Optimization of Monte-Carlo Simulation for ultra-low Background HPGe Detector Setup TU1 at Felsenkeller
Research output: Types of thesis › Bachelor thesis
Contributors
- Chair of Nuclear Physics
- TUD Dresden University of Technology
Abstract
This thesis aims to improve a simulation of the high-purity germanium (HPGe) detector setup "TU1" in Felsenkeller, which is a shallow underground laboratory. The natural shielding of the location provides a very low background of cosmic radiation, allowing ultra low background measurements of gamma radiation. The Simulation can be used to investigate effects taking place within the detector to further understand physical phenomena.
This thesis focuses on the measurement of radioactive nuclei to receive a energy-efficiency curve for the detector. This is used to optimize a Monte-Carlo simulation of the setup, in which the detector set up, as well as surrounding geometries are implemented, to achieve a higher accuracy of the simulation. Using measured efficiencies, an optimization via variation of parameters within the simulation is conducted. The main goal is to minimize the discrepancy between simulated and measured efficiencies by minimizing residuals. This was done by consecutive variation of individual parameters, and using values with minimal discrepancy.
Doing this, the simulation was optimized to have a discrepancy between highest and lowest residual of ±1.3% at 10 cm sample distance up to a maximum of ±2.85% at 7 cm sample distance. This translates to a reduction of discrepancy by up to 78.4% compared to the initial state of the simulation.
This thesis focuses on the measurement of radioactive nuclei to receive a energy-efficiency curve for the detector. This is used to optimize a Monte-Carlo simulation of the setup, in which the detector set up, as well as surrounding geometries are implemented, to achieve a higher accuracy of the simulation. Using measured efficiencies, an optimization via variation of parameters within the simulation is conducted. The main goal is to minimize the discrepancy between simulated and measured efficiencies by minimizing residuals. This was done by consecutive variation of individual parameters, and using values with minimal discrepancy.
Doing this, the simulation was optimized to have a discrepancy between highest and lowest residual of ±1.3% at 10 cm sample distance up to a maximum of ±2.85% at 7 cm sample distance. This translates to a reduction of discrepancy by up to 78.4% compared to the initial state of the simulation.
Details
| Original language | English |
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| Publication status | Published - 28 Aug 2023 |
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