• Geomechanics and Engineering
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• v.24 no.4
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• pp.359-370
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• 2021

Joint roughness is combination of primary and secondary roughness. Ordinarily primary roughness is a geostatistical part of a joint surface that has a periodic nature but secondary roughness or unevenness is a statistical part of that which have a random nature. Using roughness generating algorithms is a useful method for evaluation of joint roughness. In this paper after determining geostatistical parameters of the joint profile, were presented two roughness generating algorithms using Mount-Carlo method for evaluation of primary (GJRGAP) and secondary (GJRGAS) roughness. These based on geostatistical parameters (range and sill) and statistical parameters (standard deviation of asperities height, SDH, and standard deviation of asperities angle, SDA) for generation two-dimensional joint roughness profiles. In this study different geostatistical regions were defined depending on the range and SDH. As SDH increases, the height of the generated asperities increases and asperities become sharper and at a specific range (a specific curve) relation between SDH and SDA is linear. As the range in GJRGAP becomes larger (the base of the asperities) the shape of asperities becomes flatter. The results illustrate that joint profiles have larger SDA with increase of SDH and decrease of range. Consequencely increase of SDA leads to joint roughness parameters such Z2, Z3 and RP increases. The results showed that secondary roughness or unevenness has a great influence on roughness values. In general, it can be concluded that the shape and size of asperities are appropriate parameters to approach the field scale from the laboratory scale.

• Tunnel and Underground Space
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• v.12 no.4
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• pp.268-276
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• 2002

In this study, a 3D coordinate measurement system equipped with a laser displacement meter for digitizing rock joint surface was established and the digitized data were used to calculate several roughness parameters. The parameters used in this study were micro avenge inclination $angle(i_{ave})$, average slope of joint $asperity(SL_{ ave})$, root mean square of $i-angle(i_{rms})$, standard deviation of height(SDH), standard deviation of $i-angle(SD_i)$, roughness profile $index(R_P)$, and fractal dimension(D). The relationships between the roughness parameters based on the digitzation of the surface profile were analyzed. Since the measured value varied according to the degree of reflection and the variation of colors at the measuring point, rock joint surface was painted in white to minimize the influence of the surface conditions. The comparison of the measured values and roughness parameters before and after painting revealed the better consequence from measurement on the painted surfaces. Also, effect of measuring interval was studied. As measured interval was increased, roughness parameters were exponentially decreased. The incremental sequence of degree of decrease was $SDH\; i_{ave},\; i_{rms},\; SD_i,\;and\; R_ p-1$. As a result of comparison of parameters from pin-type measurement system and laser type measurement system, all value of parameters were higher when laser-type measurement system was used, except SDH.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.89-94
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• 2001

This paper presents a study of surface roughness prediction model by orthogonal design in turning operation. Regression analysis technique has been used to study the effects of the cutting parameters such as cutting speed, feed depth of cut, and nose radius on surface roughness. An effect of interaction between two parameters on surface roughness has also been investigated. The experiment has been conducted using coated tungsten carbide inserts without cutting fluid. The reliability of the surface roughness model as a function of the cutting parameters has been estimated. The results show that the experimental design used in turning process is a method to estimate the effects of cutting parameters on sur-face roughness.

• 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 the Korean Geotechnical Society
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• v.15 no.4
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• pp.247-260
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• 1999

It was found that surface roughness has a first-order effect on the interface shear strength and accordingly it should be accurately quantified if its role is to be properly understood. Most of the surface roughness parameters are based on the trisector approach (three dimensional parameter) which can provide a good measure of the surface roughness from a static perspective. However, if roughness is to be correlated with a directional sensitive parameter such as interface shear then a two dimensional parameter could be more meaningful if the roughness measurements are made parallel to the direction of shearing. In this paper, alternative roughness parameters which consider the direction of shearing are described. These directional parameters are compared with the existing roughness parameters, and the relationship between these directional and non-directional parameters are investigated. The surface roughness was quantified by using the Optical Profile Microscopy (OPM) method (Dove and Frost, 1996) based on the digital image analysis. The results showed that the various surface roughness parameters measured in this study exhibit similar trend of roughness values, so that, good relationships are obtained between these roughness parameters. As the surface roughness increases, the roughness values measured in trisector coupons are increasing higher than those measured in parallel coupons.

• 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.1 no.1
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• pp.133-140
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• 2002

The object of this paper is to predict the surface roughness using the experiment equation of surface roughness, which is developed with a full factorial design in turning. $3^3$ full factorial design has been used to study main and interaction effects of main cutting parameters such as cutting speed, feed rate, and depth of cut, on surface roughness. For prediction of surface roughness, the arithmetic average (Ra) is used, and stepwise regression has been used to check the significance of all effects of cutting parameters. Using the result of these, the experimental equation of surface roughness, which consists of significant effects of cutting parameters, has been developed. The coefficient of determination of this equation is 0.9908. And the prediction ability of this equation was verified by additional experiments. The result of that, the coefficient of determination is 0.9718.

• 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.

• Tunnel and Underground Space
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• v.22 no.3
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• pp.196-204
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• 2012

Quantification of roughness plays an important role in modeling strength deformability and fluid flow behaviors of rock joints. A procedure was suggested to simulate joint roughness, and characteristics of the roughness was investigated in this study. Stationary fractional Brownian profiles with known input values of the fractal parameter and other profile properties were generated based on random midpoint displacement method. Also, a procedure to simulate three dimensional roughness surface was suggested using the random midpoint displacement method. Selected statistical roughness parameters were calculated for the generated self-affine profiles to investigate the attribute of roughness. Obtained results show that statistical parameters applied in this study were able to consider correlation structure and amplitude of the profiles. However, effect of data density should be tackled to use statistical parameters for roughness quantification.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.11c
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• pp.57-68
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• 1999

This paper summarizes the results of a study which uses the recently developed Optical Profile Microscopy technique (Dove and Frost, 1996) as the basis for investigating the role of geomembrane surface roughness on the shear mechanism of geomembrane/geotextile interfaces. The alternative roughness parameters which consider the direction of shearing are described. These directional parameters are compared with the existing roughness parameters, and the relationship between these directional and non-directional parameters are investigated. Then, the relationship between interface shear strength and surface roughness quantified at the interface is investigated. The results show that interface friction can be quantitatively related to the surface roughness of the geomembrane. The peak and residual interface strengths increase dramatically through the use of textured geomembranes as opposed to smooth geomembranes. For the smooth geomembranes, the sliding of the geotextile is the main shear mechanism. For the textured geomembranes, the peak interface strength is mainly mobilized through the micro-texture of the geomembrane, however, the residual interface strength is primarily attributed to macro scale surface roughness which pulls out and breaks the filaments from the geotextile. The results of this study can be extended to the other interfaces such as joints in rock mass, and also can be used to provide a quantitative framework that can lead to a significantly improved basis for the selection and design of geotextiles and geomembranes in direct contact.