scholarly journals Minimizing the cost of splitting in Monte Carlo radiation transport simulation

1980 ◽  
Author(s):  
R.J. Juzaitis
2009 ◽  
Vol 28 (12) ◽  
pp. 1894-1901 ◽  
Author(s):  
A. Badal ◽  
I. Kyprianou ◽  
Diem Phuc Banh ◽  
A. Badano ◽  
J. Sempau

2011 ◽  
Author(s):  
Kevin Warren ◽  
Robert Reed ◽  
Robert Weller ◽  
Marcus Mendenhall ◽  
Brian Sierawski ◽  
...  

2010 ◽  
Vol 13 (2) ◽  
pp. 5-14
Author(s):  
Tan Thanh Nguyen ◽  
Phuong Nguyen Dang ◽  
Loan Thi Hong Truong

There are many radiation transport simulation codes using Monte Carlo method in the world nowaday. These codes have many applications such as: dose calculation, investigating radiation detection efficiency, designing radiation shielding, . . . However, these codes are too expensive or too difficult to be applied in many different specific purposes. In this work, we built a radiation transport simulation program based on Monte Carlo method using C++ programing language with the purpose of fast calculation and easy to use. The simulation results of this program show a good agreement in compared to MCNP results.


2001 ◽  
Vol 28 (12) ◽  
pp. 2497-2506 ◽  
Author(s):  
Jong Oh Kim ◽  
Jeffrey V. Siebers ◽  
Paul J. Keall ◽  
Mark R. Arnfield ◽  
Radhe Mohan

2021 ◽  
pp. 107962
Author(s):  
Julio Almansa ◽  
Francesc Salvat-Pujol ◽  
Gloria Díaz-Londoño ◽  
Artur Carnicer ◽  
Antonio M. Lallena ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2885
Author(s):  
Daniel Losada ◽  
Ameena Al-Sumaiti ◽  
Sergio Rivera

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.


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