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Article

Simplified, Analytically Solvable Model Problem for Non-Analog Monte Carlo Methods

by
Yiğit Çeçen
1,* and
Mehmet Tombakoğlu
2,*
1
Department of Radiation Oncology, Akdeniz University, 07058, Kampüs, Antalya, Turkey
2
Department of Nuclear Energy Engineering, Hacettepe University, 06532, Beytepe, Ankara, Turkey
*
Authors to whom correspondence should be addressed.
Math. Comput. Appl. 2014, 19(2), 134-143; https://doi.org/10.3390/mca19020134
Published: 1 August 2014

Abstract

In Monte Carlo particle transport, it is important to change the variance of calculations of relatively rare events with a technique known as non-analog Monte Carlo. In order to reduce the variance and the computation time, biasing techniques are introduced to accelerate the calculation convergence without changing the outcome. However these variance reduction techniques are often complex and can only be solved by computer codes. In this study, a simplified, analytically solvable model problem is introduced for non-analog Monte Carlo methods. A sample problem for neutrons passing through a thick shield is simulated. The drawback of this simulation is the expensive computation time and large variance for analog Monte Carlo methods. So, biasing techniques like implicit capture and splitting are introduced and the problem is solved analytically.
Keywords: non-analog Monte Carlo; variance reduction; neutron transport non-analog Monte Carlo; variance reduction; neutron transport

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MDPI and ACS Style

Çeçen, Y.; Tombakoğlu, M. Simplified, Analytically Solvable Model Problem for Non-Analog Monte Carlo Methods. Math. Comput. Appl. 2014, 19, 134-143. https://doi.org/10.3390/mca19020134

AMA Style

Çeçen Y, Tombakoğlu M. Simplified, Analytically Solvable Model Problem for Non-Analog Monte Carlo Methods. Mathematical and Computational Applications. 2014; 19(2):134-143. https://doi.org/10.3390/mca19020134

Chicago/Turabian Style

Çeçen, Yiğit, and Mehmet Tombakoğlu. 2014. "Simplified, Analytically Solvable Model Problem for Non-Analog Monte Carlo Methods" Mathematical and Computational Applications 19, no. 2: 134-143. https://doi.org/10.3390/mca19020134

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