SUFT368: Improved HPGe Detector Precise Efficiency Calibration with Monte Carlo Simulations and Radioactive Sources
Abstract
Purpose: To obtain an improved precise gamma efficiency calibration curve of HPGe (High Purity Germanium) detector with a new comprehensive approach. Methods: Both of radioactive sources and Monte Carlo simulation (CYLTRAN) are used to determine HPGe gamma efficiency for energy range of 0–8 MeV. The HPGe is a GMX coaxial 280 cm{sup 3} Ntype 70% gamma detector. Using Momentum Achromat Recoil Spectrometer (MARS) at the K500 superconducting cyclotron of Texas A&M University, the radioactive nucleus {sup 24} Al was produced and separated. This nucleus has positron decays followed by gamma transitions up to 8 MeV from {sup 24} Mg excited states which is used to do HPGe efficiency calibration. Results: With {sup 24} Al gamma energy spectrum up to 8MeV, the efficiency for γ ray 7.07 MeV at 4.9 cm distance away from the radioactive source {sup 24} Al was obtained at a value of 0.194(4)%, by carefully considering various factors such as positron annihilation, peak summing effect, beta detector efficiency and internal conversion effect. The Monte Carlo simulation (CYLTRAN) gave a value of 0.189%, which was in agreement with the experimental measurements. Applying to different energy points, then a precise efficiency calibration curve of HPGe detector up to 7.07more »
 Authors:
 Vanderbilt University, VanderbiltIngram Cancer Center, Nashville, TN 37232 (United States)
 Publication Date:
 OSTI Identifier:
 22648966
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 60 APPLIED LIFE SCIENCES; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; ACCURACY; BETA DETECTION; CALIBRATION; COMPUTERIZED SIMULATION; EFFICIENCY; ENERGY SPECTRA; GAMMA DETECTION; GAMMA RADIATION; HIGHPURITY GE DETECTORS; MEV RANGE 0110; MONTE CARLO METHOD; POSITRONS; RADIATION DOSES; RADIATION SOURCES
Citation Formats
Zhai, Y. John. SUFT368: Improved HPGe Detector Precise Efficiency Calibration with Monte Carlo Simulations and Radioactive Sources. United States: N. p., 2016.
Web. doi:10.1118/1.4956553.
Zhai, Y. John. SUFT368: Improved HPGe Detector Precise Efficiency Calibration with Monte Carlo Simulations and Radioactive Sources. United States. doi:10.1118/1.4956553.
Zhai, Y. John. 2016.
"SUFT368: Improved HPGe Detector Precise Efficiency Calibration with Monte Carlo Simulations and Radioactive Sources". United States.
doi:10.1118/1.4956553.
@article{osti_22648966,
title = {SUFT368: Improved HPGe Detector Precise Efficiency Calibration with Monte Carlo Simulations and Radioactive Sources},
author = {Zhai, Y. John},
abstractNote = {Purpose: To obtain an improved precise gamma efficiency calibration curve of HPGe (High Purity Germanium) detector with a new comprehensive approach. Methods: Both of radioactive sources and Monte Carlo simulation (CYLTRAN) are used to determine HPGe gamma efficiency for energy range of 0–8 MeV. The HPGe is a GMX coaxial 280 cm{sup 3} Ntype 70% gamma detector. Using Momentum Achromat Recoil Spectrometer (MARS) at the K500 superconducting cyclotron of Texas A&M University, the radioactive nucleus {sup 24} Al was produced and separated. This nucleus has positron decays followed by gamma transitions up to 8 MeV from {sup 24} Mg excited states which is used to do HPGe efficiency calibration. Results: With {sup 24} Al gamma energy spectrum up to 8MeV, the efficiency for γ ray 7.07 MeV at 4.9 cm distance away from the radioactive source {sup 24} Al was obtained at a value of 0.194(4)%, by carefully considering various factors such as positron annihilation, peak summing effect, beta detector efficiency and internal conversion effect. The Monte Carlo simulation (CYLTRAN) gave a value of 0.189%, which was in agreement with the experimental measurements. Applying to different energy points, then a precise efficiency calibration curve of HPGe detector up to 7.07 MeV at 4.9 cm distance away from the source {sup 24} Al was obtained. Using the same data analysis procedure, the efficiency for the 7.07 MeV gamma ray at 15.1 cm from the source {sup 24} Al was obtained at a value of 0.0387(6)%. MC simulation got a similar value of 0.0395%. This discrepancy led us to assign an uncertainty of 3% to the efficiency at 15.1 cm up to 7.07 MeV. The MC calculations also reproduced the intensity of observed singleand doubleescape peaks, providing that the effects of positron annihilationinflight were incorporated. Conclusion: The precision improved gamma efficiency calibration curve provides more accurate radiation detection and dose calculation for cancer radiotherapy treatment.},
doi = {10.1118/1.4956553},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}

Since the seminal paper by Panagiotopoulos [Mol. Phys. 61, 813 (1997)], the Gibbs ensemble Monte Carlo (GEMC) method has been the most popular particlebased simulation approach for the computation of vapor–liquid phase equilibria. However, the validity of GEMC simulations in the nearcritical region has been questioned because rigorous finitesize scaling approaches cannot be applied to simulations with fluctuating volume. Valleau [Mol. Simul. 29, 627 (2003)] has argued that GEMC simulations would lead to a spurious overestimation of the critical temperature. More recently, Patel et al. [J. Chem. Phys. 134, 024101 (2011)] opined that the use of analytical tail corrections wouldmore »

An improved multilevel Monte Carlo method for estimating probability distribution functions in stochastic oil reservoir simulations: AN IMPROVED MLMC METHOD
We develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of largescale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of highfidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challenge in estimating CDFsmore » 
Monte Carlo simulations of timeofflight PET with doubleended readout: calibration, coincidence resolving times and statistical lower bounds
Here, this paper demonstrates through Monte Carlo simulations that a practical positron emission tomograph with (1) deep scintillators for efficient detection, (2) doubleended readout for depthofinteraction information, (3) fixedlevel analog triggering, and (4) accurate calibration and timing data corrections can achieve a coincidence resolving time (CRT) that is not far above the statistical lower bound. One Monte Carlo algorithm simulates a calibration procedure that uses data from a positron point source. Annihilation events with an interaction near the entrance surface of one scintillator are selected, and data from the two photodetectors on the other scintillator provide depthdependent timing corrections. Anothermore » 
An improved multilevel Monte Carlo method for estimating probability distribution functions in stochastic oil reservoir simulations
In this paper, we develop an improved multilevel Monte Carlo (MLMC) method for estimating cumulative distribution functions (CDFs) of a quantity of interest, coming from numerical approximation of largescale stochastic subsurface simulations. Compared with Monte Carlo (MC) methods, that require a significantly large number of highfidelity model executions to achieve a prescribed accuracy when computing statistical expectations, MLMC methods were originally proposed to significantly reduce the computational cost with the use of multifidelity approximations. The improved performance of the MLMC methods depends strongly on the decay of the variance of the integrand as the level increases. However, the main challengemore »