2-s2.0-85062568669

[vc_empty_space][vc_empty_space]

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© Published under licence by IOP Publishing Ltd.The Monte Carlo codes, EGSnrc and MCNPX, have been specifically developed to study the particles transport in linear accelerator used in radiotherapy. A simple X-ray target 6 MV photon beam geometry was chosen to highlight similarities and differences of particles transport algorithms implemented in these Monte Carlo codes. The purpose of this study was to compare the particles transport in X-ray target 6 MV photon beam using EGSnrc and MCNPX codes. This target has 0.2484 cm thickness consisting of 0.0899 cm Tungsten and 0.1575 Copper. The global cut-off energies used in the simulations for electron and photon were 500 KeV and 10 KeV, respectively. Monte Carlo simulations were performed for 6.4 MeV monoenergetic beam. The parameters used in this simulation were using the DEFAULT setting. The particles fluence, spectral distribution after target and simulation time were analysed in this simulation. The results showed that the spectrum from EGSnrc and MCNPX was not well-matched. There was under 5% difference, especially in the build-up region. Meanwhile, the EGSnrc was 2 to 3 times more efficient than MCNPX code to achieve certain statistical precision. This happened because the differences of transport algorithm and approximation in these MC codes. EGSnrc just follow photons and electrons during simulation, while MCNPX can simulate transport 34 types of particles, including neutrons. It also causes the simulation time difference between these two codes. MCNPX simulation took longer than the EGSnrc. However, in some cases, differences in results as well as simulation time between 2 codes can be ignored.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Build-up region,Default setting,Monte Carlo codes,Simulation time,Simulation took,Spectral distribution,Statistical precision,Transport algorithms[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]The authors thank Varian Medical Systems for providing technical data of linear accelerator to be modelled with Monte Carlo. This study was fully supported by Riset Kerjasama Luar Negeri Dikti 2016 (077/SP2H/PL/LT/II/2016) and Hibah Disertasi Doktor Dikti 2016.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1742-6596/1127/1/012014[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]