(IT/P1-19) Disruption scenarios, their mitigation and operation window in ITER

M. Shimada1), M. Sugihara1), H. Fujieda2), Yu. Gribov1), K. Ioki3), Y. Kawano2), R. Khayrutdinov4), V. Lukash5), J. Ohmori2)
1) ITER International Team, Naka, ITER, Japan
2) JAEA, Naka, Japan
3) ITER Internationa Team, Garching, Germany
4) TRINITI, Russia
5) Kurchatov Institute, Moscow, Russia

Abstract.  Representative disruption scenarios in ITER calculated with a numerical code, DINA, based on physics guidelines derived from experimental database analysis, are examined to check the robustness of the design of the vacuum vessel (VV) and in-vessel components, e.g. blanket modules (BM) against various EM loads. Detailed examinations of the newly available experimental data have been performed using the quench time ( Δt) between 0.8 and 0.2 of plasma current before disruption. Available data indicate that the minimum value for the quench time normalized by the poloidal cross section area (S) is Δt/S∼1 ms/m2, which predicts a full current quench time of 36 ms with a linear waveform or 16 ms of time constant for an exponential waveform in ITER. Both waveforms are used for major disruptions (MD) and up/down-ward VDEs to examine the EM load. It is confirmed that the EM load on the VV and BM are within a design target value, though the margin is not large. Massive noble gas injection is investigated to prevent reduction of the availability caused by large thermal loads during disruptions. Impurity species and its amount are specified to optimize the mitigation capability. Resulting EM loads and the response time to trigger the radiation collapse are important key features in the optimization. Regarding the EM load, the current quench time after the injection must not be too short. A disruption code based on the DINA code has been developed, in which impurity rate equations are simultaneously solved. Calculations with this code show that neon is the most effective impurity since the current quench time could be longer than those at argon injection and unmitigated disruptions by a factor of 2. Neon is also superior to argon and heavier impurities regarding the response time. A recent neural network prediction scheme has been applied and it has been found that the success rate can be significantly high (80%) with an acceptable pressure on the gas inlet valve.

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