4.6 Article

The Gamma and Neutron Sensor System for Rapid Dose Rate Mapping in the CLEANDEM Project

期刊

SENSORS
卷 23, 期 9, 页码 -

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MDPI
DOI: 10.3390/s23094210

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gamma detector; neutron detector; nuclear decommissioning; nuclear accident remediation; robotic radiological inspection

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The decommissioning of nuclear installations and possible accident remediations require human operators to physically enter potentially radiologically hostile environments. The CLEANDEM project is developing a small robotic vehicle equipped with various sensors to detect areas contaminated by radiation. This paper describes the MiniRadMeter system, a compact and low-cost sensor capable of quickly mapping γ and neutron radiation fields before human operations. The system utilizes a miniature γ sensor and a neutron detector, with front-end and data acquisition electronics based on a Raspberry Pi4 microcomputer. The article presents the system's performance and preliminary test results.
The decommissioning of nuclear installations, as well as the possible necessary accident remediations, requires the physical presence of human operators in potentially radiologically hostile environments. The number of active nuclear reactors worldwide is greater than 400, and most of them are 40 to 50 years old, thus implying that soon they will have to be dismantled. In the framework of the H2020 CLEANDEM project, a small robotic vehicle is being developed that is equipped with a series of different sensors for areas that are significantly contaminated by radiation. In this work, we describe the MiniRadMeter system, a compact low-cost sensor capable of being used to perform quick gamma and neutron radiation field mapping of environments prior to the possible start of human operations. The miniature gamma sensor is a 1 cm(3) scintillator counter with moderate spectroscopic features read out by means of a 6 x 6 mm(2) SiPM, whereas neutrons are detected by means of a silicon diode coupled to a layer of (LiF)-Li-6 and placed inside a 6 x 6 x 6 cm(3) polyethylene box. The front-end and data acquisition electronics were developed based on a Raspberry Pi4 microcomputer. In this paper, the system performance and the preliminary test results are described.

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