scholarly journals Monte Carlo simulation of coherently scattered photons based on the inverse-sampling technique

2020 ◽  
Vol 76 (1) ◽  
pp. 70-78
Author(s):  
Wazir Muhammad ◽  
Ying Liang ◽  
Gregory R. Hart ◽  
Bradley J. Nartowt ◽  
Jun Deng
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Computational Efficiency ◽  
Rayleigh Scattering ◽  
Form Factors ◽  
Sampling Technique ◽  
Anomalous Scattering ◽  
Inverse Sampling ◽  
Scattering Model

The acceptance–rejection technique has been widely used in several Monte Carlo simulation packages for Rayleigh scattering of photons. However, the models implemented in these packages might fail to reproduce the corresponding experimental and theoretical results. The discrepancy is attributed to the fact that all current simulations implement an elastic scattering model for the angular distribution of photons without considering anomalous scattering effects. In this study, a novel Rayleigh scattering model using anomalous scattering factors based on the inverse-sampling technique is presented. Its performance was evaluated against other simulation algorithms in terms of simulation accuracy and computational efficiency. The computational efficiency was tested with a general-purpose Monte Carlo package named Particle Transport in Media (PTM). The evaluation showed that a Monte Carlo model using both atomic form factors and anomalous scattering factors for the angular distribution of photons (instead of the atomic form factors alone) produced Rayleigh scattering results in closer agreement with experimental data. The comparison and evaluation confirmed that the inverse-sampling technique using atomic form factors and anomalous scattering factors exhibited improved computational efficiency and performed the best in reproducing experimental measurements and related scattering matrix calculations. Furthermore, using this model to sample coherent scattering can provide scientific insight for complex systems.

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.

Reliability Assessment of Power System Using Importance Sampling Technique Based on Layer Optimization Simulation

2011 ◽  
Vol 88-89 ◽  
pp. 554-558 ◽  
Author(s):  
Bin Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power System ◽  
Importance Sampling ◽  
System Reliability ◽  
Sampling Method ◽  
Sampling Technique ◽  
Test System ◽  
Importance Sampling Method ◽  
Importance Sampling Technique

An improved importance sampling method with layer simulation optimization is presented in this paper. Through the solution sequence of the components’ optimum biased factors according to their importance degree to system reliability, the presented technique can further accelerate the convergence speed of the Monte-Carlo simulation. The idea is that the multivariate distribution’ optimization of components in power system is transferred to many steps’ optimization based on importance sampling method with different optimum biased factors. The practice is that the components are layered according to their importance degree to the system reliability before the Monte-Carlo simulation, the more forward, the more important, and the optimum biased factors of components in the latest layer is searched while the importance sampling is carried out until the demanded accuracy is reached. The validity of the presented is verified using the IEEE-RTS79 test system.

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.

scholarly journals ELECTROMAGNETIC SCATTERING MODEL FOR RICE CANOPY BASED ON MONTE CARLO SIMULATION

2005 ◽  
Vol 52 ◽  
pp. 153-171 ◽  
Author(s):  
Li-Fang Wang ◽  
Jin Au Kong ◽  
K. H. Ding ◽  
T. Le Toan ◽  
F. Ribbes ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electromagnetic Scattering ◽  
Scattering Model

An Importance Sampling Approach for Time-Dependent Reliability

2011 ◽  
Author(s):  
Amandeep Singh ◽  
Zissimos P. Mourelatos ◽  
Efstratios Nikolaidis
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Random Process ◽  
Importance Sampling ◽  
Sampling Technique ◽  
Process Time ◽  
Cumulative Probability ◽  
Repairable Systems ◽  
Importance Sampling Method ◽  
True Value

Reliability is an important engineering requirement for consistently delivering acceptable product performance through time. The reliability usually degrades with time increasing the lifecycle cost due to potential warranty costs, repairs and loss of market share. Reliability is the probability that the system will perform its intended function successfully for a specified time. In this article, we consider the first-passage reliability which accounts for the first time failure of non-repairable systems. Methods are available which provide an upper bound to the true reliability which may overestimate the true value considerably. The traditional Monte-Carlo simulation is accurate but computationally expensive. A computationally efficient importance sampling technique is presented to calculate the cumulative probability of failure for random dynamic systems excited by a stationary input random process. Time series modeling is used to characterize the input random process. A detailed example demonstrates the accuracy and efficiency of the proposed importance sampling method over the traditional Monte Carlo simulation.

Angular distribution of optical photons from β decay of oriented nuclei

1994 ◽  
Vol 72 (5-6) ◽  
pp. 210-214 ◽  
Author(s):  
A. M. Al-Harkan
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Electron Scattering ◽  
Pure Water ◽  
Β Decay ◽  
Secondary Electrons ◽  
Transparent Media ◽  
Optical Photons ◽  
Polarization States

Internal and external optical bremsstrahlung accompanying the β decay of polarized nuclei were investigated. The features of angular distribution of light photons were analyzed taking into account multiple electron scattering. Monte-Carlo simulation was used to study the fate of β electrons and to calculate the intensity and angular distribution of the optical photons. It is shown that in pure water, the contribution of secondary electrons in the production of photons reaches 30–40%. We suggest using the angular distribution of optical photons to study the polarization states of β isotopes imbedded in transparent media.

Angular distribution of sputtered neutrals in a post magnetron geometry: Measurement and Monte Carlo simulation

1995 ◽  
Vol 13 (5) ◽  
pp. 2435-2443 ◽  
Author(s):  
C. Eisenmenger‐Sittner ◽  
R. Beyerknecht ◽  
A. Bergauer ◽  
W. Bauer ◽  
G. Betz
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Geometry Measurement
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