An algorithm for smoothing three-dimensional Monte Carlo ion implantation simulation results

2004 ◽  
Vol 66 (2-3) ◽  
pp. 219-230 ◽  
Author(s):  
Clemens Heitzinger ◽  
Andreas Hössinger ◽  
Siegfried Selberherr
Keyword(s):  
Monte Carlo ◽  
Ion Implantation ◽  
Three Dimensional ◽  
Simulation Results

Study on Grain Topology with Potts Model Monte Carlo Simulation

2014 ◽  
Vol 926-930 ◽  
pp. 1538-1541
Author(s):  
Hao Wang ◽  
Guo Quan Liu
Keyword(s):  
Experimental Data ◽  
Monte Carlo ◽  
Potts Model ◽  
Three Dimensional ◽  
Wide Range ◽  
The Mean ◽  
Simulation Results ◽  
Number Of Faces ◽  
Grain Topology ◽  
Range Of Values

Three-dimensional normal grain growth has been simulated in scale 300×300×300 using the generally accepted Potts model Monte Carlo method. The studies of the topology of grains indicate that the mean number of faces in the grain network <f>=13.91 is similar to other simulation results, but higher than most of the experimental data which containing a wide range of values, i.e., <f>=11.16~13.93. The three-dimensional AboavWeaire law and Liu-Yu law are observed to hold, but the fit coefficient is different from the theory models.

Three Dimensional Monte Carlo Simulations with Real Grain Orientations for the Role of Sub-Boundaries and Precipitates in Abnormal Grain Growth

2013 ◽  
Vol 753 ◽  
pp. 367-372
Author(s):  
Tae Wook Na ◽  
Chang Soo Park ◽  
Hyung Seok Shim ◽  
Byeong Joo Lee ◽  
Chan Hee Han ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Solid State ◽  
Monte Carlo Simulations ◽  
Grain Growth ◽  
Three Dimensional ◽  
Abnormal Grain Growth ◽  
Grain Orientations ◽  
The Matrix ◽  
Simulation Results

Three-dimensional Monte Carlo simulations with real grain orientations are performed to study the role of precipitates and sub-boundaries in the abnormal grain growth. According to the simulation results, sub-boundaries in the abnormally growing grain and precipitates in the matrix grains are necessary for the abnormal grain growth. The simulation results can be best explained by the mechanism of sub-boundary enhanced solid state wetting. The simulated microstructure is very similar to that experimentally observed.

scholarly journals KINETIC EVOLUTION OF A 3D SPHERICAL CRYSTAL WITH MOBILE PARTICLESUSING MONTE CARLO - PART II

Anales AFA ◽  
2020 ◽  
pp. 79-84
Author(s):  
C.L. Di Prinzio ◽  
P.I. Achával ◽  
D. Stoler ◽  
G. Aguirre Varela
Keyword(s):  
Grain Size ◽  
Monte Carlo ◽  
Analytical Solution ◽  
Grain Boundary ◽  
Critical Radius ◽  
Three Dimensional ◽  
Size Evolution ◽  
Computational Data ◽  
Simulation Results ◽  
Spherical Crystal

In this work, the migration of the three-dimensional (3D) spherical crystal in the presence of mobile particles using aMonte Carlo algorithm was studied. Different concentrations of particles (f) and different particles mobilities (Mp)were used. It was found that the grain size reaches a critical radius (Rc) which depends exclusively onf. This dependence can be written as:Rc~f^1/3. The dynamic equation of grain size evolution and its analytical solution were alsofound. The analytical solution successfully fits the simulation results. The particles fraction in the grain boundary wasalso found analytically and it fits with the computational data.

Monte Carlo Simulation of Optical Temperature Sensors in RTP Systems

1995 ◽  
Vol 387 ◽  
Author(s):  
J. Vernon Cole ◽  
Karson L. Knutson ◽  
Anthony T. Fiory ◽  
Klavs F. Jensen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Three Dimensional ◽  
Simulation Models ◽  
Optical Probe ◽  
Temperature Sensors ◽  
General Purpose ◽  
Participating Media ◽  
Simulation Results ◽  
Present Simulation

AbstractWe present simulation and experimental results for determining the distribution of radiation throughout an RTP system and evaluating the design of optical temperature sensors. The simulations are performed with a general purpose, three dimensional Monte Carlo method. The simulation models internal reflection, absorption, and transmission within participating media explicitly, and includes wavelength, temperature, and material dependent properties. Simulation results are compared to measurements of the lamp intensity profile within the lamphouse and at possible sensor locations. Simulations are used to examine the effect of several optical probe designs. The predicted responses of potential sensor designs resulting from these studies are presented.

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