SOME FRACTAL CHARACTERS OF POROUS MEDIA

Fractals ◽  
2001 ◽  
Vol 09 (03) ◽  
pp. 365-372 ◽  
Author(s):  
BOMING YU ◽  
JIANHUA LI
Keyword(s):  
Porous Media ◽  
Fractal Theory ◽  
Unified Model ◽  
Counting Method ◽  
Statistical Property ◽  
Box Counting ◽  
Fractal Media ◽  
Proposed Model ◽  
Theoretical Predictions ◽  
Box Counting Method

In this paper, a unified model for describing the fractal characters of porous media is deduced. The theoretical predictions from the proposed unified model are compared with those from the previous models and from the box-counting method. The results from the proposed model are found to be in good agreement with both the previous models and box-counting method. The results also indicate that the proposed unified model is applicable to both the exactly and statistically self-similar fractal media. A statistical property of porous media is also described based on the basic fractal theory and technique. A criterion, for determining whether a porous medium can be characterized by fractal theory and technique or not, is proposed based on the fractal statistical property.

A one dimensional heat transfer model for wolverine (gulo-gulo) hair

2018 ◽  
Vol 30 (4) ◽  
pp. 548-558
Author(s):  
HongYan Liu ◽  
Addie Bahi ◽  
Frank K. Ko
Keyword(s):  
Heat Transfer ◽  
Cold Weather ◽  
Transfer Model ◽  
Counting Method ◽  
Content Type ◽  
Box Counting ◽  
Proposed Model ◽  
Extreme Cold ◽  
Box Counting Method ◽  
Good Agreement

Purpose Wolverine hairs with superior heat transfer properties have been used as fur ruffs for extreme cold-weather clothing. In order to understand the exclusive mechanism of wolverine surviving in the cold areas of circumpolar, the purpose of this paper is to establish a one-dimensional fractional heat transfer equation to reveal the hidden mechanism for the hairs, and also calculate the fractal dimension of the wolverine hair using the box counting method to verify the proposed theory. The observed results (from the proposed model) found to be in good agreement with the box counting method. This model can explain the phenomenon which offers the theoretical foundation for the design of extreme cold weather clothing. Design/methodology/approach The authors calculated the fractal dimension of the wolverine hair using the box counting method to verify the proposed theory. The observed results (from the proposed model) found to be in good agreement with the box counting method. Findings The box counting method proves that the theoretical model is applicable. Originality/value The authors propose the first heat transfer model for the wolverine hair.

scholarly journals Improved Image Analysis Method to Evaluate Tracking Property under Successive Flashover Based on Fractal Theory

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8253
Author(s):  
Xiaolong Li ◽  
Chen Cao ◽  
Xin Lin
Keyword(s):  
Image Analysis ◽  
Fractal Theory ◽  
Suggested Method ◽  
Future Research ◽  
Analysis Method ◽  
Counting Method ◽  
Image Analysis Method ◽  
Insulator Surface ◽  
Box Counting ◽  
Box Counting Method

Successive flashover would result in carbonized tracking on insulator surface and cause deterioration to the insulation. Thus, investigation of the tracking can be beneficial in understanding flashover characteristics during long-term operation. In this paper, DC flashover was operated on the insulator, and the image of tracking after successive discharge were captured. Improved differential box-counting method (IDBM) was applied to analyze these images based on fractal theory. Weighted item was suggested during the counting procedure for rectangle image with margin covered by cut-size box. Fractal dimension of the tracking was calculated according to the suggested method. It is claimed that the suggested method could estimate the discharge propagation property and deterioration characteristics on the insulator surface. Moreover, IDBM showed advantages in image pre-processing and deterioration property revealed compared to traditional box-counting method attributing to the consideration of color depth. This image analysis method shows universality in dealing with tracking image and could provide additional information to flashover voltage. This paper suggested a potential approach for the investigation of discharge mechanism and corresponding deterioration in future research.

FRACTAL CHARACTERS OF PORE MICROSTRUCTURES OF TEXTILE FABRICS

Fractals ◽  
2001 ◽  
Vol 09 (02) ◽  
pp. 155-163 ◽  
Author(s):  
BOMING YU ◽  
L. JAMES LEE ◽  
HANQIANG CAO
Keyword(s):  
Fractal Dimension ◽  
Fractal Analysis ◽  
Reinforced Composites ◽  
Counting Method ◽  
Box Counting ◽  
Textile Fabrics ◽  
Different Types ◽  
Theoretical Predictions ◽  
Box Counting Method ◽  
Good Agreement

It is found that the pore microstructures of textile fabrics, widely used in the manufacture of fiber-reinforced composites, exhibit the fractal characters. The fractal behaviors are described by the proposed analytical method and measured by the box-counting method for the three different types of textile fabrics: plain woven, four-harness, bidirectional-stitched fiberglass mats. The pore area fractal dimension is derived analytically and found to be the function of the porosity and architectural parameters of fabrics. The results indicate that the fractal characters are isotropic although the fabrics are rothotropic in structures. The theoretical predictions by the proposed analytical model are in good agreement with those from the box-counting method, and this verifies the proposed fractal dimension model. The present fractal analysis may have the potential and significance on fractal analysis of transport properties (such as the permeability, dispersion, thermal and mechanical properties) in porous media.

Fractal and Convolutional Analysis for Deep Atmospheric Turbulence Using Machine Learning

2021 ◽  
Author(s):  
Nicholas Dudu ◽  
Arturo Rodriguez ◽  
Gael Moran ◽  
Jose Terrazas ◽  
Richard Adansi ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Atmospheric Turbulence ◽  
Isotropic Turbulence ◽  
Passive Scalar ◽  
Counting Method ◽  
Data Set ◽  
Box Counting ◽  
Box Counting Dimension ◽  
Self Similar ◽  
Box Counting Method

Abstract Atmospheric turbulence studies indicate the presence of self-similar scaling structures over a range of scales from the inertial outer scale to the dissipative inner scale. A measure of this self-similar structure has been obtained by computing the fractal dimension of images visualizing the turbulence using the widely used box-counting method. If applied blindly, the box-counting method can lead to misleading results in which the edges of the scaling range, corresponding to the upper and lower length scales referred to above are incorporated in an incorrect way. Furthermore, certain structures arising in turbulent flows that are not self-similar can deliver spurious contributions to the box-counting dimension. An appropriately trained Convolutional Neural Network can take account of both the above features in an appropriate way, using as inputs more detailed information than just the number of boxes covering the putative fractal set. To give a particular example, how the shape of clusters of covering boxes covering the object changes with box size could be analyzed. We will create a data set of decaying isotropic turbulence scenarios for atmospheric turbulence using Large-Eddy Simulations (LES) and analyze characteristic structures arising from these. These could include contours of velocity magnitude, as well as of levels of a passive scalar introduced into the simulated flows. We will then identify features of the structures that can be used to train the networks to obtain the most appropriate fractal dimension describing the scaling range, even when this range is of limited extent, down to a minimum of one order of magnitude.

Research on a precise differential box-counting method of eliminating image background

2016 ◽  
Author(s):  
Kexue Lai ◽  
Tao He ◽  
Cancan Li ◽  
Weisong Zhou ◽  
Liangen Yang
Keyword(s):  
Counting Method ◽  
Box Counting ◽  
Box Counting Method

scholarly journals Application of An Exponential Mathematical Law of Cardiac Dynamics In 16 Hours

2021 ◽  
Author(s):  
Javier Oswaldo Rodríguez Velásquez ◽  
Sandra Catalina Correra Herrera ◽  
Yesica Tatiana Beltrán Gómez ◽  
Jorge Gómez Rojas ◽  
Signed Esperanza Prieto Bohórquez ◽  
...  
Keyword(s):  
Kappa Coefficient ◽  
Medical Attention ◽  
Chaotic Attractors ◽  
Counting Method ◽  
Statistical Validation ◽  
Overlapping Grids ◽  
Box Counting ◽  
Cardiac Dynamics ◽  
Box Counting Method ◽  
Time Required

Abstract Introduction and objectives: nonlinear dynamics and fractal geometry have allowed the advent of an exponential mathematical law applicable to diagnose cardiac dynamics in 21 hours, however, it would be beneficial to reduce the time required to diagnose cardiac dynamics with this method in critical scenarios, in order to detect earlier complications that may require medical attention. The objective of this research is to confirm the clinical applicability of the mathematical law in 16 hours, with a comparative study against the Gold Standard. Methods: There were taken 450 electrocardiographic records of healthy patients and with cardiac diseases. A physical-mathematical diagnosis was applied to study cardiac dynamics, which consists of generating cardiac chaotic attractors based on the sequence of heart rate values during 16 hours, which were then measured with two overlapping grids according to the Box-Counting method to quantify the spatial occupation and the fractal dimension of each cardiac dynamic, with its respective statistical validation. Results: The occupation spaces of normal dynamics calculated in 16 hours were compatible with previous parameters established, evidencing the precision of the methodology to differentiate normality from abnormality. Sensitivity and specificity values of 100% were found, as well as a Kappa coefficient of 1. Conclusions: it was possible to establish differences between cardiac dynamics for 16 hours, suggesting that this method could be clinically applicable to analyze and diagnose cardiac dynamics in real time.

A stress sensitivity model for the permeability of porous media based on bi-dispersed fractal theory

2018 ◽  
Vol 29 (02) ◽  
pp. 1850019 ◽  
Author(s):  
X.-H. Tan ◽  
C.-Y. Liu ◽  
X.-P. Li ◽  
H.-Q. Wang ◽  
H. Deng
Keyword(s):  
Porous Media ◽  
Fractal Dimension ◽  
Fractal Theory ◽  
Stress Sensitivity ◽  
Maximum Diameter ◽  
Proposed Model ◽  
Fractal Parameters ◽  
Stress Changes ◽  
Capillary Bundle ◽  
Definition Of

A stress sensitivity model for the permeability of porous media based on bidispersed fractal theory is established, considering the change of the flow path, the fractal geometry approach and the mechanics of porous media. It is noted that the two fractal parameters of the porous media construction perform differently when the stress changes. The tortuosity fractal dimension of solid cluster [Formula: see text] become bigger with an increase of stress. However, the pore fractal dimension of solid cluster [Formula: see text] and capillary bundle [Formula: see text] remains the same with an increase of stress. The definition of normalized permeability is introduced for the analyzation of the impacts of stress sensitivity on permeability. The normalized permeability is related to solid cluster tortuosity dimension, pore fractal dimension, solid cluster maximum diameter, Young’s modulus and Poisson’s ratio. Every parameter has clear physical meaning without the use of empirical constants. Predictions of permeability of the model is accordant with the obtained experimental data. Thus, the proposed model can precisely depict the flow of fluid in porous media under stress.

scholarly journals Study on the Fractal Dimension and Growth Time of the Electrical Treeing Degradation at Different Temperature and Moisture

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Youping Fan ◽  
Dai Zhang ◽  
Jingjiao Li
Keyword(s):  
Fractal Dimension ◽  
Tree Growth ◽  
Fractal Dimensions ◽  
Moisture Level ◽  
Growth Time ◽  
Counting Method ◽  
Box Counting ◽  
Electrical Trees ◽  
Box Counting Method ◽  
Electrical Treeing

The paper aims to understand how the fractal dimension and growth time of electrical trees change with temperature and moisture. The fractal dimension of final electrical trees was estimated using 2-D box-counting method. Four groups of electrical trees were grown at variable moisture and temperature. The relation between growth time and fractal dimension of electrical trees were summarized. The results indicate the final electrical trees can have similar fractal dimensions via similar tree growth time at different combinations of moisture level and temperature conditions.

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