Monte Carlo Simulation of Real Dynamic Systems

2013 ◽  
pp. 109-125
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Dynamic Systems

A Partition Expansion Method for Nonlinear Response Analysis of Stochastic Dynamic Systems With Local Nonlinearity

2013 ◽  
Vol 8 (3) ◽  
Author(s):  
Changqing Bai ◽  
Hongyan Zhang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Dynamic Response ◽  
Dynamic Systems ◽  
Expansion Method ◽  
Direct Monte Carlo Simulation ◽  
Stochastic Dynamic ◽  
Integration Algorithm ◽  
Local Nonlinearity ◽  
Stochastic Dynamic Systems

This paper focuses on the problem of nonlinear dynamic response variability resulting from stochastic system properties and random loads. An efficient and accurate method, which can be employed to analyze the dynamic responses of random finite element systems with local nonlinearity, is presented in this paper. This method, dubbed as the partition expansion method, is based on the partitioned time integration algorithm in conjunction with the Neumann expansion technique within the framework of the Monte Carlo simulation. Two numerical examples involving structural and mechanical stochastic vibration problems are employed to illustrate the advantage of the proposed method with respect to accuracy and efficiency. By comparing the results obtained by the direct Monte Carlo simulation, the dynamic response statistics can be accurately determined using the proposed method with four order expansion while the computational efforts are significantly reduced. The comparison of computing time indicates that the proposed method is efficient and practical for analyzing the statistical quantities of stochastic dynamic systems with local nonlinearity.

scholarly journals simlandr: Simulation-Based Landscape Construction for Dynamical Systems

2021 ◽  
Author(s):  
Jingmeng Cui ◽  
Merlijn Olthof ◽  
Anna Lichtwarck-Aschoff ◽  
Tiejun Li ◽  
Fred Hasselman
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Dynamical Systems ◽  
Dynamic Systems ◽  
Model Simulation ◽  
Simulation Based ◽  
Generalized Potential ◽  
System States ◽  
The Stability ◽  
Potential Landscape

We present the simlandr package for R, which provides a set of tools for constructing potential landscapes for dynamic systems using Monte Carlo simulation. Potential landscapes can be used to quantify the stability of system states. While the canonical form of a potential function is defined for gradient systems, generalized potential functions can also be defined for non-gradient dynamical systems. Our method is based on the potential landscape definition by Wang, Xu, and Wang (2008), and can be used for a large variety of models. Using two multistable dynamical systems as examples, we illustrate how simlandr can be used for model simulation, landscape construction, and barrier height calculation.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

Sign in / Sign up

Export Citation Format

Share Document