@article{oai:repo.qst.go.jp:00048672,
 author = {尾関, 秀将 and 諏訪, 友音 and 齊藤, 徹 and 松井, 邦浩 and 礒野, 高明 and 河野, 勝己 and 高橋, 良和 and 尾関 秀将 and 諏訪 友音 and 齊藤 徹 and 松井 邦浩 and 礒野 高明 and 河野 勝己 and 高橋 良和},
 journal = {Superconductor Science and Technology},
 month = {Apr},
 note = {The influence of a fast electromagnetic perturbation, such as plasma disruption, on the ITER toroidal field (TF) coil conductor was studied. When a fast magnetic field change is superimposed, the TF conductor is inductively heated by internally generated eddy currents. To measure the inductive heating (IH) energy amount by calorimetry, an IH experiment using short TF conductor samples with length of 20 cm was performed in a liquid He bath. The sample components used were a TF conductor, TF jacket and a TF conductor cable. A 60-turn, single layer solenoid coil was installed around each sample as an IH coil. Also, the Joule heat of the IH coil was solely measured to subtract
its thermal contribution from the other samples. A 1 kHz sinusoidal AC current was applied to each IH coil, changing the current amplitude. The heat generated in the samples, including the IH coil, was eventually absorbed into the liquid He, and the liquid He was then vaporized. Thus, the heat amount was measured by a He level sensor inside a gas collection cylinder attached above the sample. The validity of the experimental results was confirmed by comparing them with computation results of the IH energy of the samples with a computation model. Also, the consumed energy was calculated from the measured waveforms of the applied AC voltage and current to the samples. As the result, the measured and calculated IH energy were found to be in good agreement. Finally, based on the results of the experiment, the minimum magnetic field strength, which triggers quench of the TF conductor by fast dumping like plasma disruption, was evaluated using estimated TF conductor minimum quench energy.},
 title = {Evaluation of inductive heating energy of ITER toroidal field conductor by calorimetry},
 volume = {30},
 year = {2017}
}