut für Plasmaphysik, Garching, Germany [5]      EuroFusion Consortium Programme Management Unit, Culham Science Centre, OX143DB,              Abingdon, UK [6]      Institute of Plasma Physics and Laser Microfusion, Hery23, 01-497, Warsaw, Poland [7] Department of Fusion Plasma Physics, School of Electrical Engineering, KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden [8] Poznan Supercomputing and Networking Center, IChB PAS, Noskowskiego 12/14, Poznan, Poland  [9]  CEA, IRFM, F-13108 Saint-Paul-lez-Durance, France.  [10]  Department of Earth and Space Sciences, Chalmers University of Technology, SE-41296 Göteborg, Sweden Introduction Development of the operating scenario for fusion reactor requires integrated modelling addressing the critical reactor issues: plasma heating and fuelling, radiation from impurities, MHD stability, etc. Since all these issues are inter-linked, to demonstrate a successful operational scenario, the relevant physics need to be included in a single simulation. Thus, the environment used for scenario modelling should allow for the integration of multiple codes and physics modules into a single scientific workflow. The European Transport Simulator (ETS) [1] is an outstanding example of such an integrated workflow. The ETS workflow couples individual physics modules e.g. calculating the plasma magnetic equilibrium, deposition (by auxiliary heating systems) and transport of energy and particles, impurity radiation, and MHD. It offers several options of different fidelity for each physics component. Previously, ETS was verified against state-of-the-art transport codes and used to analyse data from existing tokamaks [2]. In this work, the capability of the ETS to simulate complex scenarios was used to study the possibility to control the plasma density in a reactor size machine by pellet injection.  DEMO scenario simulations with ETS Present simulations were configured to reproduce overall plasma scenario developed by the system code PROCESS [3].  ETS was configured to solve the transport equations                                                  *   See http://www.euro-fusionscipub.org/eu-im 42nd EPS Conference on Plasma Physics P2.1690.0 0.5 1.0 1.5 2.0 2.5 3.0 3.50.00.40.81.21.62.02.4ne, 1020m-3tor, m1.6 1022 part3000 m/s0.4 1022 part300 m/sFig.1 Pellet cycle averaged profiles of electron density for different injection locations, mass and velocity of the pelletfor the current, the density (for e, D, T, He, Ar and W) and the temperature (for e, D, T, He). Temperatures for Ar and W were assumed to be equal to the temperature of deuterium ions. Transport coefficients were provided by the combination of Bohm-gyroBohm and neoclassical models, assuming the edge transport barrier at tor_norm=0.97. Heat and current drive sources were calculated by the beam simulation package and -heating module. Heat balance also included the radiation from impurities (Ar and W) and Synchrotron radiation. The pellet module [4]  used in simulations calculates the ablation rate of the pellet and provides flux surface averaged changes to density and temperature profiles, treated by the transport code as instantaneous event. In addition to the original model the current implementation includes ExB  drifts following the scaling from ref.[5]. Initial simulations were aimed in determining the domain of pellet parameters and injection locations, which might provide particle fuelling sufficient for maintaining the density in the reference DEMO scenario. Therefore, the simulations for five different poloidal angles of injection position, each with several pellet sizes and velocities were performed. To keep the particle throughput constant over the scan, the injection frequency was adjusted inversely proportional to the pellet size. As expected the fuelling efficiency increases over the scan with increasing velocity and size of injected pellets (see fig.1). This provides freedom on the pellet system optimization, where the reduction of the pellet size can be compensated by deeper penetration inside of the confined plasma. Nonetheless, a critical pellet size is found in simulations, below which the pellet injection system cannot provide the fuelling necessary to maintain the density required by the 80 60 40 20 00.00.40.81.21.62.0DEMO1 Nov.2013 scenarioinjection angle [grad]<ne, vol> [1020m-3]vertical from the tophorizontal from HFSFig.2 Steady-state volume averaged electron density compared to the requirements by DEMO scenario42nd EPS Conference on Plasma Physics P2.169scenario considered for a fusion reactor. Figure 2 shows steady state volume averaged density versus the injection angle for the matrix of three different pellet sizes (4*1021, 6*1021 and 1.6*1022 particles) by three different injection velocities (triangles-300 m/s, cycles -1000 m/s, squares-3000 m/s). The required density can not be achieved with the smallest pellets under any conditions. For those pellets the ablation occurs at a very peripheral region, the majority of the ablated materials is expelled from the plasma before it can contribute to the fuelling. At the same time, simulations with larger pellets offer several possible solutions where the required density is achieved. Therefore for next sequence of simulations the intermediate pellet of 6*1021 particles and velocity of 1000 m/s was chosen. In this group of simulations the flexibility of pellet injector design in terms of injection angle was addressed. The controller for the pellet injection was configured to maintain the volume averaged density required by DEMO scenario. For the same entry point at the vessel, the injection angle (with vertical axis) was varied between 10o and 70o, see fig. 3. Results of simulations are presented in fig. 4.  Fig.3 Pellet injection geometry 2.8 3.0 3.2 3.402468ETBseparatrixpellet injectionne, 1019 [m-3]tor, [m]Fig. 4 Pellet deposition profiles for different injection geometry The change of electron density profile caused by single pellet injection for different injection angles stays nearly the same for injection angles between 35o and 70o. For smaller angles the deposition shifts in the outward direction, when the fraction of the material deposited outside of the pedestal top increases. It makes fuelling less efficient and forces the controller to increase the frequency of the pellet injection in order to maintain the required density. Figure 5 shows the frequency of injection set up by controller at the steady state phase of simulated discharge (when required plasma 42nd EPS Conference on Plasma Physics P2.169parameters are achieved) as a function of injection angle. These results show the flexibility for the design of the pellet injection system for DEMO  Conclusions & Remarks  The European Transport Simulator has reached a mature state and can be applied for complex scenario simulations, eg for predictive simulation of reactor scale plasmas. The density for the foreseen DEMO operational scenario can be maintained by medium size pellets injected from the high field side. The injector design allows for some flexibility in choosing the pellet speed and injection geometry keeping the same fuelling efficiency. The computations presented do not include stability analysis of the MHD, whereas it might cause additional physics limitations in optimizing the pellet parameters, especially for largest pellets. Integration of the MHD stability chain into the ETS is foreseen as a next important development of the simulation package. Acknowledgment  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 under grant agreement No 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. References [1] D. Kalupin et al. Nucl. Fusion 53 (2013) 123007 [2] D. Kalupin et al. 38th EPS Conference on Plasma Phys. Strassbourg, 27 June-1 July 2011, Vol35G, P-4.111 (2011) [3] N. P. Taylor (holder) and P. J. Knight, “PROCESS Reactor Systems Code”, AEA Fusion Project Work File, F/RS/CIRE5523/PWF (1992) [4] K. Gal et al, Plasma Phys. Control. Fusion 50 (2008) 055006 [5] F. Köchl  35th EPS Conference on Plasma Phys. Hersonissos, 9 - 13 June 2008 ECA Vol.32D, P-4.099 (2008)  The results presented here, obtained using the EU-IM framework, present an integrated modelling exercise testing and verifying the consistency of dedicated physics actors. They are not (yet) meant as a basis for decision making on the design and parameters of the DEMO PELLET system. 0 20 40 60 80020406080100120injection frequency, [Hz]injection angle (with vertical axis), [deg] Fig.5 Output from pellet injection controller: adjustment of the injection frequency depending on the injection angle  42nd EPS Conference on Plasma Physics P2.169

Predictive simulations of reactor-scale plasmas fuelled with multiple pellets with the European Transport Simulator

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Predictive simulations of reactor-scale plasmas fuelled with multiple pellets with the European Transport Simulator

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