Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

Federico Felici; J. Citrin; A.A. Teplukhina; J. Redondo; C. Bourdelle; F. Imbeaux; O. Sauter; Antti Hakola; Leena Aho-Mantila; Juuso Karhunen; Aki Lahtinen; Antti Salmi; Tuomas Tala; Markus Airila; Aaro Järvinen; Seppo Koivuranta; Jari Likonen; Paula Sirén; JET Contributors; EUROfusion MST1 Team

doi:10.1088/1741-4326/aac8f0

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

Federico Felici^*
, J. Citrin
, A.A. Teplukhina
, J. Redondo
, C. Bourdelle
, F. Imbeaux
, O. Sauter
, Antti Hakola
, Leena Aho-Mantila
, Juuso Karhunen
, Aki Lahtinen
, Antti Salmi
, Tuomas Tala
, Markus Airila
, Aaro Järvinen
, Seppo Koivuranta
, Jari Likonen
, Paula Sirén
, JET Contributors
, EUROfusion MST1 Team

^*Corresponding author for this work

Eindhoven University of Technology (TU/e)
Dutch Institute for Fundamental Energy Research (DIFFER)
Ecole Polytechnique Fédérale de Lausanne (EPFL)
Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA)
Max-Planck-Institut für Plasmaphysik (IPP)
National Research Council (CNR)
Czech Academy of Sciences
Universidade de Lisboa
University of Naples Federico II
University of Cagliari
Parthenope University of Naples
National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA)
National Technical University of Athens
Laboratorio Nacional de Fusión (LNF)
University of Oxford
Culham Science Centre
European Consortium for the Development of Fusion Energy (EUROfusion)
University of Seville
Hungarian Academy of Sciences
Aalto University
University of Helsinki
Seoul National University
Institute of Plasma Physics (ASIPP CAS)
Chalmers University of Technology

Research output: Contribution to journal › Article › Scientific › peer-review

62 Citations (Scopus)

Abstract

The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of T_e, T_i and n_e have been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks.

Original language	English
Article number	096006
Journal	Nuclear Fusion
Volume	58
Issue number	9
DOIs	https://doi.org/10.1088/1741-4326/aac8f0
Publication status	Published - 3 Jul 2018
MoE publication type	A1 Journal article-refereed

Funding

The work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014–2018 under grant agreement No 633053. This work was also supported in part by the Swiss National Science Foundation.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

integrated tokamak simulation
machine learning
real-time control
tokamak profiles
tokamak transport

Access to Document

10.1088/1741-4326/aac8f0

Cite this

Felici, F., Citrin, J., Teplukhina, A. A., Redondo, J., Bourdelle, C., Imbeaux, F., Sauter, O., Hakola, A., Aho-Mantila, L., Karhunen, J., Lahtinen, A., Salmi, A., Tala, T., Airila, M., Järvinen, A., Koivuranta, S., Likonen, J., Sirén, P., JET Contributors, & EUROfusion MST1 Team (2018). Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model. Nuclear Fusion, 58(9), Article 096006. https://doi.org/10.1088/1741-4326/aac8f0

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title = "Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model",

abstract = "The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Ti and ne have been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks.",

keywords = "integrated tokamak simulation, machine learning, real-time control, tokamak profiles, tokamak transport",

author = "Federico Felici and J. Citrin and A.A. Teplukhina and J. Redondo and C. Bourdelle and F. Imbeaux and O. Sauter and H. Meyer and T. Eich and M. Beurskens and S. Coda and Antti Hakola and P. Martin and J. Adamek and M. Agostini and D. Aguiam and J. Ahn and Leena Aho-Mantila and R. Akers and R. Albanese and R. Aledda and E. Alessi and S. Allan and D. Alves and R. Ambrosino and L. Amicucci and H. Anand and G. Anastassiou and Y. Andr{\`e}be and C. Angioni and G. Apruzzese and M. Ariola and H. Arnichand and W. Arter and A. Baciero and M. Barnes and L. Barrera and R. Behn and A. Bencze and J. Bernardo and Juuso Karhunen and Aki Lahtinen and Y.Q. Liu and Antti Salmi and Tuomas Tala and Markus Airila and Aaro J{\"a}rvinen and H.T. Kim and H.S. Kim and Seppo Koivuranta and Jari Likonen and Y.Q. Liu and T. Makkonen and H. Nordman and M.I.K. Santala and Paula Sir{\'e}n and \{JET Contributors\} and \{EUROfusion MST1 Team\}",

note = "Publisher Copyright: {\textcopyright} EURATOM 2018.",

year = "2018",

month = jul,

day = "3",

doi = "10.1088/1741-4326/aac8f0",

language = "English",

volume = "58",

journal = "Nuclear Fusion",

issn = "0029-5515",

publisher = "Institute of Physics IOP",

number = "9",

}

Felici, F, Citrin, J, Teplukhina, AA, Redondo, J, Bourdelle, C, Imbeaux, F, Sauter, O, Hakola, A , Aho-Mantila, L , Karhunen, J, Lahtinen, A, Salmi, A , Tala, T , Airila, M , Järvinen, A, Koivuranta, S, Likonen, J, Sirén, P, JET Contributors & EUROfusion MST1 Team 2018, 'Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model', Nuclear Fusion, vol. 58, no. 9, 096006. https://doi.org/10.1088/1741-4326/aac8f0

TY - JOUR

T1 - Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

AU - Felici, Federico

AU - Citrin, J.

AU - Teplukhina, A.A.

AU - Redondo, J.

AU - Bourdelle, C.

AU - Imbeaux, F.

AU - Sauter, O.

AU - Meyer, H.

AU - Eich, T.

AU - Beurskens, M.

AU - Coda, S.

AU - Hakola, Antti

AU - Martin, P.

AU - Adamek, J.

AU - Agostini, M.

AU - Aguiam, D.

AU - Ahn, J.

AU - Aho-Mantila, Leena

AU - Akers, R.

AU - Albanese, R.

AU - Aledda, R.

AU - Alessi, E.

AU - Allan, S.

AU - Alves, D.

AU - Ambrosino, R.

AU - Amicucci, L.

AU - Anand, H.

AU - Anastassiou, G.

AU - Andrèbe, Y.

AU - Angioni, C.

AU - Apruzzese, G.

AU - Ariola, M.

AU - Arnichand, H.

AU - Arter, W.

AU - Baciero, A.

AU - Barnes, M.

AU - Barrera, L.

AU - Behn, R.

AU - Bencze, A.

AU - Bernardo, J.

AU - Karhunen, Juuso

AU - Lahtinen, Aki

AU - Liu, Y.Q.

AU - Salmi, Antti

AU - Tala, Tuomas

AU - Airila, Markus

AU - Järvinen, Aaro

AU - Kim, H.T.

AU - Kim, H.S.

AU - Koivuranta, Seppo

AU - Likonen, Jari

AU - Liu, Y.Q.

AU - Makkonen, T.

AU - Nordman, H.

AU - Santala, M.I.K.

AU - Sirén, Paula

AU - JET Contributors

AU - EUROfusion MST1 Team

PY - 2018/7/3

Y1 - 2018/7/3

N2 - The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Ti and ne have been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks.

AB - The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Ti and ne have been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks.

KW - integrated tokamak simulation

KW - machine learning

KW - real-time control

KW - tokamak profiles

KW - tokamak transport

UR - https://www.scopus.com/pages/publications/85051239087

U2 - 10.1088/1741-4326/aac8f0

DO - 10.1088/1741-4326/aac8f0

M3 - Article

AN - SCOPUS:85051239087

SN - 0029-5515

VL - 58

JO - Nuclear Fusion

JF - Nuclear Fusion

IS - 9

M1 - 096006

ER -

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

Abstract

Funding

UN SDGs

Keywords

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