Optimization of Variance Reduction Techniques used in EGSnrc Monte Carlo Codes

摘要: Monte Carlo (MC) simulations are often used in calculations of radiation transport to enable accurate prediction radiation-dose, even though the computation is relatively time-consuming. In a typical MC simulation, significant time allocated following non-important events. To address this issue, variance reduction techniques (VRTs) have been suggested for reducing statistical same time. Among available simulation codes, electron gamma shower (National Research Council Canada) (EGSnrc) general-purpose coupled electron-photon code that also features an even-handed, rich set VRTs. The most well-known VRTs photon splitting, Russian roulette (RR), and cross-section enhancement (XCSE) techniques. objective work was determine optimal combination increases speed efficiency without compromising its accuracy. Selection performed using EGSnrc User such as cavity egs_chamber, simulating various ion chamber geometries 6 MV beams 1.25 MeV 60Co beams. results show XCSE RR yields highest ion-chamber dose inside 30 cm × water phantom. Hence, properly selecting different VRT altering underlying physics calculation.