ISSDE: A Monte Carlo implicit simulation code based on Stratonovich SDE approach of Coulomb collision

2021 ◽  
Author(s):  
Yifeng Zheng ◽  
Jianyuan Xiao ◽  
Yanpeng Wang ◽  
Jiangshan Zheng ◽  
Ge Zhuang
Keyword(s):  
Monte Carlo ◽  
Coulomb Collision ◽  
Simulation Code

McChasy2: New Monte Carlo RBS/C simulation code designed for use with large crystalline structures

2021 ◽  
Vol 498 ◽  
pp. 9-14
Author(s):  
Lech Nowicki ◽  
Jacek Jagielski ◽  
Cyprian Mieszczyński ◽  
Kazimierz Skrobas ◽  
Przemysław Jóźwik ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Simulation Code ◽  
Crystalline Structures

Development of multidimensional Monte Carlo simulation code for H− ion and neutral transport in H− ion sources

2002 ◽  
Vol 73 (2) ◽  
pp. 910-913 ◽  
Author(s):  
A. Hatayama ◽  
T. Sakurabayashi ◽  
Y. Ishi ◽  
K. Makino ◽  
M. Ogasawara ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Ion Sources ◽  
Simulation Code

scholarly journals A Monte-Carlo Simulation of the Behaviour of Electron Swarms in Hydrogen Using an Anisotropic Scattering Model

1978 ◽  
Vol 31 (4) ◽  
pp. 299 ◽  
Author(s):  
HA Blevin ◽  
J Fletcher ◽  
SR Hunter
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electron Transport ◽  
Anisotropic Scattering ◽  
Isotropic Scattering ◽  
Transport Parameters ◽  
Simulation Code ◽  
Scattering Model ◽  
Good Agreement

Hunter (1977) found that a Monte-Carlo simulation of electron swarms in hydrogen, based on an isotropic scattering model, produced discrepancies between the predicted and measured electron transport parameters. The present paper shows that, with an anisotropic scattering model, good agreement is obtained between the predicted and experimental data. The simulation code is used here to calculate various parameters which are not directly measurable.

Production Yield Estimation by the Metamodel Method With a Boundary-Focused Experiment Design

1997 ◽  
Author(s):  
Chinghsin Tu ◽  
Russell R. Barton
Keyword(s):  
Monte Carlo ◽  
Robust Design ◽  
Simulation Models ◽  
Experiment Design ◽  
Production Yield ◽  
Design Stage ◽  
Yield Estimation ◽  
Simulation Code ◽  
New Approach ◽  
A Priority

Abstract The need for yield estimation strategies in the design stage is a priority recognized by industry. Yield estimates can be employed to assess the manufacturability of a design, and allow for modification to produce a robust design. Therefore, low yield of products can be avoided and costs for manufacturing can be reduced. This paper presents an accurate and time-efficient yield estimation approach for use with simulation models. We use a metamodel-based method, which is time-efficient compared to crude Monte Carlo yield estimation using the original simulation code. The approach employs a boundary-focused experiment design, which overcomes the inaccuracy of yield estimates that can occur when using a metamodel method. The results of two examples demonstrate the effectiveness of this new approach.

Erratum to “Dosimetric parameters estimation using PENELOPE-Monte-Carlo simulation code: Model 6711 a 123I brachytherapy seed”

2006 ◽  
Vol 64 (2) ◽  
pp. 290
Author(s):  
Edgar A.V. Rodríguez ◽  
Elmer P.Q. Alcón ◽  
Miguel L. Rodriguez ◽  
F. Gutt ◽  
Carlos E. de Almeida
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Parameters Estimation ◽  
Simulation Code ◽  
Code Model

scholarly journals The application of proton spectrometers at the SG-III facility for ICF implosion areal density diagnostics

2015 ◽  
Vol 3 ◽  
Author(s):  
Xing Zhang ◽  
Jianhua Zheng ◽  
Ji Yan ◽  
Zhenghua Yang ◽  
Ming Su ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Charged Particle ◽  
Charged Particles ◽  
Areal Density ◽  
Primary Proton ◽  
Energy Response ◽  
Simulation Code ◽  
The Monte Carlo Method ◽  
Density Diagnostics ◽  
Semi Empirical

Charged particle diagnostics is one of the required techniques for implosion areal density diagnostics at the SG-III facility. Several proton spectrometers are under development, and some preliminary areal density diagnostics have been carried out. The response of the key detector, CR39, to charged particles was investigated in detail. A new track profile simulation code based on a semi-empirical model was developed. The energy response of the CR39 detector was calibrated with the accelerator protons and alphas from a 241Am source. A proton spectrometer based on the filtered CR39 detector was developed, and D–D primary proton measurements were implemented. A step range filter spectrometer was developed, and preliminary areal density diagnostics was carried out. A wedged range filter spectrometer array made of Si with a higher resolution was designed and developed at the SG-III facility. A particle response simulation code by the Monte Carlo method and a spectra unfolding code were developed. The capability was evaluated in detail by simulations.

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