scholarly journals Fractal Characteristics of Porosity of Electrospun Nanofiber Membranes

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Ting Wang ◽  
Ying Chen ◽  
Wenxia Dong ◽  
Yong Liu ◽  
Luoyi Shi ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Porosity Distribution ◽  
Filtration Resistance ◽  
Relative Porosity ◽  
Fractal Characteristics ◽  
Nanofiber Membranes ◽  
Secondary Function ◽  
Function Relationship ◽  
Fitting In ◽  
The Relationship

In this paper, the method of measuring the porosity of electrostatic nanofiber membrane by VC++ and Matlab is introduced. It is found that the ratio of the calculated porosity to the porosity measured by the mercury intrusion method accords with the famous Feigenbaum constant (α=2.5029078750957⋯). The porosity distribution of nanofiber membranes was studied by VC++ and Matlab based on the image obtained by using a scanning electron microscope. The porosity distribution calculated by using a computer is magnified by eα times which was named as relative porosity distribution. According to the relative porosity distribution, we use the algorithm proposed by Grassberger and Procaccia (briefly referred to as the G-P algorithm) to calculate the correlation fractal dimension. The correlation fractal dimension calculated from the relative porosity distribution series was between 1 and 2, consistent with geometric characteristics of coincidence samples. The fractal meaning of the Feigenbaum constant was verified again. In the end, we obtained the relationship between the associated fractal dimension and the filtration resistance by fitting in accordance with the secondary function relationship and reached the maximum correlation fractal dimension when the filtration resistance was 15–20 pa.

scholarly journals Review about the Application of Fractal Theory in the Research of Packaging Materials

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 860
Author(s):  
Qingshan Duan ◽  
Jiejie An ◽  
Hanling Mao ◽  
Dongwu Liang ◽  
Hao Li ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Fractal Analysis ◽  
Fractal Theory ◽  
Inorganic Materials ◽  
Packaging Materials ◽  
Analysis Method ◽  
Characteristic Parameters ◽  
Fractal Characteristic ◽  
Fractal Characteristics ◽  
The Relationship

The work is intended to summarize the recent progress in the work of fractal theory in packaging material to provide important insights into applied research on fractal in packaging materials. The fractal analysis methods employed for inorganic materials such as metal alloys and ceramics, polymers, and their composites are reviewed from the aspects of fractal feature extraction and fractal dimension calculation methods. Through the fractal dimension of packaging materials and the fractal in their preparation process, the relationship between the fractal characteristic parameters and the properties of packaging materials is discussed. The fractal analysis method can qualitatively and quantitatively characterize the fractal characteristics, microstructure, and properties of a large number of various types of packaging materials. The method of using fractal theory to probe the preparation and properties of packaging materials is universal; the relationship between the properties of packaging materials and fractal dimension will be a critical trend of fractal theory in the research on properties of packaging materials.

scholarly journals A study on the effects of the fractal characteristics of aggregates on the mechanical behavior of cemented sand and gravel

2021 ◽  
Vol 71 (342) ◽  
pp. e250
Author(s):  
L. Guo ◽  
S. Li ◽  
L. Zhong ◽  
L. Guo ◽  
L. Wang ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Elastic Modulus ◽  
Fractal Theory ◽  
Peak Stress ◽  
Aggregate Gradation ◽  
Cemented Sand ◽  
Ordinary Concrete ◽  
Fractal Characteristics ◽  
Sand And Gravel ◽  
The Relationship

Owing to complex aspects of cemented sand and gravel (CSG), such as included unscreened aggregates, CSG properties differ from those of ordinary concrete. Fractal theory is introduced to study the effects of aggregate characteristics on CSG properties, quantifying aggregate gradation and shape. Numerical simulation and analyses show that: (1) improved aggregate gradation decreases the gradation fractal dimension and increases the CSG peak stress and elastic modulus; (2) more irregularly shaped aggregates increase the shape fractal dimension and decrease the CSG peak stress and elastic modulus; (3) the relationship quantified between aggregate characteristics and CSG mechanical properties provides a theoretical basis for aggregate allocation in engineering design and construction. Mixing artificial aggregates can improve aggregate gradation but reduces CSG performance. Appropriately blending artificial and on-site aggregates achieves optimal CSG performance; in this study, this is attained using 20% artificial aggregates added under standard gradation.

Fractal Characteristics of the Middle-Upper Ordovician Marine Shale Nano-Scale Porous Structure from the Ordos Basin, Northeast China

2021 ◽  
Vol 21 (1) ◽  
pp. 274-283
Author(s):  
Liang Liu ◽  
Wuling Mo ◽  
Min Wang ◽  
Nengwu Zhou ◽  
Yu Yan ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Pore Structure ◽  
Pore Size ◽  
Ordos Basin ◽  
Fractal Dimensions ◽  
Upper Ordovician ◽  
Average Pore ◽  
Marine Shale ◽  
Fractal Characteristics ◽  
The Relationship

The fractal characteristics of marine shale from the Middle-Upper Ordovician Wulalike Formation (O2w) in the southwest margin of the Ordos Basin are studied. Based on low-temperature nitrogen adsorption experiments, the FHH (Frenkel-Halsey-Hill) model was employed to investigate the relationship between the marine shale composition, such as TOC, mineral content and shale gas content, and pore structure parameters, such as BET specific surface area, average pore diameter, porosity and fractal dimension. The results show that the pore size distribution curve of shale slowly decreased after the pore size was greater than 50 nm, the pore size distribution showed multiple peaks, and the peak value was mainly in the range of 2–10 nm. Most pores are nanopores, although the pore type and shape are different. Two different fractal dimensions D1 and D2 are obtained from the two segments with relative pressures of 0–0.5 and 0.5–1.0, respectively: the D1 range is 2.77–2.82, and the D2 range is 2.63–2.66. As D1 is larger than D2, the pore structure of small pores is more uniform than that of large pores in the shale samples. The relationship between the fractal dimensions D1 and D2 and the total organic carbon (TOC) content is a convex curve. Fractal dimension D reaches its maximum when TOC is 0.53 wt.%. Fractal dimension D decreases with increasing specific surface area, porosity and average pore size. The fractal dimension has a different influence on the gas storage and migration in shale; the larger the fractal dimension is, the stronger the heterogeneity and the more complex the pore structure, and this outcome is conducive to the storage of gas in shale but not beneficial to the permeability and production of gas.

scholarly journals Study on the Fractal Characteristics of Fracture Network Evolution Induced by Mining

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Tao Liang ◽  
Xiaoli Liu ◽  
Sijing Wang ◽  
Enzhi Wang ◽  
Quansheng Li
Keyword(s):  
Fractal Dimension ◽  
Fractal Dimensions ◽  
Material Model ◽  
Fracture Network ◽  
Network Evolution ◽  
Rock Properties ◽  
Fracture Formation ◽  
Fractal Characteristics ◽  
Induced Fractures ◽  
The Relationship

The evolution and distribution of fracture network induced by mining is essential to determine the mechanical properties and permeability of disturbed rock mass. In this paper, the similar material model tests are employed to simulate the stress variation, cyclic breaking, and fracture formation and distribution status of the overlying strata with different loading conditions, rock properties, and mining process. The fractal dimension of mining-induced fracture network varied with mining advancing, and the evolvement laws of fracture network with mining advancing and different mining advancing footage are concerned and obtained. By establishing the relationship between the fractal dimension and the mining length in different horizontal and vertical zones, it demonstrates that the fractal dimensions in horizontal and vertical zones have a self-similar characteristic, and the distribution of the fractal dimension of the mining-induced fractures shows generally the “W”-type trend.

scholarly journals Network-based approaches to quantify multicellular development

2017 ◽  
Vol 14 (135) ◽  
pp. 20170484 ◽  
Author(s):  
Matthew D. B. Jackson ◽  
Salva Duran-Nebreda ◽  
George W. Bassel
Keyword(s):  
Structure Function ◽  
Spatial Relations ◽  
Higher Order ◽  
Cellular Interaction ◽  
Cellular Organization ◽  
Multicellular Development ◽  
Cell Organization ◽  
Function Relationship ◽  
And Function ◽  
The Relationship

Multicellularity and cellular cooperation confer novel functions on organs following a structure–function relationship. How regulated cell migration, division and differentiation events generate cellular arrangements has been investigated, providing insight into the regulation of genetically encoded patterning processes. Much less is known about the higher-order properties of cellular organization within organs, and how their functional coordination through global spatial relations shape and constrain organ function. Key questions to be addressed include: why are cells organized in the way they are? What is the significance of the patterns of cellular organization selected for by evolution? What other configurations are possible? These may be addressed through a combination of global cellular interaction mapping and network science to uncover the relationship between organ structure and function. Using this approach, global cellular organization can be discretized and analysed, providing a quantitative framework to explore developmental processes. Each of the local and global properties of integrated multicellular systems can be analysed and compared across different tissues and models in discrete terms. Advances in high-resolution microscopy and image analysis continue to make cellular interaction mapping possible in an increasing variety of biological systems and tissues, broadening the further potential application of this approach. Understanding the higher-order properties of complex cellular assemblies provides the opportunity to explore the evolution and constraints of cell organization, establishing structure–function relationships that can guide future organ design.

scholarly journals Development of Back-calculation Model for Aggregate Gradation Determination Using Fractal Theory

2018 ◽  
Vol 159 ◽  
pp. 01006
Author(s):  
Bagus Hario Setiadji ◽  
Supriyono ◽  
Djoko Purwanto
Keyword(s):  
Fractal Dimension ◽  
Fractal Theory ◽  
Asphalt Mixture ◽  
Fractal Dimensions ◽  
Calculation Model ◽  
Careful Consideration ◽  
Upper And Lower Bounds ◽  
Aggregate Gradation ◽  
Fractal Characteristic ◽  
Fractal Characteristics

Several studies have shown that fractal theory can be used to analyze the morphology of aggregate materials in designing the gradation. However, the question arises whether a fractal dimension can actually represent a single aggregate gradation. This study, which is a part of a grand research to determine aggregate gradation based on known asphalt mixture specifications, is performed to clarify the aforementioned question. To do so, two steps of methodology were proposed in this study, that is, step 1 is to determine the fractal characteristics using 3 aggregate gradations (i.e. gradations near upper and lower bounds, and middle gradation); and step 2 is to back-calculate aggregate gradation based on fractal characteristics obtained using 2 scenarios, one-and multi-fractal dimension scenarios. The results of this study indicate that the multi-fractal dimension scenario provides a better prediction of aggregate gradation due to the ability of this scenario to better represent the shape of the original aggregate gradation. However, careful consideration must be observed when using more than two fractal dimensions in predicting aggregate gradation as it will increase the difficulty in developing the fractal characteristic equations.

An analysis of fractal dimension and tortuosity based on 2D numerical reconstruction model of reservoir rocks

2019 ◽  
Vol 7 (4) ◽  
pp. SJ1-SJ6 ◽  
Author(s):  
Liang Luo ◽  
Jiahong Jin ◽  
Wei Wei ◽  
Jianchao Cai
Keyword(s):  
Fractal Dimension ◽  
Oil And Gas ◽  
Universal Method ◽  
Structure Generation ◽  
Reservoir Rocks ◽  
Numerical Reconstruction ◽  
The Monte Carlo Method ◽  
Microstructure Parameters ◽  
Rock Model ◽  
The Relationship

The microstructure of reservoir rocks plays an important role in oil and gas accumulation and production. We examine a universal method to evaluate these properties of rocks, such as pore tortuosity, matrix porosity, and connectivity, and we respectively construct a 2D numerical reconstruction rock model with different microstructure parameters by the Monte Carlo method and the quartet structure generation set method. We further study the heterogeneity (characterized by fractal dimension and tortuosity) of the constructed image for reservoir rocks by the numerical and theoretical analysis and obtain the formulas for fractal dimension and tortuosity versus porosity. The simulation results show that the logarithmic relation is between the pore fractal dimension and porosity, and the relationship between tortuosity and porosity has the form of power. This process provided an important method to advance 2D reconstruction technology of reservoir rocks and effectively determine the relationship between microstructure and porosity.

scholarly journals On Similarity of Seismo Magnetic Power Density and Pressure Head Fractal Dimension for Characterizing Shajara Reservoirs of the Permo-Carboniferous Shajara Formation, Saudi Arabia

2020 ◽  
pp. 1-8
Author(s):  
Khalid Elyas Mohamed Elameen Alkhidir ◽  
Keyword(s):  
Fractal Dimension ◽  
Power Density ◽  
Functional Relationship ◽  
Fractal Dimensions ◽  
Pressure Head ◽  
Density Maximum ◽  
Phase Saturation ◽  
Head Pressure ◽  
Second Procedure ◽  
The Relationship

The quality and assessment of a reservoir can be documented in details by the application of seismo magnetic power density. This research aims to calculate fractal dimension from the relationship among seismo magnetic power density, maximum seismo magnetic power density and wetting phase saturation and to approve it by the fractal dimension derived from the relationship among inverse pressure head * pressure head and wetting phase saturation. Two equations for calculating the fractal dimensions have been employed. The first one describes the functional relationship between wetting phase saturation, seismo magnetic power density, maximum seismo magnetic power density and fractal dimension. The second equation implies to the wetting phase saturation as a function of pressure head and the fractal dimension. Two procedures for obtaining the fractal dimension have been utilized. The first procedure was done by plotting the logarithm of the ratio between seismo magnetic power density and maximum seismo magnetic power density versus logarithm wetting phase saturation. The slope of the first procedure = 3- Df (fractal dimension). The second procedure for obtaining the fractal dimension was determined by plotting the logarithm (inverse of pressure head and pressure head) versus the logarithm of wetting phase saturation. The slope of the second procedure = Df -3. On the basis of the obtained results of the fabricated stratigraphic column and the attained values of the fractal dimension, the sandstones of the Shajara reservoirs of the Shajara Formation were divided here into three units

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