• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.229-232
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them..

• Journal of computational fluids engineering
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• v.20 no.2
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• pp.1-6
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• 2015

In this study, a numerical prediction on propulsive performance of a ducted propeller in open water condition was carried out by solving Reynolds averaged Navier-Stokes(RANS) equation using computational fluid dynamics(CFD). A configuration of propeller Ka-470 inside duct 19A was considered. Hexahedral grid system was generated by dividing whole computational domain into three separate regions; propeller, duct and outer flow region. A commercial CFD software, ANSYS-CFX was used for numerical simulations. Results were compared with experimental data and showed considerable improvement in accuracy, in comparison to those from surface panel method which is based on potential flow assumption. The results also exhibited the importance of grid system within the gap between the inner surface of duct and blade tip for accurate prediction of propulsive performance of ducted propeller.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.1
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• pp.144-153
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• 2017

In recent years, unmanned aerial vehicles (UAVs) have been developed and studied for various applications, including drone deliveries, broadcasting, scouting, crop dusting, and firefighting. To enable the wide use of UAVs, their exact aeroacoustic characteristics must be assessed. In this study, a noise prediction method for a ducted fan UAV with complicated geometry was developed. In general, calculation efficiency is increased by simulating a ducted fan UAV without the struts that fix the fuselage to the ducts. However, numerical predictions of noise and aerodynamics differ according to whether struts are present. In terms of aerodynamic performance, the total thrust with and without struts is similar owing to the tendency of the thrust of a blade to offset the drag of the struts. However, in aeroacoustic simulations, the strut effect should be considered in order to predict the UAV's noise because noise from the blades can be changed by the strut effect. Modelling of the strut effect revealed that the dominant tonal noises were closely correlated with the blade passage frequency of the experimental results. Based on the successful detection of noise sources from a ducted fan UAV system, using the proposed noise contribution contour, methods for noise reduction can be suggested by comparing numerical results with measured noise profiles.

• Geomechanics and Engineering
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• v.22 no.1
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• pp.25-33
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• 2020

In metropolitan areas, the quantity and density of the underground structure increase rapidly in recent years. Even though most damage incidents of the underground structure were minor, there were still few incidents causing a great loss in lives and economy. Therefore, the safety evaluation of the underground structure becomes an important issue in the disaster prevention plan. Liquefaction induced uplift is one important factor damaging the underground structure. In order to perform a preliminary evaluation on the safety of the underground structure, simplified prediction equations were introduced to provide a first order estimation of the liquefaction induced uplift. From previous studies, the input motion is a major factor affecting the magnitude of the uplift. However, effects of the input motion were not studied and included in these equations in an appropriate and rational manner. In this article, a numerical simulation approach (FLAC program with UBCSAND model) is adopted to study effects of the input motion on the uplift. Numerical results show that the uplift and the Arias Intensity (Ia) are closely related. A simple modification procedure to include the input motion effects in the Sasaki and Tamura prediction equation is proposed in this article for engineering practices.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.6
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• pp.476-484
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• 2007

Recently, in accordance with the buildings are becoming to large-sizes, high-stories, the large scaled facilities and equipments in machine room are quite demanding, and the generated noise volume according to this situation is on increasing. Since such noise is becoming to the object of a serious civil appeal, it is the real situation that a reduction countermeasure against the machine room equipment noise is keenly necessitated. On such viewpoint, this study has recorded, measured the noises which were generated from each individual as same as the whole equipped machines and tools, on the object of the dormitory machine rooms of the 3 colleges that haying mutually different peculiarities, then after grasp-ing their characters and acoustic powers, this research has verified its prediction possibility and the authenticity by comparison the estimated numerical value with the actually measured numerical value through the acoustic simulation. After grasping the prediction possibility in such way, by utilization of the sound absorption material in the machinery room, from the stage of design, the soundproof measures for the noise reduction at machine room could be regulated effectively, and it is also considered that such data would be utilized as the fundamental material for an establishment of the measure for sound insulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.588-593
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• 2011

The Main design parameters of ship HVAC systems are pressure drop and noise analysis of ducts. The Noise prediction for HVAC(Heating, Ventilating and Air Conditioning) systems are normally performed by empirical method suggested by NEBB(National Environmental Balancing Bureau, 1994), but NEBB's method is not suitable for the ship HVAC systems. In this paper, numerical analysis methods are used to develop a noise prediction method for the ship HVAC systems, especially for large ducts. To develop regression formula of attenuation of sound pressure level in large duct, Boundary Element Method(BEM) is used. Using dynamic loss coefficient which is suggested by ASHRAE fitting data base and numerical methods of HVAC noise analysis, integrated HVAC noise analysis of Program is developed. The developed program can present pressure drop and noise analysis of the ship HVAC systems. To verify the accuracy and convenience of the developed program, prediction of HVAC system for Semi-Submersible Drilling RIG is carried out and the results are compared with measurement of noise level during sea trial.

• Transactions of Materials Processing
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• v.16 no.4 s.94
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• pp.250-253
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• 2007

In hot strip rolling, the work roll profile is one of the main factors in predicting and correcting the strip profile. Various studies concerning the wear profile and the thermal crown of work roll have been performed, and the results of these studies have shown that the work roll profile must be predicted accurately so as to efficiently control the strip qualities such as thickness, crown, flatness, and camber. Therefore, a precise prediction model of roll profile is called for in a perfect shape control system. In this paper, a genetic algorithm was applied to improve on the roll profile prediction model in hot strip rolling. In this approach, the optimal design problem is formulated on the basis of a numerical model so as to cover the diverse design variables and objective functions. A genetic algorithm was adopted for conducting design iteration for optimization to determine the coefficient of the numerical model for minimization of errors in the result of the calculated value and the measured data. A comparative analysis showed a satisfactory conformity between them.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.919-925
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• 2006

The regression models for the water temperatures of Ban Byeon Stream and Yong Jeon stream were developed using multi-regression method. It was also investigated that the applicability of the stream temperature prediction to two-dimensional numerical simulation to predict the vertical water temperature in Imha Reservoir. Air temperature and dew point as independent variables were selected to be applicable to cases with the different variation of flow rates. The data division of water temperature using a cutoff flow rate of $20m^3/s$ was found to reduce the prediction error of the stream temperature. The mean absolute percent error of the numerical simulation results of the vertical water temperature in Imha Reservoir using the regression models was 11%, which was only 4.3% lager than the simulation result using the measured stream temperature. Therefore, the regression models of the stream temperatures using multi-regression method applied in this study could be applied to predict the vertical water temperature in Imha Reservoir with a good accuracy.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1326-1336
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• 2018

This paper proposes a numerical approach to predict the critical flashover voltages of air gaps under lightning impulses. For an air gap, the impulse voltage waveform features and electric field features are defined to characterize its energy storage status before the initiation of breakdown. These features are taken as the input parameters of the predictive model established by support vector machine (SVM). Given an applied voltage range, the golden section search method is used to compute the prediction results efficiently. This method was applied to predict the critical flashover voltages of rod-rod, rod-plane and sphere-plane gaps over a wide range of gap lengths and impulse voltage waveshapes. The predicted results coincide well with the experimental data, with the same trends and acceptable errors. The mean absolute percentage errors of 6 groups of test samples are within 4.6%, which demonstrates the validity and accuracy of the predictive model. This method provides an effectual way to obtain the critical flashover voltage and might be helpful to estimate the safe clearances of air gaps for insulation design.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2008.10a
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• pp.43-51
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• 2008

Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.