egs++: Optimization of Simulation Transport Parameters


  • Sitti Yani Department of Physics, Faculty of Mathematics and Natural Sciences, Institut Pertanian Bogor, Bogor, 16680, Indonesia



egs , EGSnrc, Monte Carlo, Transport parameters


MC transport parameters used are common to all egs++ applications. The effect of each transport parameter need to understand to optimize the simulation process. Therefore, the purpose of this study was to investigate the efficiency of egs++ simulation for different transport parameters in water phantom. This water phantom has built using slab. Collimated source defined 100 cm above the phantom. The simulation parameters such as the efficiency, statistical uncertainty, and accuracy of selecting transport parameters such as electron and photon cut-off energies, spin effects, atomic relaxations, and bound Compton scattering was investigated. The selection of ECUT and PCUT greatly affects the simulation time. The simulation time, efficiency and energy fractions have same value for varied ECUT except for 0.521 MeV. The energy fraction have been shifted but the simulation time and efficiency were same. Turning on spin effects in this simulation increases simulation time by 25%. The simulation time increases by about 15% when relaxations are turned on. The more accurate result of deposited energy using EGSnrc algorithm is about 30% slower than the less accurate PRESTA-I algorithm. Therefore, The optimization of transport parameters is needed in the simulation of egs++ to provide the best efficiency.


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Alva-Sánchez, M., & Pianoschi, T. A. (2020). Study of the distribution of doses in tumors with hypoxia through the PENELOPE code. Radiation Physics and Chemistry.

Andreo, P. (2018). Monte Carlo simulations in radiotherapy dosimetry. Radiation Oncology, 1-15.

Arce, P., Lagares, J. I., & Aguilar-Redondo, P.-B. (2020). A proposal for a Geant4 physics list for radiotherapy optimized in physics performance and CPU time. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment.

Campos, L. T., Magalhaes, L. A., & Almeida, C. E. (2019). An Efficiency Studying of an Ion Chamber Simulation Using Variance Reduction Techniques with EGSnrc. J Biomed Phys Eng , 259-266.

Failing, T., Hartmann, G. H., Hensley, F. W., Keil, B., & Zink, K. (2022). Enhancement of the EGSnrc code egs_chamber for fast fluence calculations of charged particles. Zeitschrift für Medizinische Physik.

Jabbari, K., & Seuntjens, J. (2014). A fast Monte Carlo code for proton transport in radiation therapy based on MCNPX. Journal of Medical Physics, 156–163.

Kawrakow, I., Mainegra-Hing, E., Tessier, F., Townson, R., & Walters, B. (2019). EGSnrc C++ class library. Ottawa: National Research Council of Canada.

Kim, J.-H., Hill, R., & Kuncic, Z. (2012). An evaluation of calculation parameters in the EGSnrc/BEAMnrc Monte Carlo codes and their effect on surface dose calculation. Physics in Medicine and Biology, N267-78.

Mohammed, M., Chakir, E., Boukhal, H., Saeed, M., & Bardouni, T. E. (2016). Evaluation of variance reduction techniques in BEAMnrc Monte Carlo simulation to improve the computing efficiency. Journal of Radiation Research and Applied Sciences, 424-430.

Shanmugasundaram, S., & Chandrasekaran, S. (2018). Optimization of Variance Reduction Techniques used in EGSnrc. J Med Phys, 185-194.

Thing, R. S., & Mainegra-Hing, E. (2014). Optimizing cone beam CT scatter estimation in egs_cbct for a clinical and virtual chest phantom. Medical Physics.

Townson, R., Tessier, F., Mainegra-Hing, E., & Walters, B. (2021). Getting Started with EGSnrc. Ottawa: National Research Council of Canada.

Tuan, H. D., Tai, D. T., Oanh, L. T., & Loan, T. T. (2019). Application of variance reduction techniques in EGSnrc based. Science & Technology Development Journal, 258-263.

Yani, S., Hadijah, S., & Husin, A. D. (2022). Analisis Parameter Keluaran pada Kolom Termal Reaktor Kartini untuk Boron Neutron Capture Therapy (BNCT) dengan Software Phits. Jurnal Fisika, 55-64.

Yani, S., Tursinah, R., Rhani, M. F., Haryanto, F., & Arif, I. (2019). Comparison between EGSnrc and MCNPX for X-ray target in 6 MV photon beam. Journal of Physics: Conference Series, 012014.




How to Cite

Yani, S. . (2023). egs++: Optimization of Simulation Transport Parameters . JURNAL ILMU FISIKA | UNIVERSITAS ANDALAS, 15(1), 66–72.



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