Response Function of Collimated Detector for Non Axial Detector-Source Geometry

2013 ◽  
Vol 772 ◽  
pp. 571-578
Author(s):  
Rahadi Wirawan ◽  
M. Djamal ◽  
A. Waris ◽  
Gunawan Handayani ◽  
Hong Joo Kim
Keyword(s):  
Monte Carlo ◽  
Response Function ◽  
Gamma Ray ◽  
Geant4 Simulation ◽  
Fundamental Parameter ◽  
Response Functions ◽  
Energy Response ◽  
Simulation Code ◽  
Source Geometry ◽  
Detector Axis

Response function is a fundamental parameter for all detectors in order to analyze the energy distribution of gamma ray which undergoes scattering interaction with the material. The response functions of a 3 in. x 3 in. NaI(Tl) collimated detector for non axis detector-source geometry has been calculated using a Monte Carlo approach from GEANT4 simulation code with 0.662 MeV of mono-energetic of photon gamma ray. Collimated Pb with 4 cm thickness and 2 cm of holes diameter were employed for shielding. The source was assumed as an isotropic point source and it is placed at various positions to the detector axis. The comparison between the measured energy response functions and the simulated energy response functions after normalization were also performed in order to validate the modeling results.

scholarly journals HPGe Detector Energy Response Function Calculation Up to 400 keV Based on Monte Carlo Code

2010 ◽  
Vol 2 (3) ◽  
pp. 479 ◽  
Author(s):  
M. S. Rahman ◽  
G. Cho
Keyword(s):  
Monte Carlo ◽  
Response Function ◽  
Gamma Ray ◽  
Germanium Detector ◽  
Front Surface ◽  
Configuration Model ◽  
Monte Carlo Code ◽  
Response Functions ◽  
Energy Response ◽  
Measured Energy

A high purity germanium detector (HPGe) of crystal size of diameter 4.91 cm and length of 3.6 cm  was modeled in accordance with the Pop Top cryostat configuration (model no. GEM10P4). The energy response function was calculated in the air using Monte Carlo simulation with mono-energy g-ray photon up to 400 keV. The distance between the source and the front surface or end cap to detector was 20 cm and the source was assumed as an isotopic point source. The aluminum absorbing layers of thickness 0.127 cm was also taken into consideration in the simulation model. The input number of particles was 107 for each mono-energetic g-ray photon. The simulated energy response functions were verified with the measured energy response functions obtained using calibration sources in order to prove the accuracy of the modeling. The comparison between the measured energy response functions and the simulated energy response functions after normalization were also performed.  Keywords: HPGe; Gamma-ray spectrum; Monte Carlo. © 2010 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved. DOI: 10.3329/jsr.v2i3.4668                 J. Sci. Res. 2 (3), 479-483 (2010)  

scholarly journals Simulation code for estimating external gamma-ray doses from a radioactive plume and contaminated ground using a local-scale atmospheric dispersion model

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245932
Author(s):  
Daiki Satoh ◽  
Hiromasa Nakayama ◽  
Takuya Furuta ◽  
Tamotsu Yoshihiro ◽  
Kensaku Sakamoto
Keyword(s):  
Monte Carlo ◽  
Dose Response ◽  
Dose Distribution ◽  
Gamma Ray ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Local Scale ◽  
Response Functions ◽  
Simulation Code ◽  
Atmospheric Dispersion Model

In this study, we developed a simulation code powered by lattice dose-response functions (hereinafter SIBYL), which helps in the quick and accurate estimation of external gamma-ray doses emitted from a radioactive plume and contaminated ground. SIBYL couples with atmospheric dispersion models and calculates gamma-ray dose distributions inside a target area based on a map of activity concentrations using pre-evaluated dose-response functions. Moreover, SIBYL considers radiation shielding due to obstructions such as buildings. To examine the reliability of SIBYL, we investigated five typical cases for steady-state and unsteady-state plume dispersions by coupling the Gaussian plume model and the local-scale high-resolution atmospheric dispersion model using large eddy simulation. The results of this coupled model were compared with those of full Monte Carlo simulations using the particle and heavy-ion transport code system (PHITS). The dose-distribution maps calculated using SIBYL differed by up to 10% from those calculated using PHITS in most target locations. The exceptions were locations far from the radioactive contamination and those behind the intricate structures of building arrays. In addition, SIBYL’s computation time using 96 parallel processing elements was several tens of minutes even for the most computationally expensive tasks of this study. The computation using SIBYL was approximately 100 times faster than the same calculation using PHITS under the same computation conditions. From the results of the case studies, we concluded that SIBYL can estimate a ground-level dose-distribution map within one hour with accuracy that is comparable to that of the full Monte Carlo simulation.

Precise Monte Carlo simulation of gamma-ray response functions for an NaI(Tl) detector

2002 ◽  
Vol 57 (4) ◽  
pp. 517-524 ◽  
Author(s):  
Hu-Xia Shi ◽  
Bo-Xian Chen ◽  
Ti-Zhu Li ◽  
Di Yun
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Gamma Ray ◽  
Response Functions

scholarly journals The application of proton spectrometers at the SG-III facility for ICF implosion areal density diagnostics

2015 ◽  
Vol 3 ◽  
Author(s):  
Xing Zhang ◽  
Jianhua Zheng ◽  
Ji Yan ◽  
Zhenghua Yang ◽  
Ming Su ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Charged Particle ◽  
Charged Particles ◽  
Areal Density ◽  
Primary Proton ◽  
Energy Response ◽  
Simulation Code ◽  
The Monte Carlo Method ◽  
Density Diagnostics ◽  
Semi Empirical

Charged particle diagnostics is one of the required techniques for implosion areal density diagnostics at the SG-III facility. Several proton spectrometers are under development, and some preliminary areal density diagnostics have been carried out. The response of the key detector, CR39, to charged particles was investigated in detail. A new track profile simulation code based on a semi-empirical model was developed. The energy response of the CR39 detector was calibrated with the accelerator protons and alphas from a 241Am source. A proton spectrometer based on the filtered CR39 detector was developed, and D–D primary proton measurements were implemented. A step range filter spectrometer was developed, and preliminary areal density diagnostics was carried out. A wedged range filter spectrometer array made of Si with a higher resolution was designed and developed at the SG-III facility. A particle response simulation code by the Monte Carlo method and a spectra unfolding code were developed. The capability was evaluated in detail by simulations.

ENERGY ESTIMATION OF ULTRA-HIGH ENERGY COSMIC RAY PHOTONS BY MONTE CARLO SIMULATIONS OF EXTENSIVE AIR SHOWERS

2010 ◽  
Vol 25 (20) ◽  
pp. 3953-3964
Author(s):  
A. GERANIOS ◽  
D. KOUTSOKOSTA ◽  
O. MALANDRAKI ◽  
H. ROSAKI-MAVROULI
Keyword(s):  
Monte Carlo ◽  
Gamma Ray ◽  
Cosmic Ray ◽  
High Energy ◽  
Extensive Air Showers ◽  
Ultra High Energy ◽  
Air Showers ◽  
Simulation Code ◽  
Energy Estimation ◽  
High Energy Cosmic Rays

Ultra-High Energy Cosmic Rays (UHECR) (E ≥ 5 × 1019 eV ) are detected through Extensive Air Showers that are created when a primary cosmic ray particle interacts with the atmosphere of the Earth. The energy of the primary particle can be estimated experimentally based on simulations. In this paper, we attempt to estimate the energy of UHECR gamma ray photons by applying a Monte Carlo simulation code and we compare the results with the ones derived in our previous papers for hadron initiated showers. The scenario of simulations is adapted to the P. Auger Observatory site.

scholarly journals NEUTRON RESPONSE FUNCTION OF BONNER SPHERE SPECTROMETER WITH 6LiI(Eu) DETECTOR

2017 ◽  
Vol 20 (2) ◽  
pp. 65 ◽  
Author(s):  
Rasito Tursinah ◽  
Bunawas Bunawas ◽  
Jungho Kim
Keyword(s):  
Monte Carlo ◽  
Response Function ◽  
Neutron Fluence ◽  
Detector Response ◽  
Response Functions ◽  
Neutron Spectra ◽  
Mcnpx Code ◽  
Bonner Sphere ◽  
Bonner Sphere Spectrometer

Neutron Response Function of Bonner Sphere Spectrometer With 6LiI(Eu) Detector. The detector response function was needed to measure the neutron fluence based on the count rates from Bonner Sphere Spectrometer (BSS). The determination of response function of a BSS with 6LiI(Eu) detector has been performed using Monte Carlo MCNPX code. This calculation was performed for BSS using scintillation detector of 4 mm × 4 mm 6LiI(Eu) which is placed at the center of a set of polyethylene spheres i.e bare, 2", 3", 5", 8", 10", and 12" diameters. The BSS response functions were obtained for neutron energy of 1x10-9 MeV - 1x102  MeV in 111 energy bins and each value has an uncertainty less or equal to 2 %. The response function were compared with two response functions reported in the literature i.e IAEA document in Technical Reports Series 403 (TRS-403) and the calculation from Vega-Carrillo, et al. Also validated with measurement 252Cf neutron spectra, that shown the simulated BSS spectra were quite close to the experimental measured with a differrence of 3%.

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