Calculation of nuclide activity conversion factor for in-situ gamma-ray measurement

[Background]: In-situ gamma-ray measurements employ radiation detectors to measure the environmental gamma 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. [Purpose]:  This study aims to overcome the limitation of the integral method, simplify the calculation and broaden the scope of applications. [Methods]: We applied the monte carlo simulation technique to calculate the integral. First, we built the geometry of the surrounding materials in the Geant4. Then, we sampled and emitted Geantinos facing the detector from the surroundings. Afterwards, we logged the positions when the Geantinos passing the boundaries. Finally, we calculated the parameters for the integral, such as the track lengths, and got the conversion factor by calculating the average of the integral items of all particles. [Results]: We applied this method to calculate the conversion factors for the building materials of the large polyethylene shielding chamber in the second phase of the China Jinping Underground Laboratory (CJPL). The conversion factors for the 1-meter-thick polyethylene walls and an external 20 cm thick concrete support were determined, which allowed 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. [Conclusions]: We propose a novel method to calculate the conversion factor for in-situ gamma-ray measurement. This method 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. We applied this method to the calculation of the conversion factor of the 1-meter-thick polyethylene walls, the geometry of which is very complex, for the in-situ measurement at CJPL. And in this case, the computing efficiency is increased by more than 5 times.