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1. Overview of the EUROfusion Tokamak Exploitation programme in support of ITER and DEMO

Author

E. Joffrin, M. Wischmeier, M. Baruzzo, A. Hakola, A. Kappatou, D. Keeling, B. Labit, E. Tsitrone, N. Vianello, the ASDEX Upgrade Team, JET Contributors, the MAST-U Team, the TCV Team, the WEST Team, the EUROfusion Tokamak Exploitation Team:, D. Abate, J. Adamek, M. Agostini, C. Albert, F.C.P. Albert Devasagayam, S. Aleiferis, E. Alessi, J. Alhage, S. Allan, J. Allcock, M. Alonzo, G. Anastasiou, E. Andersson Sunden, C. Angioni, Y. Anquetin, L. Appel, G.M. Apruzzese, M. Ariola, C. Arnas, J.F. Artaud, W. Arter, O. Asztalos, L. Aucone, M.H. Aumeunier, F. Auriemma, J. Ayllon, E. Aymerich, A. Baciero, F. Bagnato, L. Bähner, F. Bairaktaris, P. Balázs, L. Balbinot, I. Balboa, M. Balden, A. Balestri, M. Baquero Ruiz, T. Barberis, C. Barcellona, O. Bardsley, S. Benkadda, T. Bensadon, E. Bernard, M. Bernert, H. Betar, R. Bianchetti Morales, J. Bielecki, R. Bilato, P. Bilkova, W. Bin, G. Birkenmeier, R. Bisson, P. Blanchard, A. Bleasdale, V. Bobkov, A. Boboc, A. Bock, K. Bogar, P. Bohm, T. Bolzonella, F. Bombarda, N. Bonanomi, L. Boncagni, D. Bonfiglio, R. Bonifetto, M. Bonotto, D. Borodin, I. Borodkina, T.O.S.J. Bosman, C. Bourdelle, C. Bowman, S. Brezinsek, D. Brida, F. Brochard, R. Brunet, D. Brunetti, V. Bruno, R. Buchholz, J. Buermans, H. Bufferand, P. Buratti, A. Burckhart, J. Cai, R. Calado, J. Caloud, S. Cancelli, F. Cani, B. Cannas, M. Cappelli, S. Carcangiu, A. Cardinali, S. Carli, D. Carnevale, M. Carole, M. Carpita, D. Carralero, F. Caruggi, I.S. Carvalho, I. Casiraghi, A. Casolari, F.J. Casson, C. Castaldo, A. Cathey, F. Causa, J. Cavalier, M. Cavedon, J. Cazabonne, M. Cecconello, L. Ceelen, A. Celora, J. Cerovsky, C.D. Challis, R. Chandra, A. Chankin, B. Chapman, H. Chen, M. Chernyshova, A.G. Chiariello, P. Chmielewski, A. Chomiczewska, C. Cianfarani, G. Ciraolo, J. Citrin, F. Clairet, S. Coda, R. Coelho, J.W. Coenen, I.H. Coffey, C. Colandrea, L. Colas, S. Conroy, C. Contre, N.J. Conway, L. Cordaro, Y. Corre, D. Costa, S. Costea, D. Coster, X. Courtois, C. Cowley, T. Craciunescu, G. Croci, A.M. Croitoru, K. Crombe, D.J. Cruz Zabala, G. Cseh, T. Czarski, A. Da Ros, A. Dal Molin, M. Dalla Rosa, Y. Damizia, O. D’Arcangelo, P. David, M. De Angeli, E. De la Cal, E. De La Luna, G. De Tommasi, J. Decker, R. Dejarnac, D. Del Sarto, G. Derks, C. Desgranges, P. Devynck, S. Di Genova, L.E. di Grazia, A. Di Siena, M. Dicorato, M. Diez, M. Dimitrova, T. Dittmar, L. Dittrich, J.J. Domínguez Palacios Durán, P. Donnel, D. Douai, S. Dowson, S. Doyle, M. Dreval, P. Drews, L. Dubus, R. Dumont, D. Dunai, M. Dunne, A. Durif, F. Durodie, G. Durr Legoupil Nicoud, B. Duval, R. Dux, T. Eich, A. Ekedahl, S. Elmore, G. Ericsson, J. Eriksson, B. Eriksson, F. Eriksson, S. Ertmer, A. Escarguel, B. Esposito, T. Estrada, E. Fable, M. Faitsch, N. Fakhrayi Mofrad, A. Fanni, T. Farley, M. Farník, N. Fedorczak, F. Felici, X. Feng, J. Ferreira, D. Ferreira, N. Ferron, O. Fevrier, O. Ficker, A.R. Field, A. Figueiredo, N. Fil, D. Fiorucci, M. Firdaouss, R. Fischer, M. Fitzgerald, M. Flebbe, M. Fontana, J. Fontdecaba Climent, A. Frank, E. Fransson, L. Frassinetti, D. Frigione, S. Futatani, R. Futtersack, S. Gabriellini, D. Gadariya, D. Galassi, K. Galazka, J. Galdon, S. Galeani, D. Gallart, A. Gallo, C. Galperti, M. Gambrioli, S. Garavaglia, J. Garcia, M. Garcia Munoz, J. Gardarein, L. Garzotti, J. Gaspar, R. Gatto, P. Gaudio, M. Gelfusa, J. Gerardin, S.N. Gerasimov, R. Gerru Miguelanez, G. Gervasini, Z. Ghani, F.M. Ghezzi, G. Ghillardi, L. Giannone, S. Gibson, L. Gil, A. Gillgren, E. Giovannozzi, C. Giroud, G. Giruzzi, T. Gleiter, M. Gobbin, V. Goloborodko, A. González Ganzábal, T. Goodman, V. Gopakumar, G. Gorini, T. Görler, S. Gorno, G. Granucci, D. Greenhouse, G. Grenfell, M. Griener, W. Gromelski, M. Groth, O. Grover, M. Gruca, A. Gude, C. Guillemaut, R. Guirlet, J. Gunn, T. Gyergyek, L. Hagg, J. Hall, C.J. Ham, M. Hamed, T. Happel, G. Harrer, J. Harrison, D. Harting, N.C. Hawkes, P. Heinrich, S. Henderson, P. Hennequin, R. Henriques, S. Heuraux, J. Hidalgo Salaverri, J. Hillairet, J.C. Hillesheim, A. Hjalmarsson, A. Ho, J. Hobirk, E. Hodille, M. Hölzl, M. Hoppe, J. Horacek, N. Horsten, L. Horvath, M. Houry, K. Hromasova, J. Huang, Z. Huang, A. Huber, E. Huett, P. Huynh, A. Iantchenko, M. Imrisek, P. Innocente, C. Ionita Schrittwieser, H. Isliker, P. Ivanova, I. Ivanova Stanik, M. Jablczynska, S. Jachmich, A.S. Jacobsen, P. Jacquet, A. Jansen van Vuuren, A. Jardin, H. Järleblad, A. Järvinen, F. Jaulmes, T. Jensen, I. Jepu, S. Jessica, T. Johnson, A. Juven, J. Kalis, J. Karhunen, R. Karimov, A.N. Karpushov, S. Kasilov, Y. Kazakov, P.V. Kazantzidis, W. Kernbichler, HT. Kim, D.B. King, V.G. Kiptily, A. Kirjasuo, K.K. Kirov, A. Kirschner, A. Kit, T. Kiviniemi, F. Kjær, E. Klinkby, A. Knieps, U. Knoche, M. Kochan, F. Köchl, G. Kocsis, J.T.W. Koenders, L. Kogan, Y. Kolesnichenko, Y. Kominis, M. Komm, M. Kong, B. Kool, S.B. Korsholm, D. Kos, M. Koubiti, J. Kovacic, Y. Kovtun, E. Kowalska Strzeciwilk, K. Koziol, M. Kozulia, A. Krämer Flecken, A. Kreter, K. Krieger, U. Kruezi, O. Krutkin, O. Kudlacek, U. Kumar, H. Kumpulainen, M.H. Kushoro, R. Kwiatkowski, M. La Matina, M. Lacquaniti, L. Laguardia, P. Lainer, P. Lang, M. Larsen, E. Laszynska, K.D. Lawson, A. Lazaros, E. Lazzaro, M.Y.K. Lee, S. Leerink, M. Lehnen, M. Lennholm, E. Lerche, Y. Liang, A. Lier, J. Likonen, O. Linder, B. Lipschultz, A. Listopad, X. Litaudon, E. Litherland Smith, D. Liuzza, T. Loarer, P.J. Lomas, J. Lombardo, N. Lonigro, R. Lorenzini, C. Lowry, T. Luda di Cortemiglia, A. Ludvig Osipov, T. Lunt, V. Lutsenko, E. Macusova, R. Mäenpää, P. Maget, C.F. Maggi, J. Mailloux, S. Makarov, K. Malinowski, P. Manas, A. Mancini, D. Mancini, P. Mantica, M. Mantsinen, J. Manyer, M. Maraschek, G. Marceca, G. Marcer, C. Marchetto, S. Marchioni, A. Mariani, M. Marin, M. Markl, T. Markovic, D. Marocco, S. Marsden, L. Martellucci, P. Martin, C. Martin, F. Martinelli, L. Martinelli, J.R. Martin Solis, R. Martone, M. Maslov, R. Masocco, M. Mattei, G.F. Matthews, D. Matveev, E. Matveeva, M.L. Mayoral, D. Mazon, S. Mazzi, C. Mazzotta, G. McArdle, R. McDermott, K. McKay, A.G. Meigs, C. Meineri, A. Mele, V. Menkovski, S. Menmuir, A. Merle, H. Meyer, K. Mikszuta Michalik, D. Milanesio, F. Militello, A. Milocco, I.G. Miron, J. Mitchell, R. Mitteau, V. Mitterauer, J. Mlynar, V. Moiseenko, P. Molna, F. Mombelli, C. Monti, A. Montisci, J. Morales, P. Moreau, J.M. Moret, A. Moro, D. Moulton, P. Mulholland, M. Muraglia, A. Murari, A. Muraro, P. Muscente, D. Mykytchuk, F. Nabais, Y. Nakeva, F. Napoli, E. Nardon, M.F. Nave, R.D. Nem, A. Nielsen, S.K. Nielsen, M. Nocente, R. Nouailletas, S. Nowak, H. Nyström, R. Ochoukov, N. Offeddu, S. Olasz, C. Olde, F. Oliva, D. Oliveira, H.J.C. Oliver, P. Ollus, J. Ongena, F.P. Orsitto, N. Osborne, R. Otin, P. Oyola Dominguez, D.I. Palade, S. Palomba, O. Pan, N. Panadero, E. Panontin, A. Papadopoulos, P. Papagiannis, G. Papp, V.V. Parail, C. Pardanaud, J. Parisi, A. Parrott, K. Paschalidis, M. Passoni, F. Pastore, A. Patel, B. Patel, A. Pau, G. Pautasso, R. Pavlichenko, E. Pawelec, B. Pegourie, G. Pelka, E. Peluso, A. Perek, E. Perelli Cippo, C. Perez Von Thun, P. Petersson, G. Petravich, Y. Peysson, V. Piergotti, L. Pigatto, C. Piron, L. Piron, A. Pironti, F. Pisano, U. Plank, B. Ploeckl, V. Plyusnin, A. Podolnik, Y. Poels, G. Pokol, J. Poley, G. Por, M. Poradzinski, F. Porcelli, L. Porte, C. Possieri, A. Poulsen, I. Predebon, G. Pucella, M. Pueschel, P. Puglia, O. Putignano, T. Pütterich, V. Quadri, A. Quercia, M. Rabinski, L. Radovanovic, R. Ragona, H. Raj, M. Rasinski, J. Rasmussen, G. Ratta, S. Ratynskaia, R. Rayaprolu, M. Rebai, A. Redl, D. Rees, D. Refy, M. Reich, H. Reimerdes, B.C.G. Reman, O. Renders, C. Reux, D. Ricci, M. Richou, S. Rienacker, D. Rigamonti, F. Rigollet, F.G. Rimini, D. Ripamonti, N. Rispoli, N. Rivals, J.F. Rivero Rodriguez, C. Roach, G. Rocchi, S. Rode, P. Rodrigues, J. Romazanov, C.F. Romero Madrid, J. Rosato, R. Rossi, G. Rubino, J. Rueda Rueda, J. Ruiz Ruiz, P. Ryan, D. Ryan, S. Saarelma, R. Sabot, M. Salewski, A. Salmi, L. Sanchis, A. Sand, J. Santos, K. Särkimäki, M. Sassano, O. Sauter, G. Schettini, S. Schmuck, P. Schneider, N. Schoonheere, R. Schramm, R. Schrittwieser, C. Schuster, N. Schwarz, F. Sciortino, M. Scotto D’Abusco, S. Scully, A. Selce, L. Senni, M. Senstius, G. Sergienko, S.E. Sharapov, R. Sharma, A. Shaw, U. Sheikh, G. Sias, B. Sieglin, S.A. Silburn, C. Silva, A. Silva, D. Silvagni, B. Simmendefeldt Schmidt, L. Simons, J. Simpson, L. Singh, S. Sipilä, Y. Siusko, S. Smith, A. Snicker, E.R. Solano, V. Solokha, M. Sos, C. Sozzi, F. Spineanu, G. Spizzo, M. Spolaore, L. Spolladore, C. Srinivasan, A. Stagni, Z. Stancar, G. Stankunas, J. Stober, P. Strand, C.I. Stuart, F. Subba, G.Y. Sun, H.J. Sun, W. Suttrop, J. Svoboda, T. Szepesi, G. Szepesi, B. Tal, T. Tala, P. Tamain, G. Tardini, M. Tardocchi, D. Taylor, G. Telesca, A. Tenaglia, A. Terra, D. Terranova, D. Testa, C. Theiler, E. Tholerus, B. Thomas, E. Thoren, A. Thornton, A. Thrysoe, Q. TICHIT, W. Tierens, A. Titarenko, P. Tolias, E. Tomasina, M. Tomes, E. Tonello, A. Tookey, M. Toscano Jiménez, C. Tsironis, C. Tsui, A. Tykhyy, M. Ugoletti, M. Usoltseva, D.F. Valcarcel, A. Valentini, M. Valisa, M. Vallar, M. Valovic, SI. Valvis, M. van Berkel, D. Van Eester, S. Van Mulders, M. van Rossem, R. Vann, B. Vanovac, J. Varela Rodriguez, J. Varje, S. Vartanian, M. Vecsei, L. Velarde Gallardo, M. Veranda, T. Verdier, G. Verdoolaege, K. Verhaegh, L. Vermare, G. Verona Rinati, J. Vicente, E. Viezzer, L. Vignitchouk, F. Villone, B. Vincent, P. Vincenzi, M.O. Vlad, G. Vogel, I. Voitsekhovitch, I. Voldiner, P. Vondracek, N.M.T. VU, T. Vuoriheimo, C. Wade, E. Wang, T. Wauters, M. Weiland, H. Weisen, N. Wendler, D. Weston, A. Widdowson, S. Wiesen, M. Wiesenberger, T. Wijkamp, M. Willensdorfer, T. Wilson, A. Wojenski, C. Wuethrich, I. Wyss, L. Xiang, S. Xu, D. Yadykin, Y. Yakovenko, H. Yang, V. Yanovskiy, R. Yi, B. Zaar, G. Zadvitskiy, L. Zakharov, P. Zanca, D. Zarzoso, Y. Zayachuk, J. Zebrowski, M. Zerbini, P. Zestanakis, C. F. B. Zimmermann, M. Zlobinski, A. Zohar, V.K. Zotta, X. Zou, M. Zuin, M. Zurita, and I. Zychor

Subjects
JET, ASDEX Upgrade, MAST-U, TCV, WEST, Tokamak Exploitation Task Force, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

Within the 9th European Framework programme, since 2021 EUROfusion is operating five tokamaks under the auspices of a single Task Force called ‘Tokamak Exploitation’. The goal is to benefit from the complementary capabilities of each machine in a coordinated way and help in developing a scientific output scalable to future largre machines. The programme of this Task Force ensures that ASDEX Upgrade, MAST-U, TCV, WEST and JET (since 2022) work together to achieve the objectives of Missions 1 and 2 of the EUROfusion Roadmap: i) demonstrate plasma scenarios that increase the success margin of ITER and satisfy the requirements of DEMO and, ii) demonstrate an integrated approach that can handle the large power leaving ITER and DEMO plasmas. The Tokamak Exploitation task force has therefore organized experiments on these two missions with the goal to strengthen the physics and operational basis for the ITER baseline scenario and for exploiting the recent plasma exhaust enhancements in all four devices (PEX: Plasma EXhaust) for exploring the solution for handling heat and particle exhaust in ITER and develop the conceptual solutions for DEMO. The ITER Baseline scenario has been developed in a similar way in ASDEX Upgrade, TCV and JET. Key risks for ITER such as disruptions and run-aways have been also investigated in TCV, ASDEX Upgrade and JET. Experiments have explored successfully different divertor configurations (standard, super-X, snowflakes) in MAST-U and TCV and studied tungsten melting in WEST and ASDEX Upgrade. The input from the smaller devices to JET has also been proven successful to set-up novel control schemes on disruption avoidance and detachment.

Published
2024
Full Text
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2. Overview of T and D–T results in JET with ITER-like wall

Author

C.F. Maggi, D. Abate, N. Abid, P. Abreu, O. Adabonyan, M. Afzal, I. Ahmad, M. Akhtar, R. Albanese, S. Aleiferis, E. Alessi, P. Aleynikov, J. Alguacil, J. Alhage, M. Ali, H. Allen, M. Allinson, M. Alonzo, E. Alves, R. Ambrosino, E. Andersson Sundén, P. Andrew, M. Angelone, C. Angioni, I. Antoniou, L. Appel, C. Appelbee, C. Aramunde, M. Ariola, G. Arnoux, G. Artaserse, J.-F. Artaud, W. Arter, V. Artigues, F.J. Artola, A. Ash, O. Asztalos, D. Auld, F. Auriemma, Y. Austin, L. Avotina, J. Ayllón, E. Aymerich, A. Baciero, L. Bähner, F. Bairaktaris, I. Balboa, M. Balden, N. Balshaw, V.K. Bandaru, J. Banks, A. Banon Navarro, C. Barcellona, O. Bardsley, M. Barnes, R. Barnsley, M. Baruzzo, M. Bassan, A. Batista, P. Batistoni, L. Baumane, B. Bauvir, L. Baylor, C. Bearcroft, P. Beaumont, D. Beckett, A. Begolli, M. Beidler, N. Bekris, M. Beldishevski, E. Belli, F. Belli, S. Benkadda, J. Bentley, E. Bernard, J. Bernardo, M. Bernert, M. Berry, L. Bertalot, H. Betar, M. Beurskens, P.G. Bhat, S. Bickerton, J. Bielecki, T. Biewer, R. Bilato, P. Bílková, G. Birkenmeier, R. Bisson, J.P.S. Bizarro, P. Blatchford, A. Bleasdale, V. Bobkov, A. Boboc, A. Bock, G. Bodnar, P. Bohm, L. Bonalumi, N. Bonanomi, D. Bonfiglio, X. Bonnin, P. Bonofiglo, J. Booth, D. Borba, D. Borodin, I. Borodkina, T.O.S.J. Bosman, C. Bourdelle, M. Bowden, I. Božičević Mihalić, S.C. Bradnam, B. Breizman, S. Brezinsek, D. Brida, M. Brix, P. Brown, D. Brunetti, M. Buckley, J. Buermans, H. Bufferand, P. Buratti, A. Burckhart, A. Burgess, A. Buscarino, A. Busse, D. Butcher, G. Calabrò, L. Calacci, R. Calado, R. Canavan, B. Cannas, M. Cannon, M. Cappelli, S. Carcangiu, P. Card, A. Cardinali, S. Carli, P. Carman, D. Carnevale, B. Carvalho, I.S. Carvalho, P. Carvalho, I. Casiraghi, F.J. Casson, C. Castaldo, J.P. Catalan, N. Catarino, F. Causa, M. Cavedon, M. Cecconello, L. Ceelen, C.D. Challis, B. Chamberlain, R. Chandra, C.S. Chang, A. Chankin, B. Chapman, P. Chauhan, M. Chernyshova, A. Chiariello, G.-C. Chira, P. Chmielewski, A. Chomiczewska, L. Chone, J. Cieslik, G. Ciraolo, D. Ciric, J. Citrin, Ł. Ciupinski, R. Clarkson, M. Cleverly, P. Coates, V. Coccorese, R. Coelho, J.W. Coenen, I.H. Coffey, A. Colangeli, L. Colas, J. Collins, S. Conroy, C. Contré, N.J. Conway, D. Coombs, P. Cooper, S. Cooper, L. Cordaro, C. Corradino, Y. Corre, G. Corrigan, D. Coster, T. Craciunescu, S. Cramp, D. Craven, R. Craven, G. Croci, D. Croft, K. Crombé, T. Cronin, N. Cruz, A. Cufar, A. Cullen, A. Dal Molin, S. Dalley, P. David, A. Davies, J. Davies, S. Davies, G. Davis, K. Dawson, S. Dawson, I. Day, G. De Tommasi, J. Deane, M. Dearing, M. De Bock, J. Decker, R. Dejarnac, E. Delabie, E. de la Cal, E. de la Luna, D. Del Sarto, A. Dempsey, W. Deng, A. Dennett, G.L. Derks, G. De Temmerman, F. Devasagayam, P. de Vries, P. Devynck, A. di Siena, D. Dickinson, T. Dickson, M. Diez, P. Dinca, T. Dittmar, L. Dittrich, J. Dobrashian, T. Dochnal, A.J.H. Donné, W. Dorland, S. Dorling, S. Dormido-Canto, R. Dotse, D. Douai, S. Dowson, R. Doyle, M. Dreval, P. Drews, G. Drummond, Ph. Duckworth, H.G. Dudding, R. Dumont, P. Dumortier, D. Dunai, T. Dunatov, M. Dunne, I. Ďuran, F. Durodié, R. Dux, T. Eade, E. Eardley, J. Edwards, T. Eich, A. Eksaeva, H. El-Haroun, R.D. Ellis, G. Ellwood, C. Elsmore, S. Emery, G. Ericsson, B. Eriksson, F. Eriksson, J. Eriksson, L.G. Eriksson, S. Ertmer, G. Evans, S. Evans, E. Fable, D. Fagan, M. Faitsch, D. Fajardo Jimenez, M. Falessi, A. Fanni, T. Farmer, I. Farquhar, B. Faugeras, S. Fazinić, N. Fedorczak, K. Felker, R. Felton, H. Fernandes, D.R. Ferreira, J. Ferreira, G. Ferrò, J. Fessey, O. Février, O. Ficker, A.R. Field, A. Figueiredo, J. Figueiredo, A. Fil, N. Fil, P. Finburg, U. Fischer, G. Fishpool, L. Fittill, M. Fitzgerald, D. Flammini, J. Flanagan, S. Foley, N. Fonnesu, M. Fontana, J.M. Fontdecaba, L. Fortuna, E. Fortuna-Zalesna, M. Fortune, C. Fowler, P. Fox, O. Franklin, E. Fransson, L. Frassinetti, R. Fresa, D. Frigione, T. Fülöp, M. Furseman, S. Gabriellini, D. Gadariya, S. Gadgil, K. Gál, S. Galeani, A. Galkowski, D. Gallart, M. Gambrioli, T. Gans, J. Garcia, M. García-Muñoz, L. Garzotti, J. Gaspar, R. Gatto, P. Gaudio, D. Gear, T. Gebhart, S. Gee, M. Gelfusa, R. George, S.N. Gerasimov, R. Gerru, G. Gervasini, M. Gethins, Z. Ghani, M. Gherendi, P.-I. Gherghina, F. Ghezzi, L. Giacomelli, C. Gibson, L. Gil, M.R. Gilbert, A. Gillgren, E. Giovannozzi, C. Giroud, G. Giruzzi, J. Goff, V. Goloborodko, R. Gomes, J.-F. Gomez, B. Gonçalves, M. Goniche, J. Gonzalez-Martin, A. Goodyear, S. Gore, G. Gorini, T. Görler, N. Gotts, E. Gow, J.P. Graves, J. Green, H. Greuner, E. Grigore, F. Griph, W. Gromelski, M. Groth, C. Grove, R. Grove, N. Gupta, S. Hacquin, L. Hägg, A. Hakola, M. Halitovs, J. Hall, C.J. Ham, M. Hamed, M.R. Hardman, Y. Haresawa, G. Harrer, J.R. Harrison, D. Harting, D.R. Hatch, T. Haupt, J. Hawes, N.C. Hawkes, J. Hawkins, S. Hazael, J. Hearmon, P. Heesterman, P. Heinrich, M. Held, W. Helou, O. Hemming, S.S. Henderson, R. Henriques, R.B. Henriques, D. Hepple, J. Herfindal, G. Hermon, J.C. Hillesheim, K. Hizanidis, A. Hjalmarsson, A. Ho, J. Hobirk, O. Hoenen, C. Hogben, A. Hollingsworth, S. Hollis, E. Hollmann, M. Hölzl, M. Hook, M. Hoppe, J. Horáček, N. Horsten, A. Horton, L.D. Horton, L. Horvath, S. Hotchin, Z. Hu, Z. Huang, E. Hubenov, A. Huber, V. Huber, T. Huddleston, G.T.A. Huijsmans, Y. Husain, P. Huynh, A. Hynes, D. Iglesias, M.V. Iliasova, M. Imríšek, J. Ingleby, P. Innocente, V. Ioannou-Sougleridis, N. Isernia, I. Ivanova-Stanik, E. Ivings, S. Jachmich, T. Jackson, A.S. Jacobsen, P. Jacquet, H. Järleblad, A. Järvinen, F. Jaulmes, N. Jayasekera, F. Jenko, I. Jepu, E. Joffrin, T. Johnson, J. Johnston, C. Jones, E. Jones, G. Jones, L. Jones, T.T.C. Jones, A. Joyce, M. Juvonen, A. Kallenbach, P. Kalnina, D. Kalupin, P. Kanth, A. Kantor, A. Kappatou, O. Kardaun, J. Karhunen, E. Karsakos, Ye.O. Kazakov, V. Kazantzidis, D.L. Keeling, W. Kelly, M. Kempenaars, D. Kennedy, K. Khan, E. Khilkevich, C. Kiefer, H.-T. Kim, J. Kim, S.H. Kim, D.B. King, D.J. Kinna, V.G. Kiptily, A. Kirjasuo, K.K. Kirov, A. Kirschner, T. Kiviniemi, G. Kizane, C. Klepper, A. Klix, G. Kneale, M. Knight, P. Knight, R. Knights, S. Knipe, U. Knoche, M. Knolker, M. Kocan, F. Köchl, G. Kocsis, J.T.W. Koenders, Y. Kolesnichenko, Y. Kominis, M. Kong, B. Kool, V. Korovin, S.B. Korsholm, B. Kos, D. Kos, M. Koubiti, Y. Kovtun, E. Kowalska-Strzęciwilk, K. Koziol, Y. Krasikov, A. Krasilnikov, V. Krasilnikov, M. Kresina, A. Kreter, K. Krieger, A. Krivska, U. Kruezi, I. Książek, H. Kumpulainen, B. Kurzan, S. Kwak, O.J. Kwon, B. Labit, M. Lacquaniti, A. Lagoyannis, L. Laguardia, A. Laing, V. Laksharam, N. Lam, H.T. Lambertz, B. Lane, M. Langley, E. Lascas Neto, E. Łaszyńska, K.D. Lawson, A. Lazaros, E. Lazzaro, G. Learoyd, C. Lee, K. Lee, S. Leerink, T. Leeson, X. Lefebvre, H.J. Leggate, J. Lehmann, M. Lehnen, D. Leichtle, F. Leipold, I. Lengar, M. Lennholm, E. Leon Gutierrez, L.A. Leppin, E. Lerche, A. Lescinskis, S. Lesnoj, L. Lewin, J. Lewis, J. Likonen, Ch. Linsmeier, X. Litaudon, E. Litherland-Smith, F. Liu, T. Loarer, A. Loarte, R. Lobel, B. Lomanowski, P.J. Lomas, J. Lombardo, R. Lorenzini, S. Loreti, V.P. Loschiavo, M. Loughlin, T. Lowe, C. Lowry, T. Luce, R. Lucock, T. Luda Di Cortemiglia, M. Lungaroni, C.P. Lungu, T. Lunt, V. Lutsenko, B. Lyons, J. Macdonald, E. Macusova, R. Mäenpää, H. Maier, J. Mailloux, S. Makarov, P. Manas, A. Manning, P. Mantica, M.J. Mantsinen, J. Manyer, A. Manzanares, Ph. Maquet, M. Maraschek, G. Marceca, G. Marcer, C. Marchetto, O. Marchuk, A. Mariani, G. Mariano, M. Marin, A. Marin Roldan, M. Marinelli, T. Markovič, L. Marot, C. Marren, S. Marsden, S. Marsen, J. Marsh, R. Marshall, L. Martellucci, A.J. Martin, C. Martin, R. Martone, S. Maruyama, M. Maslov, M. Mattei, G.F. Matthews, D. Matveev, E. Matveeva, A. Mauriya, F. Maviglia, M. Mayer, M.-L. Mayoral, S. Mazzi, C. Mazzotta, R. McAdams, P.J. McCarthy, P. McCullen, R. McDermott, D.C. McDonald, D. McGuckin, V. McKay, L. McNamee, A. McShee, D. Mederick, M. Medland, S. Medley, K. Meghani, A.G. Meigs, S. Meitner, S. Menmuir, K. Mergia, S. Mianowski, P. Middleton, J. Mietelski, K. Mikszuta-Michalik, D. Milanesio, E. Milani, E. Militello-Asp, F. Militello, J. Milnes, A. Milocco, S. Minucci, I. Miron, J. Mitchell, J. Mlynář, V. Moiseenko, P. Monaghan, I. Monakhov, A. Montisci, S. Moon, R. Mooney, S. Moradi, R.B. Morales, L. Morgan, F. Moro, J. Morris, T. Mrowetz, L. Msero, S. Munot, A. Muñoz-Perez, M. Muraglia, A. Murari, A. Muraro, B. N’Konga, Y.S. Na, F. Nabais, R. Naish, F. Napoli, E. Nardon, V. Naulin, M.F.F. Nave, R. Neu, S. Ng, M. Nicassio, D. Nicolai, A.H. Nielsen, S.K. Nielsen, D. Nina, C. Noble, C.R. Nobs, M. Nocente, H. Nordman, S. Nowak, H. Nyström, J. O’Callaghan, M. O’Mullane, C. O’Neill, C. Olde, H.J.C. Oliver, R. Olney, J. Ongena, G.P. Orsitto, A. Osipov, R. Otin, N. Pace, L.W. Packer, E. Pajuste, D. Palade, J. Palgrave, O. Pan, N. Panadero, T. Pandya, E. Panontin, A. Papadopoulos, G. Papadopoulos, G. Papp, V.V. Parail, A. Parsloe, K. Paschalidis, M. Passeri, A. Patel, A. Pau, G. Pautasso, R. Pavlichenko, A. Pavone, E. Pawelec, C. Paz-Soldan, A. Peacock, M. Pearce, I.J. Pearson, E. Peluso, C. Penot, K. Pepperell, A. Perdas, T. Pereira, E. Perelli Cippo, C. Perez von Thun, D. Perry, P. Petersson, G. Petravich, N. Petrella, M. Peyman, L. Pigatto, M. Pillon, S. Pinches, G. Pintsuk, C. Piron, A. Pironti, F. Pisano, R. Pitts, U. Planck, N. Platt, V. Plyusnin, M. Podesta, G. Pokol, F.M. Poli, O.G. Pompilian, M. Poradzinski, M. Porkolab, C. Porosnicu, G. Poulipoulis, A.S. Poulsen, I. Predebon, A. Previti, D. Primetzhofer, G. Provatas, G. Pucella, P. Puglia, K. Purahoo, O. Putignano, T. Pütterich, A. Quercia, G. Radulescu, V. Radulovic, R. Ragona, M. Rainford, P. Raj, M. Rasinski, D. Rasmussen, J. Rasmussen, J.J. Rasmussen, A. Raso, G. Rattá, S. Ratynskaia, R. Rayaprolu, M. Rebai, A. Redl, D. Rees, D. Réfy, R. Reichle, H. Reimerdes, B.C.G. Reman, C. Reux, S. Reynolds, D. Rigamonti, E. Righi, F.G. Rimini, J. Risner, J.F. Rivero-Rodriguez, C.M. Roach, J. Roberts, R. Robins, S. Robinson, D. Robson, S. Rode, P. Rodrigues, P. Rodriguez-Fernandez, S. Romanelli, J. Romazanov, E. Rose, C. Rose-Innes, R. Rossi, S. Rowe, D. Rowlands, C. Rowley, M. Rubel, G. Rubinacci, G. Rubino, M. Rud, J. Ruiz Ruiz, F. Ryter, S. Saarelma, A. Sahlberg, M. Salewski, A. Salmi, R. Salmon, F. Salzedas, F. Sanchez, I. Sanders, D. Sandiford, F. Sanni, O. Sauter, P. Sauvan, G. Schettini, A. Shevelev, A.A. Schekochihin, K. Schmid, B.S. Schmidt, S. Schmuck, M. Schneider, P.A. Schneider, N. Schoonheere, R. Schramm, D. Scoon, S. Scully, M. Segato, J. Seidl, L. Senni, J. Seo, G. Sergienko, M. Sertoli, S.E. Sharapov, R. Sharma, A. Shaw, R. Shaw, H. Sheikh, U. Sheikh, N. Shi, P. Shigin, D. Shiraki, G. Sias, M. Siccinio, B. Sieglin, S.A. Silburn, A. Silva, C. Silva, J. Silva, D. Silvagni, D. Simfukwe, J. Simpson, P. Sirén, A. Sirinelli, H. Sjöstrand, N. Skinner, J. Slater, T. Smart, R.D. Smirnov, N. Smith, P. Smith, T. Smith, J. Snell, L. Snoj, E.R. Solano, V. Solokha, C. Sommariva, K. Soni, M. Sos, J. Sousa, C. Sozzi, T. Spelzini, F. Spineanu, L. Spolladore, D. Spong, C. Srinivasan, G. Staebler, A. Stagni, I. Stamatelatos, M.F. Stamp, Ž. Štancar, P.A. Staniec, G. Stankūnas, M. Stead, B. Stein-Lubrano, A. Stephen, J. Stephens, P. Stevenson, C. Steventon, M. Stojanov, D.A. St-Onge, P. Strand, S. Strikwerda, C.I. Stuart, S. Sturgeon, H.J. Sun, S. Surendran, W. Suttrop, J. Svensson, J. Svoboda, R. Sweeney, G. Szepesi, M. Szoke, T. Tadić, B. Tal, T. Tala, P. Tamain, K. Tanaka, W. Tang, G. Tardini, M. Tardocchi, D. Taylor, A.S. Teimane, G. Telesca, A. Teplukhina, A. Terra, D. Terranova, N. Terranova, D. Testa, B. Thomas, V.K. Thompson, A. Thorman, A.S. Thrysoe, W. Tierens, R.A. Tinguely, A. Tipton, H. Todd, M. Tomeš, A. Tookey, P. Tsavalas, D. Tskhakaya, L.-P. Turică, A. Turner, I. Turner, M. Turner, M.M. Turner, G. Tvalashvili, A. Tykhyy, S. Tyrrell, A. Uccello, V. Udintsev, A. Vadgama, D.F. Valcarcel, A. Valentini, M. Valisa, M. Vallar, M. Valovic, M. Van Berkel, K.L. van de Plassche, M. van Rossem, D. Van Eester, J. Varela, J. Varje, T. Vasilopoulou, G. Vayakis, M. Vecsei, J. Vega, M. Veis, P. Veis, S. Ventre, M. Veranda, G. Verdoolaege, C. Verona, G. Verona Rinati, E. Veshchev, N. Vianello, E. Viezzer, L. Vignitchouk, R. Vila, R. Villari, F. Villone, P. Vincenzi, A. Vitins, Z. Vizvary, M. Vlad, I. Voldiner, U. Von Toussaint, P. Vondráček, B. Wakeling, M. Walker, R. Walker, M. Walsh, R. Walton, E. Wang, F. Warren, R. Warren, J. Waterhouse, C. Watts, T. Webster, M. Weiland, H. Weisen, M. Weiszflog, N. Wendler, A. West, M. Wheatley, S. Whetham, A. Whitehead, D. Whittaker, A. Widdowson, S. Wiesen, M. Willensdorfer, J. Williams, I. Wilson, T. Wilson, M. Wischmeier, A. Withycombe, D. Witts, A. Wojcik-Gargula, E. Wolfrum, R. Wood, R. Woodley, R. Worrall, I. Wyss, T. Xu, D. Yadykin, Y. Yakovenko, Y. Yang, V. Yanovskiy, R. Yi, I. Young, R. Young, B. Zaar, R.J. Zabolockis, L. Zakharov, P. Zanca, A. Zarins, D. Zarzoso Fernandez, K.-D. Zastrow, Y. Zayachuk, M. Zerbini, W. Zhang, B. Zimmermann, M. Zlobinski, A. Zocco, V.K. Zotta, M. Zuin, W. Zwingmann, and I. Zychor

Subjects
magnetic fusion, JET-ILW, D–T, tritium, alpha particles, fusion prediction, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

In 2021 JET exploited its unique capabilities to operate with T and D–T fuel with an ITER-like Be/W wall (JET-ILW). This second major JET D–T campaign (DTE2), after DTE1 in 1997, represented the culmination of a series of JET enhancements—new fusion diagnostics, new T injection capabilities, refurbishment of the T plant, increased auxiliary heating, in-vessel calibration of 14 MeV neutron yield monitors—as well as significant advances in plasma theory and modelling in the fusion community. DTE2 was complemented by a sequence of isotope physics campaigns encompassing operation in pure tritium at high T-NBI power. Carefully conducted for safe operation with tritium, the new T and D–T experiments used 1 kg of T (vs 100 g in DTE1), yielding the most fusion reactor relevant D–T plasmas to date and expanding our understanding of isotopes and D–T mixture physics. Furthermore, since the JET T and DTE2 campaigns occurred almost 25 years after the last major D–T tokamak experiment, it was also a strategic goal of the European fusion programme to refresh operational experience of a nuclear tokamak to prepare staff for ITER operation. The key physics results of the JET T and DTE2 experiments, carried out within the EUROfusion JET1 work package, are reported in this paper. Progress in the technological exploitation of JET D–T operations, development and validation of nuclear codes, neutronic tools and techniques for ITER operations carried out by EUROfusion (started within the Horizon 2020 Framework Programme and continuing under the Horizon Europe FP) are reported in (Litaudon et al Nucl. Fusion accepted), while JET experience on T and D–T operations is presented in (King et al Nucl. Fusion submitted).

Published
2024
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3. EUROfusion contributions to ITER nuclear operation

Author

X. Litaudon, U. Fantz, R. Villari, V. Toigo, M.-H. Aumeunier, J.-L. Autran, P. Batistoni, E. Belonohy, S. Bradnam, M. Cecchetto, A. Colangeli, F. Dacquait, S. Dal Bello, M. Dentan, M. De Pietri, J. Eriksson, M. Fabbri, G. Falchetto, L. Figini, J. Figueiredo, D. Flammini, N. Fonnesu, L. Frassinetti, J. Galdón-Quiroga, R. Garcia-Alia, M. Garcia-Munoz, Z. Ghani, J. Gonzalez-Martin, E. Grelier, L. Di Grazia, B. Grove, C.L. Grove, A. Gusarov, B. Heinemann, A. Hjalmarsson, O. Hyvärinen, V. Ioannou-Sougleridis, L. Jones, H.-T. Kim, M. Kłosowski, M. Kocan, B. Kos, L. Kos, D. Kotnik, E. Laszynska, D. Leichtle, I. Lengar, E. Leon-Gutierrez, A.J. López-Revelles, S. Loreti, M. Loughlin, D. Marcuzzi, K.G. Mcclements, G. Mariano, M. Mattei, K. Mergia, J. Mietelski, R. Mitteau, S. Moindjie, D. Munteanu, R. Naish, S. Noce, L.W. Packer, S. Pamela, R. Pampin, A. Pau, A. Peacock, E. Peluso, Y. Peneliau, J. Peric, V. Radulović, D. Ricci, F. Rimini, L. Sanchis-Sanchez, P. Sauvan, M.I. Savva, G. Serianni, C.R. Shand, A. Snicker, L. Snoj, I.E. Stamatelatos, Ž. Štancar, N. Terranova, T. Vasilopoulou, R. Vila, J. Waterhouse, C. Wimmer, D. Wünderlich, A. Žohar, the NBTF Team, JET Contributors, and the EUROfusion Tokamak Exploitation Team

Subjects
nuclear fusion, tokamak operation, neutral beam heating and current drive, neutronics, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract

ITER is of key importance in the European fusion roadmap as it aims to prove the scientific and technological feasibility of fusion as a future energy source. The EUROfusion consortium of labs within Europe is contributing to the preparation of ITER scientific exploitation and operation and aspires to exploit ITER outcomes in view of DEMO. The paper provides an overview of the major progress obtained recently, carried out in the frame of the new (initiated in 2021) EUROfusion work-package called ‘ Pr eparation of I TER O peration’ (PrIO). The overview paper is directly supported by the eleven EUROfusion PrIO contributions given at the 29th Fusion Energy Conference (16–21 October 2023) London, UK [ https://www.iaea.org/events/fec2023 ]. The paper covers the following topics: (i) development and validation of tools in support to ITER operation (plasma breakdown/burn-through with evolving plasma volume, new infra-red synthetic diagnostic for off-line analysis and wall monitoring using Artificial Intelligence techniques, synthetic diagnostics development, development and exploitation of multi-machine databases); (ii) R&D for the radio-frequency ITER neutral beam sources leading to long duration of negative deuterium/hydrogen ions current extraction at ELISE and participation in the neutral beam test facility with progress on the ITER source SPIDER, and, the commissioning of the 1 MV high voltage accelerator (MITICA) with lessons learned for ITER; (iii) validation of neutronic tools for ITER nuclear operation following the second JET deuterium–tritium experimental campaigns carried out in 2021 and in 2023 (neutron streaming and shutdown dose rate calculation, water activation and activated corrosion products with advanced fluid dynamic simulation; irradiation of several materials under 14.1 MeV neutron flux etc).

Published
2024
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4. Weighted Null Space Fitting (WNSF): A Link between The Prediction Error Method and Subspace Identification

Author

He, Jiabao and Hjalmarsson, Håkan

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Subspace identification method (SIM) has been proven to be very useful and numerically robust for estimating state-space models. However, it is in general not believed to be as accurate as the prediction error method (PEM). Conversely, PEM, although more accurate, comes with non-convex optimization problems and requires local non-linear optimization algorithms and good initialization points. This contribution proposes a weighted null space fitting (WNSF) method to identify a state-space model, combining some advantages of the two mainstream approaches aforementioned. It starts with the estimate of a non-parametric model using least-squares, and then the reduction to a state-space model in the observer canonical form is a multi-step least-squares procedure where each step consists of the solution of a quadratic optimization problem. Unlike SIM, which focuses on the range space of the extended observability matrix, WNSF estimates its null space, avoiding the need for singular value decomposition. Moreover, the statistically optimal weighting for the null space fitting problem is derived. It is conjectured that WNSF is asymptotically efficient, which is supported by a simulation study.

Published
2024

5. Data-informativity conditions for structured linear systems with implications for dynamic networks

Author

Hof, Paul M. J. Van den, Shi, Shengling, Fonken, Stefanie J. M., Ramaswamy, Karthik R., Hjalmarsson, Håkan, and Dankers, Arne G.

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

When estimating models of a multivariable dynamic system, a typical condition for consistency is to require the input signals to be persistently exciting, which is guaranteed if the input spectrum is positive definite for a sufficient number of frequencies. In this paper it is investigated how such a condition can be relaxed by exploiting prior structural information on the multivariable system, such as structural zero elements in the transfer matrix or entries that are a priori known and therefore not parametrized. It is shown that in particular situations the data-informativity condition can be decomposed into different MISO (multiple input single output) situations, leading to relaxed conditions for the MIMO (multiple input multiple output) model. When estimating a single module in a linear dynamic network, the data-informativity conditions can generically be formulated as path-based conditions on the graph of the network. The new relaxed conditions for data-informativity will then also lead to relaxed path-based conditions on the network graph. Additionally the new expressions are shown to be closely related to earlier derived conditions for (generic) single module identifiability., Comment: 16 pages, 4 figures

Published
2024

6. Validation of Thin-foil proton recoil neutron spectrometer prototype for application in high yield DT fusion devices

Author

Marcinkevicius, B., Sunden, E. Andersson, Ericsson, G., and Hjalmarsson, A.

Subjects
Physics - Instrumentation and Detectors, Physics - Plasma Physics
Abstract

The use of Thin-foil Proton Recoil (TPR) spectrometers for application in neutron spectroscopy is of high relevance for future fusion devices such as ITER, where neutron spectroscopy will play a crucial role in fuel content monitoring. Existing research based on simulations of the performance of TPR spectrometers at ITER has demonstrated positive results. However, experimental validation of the simulations would greatly benefit the reliability of conclusions. In this study, we designed and constructed a prototype TPR neutron spectrometer and employed a DT neutron generator as a neutron source to perform measurements. We compared the experimental results with the simulation results using the Geant4 model of the experiment. The simulation and experimental results match within silicon detector intrinsic energy resolution. This approach ensures the experimental validation of the Geant4 based simulations of the TPR spectrometer. The experimental results demonstrated the feasibility of utilizing nuclear reactions measured in silicon detectors, specifically $^{28}$Si(n,d) and $^{28}$Si(n,$\alpha$), for energy calibration purposes. A comparison of the experiment and the simulation shows that the mean peak energy and full width at half maximum are within 150 keV. The calculated detector efficiency underestimates the experimentally determined efficiency up to 33\%. Discrepancies in the measured energy spectrum indicate the need for a more refined model and experiment control. Overall, the successful validation of the developed Geant4 simulation model against the experimentally measured energy spectra increases confidence in the applicability of such simulation results in other devices. The demonstrated energy calibration highlights new possibilities for neutron spectrometer monitoring during operation at ITER., Comment: Corrected labels for figure 3

Published
2024

7. A Weighted Least-Squares Method for Non-Asymptotic Identification of Markov Parameters from Multiple Trajectories

Author

He, Jiabao, Rojas, Cristian R., and Hjalmarsson, Håkan

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Markov parameters play a key role in system identification. There exists many algorithms where these parameters are estimated using least-squares in a first, pre-processing, step, including subspace identification and multi-step least-squares algorithms, such as Weighted Null-Space Fitting. Recently, there has been an increasing interest in non-asymptotic analysis of estimation algorithms. In this contribution we identify the Markov parameters using weighted least-squares and present non-asymptotic analysis for such estimator. To cover both stable and unstable systems, multiple trajectories are collected. We show that with the optimal weighting matrix, weighted least-squares gives a tighter error bound than ordinary least-squares for the case of non-uniformly distributed measurement errors. Moreover, as the optimal weighting matrix depends on the system's true parameters, we introduce two methods to consistently estimate the optimal weighting matrix, where the convergence rate of these estimates is also provided. Numerical experiments demonstrate improvements of weighted least-squares over ordinary least-squares in finite sample settings.

Published
2024

8. Weighted Least-Squares PARSIM

Author

He, Jiabao, Rojas, Cristian R., and Hjalmarsson, Håkan

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Subspace identification methods (SIMs) have proven very powerful for estimating linear state-space models. To overcome the deficiencies of classical SIMs, a significant number of algorithms has appeared over the last two decades, where most of them involve a common intermediate step, that is to estimate the range space of the extended observability matrix. In this contribution, an optimized version of the parallel and parsimonious SIM (PARSIM), PARSIM\textsubscript{opt}, is proposed by using weighted least-squares. It not only inherits all the benefits of PARSIM but also attains the best linear unbiased estimator for the above intermediate step. Furthermore, inspired by SIMs based on the predictor form, consistent estimates of the optimal weighting matrix for weighted least-squares are derived. Essential similarities, differences and simulated comparisons of some key SIMs related to our method are also presented.

Published
2024

9. Merging Parameter Estimation and Classification Using LASSO

Author

Wang, Le, Wang, Ying, Qiu, Yu, Li, Mian, and Hjalmarsson, Håkan

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Soft sensing is a way to indirectly obtain information of signals for which direct sensing is difficult or prohibitively expensive. It may not \textit{a priori} be evident which sensors provide useful information about the target signal, and various operating conditions often necessitate different models. In this paper, we provide a systematic method to construct a soft sensor that can deal with these issues. We propose a single estimation criterion, where the objectives are encoded in terms of model fit, model sparsity (reducing the number of different models), and model parameter coefficient sparsity (to exclude irrelevant sensors). The proposed method is tested on real-world scenarios involving prototype vehicles, demonstrating its effectiveness.

Published
2024

10. Finite Sample Analysis for a Class of Subspace Identification Methods

Author

He, Jiabao, Ziemann, Ingvar, Rojas, Cristian R., and Hjalmarsson, Håkan

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

While subspace identification methods (SIMs) are appealing due to their simple parameterization for MIMO systems and robust numerical realizations, a comprehensive statistical analysis of SIMs remains an open problem, especially in the non-asymptotic regime. In this work, we provide a finite sample analysis for a class of SIMs, which reveals that the convergence rates for estimating Markov parameters and system matrices are $\mathcal{O}(1/\sqrt{N})$, in line with classical asymptotic results. Based on the observation that the model format in classical SIMs becomes non-causal because of a projection step, we choose a parsimonious SIM that bypasses the projection step and strictly enforces a causal model to facilitate the analysis, where a bank of ARX models are estimated in parallel. Leveraging recent results from finite sample analysis of an individual ARX model, we obtain an overall error bound of an array of ARX models and proceed to derive error bounds for system matrices via robustness results for the singular value decomposition.

Published
2024

11. Regret Minimization in Scalar, Static, Non-linear Optimization Problems

Author

Wang, Ying, Pasquini, Mirko, Colin, Kévin, and Hjalmarsson, Håkan

Subjects
Mathematics - Optimization and Control, Electrical Engineering and Systems Science - Systems and Control
Abstract

We study the problem of determining an effective exploration strategy in static and non-linear optimization problems, which depend on an unknown scalar parameter to be learned from online collected noisy data. An optimal trade-off between exploration and exploitation is crucial for effective optimization under uncertainties, and to achieve this we consider a cumulative regret minimization approach over a finite horizon, with each time instant in the horizon characterized by a stochastic exploration signal, whose variance is to be designed. We aim to extend the well-established concepts of regret minimization from linear to non-linear systems, with a focus on the subsequent conceptual differences and challenges. Thus, under an idealized assumption on an appropriately defined information function associated with the excitation, we are able to show that an optimal exploration strategy is either to use no exploration at all (called lazy exploration) or adding an exploration excitation only at the first time instant of the horizon (called immediate exploration). A quadratic numerical example is presented to demonstrate the effectiveness of the proposed strategy., Comment: Extended version of a paper accepted for IEEE Conference on Decision and Control (CDC 2024)

Published
2024

12. Balancing Application Relevant and Sparsity Revealing Excitation in Input Design

Author

Parsa, Javad, Rojas, Cristian R., and Hjalmarsson, Håkan

Subjects
Electrical Engineering and Systems Science - Systems and Control, Statistics - Methodology
Abstract

The maximum absolute correlation between regressors, which is called mutual coherence, plays an essential role in sparse estimation. A regressor matrix whose columns are highly correlated may result from optimal input design, since there is no constraint on the mutual coherence, making it difficult to handle sparse estimation. This paper aims to tackle this issue for fixed denominator models, which include Laguerre, Kautz, and generalized orthonormal basis function expansion models, for example. The paper proposes an optimal input design method where the achieved Fisher information matrix is fitted to the desired Fisher matrix, together with a coordinate transformation designed to make the regressors in the transformed coordinates have low mutual coherence. The method can be used together with any sparse estimation method and any desired Fisher matrix. A numerical study shows its potential for alleviating the problem of model order selection when used in conjunction with, for example, classical methods such as the Akaike Information Criterion., Comment: Accepted to the IEEE Transactions on Automatic Control

Published
2024

13. Data-driven Bayesian estimation of Monod kinetics

Author

Colin, Kévin, Hjalmarsson, Håkan, and Chotteau, Véronique

Subjects
Statistics - Methodology, Electrical Engineering and Systems Science - Systems and Control
Abstract

In this paper, we consider the well known problem of non-linear identification of the rates of the reactions involved in cells with Monod functions. In bioprocesses, generating data is very expensive and long and so it is important to incorporate prior knowledge on the Monod kinetic parameters. Bayesian estimation is an elegant estimation technique which deals with parameter estimation with prior knowledge modeled as probability density functions. However, we might not have an accurate knowledge of the kinetic parameters such as interval bounds, especially for newly developed cell lines. Hence, we consider the case when there is no accurate prior information on the kinetic parameters except qualitative knowledge such that their non-negativity. A log-Gaussian prior distribution is considered for the parameters and the mean and variances of these distribution are tuned using the Expectation Maximization algorithm. The algorithm requires to use Metropolis Hastings within Gibbs sampling which can be computationally expensive. We develop a novel variant of the Metropolis-Hastings within Gibbs sampling sampling scheme in order to accelerate and improve on the hyperparameter tuning. We show that it can give better modeling performances on a relatively large-scale simulation example compared to available methods in the literature., Comment: Preprint submitted to Automatica

Published
2024

14. Generalized super-resolution 4D Flow MRI $\unicode{x2013}$ using ensemble learning to extend across the cardiovascular system

Author

Ericsson, Leon, Hjalmarsson, Adam, Akbar, Muhammad Usman, Ferdian, Edward, Bonini, Mia, Hardy, Brandon, Schollenberger, Jonas, Aristova, Maria, Winter, Patrick, Burris, Nicholas, Fyrdahl, Alexander, Sigfridsson, Andreas, Schnell, Susanne, Figueroa, C. Alberto, Nordsletten, David, Young, Alistair A., and Marlevi, David

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods
Abstract

4D Flow Magnetic Resonance Imaging (4D Flow MRI) is a non-invasive measurement technique capable of quantifying blood flow across the cardiovascular system. While practical use is limited by spatial resolution and image noise, incorporation of trained super-resolution (SR) networks has potential to enhance image quality post-scan. However, these efforts have predominantly been restricted to narrowly defined cardiovascular domains, with limited exploration of how SR performance extends across the cardiovascular system; a task aggravated by contrasting hemodynamic conditions apparent across the cardiovasculature. The aim of our study was to explore the generalizability of SR 4D Flow MRI using a combination of heterogeneous training sets and dedicated ensemble learning. With synthetic training data generated across three disparate domains (cardiac, aortic, cerebrovascular), varying convolutional base and ensemble learners were evaluated as a function of domain and architecture, quantifying performance on both in-silico and acquired in-vivo data from the same three domains. Results show that both bagging and stacking ensembling enhance SR performance across domains, accurately predicting high-resolution velocities from low-resolution input data in-silico. Likewise, optimized networks successfully recover native resolution velocities from downsampled in-vivo data, as well as show qualitative potential in generating denoised SR-images from clinical level input data. In conclusion, our work presents a viable approach for generalized SR 4D Flow MRI, with ensemble learning extending utility across various clinical areas of interest., Comment: 10 pages, 5 figures

Published
2023

15. Global scaling of the heat transport in fusion plasmas

Author

Sara Moradi, Johan Anderson, Michele Romanelli, Hyun-Tae Kim, JET contributors, X. Litaudon, S. Abduallev, M. Abhangi, P. Abreu, M. Afzal, K. M. Aggarwal, T. Ahlgren, J. H. Ahn, L. Aho-Mantila, N. Aiba, M. Airila, R. Albanese, V. Aldred, D. Alegre, E. Alessi, P. Aleynikov, A. Alfier, A. Alkseev, M. Allinson, B. Alper, E. Alves, G. Ambrosino, R. Ambrosino, L. Amicucci, V. Amosov, E. Andersson Sundén, M. Angelone, M. Anghel, C. Angioni, L. Appel, C. Appelbee, P. Arena, M. Ariola, H. Arnichand, S. Arshad, A. Ash, N. Ashikawa, V. Aslanyan, O. Asunta, F. Auriemma, Y. Austin, L. Avotina, M. D. Axton, C. Ayres, M. Bacharis, A. Baciero, D. Baião, S. Bailey, A. Baker, I. Balboa, M. Balden, N. Balshaw, R. Bament, J. W. Banks, Y. F. Baranov, M. A. Barnard, D. Barnes, M. Barnes, R. Barnsley, A. Baron Wiechec, L. Barrera Orte, M. Baruzzo, V. Basiuk, M. Bassan, R. Bastow, A. Batista, P. Batistoni, R. Baughan, B. Bauvir, L. Baylor, B. Bazylev, J. Beal, P. S. Beaumont, M. Beckers, B. Beckett, A. Becoulet, N. Bekris, M. Beldishevski, K. Bell, F. Belli, M. Bellinger, É. Belonohy, N. Ben Ayed, N. A. Benterman, H. Bergsȧker, J. Bernardo, M. Bernert, M. Berry, L. Bertalot, C. Besliu, M. Beurskens, B. Bieg, J. Bielecki, T. Biewer, M. Bigi, P. Bìlkovà, F. Binda, A. Bisoffi, J. P. S. Bizarro, C. Björkas, J. Blackburn, K. Blackman, T. R. Blackman, P. Blanchard, P. Blatchford, V. Bobkov, A. Boboc, G. Bodnàr, O. Bogar, I. Bolshakova, T. Bolzonella, N. Bonanomi, F. Bonelli, J. Boom, J. Booth, D. Borba, D. Borodin, I. Borodkina, A. Botrugno, C. Bottereau, P. Boulting, C. Bourdelle, M. Bowden, C. Bower, C. Bowman, T. Boyce, C. Boyd, H. J. Boyer, J. M. A. Bradshaw, V. Braic, R. Bravanec, B. Breizman, S. Bremond, P. D. Brennan, S. Breton, A. Brett, S. Brezinsek, M. D. J. Bright, M. Brix, W. Broeckx, M. Brombin, A. Brosawski, D. P. D. Brown, M. Brown, E. Bruno, J. Bucalossi, J. Buch, J. Buchanan, M. A. Buckley, R. Budny, H. Bufferand, M. Bulman, N. Bulmer, P. Bunting, P. Buratti, A. Burckhart, A. Buscarino, A. Busse, N. K. Butler, I. Bykov, J. Byrne, P. Cahyna, G. Calabrò, I. Calvo, Y. Camenen, P. Camp, D. C. Campling, J. Cane, B. Cannas, A. J. Capel, P. J. Card, A. Cardinali, P. Carman, M. Carr, D. Carralero, L. Carraro, B. B. Carvalho, I. Carvalho, P. Carvalho, F. J. Casson, C. Castaldo, N. Catarino, J. Caumont, F. Causa, R. Cavazzana, K. Cave-Ayland, M. Cavinato, M. Cecconello, S. Ceccuzzi, E. Cecil, A. Cenedese, R. Cesario, C. D. Challis, M. Chandler, D. Chandra, C. S. Chang, A. Chankin, I. T. Chapman, S. C. Chapman, M. Chernyshova, G. Chitarin, G. Ciraolo, D. Ciric, J. Citrin, F. Clairet, E. Clark, M. Clark, R. Clarkson, D. Clatworthy, C. Clements, M. Cleverly, J. P. Coad, P. A. Coates, A. Cobalt, V. Coccorese, V. Cocilovo, S. Coda, R. Coelho, J. W. Coenen, I. Coffey, L. Colas, S. Collins, D. Conka, S. Conroy, N. Conway, D. Coombs, D. Cooper, S. R. Cooper, C. Corradino, Y. Corre, G. Corrigan, S. Cortes, D. Coster, A. S. Couchman, M. P. Cox, T. Craciunescu, S. Cramp, R. Craven, F. Crisanti, G. Croci, D. Croft, K. Crombé, R. Crowe, N. Cruz, G. Cseh, A. Cufar, A. Cullen, M. Curuia, A. Czarnecka, H. Dabirikhah, P. Dalgliesh, S. Dalley, J. Dankowski, D. Darrow, O. Davies, W. Davis, C. Day, I. E. Day, M. De Bock, A. de Castro, E. de la Cal, E. de la Luna, G. De Masi, J. L. de Pablos, G. De Temmerman, G. De Tommasi, P. de Vries, K. Deakin, J. Deane, F. Degli Agostini, R. Dejarnac, E. Delabie, N. den Harder, R. O. Dendy, J. Denis, P. Denner, S. Devaux, P. Devynck, F. Di Maio, A. Di Siena, C. Di Troia, P. Dinca, R. Dinca, B. Ding, T. Dittmar, H. Doerk, R. P. Doerner, T. Donné, S. E. Dorling, S. Dormido-Canto, S. Doswon, D. Douai, P. T. Doyle, A. Drenik, P. Drewelow, P. Drews, Ph. Duckworth, R. Dumont, P. Dumortier, D. Dunai, M. Dunne, I. Duran, F. Durodié, P. Dutta, B. P. Duval, R. Dux, K. Dylst, N. Dzysiuk, P. V. Edappala, J. Edmond, A. M. Edwards, J. Edwards, Th. Eich, A. Ekedahl, R. El-Jorf, C. G. Elsmore, M. Enachescu, G. Ericsson, F. Eriksson, J. Eriksson, L. G. Eriksson, B. Esposito, S. Esquembri, H. G. Esser, D. Esteve, B. Evans, G. E. Evans, G. Evison, G. D. Ewart, D. Fagan, M. Faitsch, D. Falie, A. Fanni, A. Fasoli, J. M. Faustin, N. Fawlk, L. Fazendeiro, N. Fedorczak, R. C. Felton, K. Fenton, A. Fernades, H. Fernandes, J. Ferreira, J. A. Fessey, O. Février, O. Ficker, A. Field, S. Fietz, A. Figueiredo, J. Figueiredo, A. Fil, P. Finburg, M. Firdaouss, U. Fischer, L. Fittill, M. Fitzgerald, D. Flammini, J. Flanagan, C. Fleming, K. Flinders, N. Fonnesu, J. M. Fontdecaba, A. Formisano, L. Forsythe, L. Fortuna, E. Fortuna-Zalesna, M. Fortune, S. Foster, T. Franke, T. Franklin, M. Frasca, L. Frassinetti, M. Freisinger, R. Fresa, D. Frigione, V. Fuchs, D. Fuller, S. Futatani, J. Fyvie, K. Gàl, D. Galassi, K. Galazka, J. Galdon-Quiroga, J. Gallagher, D. Gallart, R. Galvão, X. Gao, Y. Gao, J. Garcia, A. Garcia-Carrasco, M. Garca-Munoz, J.-L. Gardarein, L. Garzotti, P. Gaudio, E. Gauthier, D. F. Gear, S. J. Gee, B. Geiger, M. Gelfusa, S. Gerasimov, G. Gervasini, M. Gethins, Z. Ghani, M. Ghate, M. Gherendi, J. C. Giacalone, L. Giacomelli, C. S. Gibson, T. Giegerich, C. Gil, L. Gil, S. Gilligan, D. Gin, E. Giovannozzi, J. B. Girardo, C. Giroud, G. Giruzzi, S. Glöggler, J. Godwin, J. Goff, P. Gohil, V. Goloborod'ko, R. Gomes, B. Goncalves, M. Goniche, M. Goodliffe, A. Goodyear, G. Gorini, M. Gosk, R. Goulding, A. Goussarov, R. Gowland, B. Graham, M. E. Graham, J. P. Graves, N. Grazier, P. Grazier, N. R. Green, H. Greuner, B. Grierson, F. S. Griph, C. Grisolia, D. Grist, M. Groth, R. Grove, C. N. Grundy, J. Grzonka, D. Guard, C. Guérard, C. Guillemaut, R. Guirlet, C. Gurl, H. H. Utoh, L. J. Hackett, S. Hacquin, A. Hagar, R. Hager, A. Hakola, M. Halitovs, S. J. Hall, S. P. Hallworth Cook, C. Hamlyn-Harris, K. Hammond, C. Harrington, J. Harrison, D. Harting, F. Hasenbeck, Y. Hatano, D. R. Hatch, T. D. V. Haupt, J. Hawes, N. C. Hawkes, J. Hawkins, P. Hawkins, P. W. Haydon, N. Hayter, S. Hazel, P. J. L. Heesterman, K. Heinola, C. Hellesen, T. Hellsten, W. Helou, O. N. Hemming, T. C. Hender, M. Henderson, S. S. Henderson, R. Henriques, D. Hepple, G. Hermon, P. Hertout, C. Hidalgo, E. G. Highcock, M. Hill, J. Hillairet, J. Hillesheim, D. Hillis, K. Hizanidis, A. Hjalmarsson, J. Hobirk, E. Hodille, C. H. A. Hogben, G. M. D. Hogeweij, A. Hollingsworth, S. Hollis, D. A. Homfray, J. Horàcek, G. Hornung, A. R. Horton, L. D. Horton, L. Horvath, S. P. Hotchin, M. R. Hough, P. J. Howarth, A. Hubbard, A. Huber, V. Huber, T. M. Huddleston, M. Hughes, G. T. A. Huijsmans, C. L. Hunter, P. Huynh, A. M. Hynes, D. Iglesias, N. Imazawa, F. Imbeaux, M. Imrìŝek, M. Incelli, P. Innocente, M. Irishkin, I. Ivanova-Stanik, S. Jachmich, A. S. Jacobsen, P. Jacquet, J. Jansons, A. Jardin, A. Järvinen, F. Jaulmes, S. Jednoróq, I. Jenkins, C. Jeong, I. Jepu, E. Joffrin, R. Johnson, T. Johnson, Jane Johnston, L. Joita, G. Jones, T. T. C. Jones, K. K. Hoshino, A. Kallenbach, K. Kamiya, J. Kaniewski, A. Kantor, A. Kappatou, J. Karhunen, D. Karkinsky, I. Karnowska, M. Kaufman, G. Kaveney, Y. Kazakov, V. Kazantzidis, D. L. Keeling, T. Keenan, J. Keep, M. Kempenaars, C. Kennedy, D. Kenny, J. Kent, O. N. Kent, E. Khilkevich, H. T. Kim, H. S. Kim, A. Kinch, C. King, D. King, R. F. King, D. J. Kinna, V. Kiptily, A. Kirk, K. Kirov, A. Kirschner, G. Kizane, C. Klepper, A. Klix, P. Knight, S. J. Knipe, S. Knott, T. Kobuchi, F. Köchl, G. Kocsis, I. Kodeli, L. Kogan, D. Kogut, S. Koivuranta, Y. Kominis, M. Köppen, B. Kos, T. Koskela, H. R. Koslowski, M. Koubiti, M. Kovari, E. Kowalska-Strzeciwilk, A. Krasilnikov, V. Krasilnikov, N. Krawczyk, M. Kresina, K. Krieger, A. Krivska, U. Kruezi, I. Ksiazek, A. Kukushkin, A. Kundu, T. Kurki-Suonio, S. Kwak, R. Kwiatkowski, O. J. Kwon, L. Laguardia, A. Lahtinen, A. Laing, N. Lam, H. T. Lambertz, C. Lane, P. T. Lang, S. Lanthaler, J. Lapins, A. Lasa, J. R. Last, E. Laszynska, R. Lawless, A. Lawson, K. D. Lawson, A. Lazaros, E. Lazzaro, J. Leddy, S. Lee, X. Lefebvre, H. J. Leggate, J. Lehmann, M. Lehnen, D. Leichtle, P. Leichuer, F. Leipold, I. Lengar, M. Lennholm, E. Lerche, A. Lescinskis, S. Lesnoj, E. Letellier, M. Leyland, W. Leysen, L. Li, Y. Liang, J. Likonen, J. Linke, Ch. Linsmeier, B. Lipschultz, G. Liu, Y. Liu, V. P. Lo Schiavo, T. Loarer, A. Loarte, R. C. Lobel, B. Lomanowski, P. J. Lomas, J. Lönnroth, J. M. López, J. López-Razola, R. Lorenzini, U. Losada, J. J. Lovell, A. B. Loving, C. Lowry, T. Luce, R. M. A. Lucock, A. Lukin, C. Luna, M. Lungaroni, C. P. Lungu, M. Lungu, A. Lunniss, I. Lupelli, A. Lyssoivan, N. Macdonald, P. Macheta, K. Maczewa, B. Magesh, P. Maget, C. Maggi, H. Maier, J. Mailloux, T. Makkonen, R. Makwana, A. Malaquias, A. Malizia, P. Manas, A. Manning, M. E. Manso, P. Mantica, M. Mantsinen, A. Manzanares, Ph. Maquet, Y. Marandet, N. Marcenko, C. Marchetto, O. Marchuk, M. Marinelli, M. Marinucci, T. Markovic, D. Marocco, L. Marot, C. A. Marren, R. Marshal, A. Martin, Y. Martin, A. Martín de Aguilera, F. J. Martínez, J. R. Martín-Solís, Y. Martynova, S. Maruyama, A. Masiello, M. Maslov, S. Matejcik, M. Mattei, G. F. Matthews, F. Maviglia, M. Mayer, M. L. Mayoral, T. May-Smith, D. Mazon, C. Mazzotta, R. McAdams, P. J. McCarthy, K. G. McClements, O. McCormack, P. A. McCullen, D. McDonald, S. McIntosh, R. McKean, J. McKehon, R. C. Meadows, A. Meakins, F. Medina, M. Medland, S. Medley, S. Meigh, A. G. Meigs, G. Meisl, S. Meitner, L. Meneses, S. Menmuir, K. Mergia, I. R. Merrigan, Ph. Mertens, S. Meshchaninov, A. Messiaen, H. Meyer, S. Mianowski, R. Michling, D. Middleton-Gear, J. Miettunen, F. Militello, E. Militello-Asp, G. Miloshevsky, F. Mink, S. Minucci, Y. Miyoshi, J. Mlynàr, D. Molina, I. Monakhov, M. Moneti, R. Mooney, S. Moradi, S. Mordijck, L. Moreira, R. Moreno, F. Moro, A. W. Morris, J. Morris, L. Moser, S. Mosher, D. Moulton, A. Murari, A. Muraro, S. Murphy, N. N. Asakura, Y. S. Na, F. Nabais, R. Naish, T. Nakano, E. Nardon, V. Naulin, M. F. F. Nave, I. Nedzelski, G. Nemtsev, F. Nespoli, A. Neto, R. Neu, V. S. Neverov, M. Newman, K. J. Nicholls, T. Nicolas, A. H. Nielsen, P. Nielsen, E. Nilsson, D. Nishijima, C. Noble, M. Nocente, D. Nodwell, K. Nordlund, H. Nordman, R. Nouailletas, I. Nunes, M. Oberkofler, T. Odupitan, M. T. Ogawa, T. O'Gorman, M. Okabayashi, R. Olney, O. Omolayo, M. O'Mullane, J. Ongena, F. Orsitto, J. Orszagh, B. I. Oswuigwe, R. Otin, A. Owen, R. Paccagnella, N. Pace, D. Pacella, L. W. Packer, A. Page, E. Pajuste, S. Palazzo, S. Pamela, S. Panja, P. Papp, R. Paprok, V. Parail, M. Park, F. Parra Diaz, M. Parsons, R. Pasqualotto, A. Patel, S. Pathak, D. Paton, H. Patten, A. Pau, E. Pawelec, C. Paz Soldan, A. Peackoc, I. J. Pearson, S.-P. Pehkonen, E. Peluso, C. Penot, A. Pereira, R. Pereira, P. P. Pereira Puglia, C. Perez von Thun, S. Peruzzo, S. Peschanyi, M. Peterka, P. Petersson, G. Petravich, A. Petre, N. Petrella, V. Petrzilka, Y. Peysson, D. Pfefferlé, V. Philipps, M. Pillon, G. Pintsuk, P. Piovesan, A. Pires dos Reis, L. Piron, A. Pironti, F. Pisano, R. Pitts, F. Pizzo, V. Plyusnin, N. Pomaro, O. G. Pompilian, P. J. Pool, S. Popovichev, M. T. Porfiri, C. Porosnicu, M. Porton, G. Possnert, S. Potzel, T. Powell, J. Pozzi, V. Prajapati, R. Prakash, G. Prestopino, D. Price, M. Price, R. Price, P. Prior, R. Proudfoot, G. Pucella, P. Puglia, M. E. Puiatti, D. Pulley, K. Purahoo, Th. Pütterich, E. Rachlew, M. Rack, R. Ragona, M. S. J. Rainford, A. Rakha, G. Ramogida, S. Ranjan, C. J. Rapson, J. J. Rasmussen, K. Rathod, G. Rattà, S. Ratynskaia, G. Ravera, C. Rayner, M. Rebai, D. Reece, A. Reed, D. Réfy, B. Regan, J. Regana, M. Reich, N. Reid, F. Reimold, M. Reinhart, M. Reinke, D. Reiser, D. Rendell, C. Reux, S. D. A. Reyes Cortes, S. Reynolds, V. Riccardo, N. Richardson, K. Riddle, D. Rigamonti, F. G. Rimini, J. Risner, M. Riva, C. Roach, R. J. Robins, S. A. Robinson, T. Robinson, D. W. Robson, R. Roccella, R. Rodionov, P. Rodrigues, J. Rodriguez, V. Rohde, F. Romanelli, M. Romanelli, S. Romanelli, J. Romazanov, S. Rowe, M. Rubel, G. Rubinacci, G. Rubino, L. Ruchko, M. Ruiz, C. Ruset, J. Rzadkiewicz, S. Saarelma, R. Sabot, E. Safi, P. Sagar, G. Saibene, F. Saint-Laurent, M. Salewski, A. Salmi, R. Salmon, F. Salzedas, D. Samaddar, U. Samm, D. Sandiford, P. Santa, M. I. K. Santala, B. Santos, A. Santucci, F. Sartori, R. Sartori, O. Sauter, R. Scannell, T. Schlummer, K. Schmid, V. Schmidt, S. Schmuck, M. Schneider, K. Schöpf, D. Schwörer, S. D. Scott, G. Sergienko, M. Sertoli, A. Shabbir, S. E. Sharapov, A. Shaw, R. Shaw, H. Sheikh, A. Shepherd, A. Shevelev, A. Shumack, G. Sias, M. Sibbald, B. Sieglin, S. Silburn, A. Silva, C. Silva, P. A. Simmons, J. Simpson, J. Simpson-Hutchinson, A. Sinha, S. K. Sipilä, A. C. C. Sips, P. Sirén, A. Sirinelli, H. Sjöstrand, M. Skiba, R. Skilton, K. Slabkowska, B. Slade, N. Smith, P. G. Smith, R. Smith, T. J. Smith, M. Smithies, L. Snoj, S. Soare, E. R. Solano, A. Somers, C. Sommariva, P. Sonato, A. Sopplesa, J. Sousa, C. Sozzi, S. Spagnolo, T. Spelzini, F. Spineanu, G. Stables, I. Stamatelatos, M. F. Stamp, P. Staniec, G. Stankunas, C. Stan-Sion, M. J. Stead, E. Stefanikova, I. Stepanov, A. V. Stephen, M. Stephen, A. Stevens, B. D. Stevens, J. Strachan, P. Strand, H. R. Strauss, P. Ström, G. Stubbs, W. Studholme, F. Subba, H. P. Summers, J. Svensson, L. Swiderski, T. Szabolics, M. Szawlowski, G. Szepesi, T. T. Suzuki, B. Tàl, T. Tala, A. R. Talbot, S. Talebzadeh, C. Taliercio, P. Tamain, C. Tame, W. Tang, M. Tardocchi, L. Taroni, D. Taylor, K. A. Taylor, D. Tegnered, G. Telesca, N. Teplova, D. Terranova, D. Testa, E. Tholerus, J. Thomas, J. D. Thomas, P. Thomas, A. Thompson, C.-A. Thompson, V. K. Thompson, L. Thorne, A. Thornton, A. S. Thrysoe, P. A. Tigwell, N. Tipton, I. Tiseanu, H. Tojo, M. Tokitani, P. Tolias, M. Tomes, P. Tonner, M. Towndrow, P. Trimble, M. Tripsky, M. Tsalas, P. Tsavalas, D. Tskhakaya jun, I. Turner, M. M. Turner, M. Turnyanskiy, G. Tvalashvili, S. G. J. Tyrrell, A. Uccello, Z. Ul-Abidin, J. Uljanovs, D. Ulyatt, H. Urano, I. Uytdenhouwen, A. P. Vadgama, D. Valcarcel, M. Valentinuzzi, M. Valisa, P. Vallejos Olivares, M. Valovic, M. Van De Mortel, D. Van Eester, W. Van Renterghem, G. J. van Rooij, J. Varje, S. Varoutis, S. Vartanian, K. Vasava, T. Vasilopoulou, J. Vega, G. Verdoolaege, R. Verhoeven, C. Verona, G. Verona Rinati, E. Veshchev, N. Vianello, J. Vicente, E. Viezzer, S. Villari, F. Villone, P. Vincenzi, I. Vinyar, B. Viola, A. Vitins, Z. Vizvary, M. Vlad, I. Voitsekhovitch, P. Vondràcek, N. Vora, T. Vu, W. W. Pires de Sa, B. Wakeling, C. W. F. Waldon, N. Walkden, M. Walker, R. Walker, M. Walsh, E. Wang, N. Wang, S. Warder, R. J. Warren, J. Waterhouse, N. W. Watkins, C. Watts, T. Wauters, A. Weckmann, J. Weiland, H. Weisen, M. Weiszflog, C. Wellstood, A. T. West, M. R. Wheatley, S. Whetham, A. M. Whitehead, B. D. Whitehead, A. M. Widdowson, S. Wiesen, J. Wilkinson, J. Williams, M. Williams, A. R. Wilson, D. J. Wilson, H. R. Wilson, J. Wilson, M. Wischmeier, G. Withenshaw, A. Withycombe, D. M. Witts, D. Wood, R. Wood, C. Woodley, S. Wray, J. Wright, J. C. Wright, J. Wu, S. Wukitch, A. Wynn, T. Xu, D. Yadikin, W. Yanling, L. Yao, V. Yavorskij, M. G. Yoo, C. Young, D. Young, I. D. Young, R. Young, J. Zacks, R. Zagorski, F. S. Zaitsev, R. Zanino, A. Zarins, K. D. Zastrow, M. Zerbini, W. Zhang, Y. Zhou, E. Zilli, V. Zoita, S. Zoletnik, and I. Zychor

Subjects
Physics, QC1-999
Abstract

A global heat flux model based on a fractional derivative of plasma pressure is proposed for the heat transport in fusion plasmas. The degree of the fractional derivative of the heat flux, α, is defined through the power balance analysis of the steady state. The model was used to obtain the experimental values of α for a large database of the Joint European Torus (JET) carbon-wall as well as ITER like-wall plasmas. The fractional degrees of the electron heat flux are found to be α

Published
2020
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17. Optimal exploration strategies for finite horizon regret minimization in some adaptive control problems

Author

Colin, Kévin, Hjalmarsson, Håkan, and Bombois, Xavier

Subjects
Mathematics - Optimization and Control, Electrical Engineering and Systems Science - Systems and Control
Abstract

In this work, we consider the problem of regret minimization in adaptive minimum variance and linear quadratic control problems. Regret minimization has been extensively studied in the literature for both types of adaptive control problems. Most of these works give results of the optimal rate of the regret in the asymptotic regime. In the minimum variance case, the optimal asymptotic rate for the regret is $\log(T)$ which can be reached without any additional external excitation. On the contrary, for most adaptive linear quadratic problems, it is necessary to add an external excitation in order to get the optimal asymptotic rate of $\sqrt{T}$. In this paper, we will actually show from an a theoretical study, as well as, in simulations that when the control horizon is pre-specified a lower regret can be obtained with either no external excitation or a new exploration type termed immediate.

Published
2022

19. DeepBayes -- an estimator for parameter estimation in stochastic nonlinear dynamical models

Author

Ghosh, Anubhab, Abdalmoaty, Mohamed, Chatterjee, Saikat, and Hjalmarsson, Håkan

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control, Mathematics - Optimization and Control
Abstract

Stochastic nonlinear dynamical systems are ubiquitous in modern, real-world applications. Yet, estimating the unknown parameters of stochastic, nonlinear dynamical models remains a challenging problem. The majority of existing methods employ maximum likelihood or Bayesian estimation. However, these methods suffer from some limitations, most notably the substantial computational time for inference coupled with limited flexibility in application. In this work, we propose DeepBayes estimators that leverage the power of deep recurrent neural networks in learning an estimator. The method consists of first training a recurrent neural network to minimize the mean-squared estimation error over a set of synthetically generated data using models drawn from the model set of interest. The a priori trained estimator can then be used directly for inference by evaluating the network with the estimation data. The deep recurrent neural network architectures can be trained offline and ensure significant time savings during inference. We experiment with two popular recurrent neural networks -- long short term memory network (LSTM) and gated recurrent unit (GRU). We demonstrate the applicability of our proposed method on different example models and perform detailed comparisons with state-of-the-art approaches. We also provide a study on a real-world nonlinear benchmark problem. The experimental evaluations show that the proposed approach is asymptotically as good as the Bayes estimator.

Published
2022

20. Professional Dilemmatic Spaces in Swedish School-Age Educare

Author

Maria Hjalmarsson, Birgitta Ljung Egeland, and Peter Carlman

Abstract

Global interest in the field of extended education has increased over the past two decades. Extended education in the context of Swedish school-age educare has a unique position in the school system due to its voluntariness and governance as well as the free time and leisure activities it offers pupils and the lack of set learning outcomes. These features create dilemmas for teachers; thus, this study aims to generate knowledge about the complex and challenging dilemmas of school-age educare teachers in their professional work. The results are derived from a thematic analysis of two sets of data: oral and written reflections from 22 school-age educare teachers. The three themes of the teachers' dilemmas identified concern compulsory school vs. SAEC, offering pupils attractive teaching methods and content, and differing experiences and perspectives among the staff. The dilemmatic spaces that are recognised actualise positions and negotiations in everyday practices in relation to the teachers' professional identities. The findings are expected to be useful as a constructive starting point for policymakers, teacher trainers, and school-age educare teachers to understand this specific educational context and the need for professional development. This study contributes to a further understanding of the multifaceted professional identities of school-age educare teachers.

Published
2023
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21. Peer Victimization among Pupils in Leisure-Time Centres: Teachers' Reflections on Their Professional Work

Author

Hjalmarsson, Maria and Odenbring, Ylva

Abstract

Research has shown that peer victimization and bullying are common phenomena among pupils in different educational institutions, yet we know little about these issues in the educational context of the leisure-time centre. This study addresses leisure-time teachers' reflections on their work regarding peer victimization in the everyday practice of Swedish leisure-time centres. Methodologically, the study is based on written reflections from about a hundred teachers who have been participating in a continuing professional course. The results indicate that leisure-time teachers hold a quite unique professional position within the school organization due to their opportunities to work with pupils in various contexts during the day and their collaborations with other staff within the school organization. Yet the results also reveal a professional culture and material context where collaborations between different professionals are quite limited. The professional culture does not always support the leisure-time centre teachers' wish to have more opportunities to meet and discuss different issues with other staff members and to create a joint platform for collaboration and understanding about victimized pupils. It is hoped that this study will give professionals and policy makers new insights into how to make the leisure-time centre a safe and secure educational setting.

Published
2023
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22. Let the Right One In: Sports Leaders' Shared Experiences of Including Refugee Girls and Boys in Sports Clubs

Author

Carlman, Peter, Hjalmarsson, Maria, and Vikström, Carina

Abstract

This study investigated how gender and sports capital are expressed in sports leaders' talk about sports for young people with a refugee background. Empirical data were derived from four focus group interviews representing 21 sports club leaders in Sweden. The leaders defined boys and girls as distinct groups but also as groups within which there are differences. Compared with the boys, the girls were presented with lesser possibilities to participate in sports. According to the leaders, the differences in the group of girls rested on that the sports culture in the girls' country of origin, which may be more or less permissive for girls to be engaged in sports, whereas differences within the group of boys were understood in terms of bodies and mentalities.

Published
2020

27. Robustness of a feedback optimization scheme with application to bioprocess manufacturing

Author

Pasquini, Mirko, Colin, Kévin, Chotteau, Véronique, and Hjalmarsson, Håkan

Subjects
Mathematics - Optimization and Control
Abstract

In this work the robustness of a feedback optimization scheme is discussed. Previously known results in literature, on the convergence to local optima of the optimization problem of interest, are extended to the case where the sensitivities of the steady-state input-output map of the plant present bounded uncertainties. The application of the scheme to a biological setting, with the goal of maximizing the concentration of products of interest in a bioreactor, under a continuous perfusion framework, is suggested and the potential of the approach is exposed by means of a simple synthetic example. This extended version contains also the Numerical data for example in "Robustness of a feedback optimization scheme with application to bioprocess manufacturing" report, for the sake of reproducibility of the results., Comment: Submitted to the 2021 60th IEEE Conference on Decision and Control (CDC). Extended version containing Numerical data for example in "Robustness of a feedback optimization scheme with application to bioprocess manufacturing"

Published
2021

28. Non-causal regularized least-squares for continuous-time system identification with band-limited input excitations

Author

González, Rodrigo A., Rojas, Cristian R., and Hjalmarsson, Håkan

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

In continuous-time system identification, the intersample behavior of the input signal is known to play a crucial role in the performance of estimation methods. One common input behavior assumption is that the spectrum of the input is band-limited. The sinc interpolation property of these input signals yields equivalent discrete-time representations that are non-causal. This observation, often overlooked in the literature, is exploited in this work to study non-parametric frequency response estimators of linear continuous-time systems. We study the properties of non-causal least-square estimators for continuous-time system identification, and propose a kernel-based non-causal regularized least-squares approach for estimating the band-limited equivalent impulse response. The proposed methods are tested via extensive numerical simulations., Comment: 6 pages, 4 figures

Published
2021

38. Insurance of Marine Autonomous Surface Ships: Risk Allocation, Seaworthiness and Technological Challenges from an Underwriter’s Perspective

Author

Varela Chouciño, Manuel, Echebarria Fernández, Jonatan, Hjalmarsson, Johanna, Abbott-Halpin, Edward, Series Editor, Aguerre, Carolina, Series Editor, Asquer, Alberto, Series Editor, Campbell-Verduyn, Malcolm, Series Editor, Maia, Maria João, Series Editor, Johansson, Tafsir Matin, editor, Fernández, Jonatan Echebarria, editor, Dalaklis, Dimitrios, editor, Pastra, Aspasia, editor, and Skinner, Jon A., editor

Published
2023
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48. Learning sparse linear dynamic networks in a hyper-parameter free setting

Author

Venkitaraman, Arun, Hjalmarsson, Håkan, and Wahlberg, Bo

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

We address the issue of estimating the topology and dynamics of sparse linear dynamic networks in a hyperparameter-free setting. We propose a method to estimate the network dynamics in a computationally efficient and parameter tuning-free iterative framework known as SPICE (Sparse Iterative Covariance Estimation). The estimated dynamics directly reveal the underlying topology. Our approach does not assume that the network is undirected and is applicable even with varying noise levels across the modules of the network. We also do not assume any explicit prior knowledge on the network dynamics. Numerical experiments with realistic dynamic networks illustrate the usefulness of our method.

Published
2019

50. Robust exploration in linear quadratic reinforcement learning

Author

Umenberger, Jack, Ferizbegovic, Mina, Schön, Thomas B., and Hjalmarsson, Håkan

Subjects
Mathematics - Optimization and Control, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

This paper concerns the problem of learning control policies for an unknown linear dynamical system to minimize a quadratic cost function. We present a method, based on convex optimization, that accomplishes this task robustly: i.e., we minimize the worst-case cost, accounting for system uncertainty given the observed data. The method balances exploitation and exploration, exciting the system in such a way so as to reduce uncertainty in the model parameters to which the worst-case cost is most sensitive. Numerical simulations and application to a hardware-in-the-loop servo-mechanism demonstrate the approach, with appreciable performance and robustness gains over alternative methods observed in both.

Published
2019

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