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Designing a muon scattering scanner for nuclear debris measurement

Haruo Miyadera, Tsukasa Sugita, Takuro Fujimaki, Yuki Nakai, Kyohei Noguchi, Yudhitya Kusumawati, Shuji Yamamoto, Souichi Ueno, Naoto Kume, Kenji Kurihara, Masaki Yoda, Christopher L. Morris, Elena Guardincerri, J. Matthew Durham, and Dan Poulson

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Abstract

Removal of fuel debris is planned to start at Unit 2 of the Fukushima Daiichi Nuclear Power Plant. During the removal, it is desirable to distinguish fuel debris from radioactive wastes and to sort the fuel debris accordingly to the amounts of nuclear material contained. Muon scattering tomography invented at Los Alamos in the early 2000s is highly sensitivity to high-atomic-number materials such as uranium. A muon scanner to sort the debris is designed and currently in production. One of the challenges is to operate the muon scanner in the presence of high $\gamma$-ray radiations from the debris: muon-event-identification electronics and a muon-tracking algorithm in the presence of high $\gamma$-ray radiations were developed.

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No data were generated in the presented research.

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Figures (9)
Fig. 1.
Fig. 1. Principle of muon scattering tomography. Location of the scatterer can be identified by extending the incoming and outgoing muon tracks towards the incident direction, and by assuming the muon experienced a single scattering at the closest distance between the incoming and outgoing trajectories.

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Fig. 2.
Fig. 2. Geometry used in MCNP simulation (left). Results of fuel-weight estimation by machine learning technique (right).

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Fig. 3.
Fig. 3. Muon scanner prototype for debris measurement.

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Fig. 4.
Fig. 4. Schematic image of drift-tube detector (left). Muon tracking using multiple drift tubes (right).

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Fig. 5.
Fig. 5. Charge-sensitive amplifier and single-output three-level discriminator circuit directly mounted on a drift tube (left). Schematic image of the single-output three-level discriminator (right). The rising edge of the signal, arrival time of the drifted electron, is obtained by fitting ${{t}_1}$ and ${{t}_2}$, and ${{t}_3}$ is used to discriminate muon signal from background noises.

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Fig. 6.
Fig. 6. Simulated amplified-pulse shape by Garfield++ and LTspice (left), and r-t curve of drift tube with non-hydrocarbon gas, ${\rm Ar}:{{\rm CO}_2}:{{\rm N}_2} = {96}:{3}:{1}$, of 1 atm (right).

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Fig. 7.
Fig. 7. FPGA trigger system diagram and timing chart.

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Fig. 8.
Fig. 8. Left: track Hough transformation (blue dashed line), ${\chi ^2}$ minimization of line fit (red solid line), and true muon track (black dashed line). Right: Hough voting histogram and position obtained by ${\chi ^2}$ minimization (red cross) and true muon track (black circle). Each drift tube is assumed to suffer 40-kHz noise, which corresponds to the $\gamma$ environment of 200 µSv/h.

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Fig. 9.
Fig. 9. Conceptual drawings of muon scattering scanner for debris measurement (left). The debris will be measured through concrete radiation shields that reduce $\gamma$ background (right).

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Tables (1)

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Table 1. Densities and Radiation Lengths of Materials Used in Nuclear Reactors Except for Aluminum and Lead, which Are Shown for Comparison

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Equations (3)

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ϑ 0 = 13.6 β c p x X 0 [ 1 + 0.038 ln ( x X 0 ) ] ≈ 14.1 β c p x X 0 ,
d r i f t l e n g t h = T R ( t i − t 0 ) ,
ρ XZ = x i cos ⁡ θ XZ + z i sin ⁡ θ ± R T ( t i − t 0 ) , ρ YZ = y j cos ⁡ θ YZ + z j sin ⁡ θ ± R T ( t j − t 0 ) ,
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