一种用于校准弱辐射传感器的放射性阳性样本制备方法
The set of preparation process parameters generated by Monte Carlo simulation and reverse derivation solves the problem of the disconnect between simulation parameters and process implementation in traditional methods, realizes reliable calibration and high-precision preparation of radioactive positive samples, and improves the monitoring accuracy of nuclear radiation sensors.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN CUSTOMS IND PROD SAFETY TECH CENT
- Filing Date
- 2025-11-27
- Publication Date
- 2026-07-17
AI Technical Summary
In existing technologies, there is a lack of effective correlation between the optimized parameters obtained from computer simulations and the actual sample preparation process parameters. This leads to deviations between the radiation characteristics of the prepared positive samples and the simulation expectations, affecting the calibration basis of nuclear radiation sensors and the accuracy of on-site monitoring data.
The target distribution parameters and energy spectrum parameters are obtained through Monte Carlo simulation. A set of candidate preparation process parameters is generated by reverse derivation. Combining the energy spectrum distortion threshold and the safe operating range of the process parameters, the fine energy spectrum structure data is decomposed into source term features and matrix modulation features. A matrix effect compensation evaluation index is established, and the optimal set of preparation process parameters is selected.
A closed-loop feedback mechanism from theoretical design to experimental verification was implemented, ensuring the controllability and repeatability of the radiation characteristics of radioactive positive samples and improving the monitoring accuracy of weak radiation sensors.
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