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The Columbia Non-neutral Torus
Final report for the Columbia Non-neutral Torus. This details the results from the design, construction and initial operation of the Columbia Non-neutral Torus
Experimental confirmation of efficient island divertor operation and successful neoclassical transport optimization in Wendelstein 7-X
We present recent highlights from the most recent operation phases of Wendelstein 7-X, the most advanced stellarator in the world. Stable detachment with good particle exhaust, low impurity content, and energy confinement times exceeding 100 ms, have been maintained for tens of seconds. Pellet fueling allows for plasma phases with reduced ion-temperature-gradient turbulence, and during such phases, the overall confinement is so good (energy confinement times often exceeding 200 ms) that the attained density and temperature profiles would not have been possible in less optimized devices, since they would have had neoclassical transport losses exceeding the heating applied in W7-X. This provides proof that the reduction of neoclassical transport through magnetic field optimization is successful. W7-X plasmas generally show good impurity screening and high plasma purity, but there is evidence of longer impurity confinement times during turbulence-suppressed phases
Physics-regularized neural network of the ideal-MHD solution operator in Wendelstein 7-X configurations
The stellarator is a promising concept to produce energy from nuclear fusion
by magnetically confining a high-pressure plasma. In a stellarator, the
confining field is three-dimensional, and the computational cost of solving the
3D MHD equations currently limits stellarator research and design. Although
data-driven approaches have been proposed to provide fast 3D MHD equilibria,
the accuracy with which equilibrium properties are reconstructed is unknown. In
this work, we describe an artificial neural network (NN) that quickly
approximates the ideal-MHD solution operator in Wendelstein 7-X (W7-X)
configurations. This model fulfils equilibrium symmetries by construction. The
MHD force residual regularizes the solution of the NN to satisfy the ideal-MHD
equations. The model predicts the equilibrium solution with high accuracy, and
it faithfully reconstructs global equilibrium quantities and proxy functions
used in stellarator optimization. The regularization term enforces that the NN
reduces the ideal-MHD force residual, and solutions that are better than ground
truth equilibria can be obtained at inference time. We also optimize W7-X
magnetic configurations, where desiderable configurations can be found in terms
of fast particle confinement. This work demonstrates with which accuracy NN
models can approximate the 3D ideal-MHD solution operator and reconstruct
equilibrium properties of interest, and it suggests how they might be used to
optimize stellarator magnetic configurations.Comment: 46 pages, 23 figures, to be submitted to Nuclear Fusio
D-Mag: a laboratory for studying plasma physics and diagnostics in strong magnetic fields
We have set up a diagnostic magnet (D-Mag) laboratory for a wide range of
applications in plasma physics. It consists of a superconducting magnet for
field strengths of up to 5.9 T. The main purpose is to provide an experimental
environment for the development of plasma diagnostics for nuclear fusion
studies and the investigation of dusty plasmas in strong magnetic fields. We
describe in the article the setup and operation of the D-Mag. Some applications
are presented for the development of plasma diagnostics, such as neutral
pressure gauges and Langmuir probes that have to be operated in strong magnetic
fields. Among the examples is the test of the long-pulse capability and
stability of the diagnostic pressure gauge (DPG) for the ITER device.Comment: Superconducting Magnet - laboratory for diagnostic development and
tests in strong and variable magnetic fields of up to 6 Tesl
Barium Ions for Quantum Computation
Individually trapped 137Ba+ in an RF Paul trap is proposed as a qubit ca
ndidate, and its various benefits are compared to other ionic qubits. We report
the current experimental status of using this ion for quantum computation. Fut
ure plans and prospects are discussed
Experimental confirmation of efficient island divertor operation and successful neoclassical transport optimization in Wendelstein 7-X
We present recent highlights from the most recent operation phases of Wendelstein 7-X, the most advanced stellarator in the world. Stable detachment with good particle exhaust, low impurity content, and energy confinement times exceeding 100 ms, have been maintained for tens of seconds. Pellet fueling allows for plasma phases with reduced ion-temperature-gradient turbulence, and during such phases, the overall confinement is so good (energy confinement times often exceeding 200 ms) that the attained density and temperature profiles would not have been possible in less optimized devices, since they would have had neoclassical transport losses exceeding the heating applied in W7-X. This provides proof that the reduction of neoclassical transport through magnetic field optimization is successful. W7-X plasmas generally show good impurity screening and high plasma purity, but there is evidence of longer impurity confinement times during turbulence-suppressed phases.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 ReviewedArticle signat per 497 autors/es: Thomas Sunn Pedersen1,2,∗ , I. Abramovic3, P. Agostinetti4, M. Agredano Torres1, S. Äkäslompolo1, J. Alcuson Belloso1, P. Aleynikov1, K. Aleynikova1, M. Alhashimi1, A. Ali1, N. Allen5, A. Alonso6, G. Anda7, T. Andreeva1, C. Angioni8, A. Arkhipov8, A. Arnold1, W. Asad8, E. Ascasibar6, M.-H. Aumeunier9, K. Avramidis10, E. Aymerich11, S.-G. Baek3, J. Bähner1, A. Baillod12, M. Balden1, M. Balden8, J. Baldzuhn1, S. Ballinger3, M. Banduch1, S. Bannmann1, A. Banon Navarro8, A. Bañon Navarro ´ 1, T. Barbui13, C. Beidler1, C. Belafdil9, A. Bencze7, A. Benndorf1, M. Beurskens1, C. Biedermann1, O. Biletskyi14, B. Blackwell15, M. Blatzheim1, T. Bluhm1, D. Böckenhoff1, G. Bongiovi16, M. Borchardt1, D. Borodin17, J. Boscary8, H. Bosch1,18, T. Bosmann19, B. Böswirth8, L. Böttger1, A. Bottino8, S. Bozhenkov1, R. Brakel1, C. Brandt1, T. Bräuer1, H. Braune1, S. Brezinsek17, K. Brunner1, S. Buller1, R. Burhenn1, R. Bussiahn1, B. Buttenschön1, A. Buzás7, V. Bykov1, I. Calvo6, K. Camacho Mata1, I. Caminal20, B. Cannas11, A. Cappa6, A. Carls1, F. Carovani1, M. Carr21, D. Carralero6, B. Carvalho22, J. Casas20, D. Castano-Bardawil17, F. Castejon6, N. Chaudhary1, I. Chelis23, A. Chomiczewska24, J.W. Coenen13,17, M. Cole1, F. Cordella25, Y. Corre9, K. Crombe26, G. Cseh7, B. Csillag7, H. Damm1, C. Day10, M. de Baar27, E. De la Cal6, S. Degenkolbe1, A. Demby13, S. Denk3, C. Dhard1, A. Di Siena8,28, A. Dinklage12, T. Dittmar17, M. Dreval14, M. Drevlak1, P. Drewelow1, P. Drews17, D. Dunai7, E. Edlund3, F. Effenberg29, G. Ehrke1, M. Endler1, D.A. Ennis5, F.J. Escoto6, T. Estrada6, E. Fable8, N. Fahrenkamp1, A. Fanni11, J. Faustin1, J. Fellinger1, Y. Feng1, W. Figacz4, E. Flom13, O. Ford1, T. Fornal24, H. Frerichs13, S. Freundt1, G. Fuchert1, M. Fukuyama30, F. Füllenbach1, G. Gantenbein10, Y. Gao1, K. Garcia13, J.M. GarcÃa Regaña6, I. GarcÃa-Cortés6, J. Gaspar31, D.A. Gates29, J. Geiger1, B. Geiger13, L. Giudicotti32, A. González6, A. Goriaev26,33, D. Gradic1, M. Grahl1, J.P. Graves12, J. Green13, E. Grelier9, H. Greuner8, S. Groß1, H. Grote1, M. Groth34, M. Gruca24, O. Grulke1,35, M. Grün1, J. Guerrero Arnaiz1, S. Günter8, V. Haak1, M. Haas1, P. Hacker1, A. Hakola36,
A. Hallenbert1, K. Hammond29, X. Han17,37, S.K. Hansen3, J.H. Harris38, H. Hartfuß1, D. Hartmann1, D. Hathiramani1, R. Hatzky8, J. Hawke39, S. Hegedus7, B. Hein8, B. Heinemann8, P. Helander12, S. Henneberg1, U. Hergenhahn8,40, C. Hidalgo6, F. Hindenlang8, M. Hirsch1, U. Höfel1, K.P. Hollfeld17, A. Holtz1, D. Hopf8, D. Höschen17, M. Houry9, J. Howard19, X. Huang41, M. Hubeny17, S. Hudson29, K. Ida9, Y. Igitkhanov10, V. Igochine8, S. Illy10, C. Ionita-Schrittwieser42, M. Isobe39, M. Jabłczynska ´ 24, S. Jablonski24, B. Jagielski1, M. Jakubowski1, A. Jansen van Vuuren1, J. Jelonnek10, F. Jenko8, F. Jenko8, T. Jensen35, H. Jenzsch1, P. Junghanns8, J. Kaczmarczyk24, J. Kallmeyer1, U. Kamionka1, M. Kandler8, S. Kasilov43, Y. Kazakov26, D. Kennedy1, A. Kharwandikar1, M. Khokhlov1, C. Kiefer8, C. Killer1, A. Kirschner17, R. Kleiber1, T. Klinger12, S. Klose1, J. Knauer1, A. Knieps17, F. Köchl44, G. Kocsis7, Ya.I. Kolesnichenko45, A. Könies1, R. König1, J. Kontula34, P. Kornejew1, J. Koschinsky, M.M. Kozulia14, A. Krämer-Flecken17, R. Krampitz1, M. Krause1, N. Krawczyk24, T. Kremeyer1, L. Krier10, D.M. Kriete5, M. Krychowiak1, I. Ksiazek46, M. Kubkowska24, M. Kuczynski1, G. Kühner1, A. Kumar15, T. Kurki-Suonio34, S. Kwak1, M. Landreman47, P.T. Lang8, A. Langenberg1, H.P. Laqua12, H. Laqua1, R. Laube1, S. Lazerson1, M. Lewerentz1, C. Li17, Y. Liang17, Ch. Linsmeier17, J. Lion1, A. Litnovsky17,48, S. Liu37, J. Lobsien1, J. Loizu12, J. Lore38, A. Lorenz1, U. Losada6, F. Louche26, R. Lunsford29, V. Lutsenko45, M. Machielsen12, F. Mackel8, J. Maisano-Brown3, O. Maj8, D. Makowski49, G. Manduchi50, E. Maragkoudakis6, O. Marchuk17, S. Marsen1, E. Martines4, J. Martinez-Fernandez6, M. Marushchenko1, S. Masuzaki41, D. Maurer5, M. Mayer8, K.J. McCarthy6, O. Mccormack4, P. McNeely1, H. Meister8, B. Mendelevitch8, S. Mendes1, A. Merlo1, A. Messian26, A. Mielczarek49, O. Mishchenko1, B. Missal1, R. Mitteau9, V.E. Moiseenko14, A. Mollen1, V. Moncada9, T. Mönnich1, T. Morisaki41,
D. Moseev1, G. Motojima41, S. Mulas6, M. Mulsow1, M. Nagel1, D. Naujoks1, V. Naulin35, T. Neelis19, H. Neilson29, R. Neu8, O. Neubauer17, U. Neuner1, D. Nicolai17, S.K. Nielsen35, H. Niemann1, T. Nishiza1, T. Nishizawa1, T. Nishizawa8, C. Nührenberg1, R. Ochoukov8, J. Oelmann17, G. Offermanns17 K. Ogawa41, S. Okamura41, J. Ölmanns17, J. Ongena26, J. Oosterbeek1, M. Otte1, N. Pablant29, N. Panadero Alvarez6, N. Panadero Alvarez6, A. Pandey1, E. Pasch1, R. Pavlichenko14, A. Pavone1, E. Pawelec46, G. Pechstein1, G. Pelka24, V. Perseo1, B. Peterson41, D. Pilopp1, S. Pingel1, F. Pisano11, B. Plöckl8, G. Plunk1, P. Pölöskei1, B. Pompe2, A. Popov51, M. Porkolab3, J. Proll19, M.J. Pueschel19,27, M.-E. Puiatti52, A. Puig Sitjes1, F. Purps1, K. Rahbarnia1, M. Rasinski ´ 17, J. Rasmussen35, A. Reiman29, F. Reimold1,
M. Reisner8, D. Reiter17, M. Richou9, R. Riedl8, J. Riemann1, K. Riße1, G. Roberg-Clark1, V. Rohde8, J. Romazanov17, D. Rondeshagen1, P. Rong1, L. Rudischhauser1, T. Rummel1, K. Rummel1, A. Runov1, N. Rust1, L. Ryc24, P. Salembier20, M. Salewski35, E. Sanchez6, S. Satake41, G. Satheeswaran17, J. Schacht1, E. Scharff1, F. Schauer8,
J. Schilling1, G. Schlisio1, K. Schmid8, J. Schmitt5, O. Schmitz13, W. Schneider1, M. Schneider1, P. Schneider8, R. Schrittwieser42, T. Schröder1, M. Schröder1, R. Schroeder1, B. Schweer26, D. Schwörer1, E. Scott1, E. Scott8, B. Shanahan1, G. Sias11, P. Sichta29, M. Singer1, P. Sinha29, S. Sipliä34, C. Slaby1, M. Sleczka53, H. Smith1,
J. Smoniewski54, E. Sonnendrücker8, M. Spolaore4, A. Spring1, R. Stadler8, D. Stanczak24, T. Stange1, I. Stepanov26, L. Stephey13, J. Stober8, U. Stroth8,55, E. Strumberger8, C. Suzuki41, Y. Suzuki41, J. Svensson1, T. Szabolics7, T. Szepesi7, M. Szücs7, F.L. Tabares6, N. Tamura41, A. Tancetti35, C. Tantos10, J. Terry3, H. Thienpondt6, H. Thomsen1, M. Thumm10, J.M. Travere9, P. Traverso5, J. Tretter8, E. Trier8, H. Trimino Mora1, T. Tsujimura41, Y. Turkin1, A. Tykhyi45, B. Unterberg17, P. van Eeten1, B.Ph. van Milligen6, M. van Schoor26, L. Vano1, S. Varoutis10, M. Vecsei7, L. Vela56, J.L. Velasco6, M. Vervier17, N. Vianello50, H. Viebke1, R. Vilbrandt1, G. Vogel8, N. Vogt1, C. Volkhausen1, A. von Stechow1, F. Wagner1, E. Wang17, H. Wang57, F. Warmer1, T. Wauters26, L. Wegener1, T. Wegner1, G. Weir1, U. Wenzel1, A. White3, F. Wilde1, F. Wilms1, T. Windisch1, M. Winkler1, A. Winter1, V. Winters1, R. Wolf118, A.M. Wright29, G.A. Wurden39, P. Xanthopoulos1, S. Xu17, H. Yamada58, H. Yamaguchi41, M. Yokoyama41, M. Yoshinuma41, Q. Yu8, M. Zamanov14, M. Zanini1, M. Zarnstorff29, D. Zhang1, S. Zhou17, J. Zhu1, C. Zhu29, M. Zilker8, A. Zocco1, H. Zohm8, S. Zoletnik7 and L. Zsuga7 // 1 Max Planck Institute for Plasma Physics, Garching and Greifswald, Germany: 2 University of Greifswald, Greifswald, Germany; 3 Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, United States of America; 4 Consorzio RFX, Corso Stati Uniti, 4-35127 Padova, Italy; 5 Auburn University, Auburn, AL 36849, United States of America; 6 CIEMAT, Avenida Complutense, 40, 28040 Madrid, Spain; 7 Center for Energy Research, Konkoly-Thegeut 29-33, 1121 Budapest, Hungary; 8 Max-Planck-Institute for Plasma Physics, Boltzmannstraße 2, 85748 Garching bei München, Germany; 9 CEA Cadarache, 13115 Saint-Paul-lez-Durance, France; 10 Karlsruhe Institute of Technology, Kaiserstr. 12, 76131 Karlsruhe, Germany; 11 University of Cagliari, Via Universita, 40, 09124 Cagliari, Italy; 12 École Polytechnique Fédérale de Lausanne, Swiss Plasma Center, CH-1015 Lausanne, Switzerland; 13 University of Wisconsin–Madison, Engineering Drive, Madison, WI 53706, United States of America; 14 Institute of Plasma Physics, National Science Center ‘Kharkiv Institute of Physics and Technology’, Kharkiv, Ukraine; 15 The Australian National University, Acton ACT 2601, Canberra, Australia; 16 Department of Engineering, University of Palermo, Viale delle Scienze, Edificio 6, Palermo, 90128, Italy; 17 Forschungszentrum Jülich GmbH, Institut für Energie-und Klimaforschung—Plasmaphysik, 52425 Jülich, Germany; 18 Technical University of Berlin, Strasse des 17. Juni 135, 10623 Berlin, Germany; 19 Eindhoven University of Technology, 5600 MB Eindhoven, Netherlands; 20 Universitat Politècnica de Catalunya. BarcelonaTech, C. Jordi Girona, 31, 08034 Barcelona, Spain; 21 Culham Center for Fusion Energy, Abingdon OX14 3EB, United Kingdom; 22 Instituto de Plasmas e Fusao Nuclear, Av. Rovisco Pais, 1049-001 Lisboa, Portugal; 23 Department of Physics, National and Kapodistrian University of Athens, 15784 Athens, Greece; 24 Institute of Plasma Physics and Laser Microfusion, 23 Hery Str., 01-497 Warsaw, Poland; 25 ENEA—Centro Ricerche Frascati, Via Enrico Fermi, 45, 00044 Frascati RM, Italy; 26 Laboratory for Plasma Physics, LPP-ERM/KMS, TEC Partner, B-1000 Brussels, Belgium; 27 Dutch Institute for Fundamental Energy Research, PO Box 6336, 5600 HH Eindhoven, Netherlands; 28 University of Texas, Austin, TX, United States of America; 29 Princeton Plasma Physics Laboratory, Princeton, NJ 08543, United States of America; 30 Kyushu University, 744 Motooka Nishi-ku, Fukuoka 819-0395, Japan; 31 Aix-Marseille University, Jardin du Pharo, 58 Boulevard Charles Livon, 13007, Marseille, France; 32 Department of Physics and Astronomy, Padova University, Via Marzolo 8, 35131 Padova, Italy; 33 Department of Applied Physics, Ghent University, Sint-Pietersnieuwstraat 41 B4, 9000 Ghent, Belgium; 34 Aalto University, 02150 Espoo, Finland; 35 Department of Physics, Technical University of Denmark, Anker Engelunds Vej, 2800 Kgs Lyngby, Denmark; 36 VTT Technical Research Center of Finland Ltd., PO Box 1000, FI-02044 VTT, Finland; 37 Institute of Plasma Physics, Chinese Academy of Sciences, 230031 Hefei, Anhui, China; 38 Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37830, United States of America; 39 Los Alamos National Laboratory, NM 87545, United States of America; 40 Fritz-Haber-Institut der Max-Planck-Gesellschaft, 14195 Berlin, Germany; 41 National Institute for Fusion Science, National Institutes of Natural Sciences, 322-6 Oroshi-cho, Toki,
Gifu Prefecture 509-5292, Japan; 42 Institute for Ion Physics and Applied Physics, University of Innsbruck, Innsbruck, Austria; 43 Graz University of Technology, Rechbauerstraße 12, 8010 GRAZ, Austria; 44 Austrian Academy of Science, Doktor-Ignaz-Seipel-Platz 2, 1010 Wien, Austria; 45 Institute for Nuclear Research, prospekt Nauky 47, Kyiv 03028, Ukraine; 46 University of Opole, plac Kopernika 11a, 45-001 Opole, Poland; 47 University of Maryland, Paint Branch Drive, College Park, MA 20742, United States of America; 48 National Research Nuclear University MEPhI, 115409 Moscow, Russian Federation; 49 Department of Microelectronics and Computer Science, Lodz University of Technology, Wolczanska 221/223, 90-924 Lodz, Poland; 50 Consiglio Nazionale delle Ricerche, Piazzale Aldo Moro, 7, 00185 Roma, Italy; 51 Ioffe Physical-Technical Institute of the Russian Academy of Sciences, 26 Politekhnicheskaya, St Petersburg 194021, Russian Federation; 52 Istituto di Fisica del Plasma Piero Caldirola, Via Roberto Cozzi, 53, 20125 Milano, Italy; 53 University of Szczecin, 70-453, aleja Papieza Jana PawÅ‚a II 22A, Szczecin, Poland; 54 Lawrence University, 711 E Boldt Way, Appleton, WI 54911, United States of America; 55 Physik-Department E28, Technische Universität München, 85747 Garching, Germany; 56 Universidad Carlos III de Madrid, Av. de la Universidad, 30 Madrid, Spain; 57 Yale University, New Haven, CT 06520, United States of America; 58 University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chhiab 277-0882, JapanObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No ContaminantObjectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant::7.a - Per a 2030, augmentar la cooperació internacional per tal de facilitar l’accés a la investigació i a les tecnoloÂgies energètiques no contaminants, incloses les fonts d’energia renovables, l’eficiència energètica i les tecnologies de combustibles fòssils avançades i menys contaminants, i promoure la inversió en infraestructures energètiques i tecnologies d’energia no contaminantPostprint (published version
Accelerated Bayesian inference of plasma profiles with self-consistent MHD equilibria at W7-X via neural networks
High- operations require a fast and robust inference
of plasma parameters with a self-consistent MHD equilibrium. Precalculated MHD
equilibria are usually employed at W7-X due to the high computational cost. To
address this, we couple a physics-regularized NN model that approximates the
ideal-MHD equilibrium with the Bayesian modeling framework Minerva. We show the
fast and robust inference of plasma profiles (electron temperature and density)
with a self-consistent MHD equilibrium approximated by the NN model. We
investigate the robustness of the inference across diverse synthetic W7-X
plasma scenarios. The inferred plasma parameters and their uncertainties are
compatible with the parameters inferred using the VMEC, and the inference time
is reduced by more than two orders of magnitude. This work suggests that MHD
self-consistent inferences of plasma parameters can be performed between shots.Comment: 18 pages, 6 figure
Improvement in the simulation tools for heat distribution predictions and control of baffle and middle divertor loads in Wendelstein 7-X
Demonstration of reduced neoclassical energy transport in Wendelstein 7-X
Research on magnetic confinement of high-temperature plasmas has the ultimate goal of harnessing nuclear fusion for the production of electricity. Although the tokamak1 is the leading toroidal magnetic-confinement concept, it is not without shortcomings and the fusion community has therefore also pursued alternative concepts such as the stellarator. Unlike axisymmetric tokamaks, stellarators possess a three-dimensional (3D) magnetic field geometry. The availability of this additional dimension opens up an extensive configuration space for computational optimization of both the field geometry itself and the current-carrying coils that produce it. Such an optimization was undertaken in designing Wendelstein 7-X (W7-X)2, a large helical-axis advanced stellarator (HELIAS), which began operation in 2015 at Greifswald, Germany. A major drawback of 3D magnetic field geometry, however, is that it introduces a strong temperature dependence into the stellarator’s non-turbulent ‘neoclassical’ energy transport. Indeed, such energy losses will become prohibitive in high-temperature reactor plasmas unless a strong reduction of the geometrical factor associated with this transport can be achieved; such a reduction was therefore a principal goal of the design of W7-X. In spite of the modest heating power currently available, W7-X has already been able to achieve high-temperature plasma conditions during its 2017 and 2018 experimental campaigns, producing record values of the fusion triple product for such stellarator plasmas3,4. The triple product of plasma density, ion temperature and energy confinement time is used in fusion research as a figure of merit, as it must attain a certain threshold value before net-energy-producing operation of a reactor becomes possible1,5. Here we demonstrate that such record values provide evidence for reduced neoclassical energy transport in W7-X, as the plasma profiles that produced these results could not have been obtained in stellarators lacking a comparably high level of neoclassical optimization
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