Calculation of nuclide activity conversion factor for in-situ γ measurement

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BackgroundIn-situ γ measurements employ radiation detectors to quantify the environmental γ spectrum, and it is necessary to calculate the conversion factor that translates the characteristic peak count rate of the measured spectrum into the specific activity of radionuclides in surrounding materials. The calculation of the conversion factor essentially involves integrating the detection efficiency of gamma rays emitted from different spatial positions within the surrounding materials. However, numerical solutions for the integral are challenging in complex geometries, limiting the method's application.PurposeThis study aims to overcome the limitation of the integral method, simplify the calculation and broaden the scope of applications.MethodsThe Monte Carlo simulation technique was applied to calculating the integral of in-situ γ measurement. Firstly, the geometry of the surrounding materials was built in Geant4, and the emitted Geantinos facing the detector from the surroundings were sampled. Then, the positions whilst the Geantinos passed through the boundaries were logged. Subsequently, the parameters for the integral, such as the track lengths, were calculated and the conversion factor was obtained by calculating the average of the integral items of all particles. Finally, this method was applied to the conversion factor calculation for the building materials of the large polyethylene shielding chamber in the second phase of the China Jinping Underground Laboratory (CJPL).ResultsThe conversion factors for the 1 m thick polyethylene walls and an external 20 cm thick concrete support in CJPL are determined by abovementioned method and the computing efficiency is increased by more than 5 times, which allow us to assess the shielding capability of the polyethylene chamber against various nuclide backgrounds in the external concrete, providing support and reference for in-situ measurements in the second phase of CJPL.ConclusionsA novel method in this study to calculate the conversion factor for in-situ γ measurement overcomes the challenges of complex geometric integrations through random sampling and improves Monte Carlo simulation efficiency by transporting virtual particles, offering versatility in geometry and computational efficiency.

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