UNCERTAINTY EVALUATION FOR MULTIDETECTOR PASSIVE DOSEMETERS USING A TWO-STAGE MEASUREMENT MODEL AND THE MONTE CARLO...

Area of Science:

• Radiation protection and dosimetry
• Metrology
• Computational physics

Background:

• Passive personal dosemeters are crucial for monitoring radiation exposure.
• Existing measurement models for dosemeters involve two stages: signal development and signal evaluation.
• Previous work established a two-stage measurement model for passive dosemeters.

Purpose of the Study:

• To propose a numerical method for evaluating standard uncertainty in passive personal dosemeter measurements.
• To extend the two-stage measurement model to multielement dosemeters with multiple outputs.
• To develop an uncertainty evaluation method that avoids mathematical approximations and inherently includes correlations.

Main Methods:

• Application of the Monte Carlo numerical method for uncertainty evaluation.
• Extension of a previously proposed two-stage measurement model for passive dosemeters.
• Modeling of multielement dosemeters with multiple outputs, such as Hp(10) and Hp(0.07).

Main Results:

• The proposed Monte Carlo method provides a robust evaluation of standard uncertainty.
• The method successfully extends to multielement dosemeters, accommodating multiple outputs.
• The approach inherently includes correlations between input quantities and between multiple outputs.

Conclusions:

• The Monte Carlo method offers an accurate and comprehensive approach to uncertainty evaluation for passive personal dosemeters.
• This method eliminates the need for mathematical approximations in uncertainty assessment.
• The technique is particularly valuable for complex dosemeters with multiple outputs, ensuring accurate correlation handling.