Return to search

A method for predicting peak scanning detection efficiency of a cylindrical sodium iodide scintillation detector

Scanning surveys of building surfaces and land areas are performed with radiation
detection equipment to identify areas of elevated radioactivity. To quantify the
extent and magnitude of the contamination, follow-up radiation surveys and soil
sampling are usually required. The ability to accurately quantify discrete locations
or "hot particles" of contamination requires a full understanding of the scanning
detection efficiency of the instrument being used. A cylindrical sodium iodide
detector's scanning detection efficiency was examined theoretically using the
Monte Carlo N-Particle Code, version 4b, and examined experimentally using the
Marianno Research Sled located in the Department of Nuclear Engineering, Oregon
State University. A method is described for predicting instrument scanning
detection efficiency for a 1 s observation interval over a range of scanning speeds
using a series of static detection efficiency measurements. Testing of the prediction
method and accuracy of predicted values was performed by comparison to
experimentally determined values of scanning detection efficiency. Additionally,
the validity of the predicted scanning detection efficiency values was tested by
quantifying a radioactive source at a number of scanning speeds to quantitatively
determine its activity. Activity values determined by scanning the source were
compared against an activity value determined a by high purity germanium
detection system. Results indicate that the method is both easy to perform and
provides statistically accurate scanning detection efficiency values that can be
utilized for the quantification of discrete locations or "hot particles" of radioactive
contamination. / Graduation date: 2002

Identiferoai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/30993
Date12 September 2001
CreatorsDuffy, William L.
ContributorsHigley, Kathryn A.
Source SetsOregon State University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

Page generated in 0.0224 seconds