• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.4 no.3
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• pp.155-162
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• 1992

Theoritical Study is performed on heat transfer and fluid flow induced by square-ribbed roughness elements in a concentric annulus. The fluid properties were assumed to be constant, and the radius($r_m$) of the maximum speed point was found by using the principle of equation of Leung and Labib. The Nusselt number and friction factor as a function of the Reynolds number($R_e=10^4$, $5{\times}10^4$, $7{\times}10^4$, $10^5$) in artifical roughness $S/{\epsilon}=5,10,20,30$, $P/{\epsilon}=2,5,8$ and prandtl number = 0.72 have been discussed. In this study, it has been found that the Nusselt number and friction factor of rough wall are larger than those of smooth ones.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.5
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• pp.55-60
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• 2021

We applied an artificial neural network (ANN) and evaluated surface roughness prediction in lateral milling using an endmill. The selected workpiece was AL6061-T4 to obtain data of surface roughness measurement based on the spindle speed, feed, and depth of cut. The Bayesian optimization algorithm was applied to the number of nodes and the learning rate of each hidden layer to optimize the neural network. Experimental results show that the neural network applied to optimize using the Expected Improvement(EI) algorithm showed the best performance. Additionally, the predicted values do not exactly match during the neural network evaluation; however, the predicted tendency does march. Moreover, it is found that the neural network can be used to predict the surface roughness in the milling of aluminum alloy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.117-124
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• 2021

The development of IOT technology and artificial intelligence technology is promoting the smartization of manufacturing system. In this study, data extracted from acceleration sensor and current sensor were obtained through experiments in the cutting process of SKD11, which is widely used as a material for special mold steel, and the amount of tool wear and product surface roughness were measured. SVR (Support Vector Regression) is applied to predict the roughness of the product surface in real time using the obtained data. SVR, a machine learning technique, is widely used for linear and non-linear prediction using the concept of kernel. In particular, by applying GSVQR (Generalized Support Vector Quantile Regression), overestimation, underestimation, and neutral estimation of product surface roughness are performed and compared. Furthermore, surface roughness is predicted using the linear kernel and the RBF kernel. In terms of accuracy, the results of the RBF kernel are better than those of the linear kernel. Since it is difficult to predict the amount of tool wear in real time, the product surface roughness is predicted with acceleration and current data excluding the amount of tool wear. In terms of accuracy, the results of excluding the amount of tool wear were not significantly different from those including the amount of tool wear.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.54-61
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• 1999

The fully developed turbulent momentum and heat transfer induced by the roughness elements on the outer wall surfaces in concentric annuli are analytically studied on the basis of a modified turbu-lence model. The resulting momentum and heat transfer are discussed in terms of various parame-ters such as the radius ratio the roughness density Reynolds number and Prandtl number accord-ing to the heating condition. The study shows that certain artificial roughness elements may be used to enhance heat transfer rates with advantage from the overall efficiency point of view.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1294-1303
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• 1993

The fully developed turbulent momentum and heat transfer induced by the square-ribed roughness elements on the inner wall surface in concentric annuli is studied analytically based on a modified turbulence model. The analytical results of the fluid flow is verified by experiment. The resulting momentum and heat transfer are discussed in terms of various parameters, such as the radius ratio, the relative roughness, the roughness density, fluid Reynolds number and for heat transfer, fluid Prandtl number. The study demonstrates that certain artificial roughness elements may be used to enhance heat transfer rates with advantages from the overall efficiency point of view.

• The Journal of Engineering Geology
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• v.14 no.2
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• pp.147-168
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• 2004

Purpose of this study is to quantitatively characterize the fracture roughness which was measured with a confocal laser scanning microscope. The roughness discrete data measured by confocal laser microscope were analyzed by spectral analysis and fast Fourier transform (FFT).The roughness data by used noise reduction filter were applied for fractal analysis to describe roughness features quantitatively. Artificial fractures created by Brazilian test on granites were used to measure fracture roughness under the confocal laser scanning microscope. Measurements were performed along three scan lines on each fracture surface. 36 scan lines were determined on 12 specimens in total. Features of roughness showed that coarse and medium grained granites tend to more rough features than those of fine grained granites. Continuous analog data of roughness is possible to described as discrete data of measure roughness with a fixed interval under the confocal laser microscope. Results of FFT with the measured data showed the highest values on the second harmonics. Distribution of average amplitude of second harmonics was observed 0.9853 in coarse grained granite, 1.0792 in medium grained granite and 0.6794 in fine grained granite. This indicates that the larger roughness has the higher energy of harmonics as the result of fractal analysis in low frequency zone.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.184-189
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• 2008

In this study, an artificial wheel load generation method is proposed to assist practical engineers performing dynamic analysis with simple procedure. To generate an artificial wheel loads from running vehicle, PSD(Power Spectrum Density) profiles of actual wheel load were sampled in terms of various road roughnesses. A detailed truck and bridge models were used for sampling actual wheel load to represent the real motion of moving vehicle. These wheel load profiles were simplified for the artificial wheel load. The simplification of actual wheel load profiles was performed by regression analysis. The result showed that the artificial wheel load well represents the real profiles of wheel load.

• Corrosion Science and Technology
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• v.20 no.6
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• pp.475-483
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• 2021

Additively manufactured titanium alloy is one of the promising materials in advanced medical industries. However, these additively manufactured alloys show corrosion properties different from those of conventional materials due to their unique microstructure. In this study, the effect of surface roughness and masking conditions on the results of the potentiodynamic polarization tests on additively manufactured or conventional Ti-6Al-4V alloys in artificial saliva solution with or without fluoride was investigated. The results showed that the corrosion potential was slightly lower with a flat cell with an O-ring than with masking tape. The corrosion rate was decreased with decreases in the surface roughness. Localized corrosion involving delamination of the surface layer occurred at 7 ~ 9 V (SSC) on the additively manufactured alloy in solution with or without fluoride when the samples were finished with 1000-grit SiC paper, whereas localized corrosion was not observed in the specimens finished with 1-㎛ alumina paste.

• Tunnel and Underground Space
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• v.26 no.6
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• pp.516-523
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• 2016

Roughness of a joint surface is one of the most important parameters that affects the mechanical and hydraulic behavior of rock mass. Therefore, various studies on making constitutive model and/or roughness quantification have been conducted in experimental and empirical manners. Advances in recent 3D printing technology can be utilized to generate a joint surface with a specific roughness. In this study, a reliable technique to generate a rough joint surface was introduced and its quantitative assessment was made. Random midpoint displacement method was applied to generate a joint surface and the distribution of $Z_2$ was investigated to assess its roughness. As a result, a certain roughness can be embodied by controlling input parameters and furthermore it was able to generate a joint surface with specific roughness anisotropy.

• Tunnel and Underground Space
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• v.4 no.3
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• pp.274-286
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• 1994

Direct shear tests were on ducted in a laboratory setting in order to investigate the shear strength and deformation behavior of rock joints. Also, the characteristics of acoustic emissions (AE) during shearing of rock joints were studied. The artificial rock joints were created by splitting the intact blocks of Hwangdeung granites and Iksan marbles. Joint roughness profiles were measured by a profile gage and then digitized by Image analyzer. Roughness profile indices(Rp) of the joints were calculated with these digitized data. Peak shear strength, residual shear strength, shear stiffness and maximum acoustic emission(AE) rate were investigated with joint roughness. The peak shear strenght, the residual shear strength and the shear stiffness were increased as roughness popfile index or normal stress increased in the shear tests of granites. In the tests of marble samples, the shear deformation characteristics were not directly affected by joint roughness. As the result of two directional shear tests, the shear characteristics were varied with shear direction. AE count rates were measured during the shear deformation and the AE signals in several stages of the deformation were analyzed in a frequency domain. The AE rate peaks coincided with the stress drops during the shear deformation of joint. The dominant frequencies of the AE signals were in the vicinity of 100 kHz fo rgranite sample and 900 kHz for marble samples. The distribution of amplitude was dispersed with increasing normal stress.