Beta-particle backscatter factors and energy-absorption scaling factors for use with dose-point kernels
| Autor: | Mangini, Colby D. |
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| Rok vydání: | 2012 |
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| Druh dokumentu: | Thesis/Dissertation |
| Popis: | 'Hot particle' skin dosimetry calculations are commonly performed using homogeneous dose-point kernels (DPK) in conjunction with scaling and backscatter models to account for non-homogeneous geometries. A new scaling model for determining the actual DPK for beta-particles transmitted by a high-Z source material has been developed. The model is based on a determination of the amount of mono-energetic electron absorption that occurs in a given source thickness through the use of EGSnrc (Electron Gamma Shower) Monte Carlo simulations. Integration over a particular beta spectrum provides the beta-particle DPK following self-absorption as a function of source thickness and radial depth in water, thereby accounting for spectral hardening that may occur in higher-Z materials. Beta spectra of varying spectral shapes and endpoint energies were used to test our model for select source materials with 7.42 < Z ��� 94. A new volumetric backscatter model has also been developed. This model corrects for beta-particle backscattering that occurs both in the source medium and in the atmosphere surrounding the source. Hot particle backscatter factors are constructed iteratively through selective integration of point-source backscatter factors over a given source geometry. Selection criteria are based on individual source-point positions within the source and determine which, if any, backscatter factors are used. The new scaling model and backscatter model were implemented into the DPK-based code VARSKIN 4 for extensive dose testing and verification. Verification results were compared to equivalent Monte Carlo simulations. The results demonstrate that significant improvements can be made to DPK-based models when dealing with high-Z volumetric sources in non-homogeneous geometries. Graduation date: 2013 |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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