• Journal of Korean Tunnelling and Underground Space Association
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• v.3 no.4
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• pp.17-24
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• 2001

Four road tunnels of which the construction conditions were similar were selected in the paper, and laboratory tests and rockmass classification for the tunnels were carried out. And the analysis was performed to find out the correlation between ratio of bit abrasion or drilling parameter and support pattern of tunnel using jumbo drill machine. It was analyzed that there was average abrasion of bit from 11.85% to 3.25% per support patterns of tunnel in four tunnels. Drilling parameter happens to fluctuate according to extent of fracture zone.

• Geomechanics and Engineering
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• v.7 no.5
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• pp.553-567
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• 2014

Borehole instability during drilling process occurs frequently when drilling through shale formation. When a borehole is drilled in shale formation, the low permeability leads to an undrained loading condition. The pore pressure in the compressed area near the borehole may be higher than the initial pore pressure. However, the excess pore pressure caused by stress concentration was not considered in traditional borehole stability models. In this study, the calculation model of excess pore pressure induced by drilling was obtained with the introduction of Henkel's excess pore pressure theory. Combined with Mohr-Coulumb strength criterion, the calculation model of collapse pressure of shale in undrained condition is obtained. Furthermore, the variation of excess pore pressure and effective stress on the borehole wall is analyzed, and the influence of Skempton's pore pressure parameter on collapse pressure is also analyzed. The excess pore pressure decreases with the increasing of drilling fluid density; the excess pore pressure and collapse pressure both increase with the increasing of Skempton's pore pressure parameter. The study results provide a reference for determining drilling fluid density when drilling in shale formation.

• Advances in materials Research
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• v.13 no.1
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• pp.1-18
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• 2024

The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm²) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm²) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.99-103
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• 2012

Presently, A glass is widely used in telecommunication system, optoelectronic devices and micro electro mechanical systems. Micro drilling of glass using the laser can save processing cost and improve the accuracy. This paper experiments micro drilling using KrF excimer laser on the pyrex glass of $500{\mu}m$ thickness. We have experiment to find out optimum laser machining conditions of micro drilling of glass and ablation depth and influence by processing parameter suc'h pulse repetition rate, energy density and number of pulses. Pulse repetition rate don't influence ablation depth at the micro drilling of pyrex glass. Energy density influence micro drilling of parallelism and maximum thickness that can be drilled. Ablation depth is most influenced by number of pulses.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.61-69
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• 2020

The uniaxial compressive strength (UCS) of rock is a basic parameter in underground engineering design. The disadvantages of this commonly employed laboratory testing method are untimely testing, difficulty in performing core testing of broken rock mass and long and complicated onsite testing processes. Therefore, the development of a fast and simple in situ rock UCS testing method for field use is urgent. In this study, a multi-function digital rock drilling and testing system and a digital core bit dedicated to the system are independently developed and employed in digital drilling tests on rock specimens with different strengths. The energy analysis is performed during rock cutting to estimate the energy consumed by the drill bit to remove a unit volume of rock. Two quantitative relationship models of energy analysis-based core drilling parameters (ECD) and rock UCS (ECD-UCS models) are established in this manuscript by the methods of regression analysis and support vector machine (SVM). The predictive abilities of the two models are comparatively analysed. The results show that the mean value of relative difference between the predicted rock UCS values and the UCS values measured by the laboratory uniaxial compression test in the prediction set are 3.76 MPa and 4.30 MPa, respectively, and the standard deviations are 2.08 MPa and 4.14 MPa, respectively. The regression analysis-based ECD-UCS model has a more stable predictive ability. The energy analysis-based rock drilling method for the prediction of UCS is proposed. This method realized the quick and convenient in situ test of rock UCS.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.47.1-47
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• 2001

The drilling process has a great importance for the production technology due to its widerspread use in the manufacturing industry. In order to enhance a maximum production rate and prevent the drill from the damage, it is important to monitor and control the drilling system. Thrust force and cutting torque are the main output variables in the design of drilling control systems. In this paper, an alternative estimation method of thrust force by using flexible neural networks is proposed. Flexible neural network uses the sigmoid activation function with adjustable parameter in order to enhance the approximation accuracy ...

• Tunnel and Underground Space
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• v.18 no.6
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• pp.480-490
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• 2008

The drilling monitoring is a technique to assess rock mass properties by analyzing the mechanical quantities measured by drilling process. Since drilling survey can be conducted on real-time-basis for excavating blast holes or rockbolt holes, it may enables fast and quantitative prediction and evaluation of rock mass. Though a number of studies have been conducted on the drilling data, the selection of drilling parameters and numerical quantification of mechanical quantities or rock mass have not been well established yet. In this study, drilling tests were conducted with homogeneous rock specimen to identify drilling parameters and the relation of the drilling data. As a result, it is verified that above all drilling parameters, the percussion was the most important factor on the excavatability of hydraulic drilling.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.111-119
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• 2024

In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R²) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1523-1532
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• 1990

The objective of this study is to develope an optimized multi-facet drill (MFD). The principal factors that affect drilling performance are its geometry and the cutting conditions. In particular, the helix angle in the total twist angle of the twist drill, affects much morgen influence on the dynamic and static stiffness and on determining the characteristics of the chip disposal capacity of the drill. In this study, considering the helix angle as a major parameter, the model was developed. From this model, the deformation of transverse direction was simulated with the bending forces applied. The performance of a drill largely depends upon drilling forces. Comprehensive models for predicating the drilling thrust and torque are developed for the different drill geometries. The effects of MFD geometric parameters on thrust and torque are also deduced from the prediction models, from which an optimal drill geometry is found with the emphasis on minimum drilling forces.

• Journal of the Korean Institute of Gas
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• v.24 no.1
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• pp.66-75
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• 2020

Drilling operation is the most important and costly essential work in oil and gas exploration and development. Therefore, the studies about rate of penetration have been carried out continuously to improve drilling efficiency. In recent years, data-driven models have been developed by various researchers to overcome disadvantages of traditional mathematical models. For the data-driven models, selecting proper algorithms and parameters is very important. In addition, data-driven models should be retrained in real-time during continuous drilling operations in order to improve the model performance. In this paper, the latest studies are investigated to provide information about algorithms, drilling parameters and model retraining intervals that used in drilling optimization.