• Korean Journal of Construction Engineering and Management
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• v.14 no.6
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• pp.30-37
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• 2013

Idea creation is the most important step in the overall value engineering (VE) process. Usually the activity is done mostly relying on the experience and knowledge of the experts in the VE team. A more organized approach is needed to find the chance of design improvement during a VE workshop. This study presents an organized approach to increasing the chance of idea creation during the VE workshop. The concept of conflict resolution in TRIZ (Theory of Inventive Problem Solving) is applied to understand the problem area during design improvement. The technical parameters were identified in the problem area to explain the conflicts in design improvement. These technical parameters were used to assist problem solving and improve design functions. A case study was done on a temporary construction operation, and demonstrated that the organized idea creation can help improve the design value of the temporary construction operation.

• Tunnel and Underground Space
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• v.23 no.5
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• pp.428-441
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• 2013

Nowadays, a roadheader as a mechanical excavator is in high demand, especially for mines under various conditions and tunnels where TBMs are inapplicable. However, the records of roadheaders in Korea are seldom reported. Moreover, the number of countries with their intrinsic design and manufacturing technologies of roadheaders is very limited. Therefore, this study aimed to analyse the excavation principles of roadheader as well as its key design parameters for its optimized selection and design. In addition, the database with 143 world-widely collected roadheader design data was built, and a few statistical correlations were derived from it. A schematic procedure for roadheader design based on the database was also proposed.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• Journal of Korea Water Resources Association
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• v.40 no.12
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• pp.957-968
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• 2007

It is essential to obtain accurate and highly reliable streamflow data for quantitative management for water resources. Thereafter such real-time streamflow gauging methods as ultrasonic flowmeter and index-velocity are introduced recently. Since these methods calculate flowrate through entire cross-section by measuring partial velocities of it, rational and theoretical basis are necessary for accurate estimation of discharge. The purpose of the present study lies in analysis on the applicability of Chiu#s(1987, 1988) two dimensional velocity distribution equations by applying them to natural rivers and by comparing simulated velocity distributions with observed ones obtained with ADCP. Maximum and mean velocities are calculated from observed data to estimate entropy parameter M. Such isovel shape parameters as h and $\beta_i$ are estimated by object function based on least squares criterion. In case optimized parameters are applied, Chiu#s velocity distributions fairly well simulate observed ones. By using 14 simulated data sets which have relatively high correlation coefficients, properties of parameters are analyzed and h, $\beta_i$ are estimated for velocity-unknown river sections. When estimated parameters are adopted for verification, simulated velocity distributions well reproduce real ones. Finally, calculated discharges display rough agreement with measured data. The results of the present study mean that if parameters related are properly estimated, Chiu#s velocity distribution is likely to reproduce the real one of natural rivers.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.347-362
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• 2019

Underground excavation using TBM machines has been increasing to reduce complaints caused by noise, vibration, and traffic congestion resulted from the urban underground construction in Korea. However, TBM excavation design and construction still need improvement because those are based on standards of the technologically advanced countries (e.g., Japan, Germany) that do not consider geological environment in Korea at all. Above all, although TBM performance is a main factor determining the TBM machine type, duration and cost of the construction, it is estimated by only using UCS (uniaxial compressive strength) as the ground parameters and it often does not match the actual field conditions. This study was carried out as part of efforts to predict penetration rate suitable for Korean ground conditions. The effective parameters were defined through the correlation analysis between the penetration rate and the geotechnical parameters or TBM performance parameters. The effective parameters were then used as variables of the multiple regression analysis to derive a regression model for predicting TBM penetration rate. As a result, the regression model was estimated by UCS and joint spacing and showed a good agreement with field penetration rate measured during TBM excavation. However, when this model was applied to another site in Korea, the prediction accuracy was slightly reduced. Therefore, in order to overcome the limitation of the regression model, further studies are required to obtain a generalized prediction model which is not restricted by the field conditions.

• Computers and Concrete
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• v.8 no.3
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• pp.279-292
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• 2011

The main purpose of this study includes investigation of the rheological properties of fresh self consolidating cement paste containing chemical and mineral additives using Artificial Neural Network (ANN) model. In order to develop the model, 200 different mixes are cast in the laboratory as a part of an extensive experimental research program. The data used in the ANN model are arranged in a format of fourteen input parameters covering water-binder ratio, four different mineral additives (calcium carbonate, metakaolin, silica fume, and limestone), five different superplasticizers based on the poly carboxylate and naphthalene and four different Viscosity Modified Admixtures (VMAs). Two common output parameters including the mini slump value and flow cone time are chosen for measuring the rheological properties of fresh self consolidating cement paste. Having validated the model, the influence of effective parameters on the rheological properties of fresh self consolidating cement paste is investigated based on the ANN model outputs. The output results of the model are then compared with the results of previous studies performed by other researchers. Ultimately, the analysis of the model outputs determines the optimal percentage of additives which has a strong influence on the rheological properties of fresh self consolidating cement paste. The proposed ANN model shows that metakaolin and silica fume affect the rheological properties in the same manner. In addition, for providing the suitable rheological properties, the ANN model introduces the optimal percentage of metakaolin, silica fume, calcium carbonate and limestone as 15, 15, 20 and 20% by cement weight, respectively.

• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.167-175
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• 2002

Image Mosaicing creates a new image by composing video frames or still images that are related, and performed by arrangement, composition and redundancy analysis of images. This paper proposes a hierarchical image mosaicing system using camera and object parameters far efficient video database construction. A tree-based image mosiacing has implemented for high-speed computation time and for construction of static and dynamic image mosaic. Camera parameters are measured by using least sum of squared difference and affine model. Dynamic object detection algorithm has proposed for extracting dynamic objects. For object extraction, difference image, macro block, region splitting and 4-split detection methods are proposed and used. Also, a dynamic positioning method is used for presenting dynamic objects and a blurring method is used for creating flexible mosaic image.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.1
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• pp.1-7
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• 2012

This paper presents a method for 3D image construction using the hybrid (color and depth) camera system, in which the drawbacks of each camera can be compensated for. Prior to an image generation, intrinsic parameters and extrinsic parameters of each camera are extracted through experiments. The geometry between two cameras is established with theses parameters so as to match the color and depth images. After the preprocessing step, the relation between depth information and distance is derived experimentally as a simple linear function, and 3D image is constructed by coordinate transformations of the matched images. The present scheme has been realized using the Microsoft hybrid camera system named Kinect, and experimental results of 3D image and the distance measurements are given to evaluate the method.

• Journal of Korean Society of Steel Construction
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• v.20 no.1
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• pp.43-53
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• 2008

Because the torque control method, which is also caled the clamping method in domestic construction sites, is affected by a variation of the torque coefficient, quality control of the torque coefficient is essential. This study was focused to evaluate the effects of several environmental factors and errors when installing bolts while tightening high-strength bolts. Conditioning environmental parameters include wet, rusty and exposure-to-air-only conditions. In addition, because of errors in workability such as instalation of two washers, upset washers are selected. During the tests, torque, torque coefficient, tension and angle of nut rotation were obtained using a bolt testing machine. Test specimens of four types of bolts (High-Strength Hexagon bolt on KS B 1010, Torque Shear Bolt on KS B 2819, High-Strength Hexagon bolt coated with zinc, and ASTM 490 bolt) were recomended. Based on test results, the tightening characteristics subjected to environmental parameters were investigated and compared with the results in normal condition.

• Geomechanics and Engineering
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• v.37 no.3
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• pp.223-241
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• 2024

Evaluating the performance of Tunnel Boring Machines (TBMs) stands as a pivotal juncture in the domain of hard rock mechanized tunneling, essential for achieving both a dependable construction timeline and utilization rate. In this investigation, three advanced artificial neural networks namely, gated recurrent unit (GRU), back propagation neural network (BPNN), and simple recurrent neural network (SRNN) were crafted to prognosticate TBM-rate of penetration (ROP). Drawing from a dataset comprising 1125 data points amassed during the construction of the Alborze Service Tunnel, the study commenced. Initially, five geomechanical parameters were scrutinized for their impact on TBM-ROP efficiency. Subsequent statistical analyses narrowed down the effective parameters to three, including uniaxial compressive strength (UCS), peak slope index (PSI), and Brazilian tensile strength (BTS). Among the methodologies employed, GRU emerged as the most robust model, demonstrating exceptional predictive prowess for TBM-ROP with staggering accuracy metrics on the testing subset (R² = 0.87, NRMSE = 6.76E-04, MAD = 2.85E-05). The proposed models present viable solutions for analogous ground and TBM tunneling scenarios, particularly beneficial in routes predominantly composed of volcanic and sedimentary rock formations. Leveraging forecasted parameters holds the promise of enhancing both machine efficiency and construction safety within TBM tunneling endeavors.