• Journal of Powder Materials
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• v.14 no.6
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• pp.391-398
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• 2007

The surface roughness of Al, Ag and Ni nano-powders which were prepared by pulsed wire evaporation method was quantified based upon the fractal theory. The surface fractal dimensions of metal nano-powders were determined from the linear relationship between In $V/V_{mono}$ and Inln ($P^o/P$) using multi-layer gas adsorption theory. Moreover, the fractal surface image was realized by computer simulation. The relationship between preparation condition and surface characteristics of metal nano-powders was discussed in detail.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.1
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• pp.18-26
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• 2002

With the introduction of Fractal notation, various fields of engineering adopted fractal notation to express characteristics of geometry involved and one of the most frequently applied areas was turbulence. With research on turbulence regarding the surface as fractal geometry, attempts to analyze turbulent premised flame as fractal geometry also attracted attention as a tool for modeling, for the flame surface can be viewed as fractal geometry. Experiments focused on disclosure of flame characteristics by measuring fractal parameters were done by researchers. But robust principle or theory can't be extracted. Only reported modeling efforts using fractal dimension is flame speed model by Gouldin. This model gives good predictions of flame speed in unstrained case but not in highly strained flame condition. In this research, approaches regarding fractal dimension of flame as one representative value is pointed out as a reason for the absence of robust model. And as an extort to establish robust modeling, Presents methods treating fractal dimension as statistical variable. From this approach flame characteristics reported by experiments such as Da effect on flame structure can be seen quantitatively and shows possibility of flame modeling using fractal parameters with statistical method. From this result more quantitative model can be derived.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.251-254
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• 1995

The quality and functionality of machined products is determined by surface finish. The surface roughness is characterized by roughness parameters such as R $_{a}$ and R $_{max}$. While such parameters are useful to define the quality of surface, they are nor sufficiently descriptive characteristics of surface. The fractal dimension which can describe characteristics od surface roughness than conventional roughness parameters has been applied. In this work, Relation between fractal dimension and surface roughness will be examined as a means of characterizing surface roughness.s.s.

• Elastomers and Composites
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• v.54 no.2
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• pp.156-160
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• 2019

The changes in the dispersion of carbon black in liquid polyisoprene under shear flow with time have been investigated by time-resolved ultra small-angle X-ray scattering (USAXS) method. The analyses of USAXS profile immediately after the start of shear flow clarified that the aggregates of carbon black with a mean radius of gyration of 14 nm and surface fractal dimension of 2.5 form the fractal network structure with mass-fractal dimension of 2.9. After the application of the shear flow, the scattering intensity increases with time at the observed whole entire q region, and then the a shoulder appears at $q=0.005nm^{-1}$, indicating that the agglomerate is broken and becomes smaller by shear flow. The analysis by the Unified Guinier/Power-law approach yielded several characteristic parameters, such as the sizes of aggregate and agglomerate, mass-fractal dimension of agglomerate, and surface fractal dimension of the primary particle. While the mean radius of gyration of the agglomerate decreases with time, the mean radius of gyration of the aggregate, mass fractal dimension, and surface fractal dimension don't change with time, indicating that the aggregates peel off the surface of the agglomerate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.145-149
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• 2023

High-resolution images of surfaces provide detailed information on pores or shapes with specific sizes ranging from nano sizes to micrometers. However, it is not yet clear to determine an efficient association for pores or shapes from high-resolution images of surfaces. For the efficient association of pores and shapes, the surface characteristics of the device were considered as fractal dimensions by taking SEM photographs and binarizing the images. The fractal program was directly coded for surface analysis of the device. The device surface characteristics and electrical characteristics are thought to be related to the fractal dimension. The fractal dimension decreased with an increase in internal pores. The density and grain boundary of particles, which are structural characteristics of the device surface, were related to the fractal dimension. The particle size decreased with an increase in the fractal dimension and was uniformly formed. When the particles were uniformly formed, fewer pores were present and the fractal dimension increased.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.253-254
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• 2002

Based on 3-D surface morphology measurements of C.G. irons, the fractal analyses were made on relationship between dry sliding surface morphology and the fractal dimension. It is revealed that the values of fractal dimensions ($D_f$) of sliding surfaces are in the range between 1-2, which are closely related to the surface morphologies. With the increase in depths of grooves or pits, the $D_f$ values increase. At the same time, the increases in densities of the grooves also cause the $D_f$ values to increase. At last, relationship among $D_f$ and friction coefficient as well as wear rate is discussed.

• Journal of Mechanical Science and Technology
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• v.15 no.10
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• pp.1417-1422
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• 2001

Since fracture surface presents clear evidence to describe the circumstances of material failure event, analysis of fracture surface should provide plenty of useful information for failure prevention. Thus if we extract proper information from the fracture surface, the safety evaluation, for plant component could be more accurate. In general, the chaotic morphology of fracture surface is determined by the degree of material degradation as well as by other factors such as type of load, geometry of specimen, notch condition, microstructure of material and environment. In this research, we developed a fractal analysis technology for the fracture surface of aged turbine rotor steel based on the slit-island technique using an image analyzer. Moreover the correlation between the fractal dimension and the aging time was studied.

• Journal of the Korean association of regional geographers
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• v.11 no.6
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• pp.530-542
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• 2005

In this study, GIS method has been used to get fractal characteristics. Using the projected area and surface area, 2 dimensional fractal characteristic of terrain was found out. Correlation of fractal dimension and mean slope were also checked over. Results are as below. 1) To get a fractal dimension, the method which is using the surface area is also directly proportional to complexity of the terrain as other fractal dimension. 2) Fractal dimensions using the surface area, that is proposed in this thesis are carried out as below : Uiseong : $2.02{\sim}2.15$ Yeongcheon : $2.10{\sim}2.24$. These values are in a range of fractal $2.10{\sim}2.20$ dimensions which has known. 3) Correlation of mean slope and fractal dimension is diminished about 30% in a region which is more than $25^{\circ}$ of mean slope. So, in this region using the fractal dimension method is better than using the mean slope. From this study, on formula using the projected area and surface area is still good to get a fractal dimension that has been found. But to confirm this method the region of research should be wider and be set up the correlation of mean slope, surface area and fractal dimension. It can be applicable to restoration of terrain and traffic flow analysis in the future research.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.521-527
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• 1997

Irregular shapes and growth behavior of surface micro-crack showed very complex and nonlinear propeties and many investigators have performed theoretical analysesand experiments on them to characterize fatigue strength. They had difficulties in estimating fatigue life due to random distribution, growth and coalescence of surface micro-cracks. The straightness of crack growth along intergranular and transgranular was prevented from irregular microstructure and precipitates. Euclid geometry can't quantify shape of surface micro-crack but ftractal geometry can. Therefore, it is suggested that average fractal dimension of surface micro-cracks is able to estimate fatigue life but fractal dimension of maximum surface micro-crack is not in Al 2024-T3 alloy.

• Geomechanics and Engineering
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• v.4 no.3
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• pp.219-227
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• 2012

Pavement management systems require systematic monitoring of pavement surfaces to determine preventive and corrective maintenance. The process involves the accumulation of large amounts of visual data, typically obtained from site visitation. The pavement surface condition is then correlated to a pavement distress index that is based on a scoring system previously established by state or federal agencies. The scoring system determines if the pavement section requires maintenance, overlay or reconstruction. One of the surface distresses forming part of the overall pavement distress index is the Alligator Crack Index (AC Index). The AC Index involves the visual evaluation of the crack severity of a section of a pavement as being low, medium, or high. This evaluation is then integrated into a formula in order to obtain the AC Index. In this study a quantification of the visual evaluation of the severity of alligator cracking is carried out using photographs and the fractal dimension concept from fractal theory. Pavements with low levels of cracking were found to have a fractal dimension equal to 1.051. Pavements with moderate levels of cracking had a fractal dimension equal to 1.1754. Pavements with high degrees of cracking had a fractal dimension that varied between 1.5037 (high) and 1.7111 (very high). Pavements with a level of cracking equal to 1.8976 represented pavements that disintegrated and developed potholes. Thus, the visual evaluation of the state of cracking of a pavement (the AC Index) could be enhanced with the use of the fractal dimension concept from fractal theory.