• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.249-250
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• 2002

In this paper, the relationship among the 3-D surface topography parameters are studied. Several surface topography parameters that are important in tribology are calculated against various surface topography data. 3-D surface data with desired properties are generated by using the non-causal 2-D auto-regressive (AR) model. The non-causal 2-D AR model is a random 3-D surface topography model that can generate 3-D surface topography data with specified parameters.

• Proceedings of the KSRS Conference
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• v.1
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• pp.520-523
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• 2006

Whereas it is well known that the surface roughness parameters, the RMS height and the correlation length, of a natural soil surface are underestimated with a short surface profile, it is not clear how much the underestimated surface parameters affect the backscattering coefficients of the surface for various incidence angles and polarizations. The backscattering coefficients of simulated and measured surface profiles are computed using the integral equation method (IEM) and analyzed in this paper to answer this question. It is shown that the RMS error of the backscattering coefficients between 5-m- and 1-m-long measured surface profiles is 1.7 dB for vv-polarization and 0.5 dB for hh-polarization at a medium range of incidence angle ($15^{\circ}{\leq}{\theta}{\leq}70^{\circ}$), while the surface roughness parameters are significantly reduced; from 2.4 cm to 1.5 cm for the RMS height s and from 35.1 cm to 10.0 cm for the autocorrelation length l. This result is verified with numerous simulations with various roughness conditions and various wavelengths.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.457-458
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• 2002

The fractal dimension is the characteristics that can quantitatively define the irregularity in natural. It is useful in describing the morphology or various rubbed surface for hydraulic piston motor instead of the stylus profiling method. But fractal parameters had not constructed on the morphological characteristic or rubbed surface because of the insufficient knowledge about a conception of fractal dimension. In this study, for the purpose or applying fractal I parameters practically, we have suggested way to establish the morphological characteristic of rubbed surface with fractal parameters, and we carried out an experiment on the lubricant friction and wear by using Ball-ON-Disk type tester. Materials were the brass and the bronze which are used to slipper-pad in the hydraulic piston motor. We searched for fractal parameters or surface structure with the digital image processing, Surface fractal dimension can be determined by sum of intensity difference of surface pixel. Using the image processing and fractal parameters for rubbed surface in the friction and wear test, morphology of rubbed sur race can be effectively obtained by fractal dimensions.

• Structural Engineering and Mechanics
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• v.70 no.4
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• pp.395-405
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• 2019

In the present work, the effects of cutting parameters on surface roughness parameters (Ra), tool wear parameters (VBmax), tool vibration (Vy) and material removal rate (MRR) during hard turning of AISI 4140 steel using coated carbide tool have been evaluated. The relationships between machining parameters and output variables were modeled using response surface methodology (RSM). Analysis of variance (ANOVA) was performed to quantify the effect of cutting parameters on the studied machining parameters and to check the adequacy of the mathematical model. Additionally, Multi-objective optimization based desirability function was performed to find optimal cutting parameters to minimize surface roughness, and maximize productivity. The experiments were planned as Box Behnken Design (BBD). The results show that feed rate influenced the surface roughness; the cutting speed influenced the tool wear; the feed rate influenced the tool vibration predominantly. According to the microscopic imagery, it was observed that adhesion and abrasion as the major wear mechanism.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.8
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• pp.93-98
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• 2021

The complex effects of the machining parameters make it is difficult to control and predict surface roughness. The theoretical surface roughness observed during mechanical machining with a round tool is determined by the tool radius and pitch. However, it was revealed that other parameters, such as the depth of cut and cutting speed, also affect surface roughness. This study adapted the Taguchi method, which can analyze the effects of cutting parameters quantitatively with an efficient number of experiments, to optimize the parameters for better surface roughness. Experiments were designed based on an orthogonal array, and the quantitative effects on the surface roughness were analyzed using the S/N ratio. The surface roughness was affected by all parameters, especially the tool radius. The optimum cutting parameter values obtained in this study showed better surface roughness than the other combinations of the parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.12
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• pp.1048-1054
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• 2003

In laser surface hardening processes, the geometrical parameters such as the depth and the width of a hardened layer can be utilized to assess the hardened layer quality. However, accurate monitoring of the geometrical parameters for on-line process control as well as for on-line quality evaluation is very difficult because the hardened layer is formed beneath a material surface and is not visible. Therefore, temperature monitoring of a point of specimen surface has most frequently been used as a process monitoring method. But, a hardened layer depends on the temperature distribution and the thermal history of a specimen during laser surface hardening processing. So, this paper describes the estimation results of the geometric parameters using multi-point surface temperature monitoring. A series of hardening experiments were performed to find the relationships between the geometric parameters and the measured temperature. Estimation results using a neural network show the enhanced effectiveness of multi-point surface temperature monitoring compared to one-point monitoring.

• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.501-513
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• 2020

In the present work, the optimization of machining parameters to achieve the desired technological parameters such as surface roughness, tool radial vibration and material removal rate have been carried out using response surface methodology (RSM). The hard turning of EN19 alloy steel with coated carbide (GC3015) cutting tools was studied. The main problem faced in manufacturer of hard and high precision components is the selection of optimum combination of cutting parameters for achieving required quality of surface finish with maximum production rate. This problem can be solved by development of mathematical model and execution of experiments by RSM. A face centred central composite design (FCCD), which comes under the RSM approach, with cutting parameters (cutting speed, feed rate and depth of cut) was used for statistical analysis. A second-order regression model were developed to correlate the cutting parameters with surface roughness, tool vibration and material removal rate. Consequently, numerical and graphical optimization were performed to obtain the most appropriate cutting parameters to produce the lowest surface roughness with minimal tool vibration and maximum material removal rate using desirability function approach. Finally, confirmation experiments were performed to verify the pertinence of the developed mathematical models.

• Journal of Biosystems Engineering
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• v.22 no.4
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• pp.433-438
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• 1997

The freshness of apple was evaluated by characterizing the surface texture of flesh cells. The freshness index which was related to the amount of wrinkles on the cell surface was defined to quantify the freshness. Four parameters relevant to the amount of the cell wrinkles were selected and measured using image analysis including wrinkle extraction procedure and Fast Fourier Transform of a wrinkle-extracted image. Out of 4 parameters, three parameters had highly significant correlations with the time elapsed after harvest. But it was concluded that two parameters out of such 3 parameters could be used for description of freshness index.

• Geomechanics and Engineering
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• v.15 no.6
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• pp.1207-1217
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• 2018

Geomechanics parameters are critical to numerical simulation, stability analysis, design and construction of geotechnical engineering. Due to the limitations of laboratory and in situ experiments, back analysis is widely used in geomechancis and geotechnical engineering. In this study, a hybrid back analysis method, that coupling numerical simulation, response surface (RS) and relevance vector machine (RVM), was proposed and applied to identify geomechanics parameters from hydraulic fracturing. RVM was adapted to approximate complex functional relationships between geomechanics parameters and borehole pressure through coupling with response surface method and numerical method. Artificial bee colony (ABC) algorithm was used to search the geomechanics parameters as optimal method in back analysis. The proposed method was verified by a numerical example. Based on the geomechanics parameters identified by hybrid back analysis, the computed borehole pressure agreed closely with the monitored borehole pressure. It showed that RVM presented well the relationship between geomechanics parameters and borehole pressure, and the proposed method can characterized the geomechanics parameters reasonably. Further, the parameters of hybrid back analysis were analyzed and discussed. It showed that the hybrid back analysis is feasible, effective, robust and has a good global searching performance. The proposed method provides a significant way to identify geomechanics parameters from hydraulic fracturing.

• Geomechanics and Engineering
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• v.11 no.4
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• pp.515-530
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• 2016

In this paper, five different quantitative parameters were proposed for the characterization of the primary roughness which is the component of surface morphology that prevails during large strike-slip faults of more than 50 m. These parameters are mostly the anisotropic properties of rock surface morphology at various scales: (i) coefficient ($k_a$) and degree (${\delta}_a$) of apparent structural anisotropy of surface; (ii) coefficient ($k_r$) and degree (${\delta}_r$) of real structural anisotropy of surface; (iii) surface anisotropy function P(${\varphi}$); and (iv) degree of surface waviness ($W_s$). The coefficient and degree of apparent structural anisotropy allow qualifying the anisotropy/isotropy of a discontinuity according to a classification into four classes: anisotropic, moderately anisotropic/isotropic and isotropic. The coefficient and degree of real structural anisotropy of surface captures directly the actual surface anisotropy using geostatistical method. The anisotropy function predicts directional geometric properties of a surface of discontinuity from measurements in two orthogonal directions. These predicted data may subsequently be used to highlight the anisotropy/isotropy of the surface (radar plot). The degree of surface waviness allows qualifying the undulation of anisotropic surfaces. The proposed quantitative parameters allows their application at both lab and field scales.