KOZENY–CARMAN CONSTANT FOR GAS FLOW THROUGH FIBROUS POROUS MEDIA BY FRACTAL-MONTE CARLO SIMULATIONS

Fractals ◽  
2019 ◽  
Vol 27 (04) ◽  
pp. 1950062 ◽  
Author(s):  
BOQI XIAO ◽  
XIAN ZHANG ◽  
GUOPING JIANG ◽  
GONGBO LONG ◽  
WEI WANG ◽  
...  
Keyword(s):  
Porous Media ◽  
Monte Carlo ◽  
Fractal Dimension ◽  
Monte Carlo Simulations ◽  
Pore Size ◽  
Fiber Diameter ◽  
Structural Parameters ◽  
Probability Model ◽  
Monte Carlo Technique ◽  
Fibrous Porous Media

In this paper, the Kozeny–Carman constant of fibrous porous media is simulated by the Fractal-Monte Carlo technique. The proposed probability model of the Kozeny–Carman constant is obtained based on the fractal distribution of pore size in fibrous porous media, and thus can be expressed as a function of structural parameters of fibrous porous media, including porosity, micro-pore size, fiber diameter, tortuosity fractal dimension and area fractal dimension of pores. Our results demonstrate that the Kozeny–Carman constant of fibrous porous media increases with increases in tortuosity fractal dimension and fiber diameter. Our results also illustrate a satisfying agreement of the Fractal Monte-Carlo simulations obtained by the proposed model and the existing experimental data. Therefore, the proposed Fractal-Monte Carlo technique can be used to characterize other transport properties of fluid in fibrous porous media.

GAS DIFFUSION COEFFICIENT OF FRACTAL POROUS MEDIA BY MONTE CARLO SIMULATIONS

Fractals ◽  
2015 ◽  
Vol 23 (02) ◽  
pp. 1550012 ◽  
Author(s):  
QIAN ZHENG ◽  
XIANGPENG LI
Keyword(s):  
Porous Media ◽  
Monte Carlo ◽  
Diffusion Coefficient ◽  
Monte Carlo Simulations ◽  
Pore Size ◽  
Structural Parameters ◽  
Probability Model ◽  
Fractal Dimensions ◽  
Gas Diffusion ◽  
Monte Carlo Simulation Technique

Gas diffusion behavior in fractal porous media is simulated by Monte Carlo technique in this work. Based on the fractal character of pore size in porous media, the probability model of the effective gas diffusion coefficient is derived. The proposed model of the effective gas diffusion coefficient is explicitly expressed as a function of structural parameters of porous media, such as porosity, pore size, the fractal dimensions for pore area and tortuosity. The effect of structural parameters of porous media has been studied in detail. The results show that the present results from the Monte Carlo simulations present a good agreement with those from the available analytical model and the available experimental data. The proposed Monte Carlo simulation technique may have the potential in predictions of other gas transport properties in fractal porous media.

EFFECTIVE THERMAL CONDUCTIVITY OF POROUS MEDIA WITH ROUGHENED SURFACES BY FRACTAL-MONTE CARLO SIMULATIONS

Fractals ◽  
2020 ◽  
Vol 28 (02) ◽  
pp. 2050029 ◽  
Author(s):  
BOQI XIAO ◽  
SHUAI WANG ◽  
YAN WANG ◽  
GUOPING JIANG ◽  
YIDAN ZHANG ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Porous Media ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Effective Thermal Conductivity ◽  
Structural Parameters ◽  
Monte Carlo Model ◽  
Maximum Diameter ◽  
Empirical Constant ◽  
Relative Roughness

In this paper, the Fractal-Monte Carlo has been employed to simulate the effective thermal conductivity of porous media with roughened surfaces. The proposed probability model for the effective thermal conductivity of porous media with roughened surfaces can be expressed as a function of the relative roughness, porosity, minimum and maximum diameter of pores, fractal dimensions, and random number. The proposed model is validated by a satisfying agreement of our Fractal-Monte Carlo simulations and the experimental data. In our Fractal-Monte Carlo model, there is no extra empirical constant and each parameter has clear physical meaning. Then, the effects of micro-structural parameters of porous media on the effective thermal conductivity of porous media with roughened surfaces have been analyzed in detail. It can be found that the effective thermal conductivity of porous media with roughened surfaces decreases with the increase of relative roughness and tortuosity fractal dimension. Our results demonstrate that the proposed Fractal-Monte Carlo model can be used to characterize other transport properties such as mass transfer of porous media.

PREDICTION OF EFFECTIVE THERMAL CONDUCTIVITY OF POROUS MEDIA WITH FRACTAL-MONTE CARLO SIMULATIONS

Fractals ◽  
2014 ◽  
Vol 22 (03) ◽  
pp. 1440004 ◽  
Author(s):  
YOUSHENG XU ◽  
YOUQU ZHENG ◽  
JIANLONG KOU
Keyword(s):  
Thermal Conductivity ◽  
Porous Media ◽  
Monte Carlo ◽  
Fractal Dimension ◽  
Effective Thermal Conductivity ◽  
Scaling Laws ◽  
Volume Fraction ◽  
Probability Model ◽  
Fractal Theory ◽  
Monte Carlo Simulation Technique

On the basis of the fractal scaling laws of pore distribution in natural porous media, a probability model is developed for thermal conductivity in porous media by combining fractal theory and Monte Carlo technique. The current numerical model, which was validated by comparison with the existing experimental data, shows that the thermal conductivity of porous media is a function of the thermal conductivities of volume fraction, pore area fractal dimension, tortuosity fractal dimension and random number. The effect of microstructure parameters on the effective thermal conductivity of porous media is studied. The proposed fractal Monte Carlo simulation technique has advantages compared with conventional numerical methods and may have the potential in analyzing other transport properties of porous media.

scholarly journals New Approach for Determining Tortuosity in Fibrous Porous Media

2010 ◽  
Vol 5 (3) ◽  
pp. 155892501000500 ◽  
Author(s):  
Rahul Vallabh ◽  
Pamela Banks-Lee ◽  
Abdel-Fattah Seyam
Keyword(s):  
Porous Medium ◽  
Porous Media ◽  
Fiber Diameter ◽  
Empirical Relationship ◽  
Air Permeability ◽  
New Approach ◽  
Upper Limits ◽  
Fibrous Porous Media ◽  
Flow Through

A method to determine tortuosity in a fibrous porous medium is proposed. A new approach for sample preparation and testing has been followed to establish a relationship between air permeability and fiberweb thickness which formed the basis for the determination of tortuosity in fibrous porous media. An empirical relationship between tortuosity and fiberweb structural properties including porosity, fiber diameter and fiberweb thickness has been proposed unlike the models in the literature which have expressed tortuosity as a function of porosity only. Transverse air flow through a fibrous porous media increasingly becomes less tortuous with increasing porosity, with the value of tortuosity approaching 1 at upper limits of porosity. Tortuosity also decreased with increase in fiber diameter whereas increase in fiberweb thickness resulted in the increase in tortuosity within the range of fiberweb thickness tested.

Fractal Model for Thermal Conductivity of Wetting, Fibrous Porous Media

2012 ◽  
Vol 496 ◽  
pp. 12-16
Author(s):  
Fang Long Zhu ◽  
De Hong Xia ◽  
Yu Zhou
Keyword(s):  
Thermal Conductivity ◽  
Porous Media ◽  
Fractal Dimension ◽  
Effective Thermal Conductivity ◽  
Fractal Model ◽  
Self Similarity ◽  
Conductivity Model ◽  
Electrical Analogy ◽  
Fibrous Porous Media ◽  
Thermal Conductivity Model

The current paper deals with the fractal effective thermal conductivity model for fibrous porous media containing unsaturated water moisture. The model is based on the thermal-electrical analogy and statistical self-similarity of porous media. The fractal effective thermal conductivity model can be expressed as a function of the pore structure (fractal dimension) and architectural parameters of porous media. It is expected that the model will be helpful in the evaluation of thermal comfort for textiles in the whole range of porosity.

scholarly journals Adsorption and separation of binary and ternary mixtures of SO2, CO2 and N2 by ordered carbon nanotube arrays: grand-canonical Monte Carlo simulations

2016 ◽  
Vol 18 (5) ◽  
pp. 4112-4120 ◽  
Author(s):  
Mahshid Rahimi ◽  
Jayant K. Singh ◽  
Florian Müller-Plathe
Keyword(s):  
Monte Carlo ◽  
Carbon Nanotube ◽  
Monte Carlo Simulations ◽  
Pore Size ◽  
Ternary Mixtures ◽  
Nanotube Arrays ◽  
Grand Canonical Monte Carlo ◽  
Carbon Nanotube Arrays ◽  
Binary And Ternary Mixtures ◽  
Grand Canonical

The selectivity value is found here to range from 4 to 16, indicating that the optimization of pore size tuning can increase it by 4 times.

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