02/17/2021
By Susan Pryputniewicz

The Biomedical Engineering and Biotechnology Program invites you to attend a dissertation defense by Matthew Carey on “Dosimetric Correction Factors and Determination of Incident Neutron Energies for Tissue Equivalent Proportional Counters using Maximum Entropy Methods and Artificial Neural Networks.”

Ph.D. Candidate: Matthew Carey
Date: Wednesday, March 3, 2021
Time: 10 a.m. to 12:30 p.m.
Location: This will be a virtual defense via Zoom. Those interested in attending should contact Matthew Carey and committee chair Mark Tries at least 24 hours prior to the defense to request access to the meeting.

Committee Chair (Advisor): Mark Tries, Ph.D., Associate Professor, Department of Physics and Applied Physics, University of Massachusetts Lowell

Committee Members:

  • Erno Sajo, Ph.D., Professor, Department of Physics and Applied Physics, University of Massachusetts Lowell
  • Farhad Pourkamali Anaraki, Ph.D., Assistant Professor, Department of Computer Science, University of Massachusetts Lowell
  • Clayton French, Ph.D., Professor Emeritus, Department of Physics and Applied Physics, University of Massachusetts Lowell

Abstract:
This research relates the linear energy transfer spectrum created by neutron radiation incident upon a REM500 tissue equivalent proportional counter with fluence-based dose quantities. These relations were investigated by modeling the detector’s energy deposition response per incident neutron using MCNP6 and comparing the results using ICRP 60 based dose equivalent and newer ICRP 74/103 dose quantities. A difference was expected between the dose equivalent and dose quantities due to the smaller size of the TEPC detector walls compared to a human body; which results in a lower response due to less moderating material at lower neutron energies and a decreased secondary proton range at epi-thermal energies. Inversion of the incident neutron energy from the linear energy transfer spectrum was performed using both the maximum entropy method and an artificial neural network. To enhance the ability of the inverse methods to reconstruct the incident energy spectrum, an additional measurement was simulated using cadmium surrounding the REM500 detector. The neutron energy range for this research spans from 10−9 MeV to 20 MeV. The results reveal that the maximum entropy method with cadmium can best resolve highly thermalized spectra and both methods produce reasonable results for spectra dominated by fast neutrons. It is recommended to use both approaches to gain insight into the neutron energy distributions using the linear energy transfer data.

All interested students and faculty members are invited to attend the online defense via remote access.