Solution of radiative transfer theory problems for ‘realistic’ models of random media using the Monte Carlo method

2016 ◽  
Vol 31 (3) ◽  
Author(s):  
Andrey Yu. Ambos ◽  
Gennady A. Mikhailov
Keyword(s):  
Random Fields ◽  
Random Media ◽  
Computational Models ◽  
Quantum Particle ◽  
Radiation Model ◽  
One Dimensional ◽  
Stochastic Media ◽  
The Monte Carlo Method ◽  
Dimensional Distribution ◽  
Correlation Scale

AbstractA methodology of efficient homogenization of a radiation model for a stochastic media is developed. In this connection, ‘realistic’ computational models of random fields are constructed, implementations of those fields are close to continuous ones, and the conditional one-dimensional distribution in the nonempty part of the medium is quite natural. It is shown that the corresponding homogenized probability of the passage of a quantum particle is actually determined by the correlation scale and the occupancy of the medium and also by the above conditional distribution.

scholarly journals Anomalous Anderson localization behavior in gain-loss balanced non-Hermitian systems

Nanophotonics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 443-452
Author(s):  
Tianshu Jiang ◽  
Anan Fang ◽  
Zhao-Qing Zhang ◽  
Che Ting Chan
Keyword(s):  
Wave Propagation ◽  
Electromagnetic Waves ◽  
Anderson Localization ◽  
Random Media ◽  
Normal Incidence ◽  
Disordered Media ◽  
One Dimensional ◽  
Gain Loss ◽  
The Waves ◽  
Localization Behavior

AbstractIt has been shown recently that the backscattering of wave propagation in one-dimensional disordered media can be entirely suppressed for normal incidence by adding sample-specific gain and loss components to the medium. Here, we study the Anderson localization behaviors of electromagnetic waves in such gain-loss balanced random non-Hermitian systems when the waves are obliquely incident on the random media. We also study the case of normal incidence when the sample-specific gain-loss profile is slightly altered so that the Anderson localization occurs. Our results show that the Anderson localization in the non-Hermitian system behaves differently from random Hermitian systems in which the backscattering is suppressed.

Line-by-Line Random-Number Database for Monte Carlo Simulations of Radiation in Combustion System

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Tao Ren ◽  
Michael F. Modest
Keyword(s):  
Heat Transfer ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Radiative Heat ◽  
Random Number ◽  
Test Cases ◽  
Combustion System ◽  
Absorption Coefficients ◽  
One Dimensional ◽  
The Monte Carlo Method

With today's computational capabilities, it has become possible to conduct line-by-line (LBL) accurate radiative heat transfer calculations in spectrally highly nongray combustion systems using the Monte Carlo method. In these calculations, wavenumbers carried by photon bundles must be determined in a statistically meaningful way. The wavenumbers for the emitting photons are found from a database, which tabulates wavenumber–random number relations for each species. In order to cover most conditions found in industrial practices, a database tabulating these relations for CO2, H2O, CO, CH4, C2H4, and soot is constructed to determine emission wavenumbers and absorption coefficients for mixtures at temperatures up to 3000 K and total pressures up to 80 bar. The accuracy of the database is tested by reconstructing absorption coefficient spectra from the tabulated database. One-dimensional test cases are used to validate the database against analytical LBL solutions. Sample calculations are also conducted for a luminous flame and a gas turbine combustion burner. The database is available from the author's website upon request.

Quasi-one-dimensional distribution of macropores in anodically etched uniaxially stressed silicon plates

2003 ◽  
Vol 29 (3) ◽  
pp. 226-229 ◽  
Author(s):  
V. I. Emel’yanov ◽  
K. I. Eremin ◽  
V. V. Starkov ◽  
E. Yu. Gavrilin
Keyword(s):  
One Dimensional ◽  
Dimensional Distribution ◽  
Stressed Silicon

scholarly journals Autoregressive Models of the Random fields—A Survey

2020 ◽  
pp. 1-9
Keyword(s):  
Random Fields ◽  
Linear Models ◽  
Estimation Methods ◽  
Suitable Model ◽  
Main Mode ◽  
One Dimensional ◽  
Non Linear ◽  
The Status ◽  
Ar Models ◽  
Shed Light

Autoregressive (AR) random fields are widely use to describe changes in the status of real-physical objects and implemented for analyzing linear & non-linear models. AR models are Markov processes with a higher order dependence for one-dimensional time series. Actually, various estimation methods were used in order to evaluate the autoregression parameters. Although in many applications background knowledge can often shed light on the search for a suitable model, but other applications lack this knowledge and often require the type of trial errors to choose a model. This article presents a brief survey of the literatures related to the linear and non-linear autoregression models, including several extensions of the main mode models and the models developed. The use of autoregression to describe such system requires that they be of sufficiently high orders which leads to increase the computational costs.

Determination of one-dimensional distribution of14C-labelled compounds

1988 ◽  
Vol 126 (6) ◽  
pp. 443-453 ◽  
Author(s):  
R. Rexa ◽  
I. Kron ◽  
P. Kralik ◽  
R. Tykva
Keyword(s):  
One Dimensional ◽  
Dimensional Distribution
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