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The application of non-parametric statistical techniques to an ALARA programme
1Department of Nuclear Engineering, Seoul National University, Republic of Korea. jhmoonsnu@hanmail.net
Radiation Protection Dosimetry
|September 27, 2001
Summary
Identifying high occupational radiation dose (ORD) processes in nuclear power plants is crucial for cost-effective reduction. A non-parametric analysis method effectively identifies repetitive high ORD processes, unlike traditional point value methods.
Area of Science:
- Nuclear Engineering
- Radiation Protection
- Data Analysis
Background:
- Cost-effective reduction of occupational radiation dose (ORD) in nuclear power plants requires identifying high-dose maintenance and repair processes.
- Traditional statistical methods like mean and median can misrepresent dose distributions and job frequencies, hindering accurate identification of repetitive high ORD processes.
Observation:
- Point value analyses (mean, median) are insufficient for characterizing repetitive high ORD processes due to limitations in showing dose distributions and job frequencies.
- A non-parametric analysis method offers a more effective alternative for identifying processes with repetitive high ORD.
Findings:
- The non-parametric analysis method was successfully applied to ORD data from maintenance and repair operations at Kori Units 3 and 4 (Pressurized Water Reactors).
- The case study demonstrated the non-parametric method's efficiency in analyzing ORD data and identifying high-dose processes.
Implications:
- This method provides a more accurate approach to understanding and managing occupational radiation dose in nuclear facilities.
- Improved identification of high ORD processes can lead to more targeted and effective radiation protection strategies and cost savings.