Evaluation of virtual point detector, for HPGe spectrometers of different sizes, using Monte Carlo simulations, and artificial neural networks / Sedigheh Sina ...[et al.]

• Main Authors: Sina, Sedigheh (Author), Molaeimanesh, Zahra (Author), Karimipoorfard, Mehrnoosh (Author)
• Format: Book
• Published: UiTM Press and Research Management Centre Universiti Teknologi MARA, 2020.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/30091/1/30091.pdf; Evaluation of virtual point detector, for HPGe spectrometers of different sizes, using Monte Carlo simulations, and artificial neural networks / Sedigheh Sina ...[et al.]. (2020) Scientific Research Journal <https://ir.uitm.edu.my/view/publication/Scientific_Research_Journal/>, 17 (1). pp. 15-26. ISSN 2289-649X
• Keywords: Radiation physics (General)

The virtual point detector concept is useful in gamma-ray spectroscopy. In this study, the virtual point detector, h0, was obtained for High Purity Germanium (HPGe) detectors of different sizes using MCNP5 Monte Carlo simulations. The HPGe detectors with different radii (rd), and height (hd), having aluminum, or Carbon windows, were simulated. A point photon source emitting several gammas with specific energies was defined at a distance x of the detectors. The pulse height distribution was scored using F8 tally. Finally, the artificial neural network was used for predicting the h0 values for every value of hd, rd, and x. Because of the high simulation duration of MCNP code, a trained ANN is used to predict the value of h0 for each detector size. The results indicate that the Artificial Neural Network (ANN) can predict the virtual point detector good accuracy.