A method of determining accuracy and precision for dosimeter systems using accreditation data.
A study of the uncertainty of dosimeter results is required by the national accreditation programs for each dosimeter model for which accreditation is sought. Typically, the methods used to determine uncertainty have included the partial differentiation method described in the U.S. Guide to Uncertainty in Measurements or the use of Monte Carlo techniques and probability distribution functions to generate simulated dose results. Each of these techniques has particular strengths and should be employed when the areas of uncertainty are required to be understood in detail. However, the uncertainty of dosimeter results can also be determined using a Model II One-Way Analysis of Variance technique and accreditation testing data. The strengths of the technique include (1) the method is straightforward and the data are provided under accreditation testing and (2) the method provides additional data for the analysis of long-term uncertainty using Statistical Process Control (SPC) techniques. The use of SPC to compare variances and standard deviations over time is described well in other areas and is not discussed in detail in this paper. The application of Analysis of Variance to historic testing data indicated that the accuracy in a representative dosimetry system (Panasonic® Model UD-802) was 8.2%, 5.1%, and 4.8% and the expanded uncertainties at the 95% confidence level were 10.7%, 14.9%, and 15.2% for the Accident, Protection Level-Shallow, and Protection Level-Deep test categories in the Department of Energy Laboratory Accreditation Program, respectively. The 95% level of confidence ranges were (0.98 to 1.19), (0.90 to 1.20), and (0.90 to 1.20) for the three groupings of test categories, respectively.
National Security Technologies, LLC, Nevada Test Site, PO Box 677, M/S NTS270, Mercury, NV 89023, USA. cumminfm@nv.doe.gov
Frederick
F
Cummings
John R
JR
Flood
D000068:Accreditation / Q000379:methods*; D017408:Guidelines as Topic; D009010:Monte Carlo Method; D011336:Probability; D011874:Radiometry / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017749:Total Quality Management / Q000379:methods*; D035501:Uncertainty