2D PIC-MC Simulation of Reactive Dual Magnetron Discharges on TiO2

2014 ◽  
Author(s):  
T. Melzig ◽  
M. Siemers ◽  
A. Pflug
Keyword(s):  
Mc Simulation

scholarly journals Complex response analysis of a non-smooth oscillator under harmonic and random excitations

2021 ◽  
Vol 42 (5) ◽  
pp. 641-648
Author(s):  
Shichao Ma ◽  
Xin Ning ◽  
Liang Wang ◽  
Wantao Jia ◽  
Wei Xu
Keyword(s):  
Excitation Frequency ◽  
System Stability ◽  
Response Analysis ◽  
External Excitation ◽  
Stochastic Response ◽  
Impact Oscillator ◽  
Nonlinear Parameters ◽  
Bifurcation Phenomena ◽  
Mc Simulation ◽  
Smooth System

AbstractIt is well-known that practical vibro-impact systems are often influenced by random perturbations and external excitation forces, making it challenging to carry out the research of this category of complex systems with non-smooth characteristics. To address this problem, by adequately utilizing the stochastic response analysis approach and performing the stochastic response for the considered non-smooth system with the external excitation force and white noise excitation, a modified conducting process has proposed. Taking the multiple nonlinear parameters, the non-smooth parameters, and the external excitation frequency into consideration, the steady-state stochastic P-bifurcation phenomena of an elastic impact oscillator are discussed. It can be found that the system parameters can make the system stability topology change. The effectiveness of the proposed method is verified and demonstrated by the Monte Carlo (MC) simulation. Consequently, the conclusions show that the process can be applied to stochastic non-autonomous and non-smooth systems.

Multilevel Monte Carlo by using the Halton sequence

2020 ◽  
Vol 26 (3) ◽  
pp. 193-203
Author(s):  
Shady Ahmed Nagy ◽  
Mohamed A. El-Beltagy ◽  
Mohamed Wafa
Keyword(s):  
Monte Carlo ◽  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Computational Cost ◽  
Random Numbers ◽  
Multilevel Monte Carlo ◽  
Halton Sequence ◽  
Random Generator ◽  
Mc Simulation ◽  
Multilevel Monte Carlo Method

AbstractMonte Carlo (MC) simulation depends on pseudo-random numbers. The generation of these numbers is examined in connection with the Brownian motion. We present the low discrepancy sequence known as Halton sequence that generates different stochastic samples in an equally distributed form. This will increase the convergence and accuracy using the generated different samples in the Multilevel Monte Carlo method (MLMC). We compare algorithms by using a pseudo-random generator and a random generator depending on a Halton sequence. The computational cost for different stochastic differential equations increases in a standard MC technique. It will be highly reduced using a Halton sequence, especially in multiplicative stochastic differential equations.

A Study on First Principle Calculation of Alloy Phase Diagram by Monte Carlo Simulation

1992 ◽  
Vol 291 ◽  
Author(s):  
Hideaki Sawada ◽  
Atsushi Nogami ◽  
Wataru Yamada ◽  
Tooru Matsiuniya
Keyword(s):  
Phase Diagram ◽  
Monte Carlo ◽  
Alloy Phase Diagram ◽  
Lattice Constant ◽  
Local Concentration ◽  
First Principle ◽  
Principle Calculation ◽  
First Principle Calculation ◽  
Local Lattice ◽  
Mc Simulation

ABSTRACTA method of first principle calculation of alloy phase diagram was developed by the combination of first principle energy band calculation, cluster expansion method (CEM) and Monte Carlo (MC) simulation, where the effective multi-body potential energy for the flip test in MC simulation was obtained by the decomposition of the total energy by CEM. This method was applied to Cu-Au binary system. The calculated phase diagram agreed with that of CVM by introducing the dependence of the lattice constant on the concentration of the whole system. Furthermore an attempt of introducing the effect of local lattice relaxation was performed by the consideration of the local concentration. The order-disorder transition temperature became closer to the experimental value by adjustment of the local lattice constant depending on the concentration in the local region consisted of up to the second nearest neighbors of the atom tested for flipping.

scholarly journals Markovian MC simulation of QCD evolution at NLO level with minimum k T

2009 ◽  
Vol 60 (2) ◽  
pp. 213-232
Author(s):  
P. Stokłosa ◽  
W. Płaczek ◽  
M. Skrzypek
Keyword(s):  
Mc Simulation

Statistical Approach to Radiative Transfer in the Heterogeneous Media of Thin-Wall Morphology—II: Applications

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
A. V. Gusarov
Keyword(s):  
Statistical Approach ◽  
Heterogeneous Media ◽  
Biological Tissues ◽  
Radiative Properties ◽  
Thin Wall ◽  
Porous Structures ◽  
Regular Arrangement ◽  
Mc Simulation ◽  
The Difference ◽  
Radiative Thermal Conductivity

The statistical multiphase approach (MPA) proposed in the first part of this work to evaluate radiative properties of composite materials is applied to porous structures of opaque material and biological tissues. Radiative thermal conductivity is calculated for the bundle of circular rods, packed pebble beds, and metal foams. The results generally agree with the reference calculations by other methods. The small difference can be explained by different approaches to scattering and assumptions about the temperature distribution. Attenuation of light in skin tissues is calculated by the diffusion approximation. The attenuation coefficient generally agrees with the reference Monte Carlo simulation (MC). The difference observed at certain combination of parameters can be due to the assumption of regular arrangement of vessels at the MC simulation.

scholarly journals Benchmarking of Siemens Linac in Electron Modes: 8-14 MeV Electron Beams

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
H Dowlatabadi ◽  
A A Mowlavi ◽  
M Ghorbani ◽  
S Mohammadi ◽  
F Akbari
Keyword(s):  
Monte Carlo ◽  
Radiation Treatment ◽  
Electron Beams ◽  
Dose Profile ◽  
Depth Dose ◽  
Mcnpx Code ◽  
Gamma Index ◽  
Simulation Results ◽  
Mc Simulation ◽  
Good Agreement

Introduction: Radiation therapy using electron beams is a promising method due to its physical dose distribution. Monte Carlo (MC) code is the best and most accurate technique for forespeaking the distribution of dose in radiation treatment of patients.Materials and Methods: We report an MC simulation of a linac head and depth dose on central axis, along with profile calculations. The purpose of the present research is to carefully analyze the application of MC methods for the calculation of dosimetric parameters for electron beams with energies of 8–14 MeV at a Siemens Primus linac. The principal components of the linac head were simulated using MCNPX code for different applicators. Results: The consequences of measurements and simulations revealed a good agreement. Gamma index values were below 1 for most points, for all energy values and all applicators in percent depth dose and dose profile computations. A number of states exhibited rather large gamma indices; these points were located at the tail of the percent depth dose graph; these points were less used in in radiotherapy. In the dose profile graph, gamma indices of most parts were below 1. The discrepancies between the simulation results and measurements in terms of Zmax, R90, R80 and R50 were insignificant. The results of Monte Carlo simulations showed a good agreement with the measurements. Conclusion: The software can be used for simulating electron modes of a Siemens Primus linac when direct experimental measurements are not feasible.

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