774 research outputs found
Real-time identification of the current density profile in the JET Tokamak: method and validation
International audienceThe real-time reconstruction of the plasma magnetic equilibrium in a Tokamak is a key point to access high performance regimes. Indeed, the shape of the plasma current density profile is a direct output of the reconstruction and has a leading effect for reaching a steady-state high performance regime of operation. In this paper we present the methodology followed to identify numerically the plasma current density in a Tokamak and its equilibrium. In order to meet the real-time requirements a C++ software has been developed using the combination of a finite element method, a nonlinear fixed point algorithm associated to a least square optimization procedure. The experimental measurements that enable the identification are the magnetics on the vacuum vessel, the interferometric and polarimetric measurements on several chords and the motional Stark effect. Details are given about the validation of the reconstruction on the JET tokamak, either by comparison with 'off-line' equilibrium codes or real time software computing global quantities
Reconstruction of the equilibrium of the plasma in a Tokamak and identification of the current density profile in real time
The reconstruction of the equilibrium of a plasma in a Tokamak is a free
boundary problem described by the Grad-Shafranov equation in axisymmetric
configuration. The right-hand side of this equation is a nonlinear source,
which represents the toroidal component of the plasma current density. This
paper deals with the identification of this nonlinearity source from
experimental measurements in real time. The proposed method is based on a fixed
point algorithm, a finite element resolution, a reduced basis method and a
least-square optimization formulation. This is implemented in a software called
Equinox with which several numerical experiments are conducted to explore the
identification problem. It is shown that the identification of the profile of
the averaged current density and of the safety factor as a function of the
poloidal flux is very robust
Reconstruction of the equilibrium of the plasma in a Tokamak and identification of the current density profile in real time
International audienceThe reconstruction of the equilibrium of a plasma in a Tokamak is a free boundary problem described by the Grad-Shafranov equation in axisymmetric configuration. The right-hand side of this equation is a nonlinear source, which represents the toroidal component of the plasma current density. This paper deals with the identification of this nonlinearity source from experimental measurements in real time. The proposed method is based on a fixed point algorithm, a finite element resolution, a reduced basis method and a least-square optimization formulation. This is implemented in a software called Equinox with which several numerical experiments are conducted to explore the identification problem. It is shown that the identification of the profile of the averaged current density and of the safety factor as a function of the poloidal flux is very robust
Real-Time Equilibrium Reconstruction in a Tokamak
This paper deals with the numerical reconstruction of the plasma current
density in a Tokamak and of its equilibrium. The problem consists in the
identification of a non-linear source in the 2D Grad-Shafranov equation, which
governs the axisymmetric equilibrium of a plasma in a Tokamak. The experimental
measurements that enable this identification are the magnetics on the vacuum
vessel, but also polarimetric and interferometric measures on several chords,
as well as motional Stark effect or pressure measurements. The reconstruction
can be obtained in real-time using a finite element method, a non-linear
fixed-point algorithm and a least-square optimization procedure
New applications of Equinox code for real-time plasma equilibrium and profile reconstruction for tokamaks
Recent development of real-time equilibrium code Equinox [1] using a
fixed-point algorithm [2] allow major plasma magnetic parameters to be
identified in real-time, using rigorous analytical method. The code relies on
the boundary flux code providing flux values on the first wall of vacuum
vessel. By means of least-square minimization of differences between magnetic
field obtained from previous solution and the next measurements the code
identifies the source term of the non-linear Grad-Shafranov equation [3]. The
strict use of analytical equations together with a flexible algorithm offers an
opportunity to include new measurements into stable magnetic equilibrium code
and compare the results directly between several tokamaks while maintaining the
same physical model (i.e. no iron model is necessary inside the equilibrium
code). The successful implementation of this equilibrium code for JET and Tore
Supra have been already published [1], in this paper, we show the preliminary
results of predictive runs of the Equinox code using the ITER geometry.Comment: 12th International Congress on Plasma Physics, 25-29 October 2004,
Nice (France
Developement of real time diagnostics and feedback algorithms for JET in view of the next step
Real time control of many plasma parameters will be an essential aspect in
the development of reliable high performance operation of Next Step Tokamaks.
The main prerequisites for any feedback scheme are the precise real-time
determination of the quantities to be controlled, requiring top quality and
highly reliable diagnostics, and the availability of robust control algorithms.
A new set of real time diagnostics was recently implemented on JET to prove the
feasibility of determining, with high accuracy and time resolution, the most
important plasma quantities. With regard to feedback algorithms, new
model–based controllers were developed to allow a more robust control of
several plasma parameters. Both diagnostics and algorithms were successfully
used in several experiments, ranging from H-mode plasmas to configuration with
ITBs. Since elaboration of computationally heavy measurements is often
required, significant attention was devoted to non-algorithmic methods like
Digital or Cellular Neural/Nonlinear Networks. The real time hardware and
software adopted architectures are also described with particular attention to
their relevance to ITER.Comment: 12th International Congress on Plasma Physics, 25-29 October 2004,
Nice (France
A machine-learning-based tool for last closed magnetic flux surface reconstruction on tokamak
Nuclear fusion power created by tokamak devices holds one of the most
promising ways as a sustainable source of clean energy. One main challenge
research field of tokamak is to predict the last closed magnetic flux surface
(LCFS) determined by the interaction of the actuator coils and the internal
tokamak plasma. This work requires high-dimensional, high-frequency,
high-fidelity, real-time tools, further complicated by the wide range of
actuator coils input interact with internal tokamak plasma states. In this
work, we present a new machine learning model for reconstructing the LCFS from
the Experimental Advanced Superconducting Tokamak (EAST) that learns
automatically from the experimental data of EAST. This architecture can check
the control strategy design and integrate it with the tokamak control system
for real-time magnetic prediction. In the real-time modeling test, our approach
achieves over 99% average similarity in LCFS reconstruction of the entire
discharge process. In the offline magnetic reconstruction, our approach reaches
over 93% average similarity
Development and Validation of a Tokamak Skin Effect Transformer model
A control oriented, lumped parameter model for the tokamak transformer
including the slow flux penetration in the plasma (skin effect transformer
model) is presented. The model does not require detailed or explicit
information about plasma profiles or geometry. Instead, this information is
lumped in system variables, parameters and inputs. The model has an exact
mathematical structure built from energy and flux conservation theorems,
predicting the evolution and non linear interaction of the plasma current and
internal inductance as functions of the primary coil currents, plasma
resistance, non-inductive current drive and the loop voltage at a specific
location inside the plasma (equilibrium loop voltage). Loop voltage profile in
the plasma is substituted by a three-point discretization, and ordinary
differential equations are used to predict the equilibrium loop voltage as
function of the boundary and resistive loop voltages. This provides a model for
equilibrium loop voltage evolution, which is reminiscent of the skin effect.
The order and parameters of this differential equation are determined
empirically using system identification techniques. Fast plasma current
modulation experiments with Random Binary Signals (RBS) have been conducted in
the TCV tokamak to generate the required data for the analysis. Plasma current
was modulated in Ohmic conditions between 200kA and 300kA with 30ms rise time,
several times faster than its time constant L/R\approx200ms. The model explains
the most salient features of the plasma current transients without requiring
detailed or explicit information about resistivity profiles. This proves that
lumped parameter modeling approach can be used to predict the time evolution of
bulk plasma properties such as plasma inductance or current with reasonable
accuracy; at least in Ohmic conditions without external heating and current
drive sources
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