Presentation Fiber-optic remote LIBS of materials in environment of high-dose radiation

大場, 弘則  ,  佐伯, 盛久  ,  田村, 浩司  ,  Taguchi, Tomitsugu  ,  Yamamoto, Shiyunya  ,  松本歩  ,  若井田育夫  ,  赤岡, 克昭

Decommissioning of TEPCO Fukushima Daiichi nuclear power plant (F1-NPP) needs information on post-accident environment inside nuclear reactor core. In the F1-NPP, molten fuel debris (mixture of melted fuel core (U), fuel cladding (Zr) and construction materials (Fe)) might be submerged in water inside the reactor core. There is not enough space for inspecting the reactor core, because many pipes for water and electric supply occupy the inside space. Moreover, a high radiation field hinders people’s access. Thus, a remote sensing technique that is available in a narrow space is crucial for the inspection of the F1-NPP.There are some probes related inspection systems to be considered to make the process faster and easier, more secure. For the internal survey of the damaged reactor core in F1-NPP, combining the imaging observation and a laser-induced breakdown spectroscopy (LIBS) analysis provides more rich information, because it is difficult to distinguish the kind of material of the debris only by imaging. Information concerning the kind of material helps us to select the cutting technique of the debris during the decommissioning process. For this purpose, we have proposed a fiber-optic probe LIBS, and confirmed that the light transmission of the employed fiber optics is not degraded by the radiation exposure in near infrared region, which is used for the laser and emission transmission. In addition to the radiation resistivity, we have demonstrated underwater LIBS using simulated debris. However, it is unknown how the LIBS emission is observed in an environment of high-dose radiation. In the present work, we investigate laser-produced plasma in the fiber-optic probe LIBS under high radiation dose rates using the 60Co gamma irradiation facility number-1 at QST Takasaki.
2 nd Asian Symposium on Laser Induced Breakdown Spectroscopy (ASLIBS2017 )

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