MCNPX simulation and experimental validation of an unmanned aerial radiological system (UARS) for rapid qualitative identification of weak hotspots

J Environ Radioact. 2023 Mar:258:107105. doi: 10.1016/j.jenvrad.2022.107105. Epub 2023 Jan 2.

Abstract

Nuclear threats such as dirty bombs and illicit trafficking of radioactive sources are major concerns of humanity. Fast detection and accurate localization of radioactive material out of regulatory control (MORC) by autonomous and semi-autonomous monitoring systems like robots can help to reduce radiation exposure to the public and workers, and it will improve security and peace in the world. This study proposes an autonomous radiological monitoring system consisting of a 2-inch NaI detector coupled to a PM tube and mounted on a multi-rotor UAV to detect radioactive sources. First, an experimental scenario was modeled using the MCNPX Monte Carlo (MC) code. In this modeling, the gamma spectra in 15 detectors were recorded from the rays emitted simultaneously from the areas' sources. The total count under the spectrum was measured for each of the detectors at different heights. The experimental tests were also performed to detect the simultaneous effect of five low-level Co-60 and Cs-137 point sources on a soccer field. Next, the modeling results were compared with the experimental ones, which showed good agreement and the capability to use MC modeling to simulate different radiological scenarios. The experimental results also showed that at 50 cm, all radioactive sources were successfully detected in their actual location. By decreasing the flight height, the ability of the monitoring unmanned aerial to detect radioactive sources was increased significantly.

Keywords: Anomaly; MCNP; NaI detector; Radiological map; Radiological monitoring; UARS.

MeSH terms

  • Cesium Radioisotopes*
  • Computer Simulation
  • Humans
  • Monte Carlo Method
  • Radiation Monitoring* / methods

Substances

  • Cesium-137
  • Cesium Radioisotopes