سازگاری مدل شبیه سازی منفعل جاری MAST برای کنترل پلاسما در زمان واقعی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|9342||2008||5 صفحه PDF||سفارش دهید|
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|شرح||تعرفه ترجمه||زمان تحویل||جمع هزینه|
|ترجمه تخصصی - سرعت عادی||هر کلمه 90 تومان||6 روز بعد از پرداخت||270,450 تومان|
|ترجمه تخصصی - سرعت فوری||هر کلمه 180 تومان||3 روز بعد از پرداخت||540,900 تومان|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Fusion Engineering and Design, Volume 83, Issues 2–3, April 2008, Pages 188–192
Successful equilibrium reconstruction on MAST depends on a reliable estimate of the passive current induced in the thick vacuum vessel (which also acts as the load assembly) and other toroidally continuous internal support structures. For the EFIT reconstruction code, a pre-processing program takes the measured plasma and PF coil current evolution and uses a sectional model of the passive structure to solve the ODEs for electromagnetic induction. The results are written to a file, which is treated by EFIT as a set of virtual measurements of the passive current in each section. However, when a real-time version of EFIT was recently installed in the MAST plasma control system, a similar function was required for real-time estimation of the instantaneous passive current. This required several adaptation steps for the induction model to reduce the computational overhead to the absolute minimum, whilst preserving accuracy of the result. These include: • conversion of the ODE to use an auxiliary variable, avoiding the need to calculate the time derivative of current; • minimise the order of the system via model reduction techniques with a state-space representation of the problem; • transformation to eigenmode form, to diagonalise the main matrix for faster computation; • discretisation of the ODE; • hand-optimisation to use vector instruction extensions in the real-time processor; • splitting the task into two parts: the time-critical feedback part, and the next cycle pre-calculation part. After these optimisations, the algorithm was successfully implemented at a cost of just 65 μs per 500 μs control cycle, with only 27 μs added to the control latency. The results show good agreement with the original off-line version. Some of these optimisations have also been used subsequently to improve the performance of the off-line version.
The main tool for plasma equilibrium reconstruction on MAST is EFIT , a free-boundary Grad Shafranov equilibrium solver. This code fits the plasma current distribution to a constrained current profile function that is consistent with the measured signals from the flux and field diagnostics, the measured coil currents and the Grad Shafranov equation. The “coil set” as configured in EFIT (see Fig. 1) actually consists of both active poloidal field coils and passive (toroidally continuous) vessel elements and support structures, but only the active currents are measured. The MAST vacuum vessel also serves as the load assembly, so it is much thicker than is needed for a mere vacuum boundary and the total-induced passive current can be of the order of 100 kA. Since this is significant enough to adversely affect the reconstruction of the plasma equilibrium, the EFIT code needs to be given an estimate of the induced passive currents and their distribution so that it can take them into account.
نتیجه گیری انگلیسی
The EFIT code on MAST needs to take account of passive currents in the thick conducting vessel and other support structures. It does so using a code that runs after the shot to solve the induction equation of the MAST circuit model. The recent implementation of rtefit, a real-time version of EFIT for real-time plasma boundary control, has required the same passive current estimation to be implemented as a real-time code. A range of optimisations as presented here have been used with success to implement a fast real-time estimator, which in turn has led to the successful implementation of real-time feedback control of the plasma edge radius as determined by rtefit. Some of the results of this optimisation have also been applied to the original code for EFIT to improve its performance.