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4. EuroPED-NN: Uncertainty aware surrogate model

Author

Alvarez, A. Panera, Ho, A., Jarvinen, A., Saarelma, S., Wiesen, S., Contributors, JET, and team, the AUG

Subjects
Physics - Plasma Physics, Computer Science - Machine Learning
Abstract

This work successfully generates an uncertainty-aware surrogate model of the EuroPED plasma pedestal model using the Bayesian neural network with noise contrastive prior (BNN-NCP) technique. This model is trained using data from the JET-ILW pedestal database and subsequent model evaluations, conforming to EuroPED-NN. The BNN-NCP technique has been proven to be a suitable method for generating uncertainty-aware surrogate models. It matches the output results of a regular neural network while providing confidence estimates for predictions as uncertainties. Additionally, it highlights out-of-distribution (OOD) regions using surrogate model uncertainties. This provides critical insights into model robustness and reliability. EuroPED-NN has been physically validated, first, analyzing electron density $n_e\!\left(\psi_{\text{pol}}=0.94\right)$ with respect to increasing plasma current, $I_p$, and second, validating the $\Delta-\beta_{p,ped}$ relation associated with the EuroPED model. This affirms the robustness of the underlying physics learned by the surrogate model. On top of that, the method was used to develop a EuroPED-like model fed with experimental data, i.e. an uncertainty aware experimental model, which is functional in JET database. Both models have been also tested in $\sim 50$ AUG shots.

Published
2024
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7. On learning latent dynamics of the AUG plasma state

Author

Kit, A., Järvinen, A. E., Poels, Y. R. J., Wiesen, S., Menkovski, V., Fischer, R., Dunne, M., and Team, ASDEX-Upgrade

Subjects
Physics - Plasma Physics
Abstract

In this work, we demonstrate the utility of state representation learning applied to modeling the time evolution of electron density and temperature profiles at ASDEX-Upgrade (AUG). The proposed model is a deep neural network which learns to map the high dimensional profile observations to a lower dimensional state. The mapped states, alongside the original profile's corresponding machine parameters are used to learn a forward model to propagate the state in time. We show that this approach is able to predict AUG discharges using only a selected set of machine parameters. The state is then further conditioned to encode information about the confinement regime, which yields a simple baseline linear classifier, while still retaining the information needed to predict the evolution of profiles. We then discuss the potential use cases and limitations of state representation learning algorithms applied to fusion devices., Comment: 9 pages, 11 figures, 4th International Conference on Data-Driven Plasma Sciences

Published
2023
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8. Title, Copyright, Dedication

Author

Leighninger, Pamela Swett, Wiesen, S. Jonathan, Zatlin, Jonathan R., and De Grazia, Victoria

Published
2007

9. Cover

Author

Leighninger, Pamela Swett, Wiesen, S. Jonathan, Zatlin, Jonathan R., and De Grazia, Victoria

Published
2007

10. Index

Author

Leighninger, Pamela Swett, Wiesen, S. Jonathan, Zatlin, Jonathan R., and De Grazia, Victoria

Published
2007

15. Bibliography

Author

Leighninger, Pamela Swett, Wiesen, S. Jonathan, Zatlin, Jonathan R., and De Grazia, Victoria

Published
2007

19. Acknowledgments

Author

Leighninger, Pamela Swett, Wiesen, S. Jonathan, Zatlin, Jonathan R., and De Grazia, Victoria

Published
2007

25. Foreword

Author

Leighninger, Pamela Swett, Wiesen, S. Jonathan, Zatlin, Jonathan R., and De Grazia, Victoria

Published
2007

26. List of Illustrations

Author

Leighninger, Pamela Swett, Wiesen, S. Jonathan, Zatlin, Jonathan R., and De Grazia, Victoria

Published
2007

31. Developing Deep Learning Algorithms for Inferring Upstream Separatrix Density at JET

Author

Kit, A., Jaervinen, A., Wiesen, S., Poels, Y., and Frassinetti, L.

Subjects
Physics - Plasma Physics
Abstract

Predictive and real-time inference capability for the upstream separatrix electron density, $n_\text{e, sep}$, is essential for design and control of core-edge integrated plasma scenarios. In this study, both supervised and semi-supervised machine learning algorithms are explored to establish direct mapping as well as indirect compressed representation of the pedestal profiles for predictions and inference of $n_{\text{e, sep}}$. Based on the EUROfusion pedestal database for JET, a tabular dataset was created, consisting of machine parameters, fraction of ELM cycle, high resolution Thomson scattering profiles of electron density and temperature, and $n_{\text{e, sep}}$ for 608 JET shots. Using the tabular dataset, the direct mapping approach provides a mapping of machine parameters and ELM percentage to $n_{\text{e, sep}}$. Through representation learning, a compressed representation of the experimental pedestal electron density and temperature profiles is established. By conditioning the representation with machine control parameters, a probabilistic generative predictive model is established. For prediction, the machine parameters can be used to establish a conditional distribution of the compressed pedestal profiles, and the decoder that is trained as part of the algorithm can be used to decode the compressed representation back to full pedestal profiles. Although, in this work, a proof-of-principle for predicting and inferring $n_{\text{e, sep}}$ is given, such a representation learning can be used also for many other applications as the full pedestal profile is predicted. An implementation of this work can be found at https://github.com/fusionby2030/moxie., Comment: 6 pages, 5 figures, accepted contribution to the 25th International Conference on Plasma Surface Interaction in Controlled Fusion Devices(PSI-25)

Published
2022
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36. The radiated power limit in impurity seeded JET-ILW plasmas

Author

Huber, A., Wischmeier, M., Wiesen, S., Bernert, M., Chankin, A.V., Aleiferis, S., Brezinsek, S., Huber, V., Sergienko, G., Giroud, C., Groth, M., Jachmich, S., Linsmeier, Ch., Lomanowski, B., Lowry, C., Matthews, G.F., Meigs, A.G., Mertens, Ph., Silburn, S., and Telesca, G.

Published
2022
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38. SOLPS-ITER simulations of an X-point radiator in the ASDEX Upgrade tokamak

Author

Pan, O, Bernert, M, Lunt, T, Cavedon, M, Kurzan, B, Wiesen, S, Wischmeier, M, Stroth, U, Pan O., Bernert M., Lunt T., Cavedon M., Kurzan B., Wiesen S., Wischmeier M., Stroth U., Pan, O, Bernert, M, Lunt, T, Cavedon, M, Kurzan, B, Wiesen, S, Wischmeier, M, Stroth, U, Pan O., Bernert M., Lunt T., Cavedon M., Kurzan B., Wiesen S., Wischmeier M., and Stroth U.

Abstract

The X-point radiator (XPR) is an attractive scenario that may contribute to solving the power exhaust problem in future fusion devices. The 2D transport code SOLPS-ITER was applied to reproduce the experimentally measured plasma condition with an XPR in the ASDEX Upgrade tokamak and to compare with a reduced model. Neutrals penetrating from the adjoining cold divertor region and the large connection length near the X-point play an important role in initiating an XPR. However, once such a radiator is created, it persists even if the fueling and impurity seeding rates were reduced. The redistribution of plasma density and radiation near the X-point caused by fluid drifts at the XPR was studied in the simulation.

Published
2023

39. The X-Point radiating regime at ASDEX Upgrade and TCV

Author

Bernert, M, Wiesen, S, Fevrier, O, Kallenbach, A, Koenders, J, Sieglin, B, Stroth, U, Bosman, T, Brida, D, Cavedon, M, David, P, Dunne, M, Henderson, S, Kool, B, Lunt, T, Mcdermott, R, Pan, O, Perek, A, Reimerdes, H, Sheikh, U, Theiler, C, van Berkel, M, Wijkamp, T, Wischmeier, M, Bernert M., Wiesen S., Fevrier O., Kallenbach A., Koenders J. T. W., Sieglin B., Stroth U., Bosman T. O. S. J., Brida D., Cavedon M., David P., Dunne M. G., Henderson S., Kool B., Lunt T., McDermott R. M., Pan O., Perek A., Reimerdes H., Sheikh U., Theiler C., van Berkel M., Wijkamp T., Wischmeier M., Bernert, M, Wiesen, S, Fevrier, O, Kallenbach, A, Koenders, J, Sieglin, B, Stroth, U, Bosman, T, Brida, D, Cavedon, M, David, P, Dunne, M, Henderson, S, Kool, B, Lunt, T, Mcdermott, R, Pan, O, Perek, A, Reimerdes, H, Sheikh, U, Theiler, C, van Berkel, M, Wijkamp, T, Wischmeier, M, Bernert M., Wiesen S., Fevrier O., Kallenbach A., Koenders J. T. W., Sieglin B., Stroth U., Bosman T. O. S. J., Brida D., Cavedon M., David P., Dunne M. G., Henderson S., Kool B., Lunt T., McDermott R. M., Pan O., Perek A., Reimerdes H., Sheikh U., Theiler C., van Berkel M., Wijkamp T., and Wischmeier M.

Abstract

Future fusion reactors require a safe, steady-state divertor operation. With deep divertor detachment, which is typically induced by impurity seeding, the radiation concentrates in a small region at the X-point or on closed flux surfaces above the X-point. This so-called X-point radiator (XPR) moves further inside the confined region with increasing seeding and the location can be actively controlled. At AUG, the parameter space for operation with an XPR was significantly extended, using active feedback on the XPR location. The XPR is observed in nearly the whole operational space of AUG in the high-densities or high collisionality regime. ELM suppression is consistently observed in all cases where the XPR was moved to a significant height above the X-point. Direct measurements of density and temperature from the region around the XPR using the new divertor Thomson scattering system at AUG indicate that the temperature at the location of the XPR remains high (>30eV) and only the region towards the X-point cools down further. In this cold XPR core, the temperature reduces to about 1eV. An XPR is also observed in TCV by the injection of nitrogen as extrinsic impurity. This highlights that the wall material (W for AUG, C for TCV) or machine size does not play a significant role for the existence of the regime. However, the scenario appears to be less stable in TCV. First experiments show the necessity of an active control for the XPR: Depending on the wall conditions and the nitrogen wall storage, the required nitrogen seeding level to achieve an XPR changes. Both, the low temperatures measured radially outside of the radiation zone at AUG, and the lower stability of the XPR regime at TCV with the presence of carbon are consistent with the predictions of a one-dimensional model of the XPR. However, the model would predict the development of the cold XPR core, and significant radiation at the X-point might already exist before reaching this cold temperature solution.

Published
2023

40. Impact of nitrogen seeding on confinement and power load control of a high-triangularity JET ELMy H-mode plasma with a metal wall

Author

Giroud, C, Maddison, G P, Jachmich, S, Rimini, F, Beurskens, M N A, Balboa, I, Brezinsek, S, Coelho, R, Coenen, J W, Frassinetti, L, Joffrin, E, Oberkofler, M, Lehnen, M, Liu, Y, Marsen, S, K, K McCormick, Meigs, A, Neu, R, Sieglin, B, van Rooij, G, Arnoux, G, Belo, P, Brix, M, Clever, M, Coffey, I, Devaux, S, Douai, D, Eich, T, Flanagan, J, Grunhagen, S, Huber, A, Kempenaars, M, Kruezi, U, Lawson, K, Lomas, P, Lowry, C, Nunes, I, Sirinnelli, A, Sips, A C C, Stamp, M, Wiesen, S, and contributors, JET-EFDA

Subjects
Physics - Plasma Physics
Abstract

This paper reports the impact on confinement and power load of the high-shape 2.5MA ELMy H-mode scenario at JET of a change from an all carbon plasma facing components to an all metal wall. In preparation to this change, systematic studies of power load reduction and impact on confinement as a result of fuelling in combination with nitrogen seeding were carried out in JET-C and are compared to their counterpart in JET with a metallic wall. An unexpected and significant change is reported on the decrease of the pedestal confinement but is partially recovered with the injection of nitrogen., Comment: 30 pages, 16 figures

Published
2013
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41. Representation learning algorithms for inferring machine independent latent features in pedestals in JET and AUG.

Author

Järvinen, A. E., Kit, A., Poels, Y. R. J., Wiesen, S., Menkovski, V., Frassinetti, L., and Dunne, M.

Subjects
MACHINE learning, ELECTRON distribution, PEDESTALS, MAGNETIC confinement, LATENT variables
Abstract

Variational autoencoder (VAE)-based representation learning algorithms are explored for their capability to disentangle tokamak size dependence from other dependencies in a dataset of thousands of observed pedestal electron density and temperature profiles from JET and ASDEX Upgrade tokamaks. Representation learning aims to establish a useful representation that characterizes the dataset. In the context of magnetic confinement fusion devices, a useful representation could be considered to map the high-dimensional observations to a manifold that represents the actual degrees of freedom of the plasma scenario. A desired property for these representations is organization of the information into disentangled variables, enabling interpretation of the latent variables as representations of semantically meaningful characteristics of the data. The representation learning algorithms in this work are based on VAE that encodes the pedestal profile information into a reduced dimensionality latent space and learns to reconstruct the full profile information given the latent representation. Attaching an auxiliary regression objective for the machine control parameter configuration, broadly following the architecture of the domain invariant variational autoencoder (DIVA), the model learns to associate device control parameters with the latent representation. With this multimachine dataset, the representation does encode density scaling with device size that is qualitatively consistent with Greenwald density limit scaling. However, if the major radius of the device is given through a common regression objective with the other machine control parameters, the latent state of the representation struggles to clearly disentangle the device size from changes of the other machine control parameters. When separating the device size as an independent latent variable with dedicated regression objectives, similar to separation of domain and class labels in the original DIVA publication, the latent space becomes well organized as a function of the device size. [ABSTRACT FROM AUTHOR]

Published
2024
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42. On learning latent dynamics of the AUG plasma state.

Author

Kit, A., Järvinen, A. E., Poels, Y. R. J., Wiesen, S., Menkovski, V., Fischer, R., and Dunne, M.

Subjects
ARTIFICIAL neural networks, ELECTRON distribution, PLASMA dynamics, MACHINE learning
Abstract

In this work, we demonstrate the utility of state representation learning applied to modeling the time evolution of electron density and temperature profiles at ASDEX-Upgrade (AUG). The proposed model is a deep neural network, which learns to map the high dimensional profile observations to a lower dimensional state. The mapped states, alongside the original profile's corresponding machine parameters, are used to learn a forward model to propagate the state in time. We show that this approach is able to predict AUG discharges using only a selected set of machine parameters. The state is then further conditioned to encode information about the confinement regime, which yields a simple baseline linear classifier, while still retaining the information needed to predict the evolution of profiles. We, then, discuss the potential use cases and limitations of state representation learning algorithms applied to fusion devices. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Numerical implications of including drifts in SOLPS-ITER simulations of EAST.

Author

Boeyaert, D., Carli, S., Dekeyser, W., Wiesen, S., and Baelmans, M.

Subjects
PLASMA potentials, DEUTERIUM
Abstract

The inclusion of drifts in plasma edge codes like SOLPS-ITER is required to match simulation data with experimental profiles. However, this remains numerically challenging. In this paper, the effect of some numerical factors on the final plasma solution is investigated. This study is performed on three EAST simulations in the upper single null configuration: an attached purely deuterium case, an attached case with limited Ne-seeding, and a detached Ne-seeded case. The effects of the anomalous conductivity and anomalous thermo-electric coefficient on the plasma potential are investigated. Next, the effect of the employed grids is shown. In order to investigate these effects, accurate drift simulations are needed. Therefore, the employed time step and numerical parameters are discussed for the three studied simulations. For all presented simulations, it is verified that the restriction of the grid to the first flux surface tangent to the main chamber wall is sufficient within the context of non-extended simulations. This means that the main power dissipation takes place inside the simulated domain, and only a small fraction of the power is leaving the B2.5 grid through the grid boundary closest to the first wall. Finally, the effect of drifts on the asymmetry between the inner and outer target for EAST simulations is demonstrated. [ABSTRACT FROM AUTHOR]

Published
2024
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44. The X-Point radiating regime at ASDEX Upgrade and TCV

Author

Bernert, M., Wiesen, S., Février, O., Kallenbach, A., Koenders, J.T.W., Sieglin, B., Bosman, T.O.S.J., Kool, B., van Berkel, M., Wijkamp, T.A., Stroth, U., Brida, D., Cavedon, M., David, P., Dunne, M.G., Henderson, S., Lunt, T., McDermott, R.M., Pan, O., Perek, A., Reimerdes, H., Sheikh, U., Theiler, C., Wischmeier, M., Team, EUROfusionMST1, team, TCV, Team, ASDEXUpgrade, Bernert, M, Wiesen, S, Fevrier, O, Kallenbach, A, Koenders, J, Sieglin, B, Stroth, U, Bosman, T, Brida, D, Cavedon, M, David, P, Dunne, M, Henderson, S, Kool, B, Lunt, T, Mcdermott, R, Pan, O, Perek, A, Reimerdes, H, Sheikh, U, Theiler, C, van Berkel, M, Wijkamp, T, Wischmeier, M, Group Heemels, Control Systems Technology, Science and Technology of Nuclear Fusion, Fluids and Flows, EUROfusion MST1 Team, TCV Team, and ASDEX Upgrade Team, Max Planck Institute for Plasma Physics, Max Planck Society

Subjects
Radiative scenario, operation, Nuclear and High Energy Physics, Nuclear Energy and Engineering, X-point radiation, Materials Science (miscellaneous), Divertor detachment, Power exhaust, Radiative scenarios, marfe
Abstract

Future fusion reactors require a safe, steady-state divertor operation. With deep divertor detachment, which is typically induced by impurity seeding, the radiation concentrates in a small region at the X-point or on closed flux surfaces above the X-point. This so-called X-point radiator (XPR) moves further inside the confined region with increasing seeding and the location can be actively controlled. At AUG, the parameter space for operation with an XPR was significantly extended, using active feedback on the XPR location. The XPR is observed in nearly the whole operational space of AUG in the high-densities or high collisionality regime. ELM suppression is consistently observed in all cases where the XPR was moved to a significant height above the X-point. Direct measurements of density and temperature from the region around the XPR using the new divertor Thomson scattering system at AUG indicate that the temperature at the location of the XPR remains high (>30eV) and only the region towards the X-point cools down further. In this cold XPR core, the temperature reduces to about 1eV. An XPR is also observed in TCV by the injection of nitrogen as extrinsic impurity. This highlights that the wall material (W for AUG, C for TCV) or machine size does not play a significant role for the existence of the regime. However, the scenario appears to be less stable in TCV. First experiments show the necessity of an active control for the XPR: Depending on the wall conditions and the nitrogen wall storage, the required nitrogen seeding level to achieve an XPR changes. Both, the low temperatures measured radially outside of the radiation zone at AUG, and the lower stability of the XPR regime at TCV with the presence of carbon are consistent with the predictions of a one-dimensional model of the XPR. However, the model would predict the development of the cold XPR core, and significant radiation at the X-point might already exist before reaching this cold temperature solution.

Published
2023

47. Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions

Author

Mazzi, S., Garcia, J., Zarzoso, D., Kazakov, Y., Ongena, J., Dreval, M., Nocente, M., Stancar, Z., Szepesi, G., Eriksson, J., Sahlberg, A., Benkadda, S., Abid, N., Abraham, K., Abreu, P., Adabonyan, O., Adrich, P., Afanasev, V., Afzal, M., Ahlgren, T., Aho-Mantila, L., Aiba, N., Airila, M., Akhtar, M., Albanese, R., Alderson-Martin, M., Alegre, D., Aleiferis, S., Aleksa, A., Alekseev, A., Alessi, E., Aleynikov, P., Algualcil, J., Ali, M., Allinson, M., Alper, B., Alves, E., Ambrosino, G., Ambrosino, R., Amosov, V., Andersson Sunden, E., Andrew, P., Angelini, B., Angioni, C., Antoniou, I., Appel, L., Appelbee, C., Aria, S., Ariola, M., Artaserse, G., Arter, W., Artigues, V., Asakura, N., Ash, A., Ashikawa, N., Aslanyan, V., Astrain, M., Asztalos, O., Auld, D., Auriemma, F., Austin, Y., Avotina, L., Aymerich, E., Baciero, A., Bairaktaris, F., Balbin, J., Balbinot, L., Balboa, I., Balden, M., Balshaw, C., Balshaw, N., Bandaru, V., Banks, J., Baranov, Y., Barcellona, C., Barnard, A., Barnard, M., Barnsley, R., Barth, A., Baruzzo, M., Barwell, S., Bassan, M., Batista, A., Batistoni, P., Baumane, L., Bauvir, B., Baylor, L., Beaumont, P., Beckett, D., Begolli, A., Beidler, M., Bekris, N., Beldishevski, M., Belli, E., Belli, F., Belonohy, E., Ben Yaala, M., Benayas, J., Bentley, J., Bergsaker, H., Bernardo, J., Bernert, M., Berry, M., Bertalot, L., Betar, H., Beurskens, M., Bickerton, S., Bieg, B., Bielecki, J., Bierwage, A., Biewer, T., Bilato, R., Bílkova, P., Birkenmeier, G., Bishop, H., Bizarro, J., Blackburn, J., Blanchard, P., Blatchford, P., Bobkov, V., Boboc, A., Bohm, P., Bohm, T., Bolshakova, I., Bolzonella, T., Bonanomi, N., Bonfiglio, D., Bonnin, X., Bonofiglo, P., Boocock, S., Booth, A., Booth, J., Borba, D., Borodin, D., Borodkina, I., Boulbe, C., Bourdelle, C., Bowden, M., Boyd, K., Bozicevic Mihalic, I., Bradnam, S., Braic, V., Brandt, L., Bravanec, R., Breizman, B., Brett, A., Brezinsek, S., Brix, M., Bromley, K., Brown, B., Brunetti, D., Buckingham, R., Buckley, M., Budny, R., Buermans, J., Bufferand, H., Buratti, P., Burgess, A., Buscarino, A., Busse, A., Butcher, D., Cal, E., Calabro, G., Calacci, L., Calado, R., Camenen, Y., Canal, G., Cannas, B., Cappelli, M., Carcangiu, S., Card, P., Cardinali, A., Carman, P., Carnevale, D., Carr, M., Carralero, D., Carraro, L., Carvalho, I., Carvalho, P., Casiraghi, I., Casson, F., Castaldo, C., Catalan, J., Catarino, N., Causa, F., Cavedon, M., Cecconello, M., Challis, C., Chamberlain, B., Chang, C., Chankin, A., Chapman, B., Chernyshova, M., Chiariello, A., Chmielewski, P., Chomiczewska, A., Chone, L., Ciraolo, G., Ciric, D., Citrin, J., Ciupinski, t., Clark, M., Clarkson, R., Clements, C., Cleverly, M., Coad, J., Coates, P., Cobalt, A., Coccorese, V., Coelho, R., Coenen, J., Coffey, I., Colangeli, A., Colas, L., Collins, C., Collins, J., Collins, S., Conka, D., Conroy, S., Conway, B., Conway, N., Coombs, D., Cooper, P., Cooper, S., Corradino, C., Corrigan, G., Coster, D., Cox, P., Craciunescu, T., Cramp, S., Crapper, C., Craven, D., Craven, R., Crialesi Esposito, M., Croci, G., Croft, D., Croitoru, A., Crombe, K., Cronin, T., Cruz, N., Crystal, C., Cseh, G., Cufar, A., Cullen, A., Curuia, M., Czarski, T., Dabirikhah, H., Dal Molin, A., Dale, E., Dalgliesh, P., Dalley, S., Dankowski, J., David, P., Davies, A., Davies, S., Davis, G., Dawson, K., Dawson, S., Day, I., De Bock, M., De Temmerman, G., De Tommasi, G., Deakin, K., Deane, J., Dejarnac, R., Del Sarto, D., Delabie, E., Del-Castillo-Negrete, D., Dempsey, A., Dendy, R., Devynck, P., Di Siena, A., Di Troia, C., Dickson, T., Dinca, P., Dittmar, T., Dobrashian, J., Doerner, R., Donne, A., Dorling, S., Dormido-Canto, S., Douai, D., Dowson, S., Doyle, R., Drewelow, P., Drews, P., Drummond, G., Duckworth, P., Dudding, H., Dumont, R., Dumortier, P., Dunai, D., Dunatov, T., Dunne, M., Duran, I., Durodie, F., Dux, R., Dvornova, A., Eastham, R., Edwards, J., Eich, T., Eichorn, A., Eidietis, N., Eksaeva, A., Haroun, H., Ellwood, G., Elsmore, C., Embreus, O., Emery, S., Ericsson, G., Eriksson, B., Eriksson, F., Eriksson, L., Ertmer, S., Esquembri, S., Esquisabel, A., Estrada, T., Evans, G., Evans, S., Fable, E., Fagan, D., Faitsch, M., Falessi, M., Fanni, A., Farahani, A., Farquhar, I., Fasoli, A., Faugeras, B., Fazinie, S., Felici, F., Felton, R., Fernandes, A., Fernandes, H., Ferrand, J., Ferreira, D., Ferreira, J., Ferro, G., Fessey, J., Ficker, O., Field, A., Figueiredo, A., Figueiredo, J., Fil, A., Fil, N., Finburg, P., Fiorucci, D., Fischer, U., Fishpool, G., Fittill, L., Fitzgerald, M., Flammini, D., Flanagan, J., Flinders, K., Foley, S., Fonnesu, N., Fontana, M., Fontdecaba, J., Forbes, S., Formisano, A., Fornal, T., Fortuna, L., Fortuna-Zalesna, E., Fortune, M., Fowler, C., Fransson, E., Frassinetti, L., Freisinger, M., Fresa, R., Fridstrom, R., Frigione, D., Fülop, T., Furseman, M., Fusco, V., Futatani, S., Gadariya, D., Gal, K., Galassi, D., Gafezka, K., Galeani, S., Gallart, D., Galvao, R., Gao, Y., Garcia-Munoz, M., Gardener, M., Garzotti, L., Gaspar, J., Gatto, R., Gaudio, P., Gear, D., Gebhart, T., Gee, S., Gelfusa, M., George, R., Gerasimov, S., Gervasini, G., Gethins, M., Ghani, Z., Gherendi, M., Ghezzi, F., Giacalone, J., Giacomelli, L., Giacometti, G., Gibson, C., Gibson, K., Gil, L., Gillgren, A., Gin, D., Giovannozzi, E., Giroud, C., Glen, R., Gloggler, S., Goff, J., Gohil, P., Goloborodko, V., Gomes, R., Goncalves, B., Goniche, M., Goodyear, A., Gore, S., Gorini, G., Görler, T., Gotts, N., Goulding, R., Gow, E., Graham, B., Graves, J., Greuner, H., Grierson, B., Griffiths, J., Griph, S., Grist, D., Gromelski, W., Groth, M., Grove, R., Gruca, M., Guard, D., Gupta, N., Gurl, C., Gusarov, A., Hackett, L., Hacquin, S., Hager, R., Hagg, L., Hakola, A., Halitovs, M., Hall, S., Hallworth-Cook, S., Ham, C., Hamaguchi, D., Hamed, M., Hamlyn-Harris, C., Hammond, K., Harford, E., Harrison, J., Harting, D., Hatano, Y., Hatch, D., Haupt, T., Hawes, J., Hawkes, N., Hawkins, 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moléculaires (PIIM), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche sur la Fusion par confinement Magnétique (IRFM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Swiss Plasma Center (SPC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Laboratory for Plasma Physics (LPP), Ecole Royale Militaire / Koninklijke Militaire School (ERM KMS), Kharkiv Institute of Physics and Technology (Ukraine), V.N. Karazin Kharkiv National University (KhNU), Dipartimento di Fisica (Milano), Università degli Studi di Milano = University of Milan (UNIMI), Consiglio Nazionale delle Ricerche [Milano] (CNR), Jozef Stefan Institute [Ljubljana] (IJS), Culham Centre for Fusion Energy (CCFE), Department of Physics and Astronomy [Uppsala], Uppsala University, 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., Mazzi, S, Garcia, J, Zarzoso, D, Kazakov, Y, Ongena, J, Dreval, M, Nocente, M, Stancar, Z, Szepesi, G, Eriksson, J, Sahlberg, A, Benkadda, S, Abid, N, Abraham, K, Abreu, P, Adabonyan, O, Adrich, P, Afzal, M, Ahlgren, T, Aho-Mantila, L, Aiba, N, Airila, M, Akhtar, M, Albanese, R, Alderson-Martin, M, Alegre, D, Aleiferis, S, Aleksa, A, Alessi, E, Aleynikov, P, Algualcil, J, Ali, M, Allinson, M, Alper, B, Alves, E, Ambrosino, G, Ambrosino, R, 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K., Zoulias, I., Zwingmann, W., Zychor, I., JET Contributors, Science and Technology of Nuclear Fusion, EIRES Eng. for Sustainable Energy Systems, Magneto-Hydro-Dynamic Stability of Fusion Plasmas, Applied Physics and Science Education, Kazakov, Yo, VTT Technical Research Centre of Finland, Culham Science Centre, Princeton Plasma Physics Laboratory, Department of Applied Physics, European Commission, Forschungszentrum Jülich, Universidade Lisboa, Fusion and Plasma Physics, University of Milan - Bicocca, Aalto University, General Atomics, ITER, University of Toyama, CEA, Oak Ridge National Laboratory, Technical University of Madrid, Swiss Federal Institute of Technology Lausanne, Dutch Institute for Fundamental Energy Research, Royal Military Academy, Seoul National University, Chalmers University of Technology, Max Planck Institute for Plasma Physics, KTH Royal Institute of Technology, and Aalto-yliopisto

Subjects
[PHYS]Physics [physics], Settore FIS/01, Settore ING-IND/18 - Fisica dei Reattori Nucleari, General Physics and Astronomy, simulation, magnetically confined plasma, nuclear fusion, tokamaks, turbulence suppression, Plasma, [PHYS.PHYS.PHYS-PLASM-PH]Physics [physics]/Physics [physics]/Plasma Physics [physics.plasm-ph], confinement, transport, Alpha particles, Fusion reactors, Turbulence, physics
Abstract

openaire: EC/H2020/633053/EU//EUROfusion Funding Information: We thank M. Baruzzo and F. Nave for the preparation and execution of JET experiments discussed in this paper; E. de la Luna for support in detailing the experimental diagnostics of JET; A. Ho for assistance in processing the experimental data; T. Görler for providing essential advice to ensure the correct numerical setup for the GENE modelling reported in this paper; Y. Camenen, X. Garbet and A. Bierwage for fruitful discussions about the gyrokinetic analyses; G. Giruzzi for valuable suggestions on the article strategy. The simulations were performed on the IRENE Joliot-Curie HPC system, in the framework of the PRACE projects IONFAST and AFIETC, led by J. Garcia, and on the CINECA Marconi HPC within the project GENE4EP, led by D. Zarzoso. 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. The views and opinions express herein do not necessarily reflect those of the European Commission. Part of the work by Ye. O. Kazakov and J.Ongena was also carried out in the framework of projects done for the ITER Scientist Fellow Network (ISFN). Funding Information: We thank M. Baruzzo and F. Nave for the preparation and execution of JET experiments discussed in this paper; E. de la Luna for support in detailing the experimental diagnostics of JET; A. Ho for assistance in processing the experimental data; T. Görler for providing essential advice to ensure the correct numerical setup for the GENE modelling reported in this paper; Y. Camenen, X. Garbet and A. Bierwage for fruitful discussions about the gyrokinetic analyses; G. Giruzzi for valuable suggestions on the article strategy. The simulations were performed on the IRENE Joliot-Curie HPC system, in the framework of the PRACE projects IONFAST and AFIETC, led by J. Garcia, and on the CINECA Marconi HPC within the project GENE4EP, led by D. Zarzoso. 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. The views and opinions express herein do not necessarily reflect those of the European Commission. Part of the work by Ye. O. Kazakov and J.Ongena was also carried out in the framework of projects done for the ITER Scientist Fellow Network (ISFN). Publisher Copyright: © 2022, The Author(s), under exclusive licence to Springer Nature Limited. Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.

Published
2022

48. Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions

Author

Mazzi, S, Garcia, J, Zarzoso, D, Kazakov, Y, Ongena, J, Dreval, M, Nocente, M, Stancar, Z, Szepesi, G, Eriksson, J, Sahlberg, A, Benkadda, S, Abid, N, Abraham, K, Abreu, P, Adabonyan, O, Adrich, P, Afzal, M, Ahlgren, T, Aho-Mantila, L, Aiba, N, Airila, M, Akhtar, M, Albanese, R, Alderson-Martin, M, Alegre, D, Aleiferis, S, Aleksa, A, Alessi, E, Aleynikov, P, Algualcil, J, Ali, M, Allinson, M, Alper, B, Alves, E, Ambrosino, G, Ambrosino, R, Andersson Sunden, E, Andrew, P, Angelini, B, Angioni, C, Antoniou, I, Appel, L, Appelbee, C, Aria, S, Ariola, M, Artaserse, G, Arter, W, Artigues, V, Asakura, N, Ash, A, Ashikawa, N, Aslanyan, V, Astrain, M, Asztalos, O, Auld, D, Auriemma, F, Austin, Y, Avotina, L, Aymerich, E, Baciero, A, Bairaktaris, F, Balbin, J, Balbinot, L, Balboa, I, Balden, M, Balshaw, C, Balshaw, N, Bandaru, V, Banks, J, Baranov, Y, Barcellona, C, Barnard, A, Barnard, M, Barnsley, R, Barth, A, Baruzzo, M, Barwell, S, Bassan, M, Batista, A, Batistoni, P, Baumane, L, Bauvir, B, Baylor, L, Beaumont, P, Beckett, D, Begolli, A, Beidler, M, Bekris, N, Beldishevski, M, Belli, E, Belli, F, Belonohy, E, Ben Yaala, M, Benayas, J, Bentley, J, Bergsaker, H, Bernardo, J, Bernert, M, Berry, M, Bertalot, L, Betar, H, Beurskens, M, Bickerton, S, Bieg, B, Bielecki, J, Bierwage, A, Biewer, T, Bilato, R, Bilkova, P, Birkenmeier, G, Bishop, H, Bizarro, J, Blackburn, J, Blanchard, P, Blatchford, P, Bobkov, V, Boboc, A, Bohm, P, Bohm, T, Bolshakova, I, Bolzonella, T, Bonanomi, N, Bonfiglio, D, Bonnin, X, Bonofiglo, P, Boocock, S, Booth, A, Booth, J, Borba, D, Borodin, D, Borodkina, I, Boulbe, C, Bourdelle, C, Bowden, M, Boyd, K, Bozicevic Mihalic, I, Bradnam, S, Braic, V, Brandt, L, Bravanec, R, Breizman, B, Brett, A, Brezinsek, S, Brix, M, Bromley, K, Brown, B, Brunetti, D, Buckingham, R, Buckley, M, Budny, R, Buermans, J, Bufferand, H, Buratti, P, Burgess, A, Buscarino, A, Busse, A, Butcher, D, de la Cal, E, Calabro, G, Calacci, L, Calado, R, Camenen, Y, Canal, G, Cannas, B, 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R., Kotschenreuther M., Koubiti M., Kowalska-Strzeciwilk E., Koziol K., Krasilnikov V., Kresina M., Krieger K., Krishnan N., Krivska A., Kruezi U., Ksiazek I., Kukushkin A. B., Kumpulainen H., Kurki-Suonio T., Kurotaki H., Kwak S., Kwon O. J., Laguardia L., Lagzdina E., Lahtinen A., Laing A., Lam N., Lambertz H. T., Lane B., Lane C., Lascas Neto E., Laszynska E., Lawson K. D., Lazaros A., Lazzaro E., Learoyd G., Lee C., Lee S. E., Leerink S., Leeson T., Lefebvre X., Leggate H. J., Lehmann J., Lehnen M., Leichtle D., Leipold F., Lengar I., Lennholm M., Leon Gutierrez E., Lepiavko B., Leppanen J., Lerche E., Lescinskis A., Lewis J., Leysen W., Li L., Li Y., Likonen J., Linsmeier C., Lipschultz B., Litaudon X., Litherland-Smith E., Liu F., Loarer T., Loarte A., Lobel R., Lomanowski B., Lomas P. J., Lopez J. M., Lorenzini R., Loreti S., Losada U., Loschiavo V. P., Loughlin M., Louka Z., Lovell J., Lowe T., Lowry C., Lubbad S., Luce T., Lucock R., Luna C., de la Luna E., Lungaroni M., Lungu C. P., Lunt T., Lutsenko V., Lyons B., Lyssoivan A., Machielsen M., Macusova E., Maenpaa R., Maggi C. F., Maggiora R., Magness M., Mahesan S., Maier H., Mailloux J., Maingi R., Malinowski K., Manas P., Mantica P., Mantsinen M. J., Manyer J., Manzanares A., Maquet P., Marceca G., Marchetto C., Marchuk O., Mariani A., Mariano G., Marin M., Marinelli M., Markovic T., Marocco D., Marot L., Marsden S., Marsh J., Marshall R., Martellucci L., Martin A., Martin A. J., Martone R., Maruyama S., Maslov M., Masuzaki S., Matejcik S., Mattei M., Matthews G. F., Matveev D., Matveeva E., Mauriya A., Maviglia F., Mayer M., Mayoral M. -L., Mazzotta C., McAdams R., McCarthy P. J., McClements K. G., McClenaghan J., McCullen P., McDonald D. C., McGuckin D., McHugh D., McIntyre G., McKean R., McKehon J., McMillan B., McNamee L., McShee A., Meakins A., Medley S., Meekes C. J., Meghani K., Meigs A. G., Meisl G., Meitner S., Menmuir S., Mergia K., Merriman S., Mertens P., Messiaen A., Michling R., Middleton P., Middleton-Gear D., Mietelski J., Milanesio D., Milani E., Militello F., Militello Asp A., Milnes J., Milocco A., Miloshevsky G., Minghao C., Minucci S., Miron I., Miyamoto M., Mlynar J., Moiseenko V., Monaghan P., Monakhov I., Moody T., Moon S., Mooney R., Moradi S., Morales J., Morales R. B., Mordijck S., Moreira L., Morgan L., Moro F., Morris J., Morrison K. -M., Moser L., Moulton D., Mrowetz T., Mundy T., Muraglia M., Murari A., Muraro A., Muthusonai N., N'Konga B., Na Y. -S., Nabais F., Naden M., Naish J., Naish R., Napoli F., Nardon E., Naulin V., Nave M. F. F., Nedzelskiy I., Nestoras I., Neu R., Ng S., Nicassio M., Nielsen A. H., Nina D., Nishijima D., Noble C., Nobs C. R., Nodwell D., Nordlund K., Nordman H., Normanton R., Noterdaeme J. -M., Nowak S., Nunn E., Nystrom H., Oberparleiter M., Obryk B., O'Callaghan J., Odupitan T., Oliver H. J. 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C., Olney R., O'Mullane M., Organ E., Orsitto F., Orszagh J., Osborne T., Otin R., Otsuka T., Owen A., Oya Y., Oyaizu M., Paccagnella R., Pace N., Packer L. W., Paige S., Pajuste E., Palade D., Pamela S. J. P., Panadero N., Panontin E., Papadopoulos A., Papp G., Papp P., Parail V. V., Pardanaud C., Parisi J., Parra Diaz F., Parsloe A., Parsons M., Parsons N., Passeri M., Patel A., Pau A., Pautasso G., Pavlichenko R., Pavone A., Pawelec E., Soldan C. P., Peacock A., Pearce M., Peluso E., Penot C., Pepperell K., Pereira R., Pereira T., Cippo E. P., Pereslavtsev P., von Thun C. P., Pericoli V., Perry D., Peterka M., Petersson P., Petravich G., Petrella N., Peyman M., Pillon M., Pinches S., Pintsuk G., de Sa W. P., dos Reis A. P., Piron C., Piron L., Pironti A., Pitts R., van de Plassche K. L., Platt N., Plyusnin V., Podesta M., Pokol G., Poli F. M., Pompilian O. G., Popovichev S., Poradzinski M., Porfiri M. T., Porkolab M., Porosnicu C., Porton M., Poulipoulis G., Predebon I., Prestopino G., Price C., Price D., Price M., Primetzhofer D., Prior P., Provatas G., Pucella G., Puglia P., Purahoo K., Pusztai I., Putignano O., Putterich T., Quercia A., Rachlew E., Radulescu G., Radulovic V., Rainford M., Raj P., Ralph G., Ramogida G., Rasmussen D., Rasmussen J. J., Ratta G., Ratynskaia S., Rebai M., Refy D., Reichle R., Reinke M., Reiser D., Reux C., Reynolds S., Richiusa M. L., Richyal S., Rigamonti D., Rimini F. G., Risner J., Riva M., Rivero-Rodriguez J., Roach C. M., Robins R., Robinson S., Robson D., Rodrigues P., Rodriguez Ramos M., Rodriguez-Fernandez P., Romanelli F., Romanelli M., Romanelli S., Romazanov J., Rossi R., Rowe S., Rowlands D., Rubel M., Rubinacci G., Rubino G., Ruchko L., Ruiz M., Ruiz J. R., Ruset C., Rzadkiewicz J., Saarelma S., Safi E., Salewski M., Salmi A., Salmon R., Salzedas F., Sanders I., Sandiford D., Santos B., Santucci A., Sarkimaki K., Sarwar R., Sarychev I., Sauter O., Sauwan P., Scapin N., Schluck F., Schmid K., Schmuck S., Schneider M., Schneider P. A., Schworer D., Scott G., Scott M., Scraggs D., Scully S., Segato M., Seo J., Sergienko G., Sertoli M., Sharapov S. E., Shaw A., Sheikh H., Sheikh U., Shepherd A., Shigin P., Shinohara K., Shiraiwa S., Shiraki D., Short M., Sias G., Silburn S. A., Silva A., Silva C., Silva J., Silvagni D., Simfukwe D., Simpson J., Sinclair D., Sipila S. K., Sips A. C. C., Siren P., Sirinelli A., Sjostrand H., Skinner N., Slater J., Smith N., Smith P., Snell J., Snoep G., Snoj L., Snyder P., Soare S., Solano E. R., Solokha V., Somers A., Sommariva C., Soni K., Sorokovoy E., Sos M., Sousa J., Sozzi C., Spagnolo S., Spelzini T., Spineanu F., Spong D., Sprada D., Sridhar S., Srinivasan C., Stables G., Staebler G., Stamatelatos I., Staniec P., Stankunas G., Stead M., Stefanikova E., Stephen A., Stephens J., Stevenson P., Stojanov M., Strand P., Strauss H. R., Strikwerda S., Strom P., Stuart C. I., Studholme W., Subramani M., Suchkov E., Sumida S., Sun H. J., Susts T. E., Svensson J., Svoboda J., Sweeney R., Sytnykov D., Szabolics T., Tabia B., Tadic T., Tal B., Tala T., Tallargio A., Tamain P., Tan H., Tanaka K., Tang W., Tardocchi M., Taylor D., Teimane A. S., Telesca G., Teplukhina A., Terentyev D., Terra A., Terranova D., Terranova N., Testa D., Tholerus E., Thomas J., Thoren E., Thorman A., Tierens W., Tinguely R. A., Tipton A., Todd H., Tokitani M., Tolias P., Tomes M., Tookey A., Torikai Y., von Toussaint U., Tsavalas P., Tskhakaya D., Turner I., Turner M., Turner M. M., Turnyanskiy M., Tvalashvili G., Tyrrell S., Tyshchenko M., Uccello A., Udintsev V., Urbanczyk G., Vadgama A., Valcarcel D., Valisa M., Vallejos Olivares P., Vallhagen O., Valovic M., Van Eester D., Varje J., Vartanian S., Vasilopoulou T., Vayakis G., Vecsei M., Vega J., Ventre S., Verdoolaege G., Verona C., Rinati G. V., Veshchev E., Vianello N., Viezzer E., Vignitchouk L., Vila R., Villari R., Villone F., Vincenzi P., Viola B., Virtanen A. J., Vitins A., Vizvary Z., Vlad G., Vlad M., Vondracek P., de Vries P., Wakeling B., Walkden N. R., Walker M., Walker R., Walsh M., Wang E., Wang N., Warder S., Warren R., Waterhouse J., Watts C., Wauters T., Weckmann A., Wedderburn Maxwell H., Weiland M., Weisen H., Weiszflog M., Welch P., Wendler N., West A., Wheatley M., Wheeler S., Whitehead A., Whittaker D., Widdowson A., Wiesen S., Wilkinson J., Williams J. C., Willoughby D., Wilson I., Wilson J., Wilson T., Wischmeier M., Wise P., Withenshaw G., Withycombe A., Witts D., Wojcik-Gargula A., Wolfrum E., Wood R., Woodley C., Woodley R., Woods B., Wright J., Wright J. C., Xu T., Yadikin D., Yajima M., Yakovenko Y., Yang Y., Yanling W., Yanovskiy V., Young I., Young R., Zabolockis R. J., Zacks J., Zagorski R., Zaitsev F. S., Zakharov L., Zarins A., Zastrow K. -D., Zayachuk Y., Zerbini M., Zhang W., Zhou Y., Zlobinski M., Zocco A., Zohar A., Zoita V., Zoletnik S., Zotta V. K., Zoulias I., Zwingmann W., and Zychor I.

Abstract

Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvénic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvénic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity.

Published
2022

49. Overview of the TCV tokamak experimental programme

Author

Reimerdes, H, Agostini, M, Alessi, E, Alberti, S, Andrebe, Y, Arnichand, H, Balbin, J, Bagnato, F, Baquero-Ruiz, M, Bernert, M, Bin, W, Blanchard, P, Blanken, T, Boedo, J, Brida, D, Brunner, S, Bogar, C, Bogar, O, Bolzonella, T, Bombarda, F, Bouquey, F, Bowman, C, Brunetti, D, Buermans, J, Bufferand, H, Calacci, L, Camenen, Y, Carli, S, Carnevale, D, Carpanese, F, Causa, F, Cavalier, J, Cavedon, M, Cazabonne, J, Cerovsky, J, Chandra, R, Chandrarajan Jayalekshmi, A, Chellai, O, Chmielewski, P, Choi, D, Ciraolo, G, Classen, I, Coda, S, Colandrea, C, Dal Molin, A, David, P, De Baar, M, Decker, J, Dekeyser, W, De Oliveira, H, Douai, D, Dreval, M, Dunne, M, Duval, B, Elmore, S, Embreus, O, Eriksson, F, Faitsch, M, Falchetto, G, Farnik, M, Fasoli, A, Fedorczak, N, Felici, F, Fevrier, O, Ficker, O, Fil, A, Fontana, M, Fransson, E, Frassinetti, L, Furno, I, Gahle, D, Galassi, D, Galazka, K, Galperti, C, Garavaglia, S, Garcia-Munoz, M, Geiger, B, Giacomin, M, Giruzzi, G, Gobbin, M, Golfinopoulos, T, Goodman, T, Gorno, S, Granucci, G, Graves, J, Griener, M, Gruca, M, Gyergyek, T, Haelterman, R, Hakola, A, Han, W, Happel, T, Harrer, G, Harrison, J, Henderson, S, Hogeweij, G, Hogge, J, Hoppe, M, Horacek, J, Huang, Z, Iantchenko, A, Innocente, P, Insulander Bjork, K, Ionita-Schrittweiser, C, Isliker, H, Jardin, A, Jaspers, R, Karimov, R, Karpushov, A, Kazakov, Y, Komm, M, Kong, M, Kovacic, J, Krutkin, O, Kudlacek, O, Kumar, U, Kwiatkowski, R, Labit, B, Laguardia, L, Lammers, J, Laribi, E, Laszynska, E, Lazaros, A, Linder, O, Linehan, B, Lipschultz, B, Llobet, X, Loizu, J, Lunt, T, Macusova, E, Marandet, Y, Maraschek, M, Marceca, G, Marchetto, C, Marchioni, S, Marmar, E, Martin, Y, Martinelli, L, Matos, F, Maurizio, R, Mayoral, M, Mazon, D, Menkovski, V, Merle, A, Merlo, G, Meyer, H, Mikszuta-Michalik, K, Molina Cabrera, P, Morales, J, Moret, J, Moro, A, Moulton, D, Muhammed, H, Myatra, O, Mykytchuk, D, Napoli, F, Nem, R, Nielsen, A, Nocente, M, Nowak, S, Offeddu, N, Olsen, J, Orsitto, F, Pan, O, Papp, G, Pau, A, Perek, A, Pesamosca, F, Peysson, Y, Pigatto, L, Piron, C, Poradzinski, M, Porte, L, Putterich, T, Rabinski, M, Raj, H, Rasmussen, J, Ratta, G, Ravensbergen, T, Ricci, D, Ricci, P, Rispoli, N, Riva, F, Rivero-Rodriguez, J, Salewski, M, Sauter, O, Schmidt, B, Schrittweiser, R, Sharapov, S, Sheikh, U, Sieglin, B, Silva, M, Smolders, A, Snicker, A, Sozzi, C, Spolaore, M, Stagni, A, Stipani, L, Sun, G, Tala, T, Tamain, P, Tanaka, K, Tema Biwole, A, Terranova, D, Terry, J, Testa, D, Theiler, C, Thornton, A, Thrysoe, A, Torreblanca, H, Tsui, C, Vaccaro, D, Vallar, M, Van Berkel, M, Van Eester, D, Van Kampen, R, Van Mulders, S, Verhaegh, K, Verhaeghe, T, Vianello, N, Villone, F, Viezzer, E, Vincent, B, Voitsekhovitch, I, Vu, N, Walkden, N, Wauters, T, Weisen, H, Wendler, N, Wensing, M, Widmer, F, Wiesen, S, Wischmeier, M, Wijkamp, T, Wunderlich, D, Wuthrich, C, Yanovskiy, V, Zebrowski, J, Reimerdes H., Agostini M., Alessi E., Alberti S., Andrebe Y., Arnichand H., Balbin J., Bagnato F., Baquero-Ruiz M., Bernert M., Bin W., Blanchard P., Blanken T. C., Boedo J. A., Brida D., Brunner S., Bogar C., Bogar O., Bolzonella T., Bombarda F., Bouquey F., Bowman C., Brunetti D., Buermans J., Bufferand H., Calacci L., Camenen Y., Carli S., Carnevale D., Carpanese F., Causa F., Cavalier J., Cavedon M., Cazabonne J. A., Cerovsky J., Chandra R., Chandrarajan Jayalekshmi A., Chellai O., Chmielewski P., Choi D., Ciraolo G., Classen I. G. J., Coda S., Colandrea C., Dal Molin A., David P., De Baar M. R., Decker J., Dekeyser W., De Oliveira H., Douai D., Dreval M., Dunne M. G., Duval B. P., Elmore S., Embreus O., Eriksson F., Faitsch M., Falchetto G., Farnik M., Fasoli A., Fedorczak N., Felici F., Fevrier O., Ficker O., Fil A., Fontana M., Fransson E., Frassinetti L., Furno I., Gahle D. S., Galassi D., Galazka K., Galperti C., Garavaglia S., Garcia-Munoz M., Geiger B., Giacomin M., Giruzzi G., Gobbin M., Golfinopoulos T., Goodman T., Gorno S., Granucci G., Graves J. P., Griener M., Gruca M., Gyergyek T., Haelterman R., Hakola A., Han W., Happel T., Harrer G., Harrison J. R., Henderson S., Hogeweij G. M. D., Hogge J. -P., Hoppe M., Horacek J., Huang Z., Iantchenko A., Innocente P., Insulander Bjork K., Ionita-Schrittweiser C., Isliker H., Jardin A., Jaspers R. J. E., Karimov R., Karpushov A. N., Kazakov Y., Komm M., Kong M., Kovacic J., Krutkin O., Kudlacek O., Kumar U., Kwiatkowski R., Labit B., Laguardia L., Lammers J. T., Laribi E., Laszynska E., Lazaros A., Linder O., Linehan B., Lipschultz B., Llobet X., Loizu J., Lunt T., Macusova E., Marandet Y., Maraschek M., Marceca G., Marchetto C., Marchioni S., Marmar E. S., Martin Y., Martinelli L., Matos F., Maurizio R., Mayoral M. -L., Mazon D., Menkovski V., Merle A., Merlo G., Meyer H., Mikszuta-Michalik K., Molina Cabrera P. A., Morales J., Moret J. -M., Moro A., Moulton D., Muhammed H., Myatra O., Mykytchuk D., Napoli F., Nem R. D., Nielsen A. H., Nocente M., Nowak S., Offeddu N., Olsen J., Orsitto F. P., Pan O., Papp G., Pau A., Perek A., Pesamosca F., Peysson Y., Pigatto L., Piron C., Poradzinski M., Porte L., Putterich T., Rabinski M., Raj H., Rasmussen J. J., Ratta G. A., Ravensbergen T., Ricci D., Ricci P., Rispoli N., Riva F., Rivero-Rodriguez J. F., Salewski M., Sauter O., Schmidt B. S., Schrittweiser R., Sharapov S., Sheikh U. A., Sieglin B., Silva M., Smolders A., Snicker A., Sozzi C., Spolaore M., Stagni A., Stipani L., Sun G., Tala T., Tamain P., Tanaka K., Tema Biwole A., Terranova D., Terry J. L., Testa D., Theiler C., Thornton A., Thrysoe A., Torreblanca H., Tsui C. K., Vaccaro D., Vallar M., Van Berkel M., Van Eester D., Van Kampen R. J. R., Van Mulders S., Verhaegh K., Verhaeghe T., Vianello N., Villone F., Viezzer E., Vincent B., Voitsekhovitch I., Vu N. M. T., Walkden N., Wauters T., Weisen H., Wendler N., Wensing M., Widmer F., Wiesen S., Wischmeier M., Wijkamp T. A., Wunderlich D., Wuthrich C., Yanovskiy V., Zebrowski J., Reimerdes, H, Agostini, M, Alessi, E, Alberti, S, Andrebe, Y, Arnichand, H, Balbin, J, Bagnato, F, Baquero-Ruiz, M, Bernert, M, Bin, W, Blanchard, P, Blanken, T, Boedo, J, Brida, D, Brunner, S, Bogar, C, Bogar, O, Bolzonella, T, Bombarda, F, Bouquey, F, Bowman, C, Brunetti, D, Buermans, J, Bufferand, H, Calacci, L, Camenen, Y, Carli, S, Carnevale, D, Carpanese, F, Causa, F, Cavalier, J, Cavedon, M, Cazabonne, J, Cerovsky, J, Chandra, R, Chandrarajan Jayalekshmi, A, Chellai, O, Chmielewski, P, Choi, D, Ciraolo, G, Classen, I, Coda, S, Colandrea, C, Dal Molin, A, David, P, De Baar, M, Decker, J, Dekeyser, W, De Oliveira, H, Douai, D, Dreval, M, Dunne, M, Duval, B, Elmore, S, Embreus, O, Eriksson, F, Faitsch, M, Falchetto, G, Farnik, M, Fasoli, A, Fedorczak, N, Felici, F, Fevrier, O, Ficker, O, Fil, A, Fontana, M, Fransson, E, Frassinetti, L, Furno, I, Gahle, D, Galassi, D, Galazka, K, Galperti, C, Garavaglia, S, Garcia-Munoz, M, Geiger, B, Giacomin, M, Giruzzi, G, Gobbin, M, Golfinopoulos, T, Goodman, T, Gorno, S, Granucci, G, Graves, J, Griener, M, Gruca, M, Gyergyek, T, Haelterman, R, Hakola, A, Han, W, Happel, T, Harrer, G, Harrison, J, Henderson, S, Hogeweij, G, Hogge, J, Hoppe, M, Horacek, J, Huang, Z, Iantchenko, A, Innocente, P, Insulander Bjork, K, Ionita-Schrittweiser, C, Isliker, H, Jardin, A, Jaspers, R, Karimov, R, Karpushov, A, Kazakov, Y, Komm, M, Kong, M, Kovacic, J, Krutkin, O, Kudlacek, O, Kumar, U, Kwiatkowski, R, Labit, B, Laguardia, L, Lammers, J, Laribi, E, Laszynska, E, Lazaros, A, Linder, O, Linehan, B, Lipschultz, B, Llobet, X, Loizu, J, Lunt, T, Macusova, E, Marandet, Y, Maraschek, M, Marceca, G, Marchetto, C, Marchioni, S, Marmar, E, Martin, Y, Martinelli, L, Matos, F, Maurizio, R, Mayoral, M, Mazon, D, Menkovski, V, Merle, A, Merlo, G, Meyer, H, Mikszuta-Michalik, K, Molina Cabrera, P, Morales, J, Moret, J, Moro, A, Moulton, D, Muhammed, H, Myatra, O, Mykytchuk, D, Napoli, F, Nem, R, Nielsen, A, Nocente, M, Nowak, S, Offeddu, N, Olsen, J, Orsitto, F, Pan, O, Papp, G, Pau, A, Perek, A, Pesamosca, F, Peysson, Y, Pigatto, L, Piron, C, Poradzinski, M, Porte, L, Putterich, T, Rabinski, M, Raj, H, Rasmussen, J, Ratta, G, Ravensbergen, T, Ricci, D, Ricci, P, Rispoli, N, Riva, F, Rivero-Rodriguez, J, Salewski, M, Sauter, O, Schmidt, B, Schrittweiser, R, Sharapov, S, Sheikh, U, Sieglin, B, Silva, M, Smolders, A, Snicker, A, Sozzi, C, Spolaore, M, Stagni, A, Stipani, L, Sun, G, Tala, T, Tamain, P, Tanaka, K, Tema Biwole, A, Terranova, D, Terry, J, Testa, D, Theiler, C, Thornton, A, Thrysoe, A, Torreblanca, H, Tsui, C, Vaccaro, D, Vallar, M, Van Berkel, M, Van Eester, D, Van Kampen, R, Van Mulders, S, Verhaegh, K, Verhaeghe, T, Vianello, N, Villone, F, Viezzer, E, Vincent, B, Voitsekhovitch, I, Vu, N, Walkden, N, Wauters, T, Weisen, H, Wendler, N, Wensing, M, Widmer, F, Wiesen, S, Wischmeier, M, Wijkamp, T, Wunderlich, D, Wuthrich, C, Yanovskiy, V, Zebrowski, J, Reimerdes H., Agostini M., Alessi E., Alberti S., Andrebe Y., Arnichand H., Balbin J., Bagnato F., Baquero-Ruiz M., Bernert M., Bin W., Blanchard P., Blanken T. C., Boedo J. A., Brida D., Brunner S., Bogar C., Bogar O., Bolzonella T., Bombarda F., Bouquey F., Bowman C., Brunetti D., Buermans J., Bufferand H., Calacci L., Camenen Y., Carli S., Carnevale D., Carpanese F., Causa F., Cavalier J., Cavedon M., Cazabonne J. A., Cerovsky J., Chandra R., Chandrarajan Jayalekshmi A., Chellai O., Chmielewski P., Choi D., Ciraolo G., Classen I. G. J., Coda S., Colandrea C., Dal Molin A., David P., De Baar M. R., Decker J., Dekeyser W., De Oliveira H., Douai D., Dreval M., Dunne M. G., Duval B. P., Elmore S., Embreus O., Eriksson F., Faitsch M., Falchetto G., Farnik M., Fasoli A., Fedorczak N., Felici F., Fevrier O., Ficker O., Fil A., Fontana M., Fransson E., Frassinetti L., Furno I., Gahle D. S., Galassi D., Galazka K., Galperti C., Garavaglia S., Garcia-Munoz M., Geiger B., Giacomin M., Giruzzi G., Gobbin M., Golfinopoulos T., Goodman T., Gorno S., Granucci G., Graves J. P., Griener M., Gruca M., Gyergyek T., Haelterman R., Hakola A., Han W., Happel T., Harrer G., Harrison J. R., Henderson S., Hogeweij G. M. D., Hogge J. -P., Hoppe M., Horacek J., Huang Z., Iantchenko A., Innocente P., Insulander Bjork K., Ionita-Schrittweiser C., Isliker H., Jardin A., Jaspers R. J. E., Karimov R., Karpushov A. N., Kazakov Y., Komm M., Kong M., Kovacic J., Krutkin O., Kudlacek O., Kumar U., Kwiatkowski R., Labit B., Laguardia L., Lammers J. T., Laribi E., Laszynska E., Lazaros A., Linder O., Linehan B., Lipschultz B., Llobet X., Loizu J., Lunt T., Macusova E., Marandet Y., Maraschek M., Marceca G., Marchetto C., Marchioni S., Marmar E. S., Martin Y., Martinelli L., Matos F., Maurizio R., Mayoral M. -L., Mazon D., Menkovski V., Merle A., Merlo G., Meyer H., Mikszuta-Michalik K., Molina Cabrera P. A., Morales J., Moret J. -M., Moro A., Moulton D., Muhammed H., Myatra O., Mykytchuk D., Napoli F., Nem R. D., Nielsen A. H., Nocente M., Nowak S., Offeddu N., Olsen J., Orsitto F. P., Pan O., Papp G., Pau A., Perek A., Pesamosca F., Peysson Y., Pigatto L., Piron C., Poradzinski M., Porte L., Putterich T., Rabinski M., Raj H., Rasmussen J. J., Ratta G. A., Ravensbergen T., Ricci D., Ricci P., Rispoli N., Riva F., Rivero-Rodriguez J. F., Salewski M., Sauter O., Schmidt B. S., Schrittweiser R., Sharapov S., Sheikh U. A., Sieglin B., Silva M., Smolders A., Snicker A., Sozzi C., Spolaore M., Stagni A., Stipani L., Sun G., Tala T., Tamain P., Tanaka K., Tema Biwole A., Terranova D., Terry J. L., Testa D., Theiler C., Thornton A., Thrysoe A., Torreblanca H., Tsui C. K., Vaccaro D., Vallar M., Van Berkel M., Van Eester D., Van Kampen R. J. R., Van Mulders S., Verhaegh K., Verhaeghe T., Vianello N., Villone F., Viezzer E., Vincent B., Voitsekhovitch I., Vu N. M. T., Walkden N., Wauters T., Weisen H., Wendler N., Wensing M., Widmer F., Wiesen S., Wischmeier M., Wijkamp T. A., Wunderlich D., Wuthrich C., Yanovskiy V., and Zebrowski J.

Abstract

The tokamak à configuration variable (TCV) continues to leverage its unique shaping capabilities, flexible heating systems and modern control system to address critical issues in preparation for ITER and a fusion power plant. For the 2019-20 campaign its configurational flexibility has been enhanced with the installation of removable divertor gas baffles, its diagnostic capabilities with an extensive set of upgrades and its heating systems with new dual frequency gyrotrons. The gas baffles reduce coupling between the divertor and the main chamber and allow for detailed investigations on the role of fuelling in general and, together with upgraded boundary diagnostics, test divertor and edge models in particular. The increased heating capabilities broaden the operational regime to include Te/Ti ∼1 and have stimulated refocussing studies from L-mode to H-mode across a range of research topics. ITER baseline parameters were reached in type-I ELMy H-modes and alternative regimes with 'small' (or no) ELMs explored. Most prominently, negative triangularity was investigated in detail and confirmed as an attractive scenario with H-mode level core confinement but an L-mode edge. Emphasis was also placed on control, where an increased number of observers, actuators and control solutions became available and are now integrated into a generic control framework as will be needed in future devices. The quantity and quality of results of the 2019-20 TCV campaign are a testament to its successful integration within the European research effort alongside a vibrant domestic programme and international collaborations.

Published
2022

50. Characterisation of divertor detachment onset in JET-ILW hydrogen, deuterium, tritium and deuterium–tritium low-confinement mode plasmas

Author

Groth, M., primary, Solokha, V., additional, Aleiferis, S., additional, Brezinsek, S., additional, Brix, M., additional, Carvalho, I.S., additional, Carvalho, P., additional, Corrigan, G., additional, Harting, D., additional, Horsten, N., additional, Jepu, I., additional, Karhunen, J., additional, Kirov, K., additional, Lomanowski, B., additional, Lawson, K.D., additional, Lowry, C., additional, Meigs, A.G., additional, Menmuir, S., additional, Pawelec, E., additional, Pereira, T., additional, Shaw, A., additional, Silburn, S., additional, Thomas, B., additional, Wiesen, S., additional, Börner, P., additional, Borodin, D., additional, Jachmich, S., additional, Reiter, D., additional, Sergienko, G., additional, Stancar, Z., additional, Viola, B., additional, Beaumont, P., additional, Bernardo, J., additional, Coffey, I., additional, Conway, N.J., additional, de la Luna, E., additional, Douai, D., additional, Giroud, C., additional, Hillesheim, J., additional, Horvath, L., additional, Huber, A., additional, Lomas, P., additional, Maggi, C.F., additional, Maslov, M., additional, Perez von Thun, C., additional, Scully, S., additional, Vianello, N., additional, and Wischmeier, M., additional

Published
2023
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