• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.5
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• pp.115-120
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• 2006

A Korean Road Roughness Classification(KRC) method is proposed. Using a dynamic road profiling device equipped with the Accelerometer Established Inertial Profiling Reference(AEIPR) method, road profile measurement is performed on various types of public paved roads in Korea. The road profiling data are processed to classify the characteristics of Korean road roughness. The resultant Korean road roughness classification(KRC) is shown different characteristics compared to the road classification proposed by ISO, MIRA, and Wong. The proposed KRC is composed of 8 classes(A-H, very good-poor) based on the power spectral density and is in good agreements with the characteristics of Korean paved road roughness and can be used well in vehicle ride comfort simulation using domestic road profile.

• Journal of Korean Tunnelling and Underground Space Association
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• v.8 no.2
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• pp.183-196
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• 2006

Rock joint roughness obtained from the camera-type 3D scanner was classified into waviness and unevenness. The classification criteria were established in the previous study; digital filtering was used to distinguish one from another. The classified and original profiles were used to produce metal moulds. For accurate machining of the moulds, the WEDM(Wire-cut Electric Discharge Machining) was adopted. Specimens were cast using high strength gypsum, and joint shear tests were performed by varying normal stress from low value to high one. Roughness mobilization characteristics depending on the asperity scale and the applied normal stress were investigated. A new equation was proposed to predict shear strength of rock joint, which can consider the characteristics of roughness mobilization and roughness parameters. The roughness quantification composed of waviness and unevenness was found to be a useful method to predict the joint shear strength.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.1
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• pp.39-49
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• 2019

Acoustics are increasingly regarded as a remote-sensing tool that provides the basis for classifying and mapping ocean resources including seabed classification. It has long been understood that details about the character of the seabed (roughness, sediment type, grain-size distribution, porosity, and material density) are embedded in the acoustical echoes from the seabed. This study developed a sophisticated yet easy-to-use technique to discriminate seabed characteristics using a split beam echosounder. Acoustic survey was conducted in Tongyeong waters, South Korea in June 2018, and the verification of acoustic seabed classification was made by the Van Veen grab sampler. The acoustic scattering signals extracted the seabed hardness and roughness components as well as various seabed features. The seabed features were selected using the principal component analysis, and the seabed classification was performed by the K-means clustering. As a result, three seabed types such as sand, mud, and shell were discriminated. This preliminary study presented feasible application of a sounder to classify the seabed substrates. It can be further developed for characterizing marine habitats on a variety of spatial scales and studying the ecological characteristic of fishes near the habitats.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.1-8
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• 2012

Obstacle detection is much studied by using sensors such as laser, vision, radar and ultrasonic in path planning for UGV(Unmanned Ground Vehicle), but not much reported about its characterization. In this paper not only an obstacle classification method using 2-dimensional LMS(Laser Measurement System) but also a decision making method whether to avoid or traverse the obstacle is proposed. The basic idea of decision making is to classify the characteristics by 2D laser scanned data and intensity data. Roughness features are obtained by range data using a simple linear regression model. The standard deviations of roughness and intensity data are used as measures for decision making by comparing with those of reference data. The obstacle classification and decision making for the UGV can facilitate a short path to the target position and the survivability of the robot.

• Tunnel and Underground Space
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• v.25 no.2
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• pp.210-219
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• 2015

This paper describes a new quantitative process for evaluating the roughness of discontinuity, which is suggested as a qualitative criteria in RMR or Q-system. For this purpose, the Delphi method which is one of the surveying methods was introduced. The selected panels were asked to evaluate the roughness of discontinuities on the Web which was hosted by authors in advance. A total of 3 surveys were performed using JRCs suggested by Barton and Choubey as well as Ai generated by the Monte Carlo simulations. After each survey, the results were provided to all panels for comparing their decisions to others. As surveys proceeded, better consensus and convergence were achieved. With a good agreement of panels on roughness classification, the quantitative criteria for roughness of discontinuity in RMR and Q-system was established in this study.

• 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.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1205-1210
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• 2005

The behavior of rock mass and solute(e.g. groundwater, radioactivity) flow in fractured rock can be directly influenced by joint roughness. The characteristics of joint roughness is also a main factor for the rock classification(e.g. RMR, Q system) which is usually used in tunnel design. Nevertheless, most of JRC estimation has been carried out only by the examination with the naked eye. This JRC estimation has a lack of objectivity because each investigator judges JRC by his subjective opinion. Therefore, it will be desirable that the assessment of JRC is performed by a numerical analysis which can give a quantitative value corresponding to the characteristics of a roughness curve. Meanwhile, roughness curves for joint surfaces which are observed in drill cores have been obtained only along linear profiles. Although roughness curves are measured in the same joint surface, they can frequently show diverse aspects in a standpoint of roughness characteristics. If roughness curves can be measured along the elliptical circumferences of joint surfaces from core scanning images or Televiewer images, they will certainly be more comprehensive than those measured along linear profiles for roughness characteristics of joint surfaces. This study is focus on dealing with (1) extracting automatically roughness curves from core scan image or Televiewer image, (2) improving the accuracy of quantitative assessment of JRC using fractal dimension concept.

• Journal of Korean Society of Water and Wastewater
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• v.21 no.3
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• pp.287-294
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• 2007

When we use the circular pipes for wastewater and storm water, we should be known the characteristics of the flow for accurate design. To elevate the design accuracy, we want to know the profile of flow. The roughness coefficient in the Manning equation is constant, but in actuality changed with the relative depth in circular pipe. This study was conducted to calculate the relative normal depth in changing the roughness coefficient (named relative roughness coefficient) with the relative depth in the analysis of gradually varied flow in the circular pipe by Newton-Raphson method. We performed the analysis of gradually varied flow using the relative normal depth and the relative roughness coefficient. We presented the 12 flow profiles with the relative depth and the relative roughness coefficient in circular pipe. The flow classification considering relative depth in circular pipe is available to analyse gradually varied flow profiles.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.6
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• pp.120-126
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• 2006

Vehicle dynamic simulation has been carried out using the coherence of road roughness between left and right wheels. The generated twin tracks with the coherence of road roughness between left and right wheels are in good agreements with the measured coherence relation of left and right wheels. And these tracks reflect well on the roughness characteristics of real roads. Using the generated roads and multibody dynamic simulation program, vehicle dynamic simulation is performed. The vertical and roll motion analysis of a vehicle are carried out using the realistic road profiles with the coherence between left and right wheels and the results are in good agreements with the dynamic characteristics of a vehicle.

• Journal of Korean Tunnelling and Underground Space Association
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• v.7 no.4
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• pp.269-283
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• 2005

To figure out the cause of underestimating the roughness and shear strength of rock joints suggested by numerous researchers, we analyzed roughness mobilization characteristics, characteristics of roughness parameters, effects of sampling interval, and waviness for roughness parameters. It was found out that lack of understanding of the roughness mobilization characteristics, inappropriate applications of roughness parameters, and effect of aliasing provide a main reasons for those problems. Several practical alternatives for improving those problems were suggested. As far as digitizing methods are concerned, we can find that using a 3D scanner can give a relatively effective result. To avoid aliasing, sampling interval should be less than one-quarter of the minimum asperities. As for the quantification of roughness, it was analyzed that the roughness parameter should be classified into two components depending on the scale of roughness to apply the shear strength model. For classifying the roughness, a framework of the criterion was suggested based on the plastic flow concept for the asperity failure, and the basis for proposing a new alternative shear strength model was established.