• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.2109-2124
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• 1991

A simulation program is developed to analyse the performance of an axial flow turbine stage based on the meanline prediction method. The gradient projection method is utilized to minimize the aerodynamic losses under the specified constraints on such as flow coefficient, total pressure ratio, stage power and blade loading coefficient. After obtaining the optimum point for minimizing the stage loss, a sensitivity analysis is carried out ground the optimum point to find the effects of the design variables and the design constraints on the stage performance. The result of the senitivity analysis under a constant blade loading coefficient shows that the total loss is more sensitive to the mean diameter, the absolute flow angle at nozzle outlet, the relative flow angle at rotor outlet and the axial mean velocity compared to the chords and the pitches. Moreover, the design constraints on the degree of reaction at root and the blade length-to-diameter ratio are found to be most influencial on the maximization of the overall aerodynamic efficiency.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.99-106
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• 2005

Instantaneous Frequency(IF) of Doppler signals is used to get the information of relative velocity and miss distance between a missile and the corresponding target. Though Short-Time Fourier Transform(STFT) is mainly used to estimate IF, it has many errors in wide band signals where frequency changes sharply. Because it has a fixed window in time and frequency axes. This paper deals with IF estimation of Doppler signal using a Continuous Wavelet Transform(CWT) which has adaptive window in time and frequency axes. The proposed method is able to estimate IF regardless of frequency changes because it has a narrow window in high frequency band and a wide window in low frequency band. The experimental results demonstrate that the proposed method outperforms STFT in estimating IF.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.133-140
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• 2015

In this paper, a roll angle estimation method of a rolling airframe using a low grade GPS and a roll rate gyro is proposed. The strength of the received signal of the GPS antenna attached on the rolling airframe is maximized when the GPS satellite is placed on the plane determined by the x-axis of the rolling airframe and the GPS antenna axis. Under the assumption that the x-axis of the rolling airframe is coincident with its velocity vector, the roll angle of the rolling airframe is calculated from the relative position vector of the satellite to the GPS when the GPS signal strength becomes maximum. The Kalman filter combined with a roll rate gyro is introduced to increase the determination accuracy of the roll angle. The performance of the proposed method is verified via 6-DOF simulations.

• Bulletin of the Korean Chemical Society
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• v.31 no.10
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• pp.2841-2848
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• 2010

Quasiclassical trajectory (QCT) method has been used to investigate stereodynamics information of the reaction $O(^1D)+H_2{\rightarrow}\;OH$+H on the DK (Dobbyn and Knowles) potential energy surface (PES) at a collision energy of 23.06 kcal/mol, with the initial quantum state of reactant $H_2$ being set for v = 0 (vibration quantum number) and j = 0-5 (rotation quantum number). The PDDCSs (polarization dependent differential cross sections) and the distributions of P($\theta_r$), P($\phi_r$), P($\theta_r$, $\phi_r$) have been presented in this work. The results demonstrate that the products are both forward and backward scattered. As j increases, the backward scattering becomes weaker while the forward scattering becomes slightly stronger. The distribution of P($\theta_r$) indicates that the product rotational angular momentum j' tends to align along the direction perpendicular to the reagent relative velocity vector k, but this kind of product alignment is found to be rather insensitive to j. Furthermore, the distribution of P($\phi_r$) indicates that the rotational angular momentum vector of the OH product is preferentially oriented along the positive direction of y-axis, and such product orientation becomes stronger with increasing j.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.200-207
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• 2017

The purpose in having a control surface on ships is to control the motion of the ship. The control surface may be composed entirely of a single movable surface or of a combination of fixed and movable portions. A control surface has one sole function to perform in meeting its purpose, and that is to develop a control force in consequence of its orientation and movement relative to the water. The forces and moments generated as a result of this rotation and angle of attack then determine the manoeuvring characteristics of the ship. In this paper, two-dimensional flow characteristics of a flapped rudder and a water-blowing control rudder were accomplished respectively by PIV method in a circulating water channel. Model test has been carried out with different angles of attack of main foil (NACA 0012) and flap's deflection angles to predict the performance of the flapped rudder and the water-blowing control rudder. The 2-frame particle tracking method has been used to obtain the velocity distribution in the flow field. $Re{\fallingdotseq}3.0{\times}10^4$ has been used during the whole experiments and measured results have been compared with each other.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.641-649
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• 2021

Fuel oil consumption (FOC) must be minimized to determine the economic route of a ship; hence, the ship power must be predicted prior to route planning. For this purpose, a numerical method using test results of a model has been widely used. However, predicting ship power using this method is challenging owing to the uncertainty of the model test. An onboard test should be conducted to solve this problem; however, it requires considerable resources and time. Therefore, in this study, a deep feed-forward neural network (DFN) is used to predict ship power using deep learning methods that involve data pattern recognition. To use data in the DFN, the input data and a label (output of prediction) should be configured. In this study, the input data are configured using ocean environmental data (wave height, wave period, wave direction, wind speed, wind direction, and sea surface temperature) and the ship's operational data (draft, speed, and heading). The ship power is selected as the label. In addition, various treatments have been used to improve the prediction accuracy. First, ocean environmental data related to wind and waves are preprocessed using values relative to the ship's velocity. Second, the structure of the DFN is changed based on the characteristics of the input data. Third, the prediction accuracy is analyzed using a combination comprising five hyperparameters (number of hidden layers, number of hidden nodes, learning rate, dropout, and gradient optimizer). Finally, k-means clustering is performed to analyze the effect of the sea state and ship operational status by categorizing it into several models. The performances of various prediction models are compared and analyzed using the DFN in this study.

• Resources Recycling
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• v.15 no.4 s.72
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• pp.36-43
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• 2006

There was some difficulty dewatering properties due to small porosity diameter of cake, when pigment sludge contained fine particle was formed by cake under the dewatering. It was difficult to dewater the sludge with fine particles with the conventional mechanical dewatering method. This study was to improve the dewatering rate as discharging the water from porosity of cake easily, supplying the low heat to the cake layer. Thermal dewatering equipment of piston type to keep up constant temperature on the cake was set up and relative experiment was conducted for sludge of 200 g with fine pigment particle. As test results. filtration of 176.8 g, cake weight of 19.4 g, cake thickness of 4.2 mm was measured, and it was analyzed that the water content of cake was 47 wt% and dewatering velocity, which moaned the residual d교 sloid amount per dewatering area, was $2.1DS\;m^{2}{\cdot}cycle$. This results showed that filtration increased, cake weight and thickness decreased and dewatering velocity increased against mechanical dewatering method. And water content of cake decreased about 30%, so the result which dewatering rate improved was drew generally. The reason is that the inner vapor pressure working at the cake porosity increased as applying the low heat to the cake layer, which lead to discharge the water from porosity easily. Therefore, this study was estimated by the useful technology for sludge reduction.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• Geotechnical Engineering
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• v.14 no.3
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• pp.25-46
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• 1998

This paper shows that there are the results of a series of model tests on the behavior of single pipe pile which is subjected to lateral load in, Nak-dong River sand. The purpose of the present paper is to estimate the effect of Non-homogeneity. constraint condition of pile head, lateral load velocity, relative density, and embedded length of pile on the behavior of single pile. These effects can be quantified only by the results of model tests. Also, these are compared with the results of the numerical methods (p-y method, modified Vlasov method; new ${\gamma}$ parameter, Characteristic Load Method'CLM). In this study, a new ${\gamma}$ parameter equation based on the Vlasov method was developed to calculate the modulus of subgrade reaction (E. : nhz.) proportional to the depth. The p-y method of analysis is characterized by nonlinear behavior. and is an effective method of designing deep foundations subjected to lateral loads. The new method, which is called the characteristic load method (CLM). is simpler than p-y analysis. but its results closely approximates p-y analysis results. The method uses dimensional analysis to characterize the nonlinear behavior of laterally loaded piles with respect to be relationships among dimensionless variables. The modulus of subgrade reaction used in p-y analysis and modified Vlasov method obtained from back analysis using direct shear test (DST) results. The coefficients obtained from DST and the modified ones used for the prediction of lateral behavior of ultimate soil reaction range from 0.014 to 0.05. and from 0.2 to 0.4 respectively. It is shown that the predicted numerical results by the new method (CLM), p-y analysis, and modified Vlasov method (new parameter) agree well with measured results as the relative density increases. Also, the characteristic load method established applicability on the Q-Mnu. relationship below y/D=0.2.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.8
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• pp.915-921
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• 2007

As a preliminary measurement of siloxanes in landfill gas(LFG), this study was conducted to determine the best suitable solvent applicable to the extraction of siloxanes in the domestic landfill using liquid-absorption method. Three solvents of n-hexane, acetone, and methanol were tested and the results obtained from GC analysis for each solvent were compared to their properties. Results showed that the resolution in the GC spectrum was the best from methanol due to the lack of overlapping of the peaks between silane and solvent. The detected siloxanes concentration were varied at maximum 2.6 times depending on the types of solvent as well as extraction velocity and impinger steps. In total, the highest concentration of siloxanes was obtained from methanol, which showed ideal pattern in the absorption of each impinger step and the least relative standard deviation. Accordingly, it is concluded that methanol is the most suitable solvent for the extraction of siloxanes in the domestic landfill. However, it is considered that solvent suitability can vary depending on the waste components and landfill record in landfills.