Interpretation of time-of-flight distributions for neutral particles under pulsed laser evaporation using direct Monte Carlo simulation

2013 ◽  
Vol 139 (23) ◽  
pp. 234706 ◽  
Author(s):  
Alexey A. Morozov
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Time Of Flight ◽  
Pulsed Laser ◽  
Laser Evaporation ◽  
Direct Monte Carlo Simulation ◽  
Neutral Particles

Investigation of Neutral Particles Using High Speed Camera and Monte-Carlo Simulation in the GAMMA 10 Central-Cell

2007 ◽  
Vol 51 (2T) ◽  
pp. 82-85 ◽  
Author(s):  
Y. Nakashima ◽  
Y. Higashizono ◽  
N. Nishino ◽  
H. Kawano ◽  
M.K. Islam ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
High Speed ◽  
Central Cell ◽  
High Speed Camera ◽  
Neutral Particles

Monte Carlo simulation of the subsurface growth mode during pulsed laser deposition

2011 ◽  
Vol 110 (4) ◽  
pp. 043304 ◽  
Author(s):  
M. R. Rashidian Vaziri ◽  
F. Hajiesmaeilbaigi ◽  
M. H. Maleki
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Pulsed Laser Deposition ◽  
Pulsed Laser ◽  
Laser Deposition ◽  
Growth Mode

Variation Simulation for Deformable Sheet Metal Assemblies Using Finite Element Methods

1997 ◽  
Vol 119 (3) ◽  
pp. 368-374 ◽  
Author(s):  
S. Charles Liu ◽  
S. Jack Hu
Keyword(s):  
Monte Carlo Simulation ◽  
Finite Element ◽  
Monte Carlo ◽  
Sheet Metal ◽  
Finite Element Methods ◽  
Free Form ◽  
Direct Monte Carlo Simulation ◽  
Free Form Surfaces ◽  
Variation Simulation ◽  
Sheet Metal Assembly

Traditional variation analysis methods, such as Root Sum Square method and Monte Carlo simulation, are not applicable to sheet metal assemblies because of possible part deformation during the assembly process. This paper proposes the use of finite element methods (FEM) in developing mechanistic variation simulation models for deformable sheet metal parts with complex two or three dimensional free form surfaces. Mechanistic variation simulation provides improved analysis by combining engineering structure models and statistical analysis in predicting the assembly variation. Direct Monte Carlo simulation in FEM is very time consuming, because hundreds or thousands of FEM runs are required to obtain a realistic assembly distribution. An alternative method, based on the Method of Influence Coefficients, is developed to improve the computational efficiency, producing improvements by several orders of magnitude. Simulations from both methods yield almost identical results. An example illustrates the developed methods used for evaluating sheet metal assembly variation. The new approaches provide an improved understanding of sheet metal assembly processes.

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