• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.690-699
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• 2008

In this paper a conventional approach for design and analysis of subsonic air vehicle is used. First of all subsonic aerodynamic coefficients are calculated using Computational Fluid Dynamics(CFD) tools and then wind-tunnel model was developed that integrates vehicle components including control surfaces and initial data is validated as well as refined to enhance aerodynamic efficiency of control surfaces. Experimental data and limited computational fluid dynamics solutions were obtained over a Mach number range of 0.5 to 0.8. The experimental data show the component build-up effects and the aerodynamic characteristics of the fully integrated configurations, including control surface effectiveness. The aerodynamic performance of the fully integrated configurations is comparable to previously tested subsonic vehicle models. Mathematical model of the dynamic equations in 6-Degree of Freedom(DOF) is then simulated using MATLAB/SIMULINK to simulate trajectory of vehicle. Effect of altitude on range, Mach no and stability is also shown. The approach presented here is suitable enough for preliminary conceptual design. The trajectory evaluation method devised accurately predicted the performance for the air vehicle studied. Formulas for the aerodynamic coefficients for this model are constructed to include the effects of several different aspects contributing to the aerodynamic performance of the vehicle. Characteristic parameter values of the model are compared with those found in a different set of similar air vehicle simulations. We execute a set of example problems which solve the dynamic equations to find the aircraft trajectory given specified control inputs.

• Journal of Information Technology Applications and Management
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• v.19 no.1
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• pp.1-12
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• 2012

Data mining is the process of searching and analyzing large quantities of data for finding out meaningful patterns and rules. Artificial Neural Network (ANN) is one of the tools of data mining which is becoming very popular in forecasting the future values. Some of the areas where it is used are banking, medicine, retailing and fraud detection. In finance, artificial neural network is used in various disciplines including stock market forecasting. In the stock market time series, due to high volatility, it is very important to choose a model which reads volatility and forecasts the future values considering volatility as one of the major attributes for forecasting. In this paper, an attempt is made to develop two models - one using feed forward back propagation Artificial Neural Network and the other using Autoregressive Conditional Heteroskedasticity (ARCH) technique for forecasting stock market returns. Various parameters which are considered for the design of optimal ANN model development are input and output data normalization, transfer function and neuron/s at input, hidden and output layers, number of hidden layers, values with respect to momentum, learning rate and error tolerance. Simulations have been done using prices of daily close of Sensex. Stock market returns are chosen as input data and output is the forecasted return. Simulations of the Model have been done using MATLAB$^{(R)}$ 6.1.0.450 and EViews 4.1. Convergence and performance of models have been evaluated on the basis of the simulation results. Performance evaluation is done on the basis of the errors calculated between the actual and predicted values.

• ETRI Journal
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• v.42 no.4
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• pp.575-584
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• 2020

Electromagnetic (EM) waves used to send signals under seawater are normally restricted to low frequencies (f) because of sudden exponential increases of attenuation (𝛼) at higher f. The mathematics of EM wave propagation in seawater demonstrate dependence on relative permeability (𝜇_r), relative permittivity (𝜀_r), conductivity (𝜎), and f of transmission. Estimation of 𝜀_r and 𝜎 based on the W. Ellison interpolation model was performed for averaged real-time data of temperature (T) and salinity (S) from 1955 to 2012 for all oceans with 41 088 latitude/longitude points and 101 depth points up to 5500 m. Estimation of parameters such as real and imaginary parts of 𝜀_r, 𝜀_r', 𝜀_r", 𝜎, loss tangent (tan 𝛿), propagation velocity (V_p), phase constant (𝛽), and α contributes to absorption loss (L_a) for seawater channels carried out by using normal distribution fit in the 3 GHz-40 GHz f range. We also estimated total path loss (L_PL) in seawater for given transmission power P_t and antenna (dipole) gain. MATLAB is the simulation tool used for analysis.

• Advances in aircraft and spacecraft science
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• v.5 no.4
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• pp.499-513
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• 2018

One of the major problems in glass fiber reinforced epoxy (GFRE) composite pipes is the durability under water absorption. This condition is generally recognized to cause degradations in strength and mechanical properties. Therefore, there is a need for an intelligent system for detecting the absorption rate and computing the mass of water absorption (M%) as a function of absorption time (t). The present work represents a new non-destructive evaluation (NDE) technique for detecting the water absorption rate by evaluating the dielectric properties of glass fiber and epoxy resin composite pipes subjected to internal hydrostatic pressure at room temperature. The variation in the dielectric signatures is employed to design an electrical capacitance sensor (ECS) with high sensitivity to detect such defects. ECS consists of twelve electrodes mounted on the outer surface of the pipe. Radius-electrode ratio is defined as the ratio of inner and outer radius of pipe. A finite element (FE) simulation model is developed to measure the capacitance values and node potential distribution of ECS electrodes on the basis of water absorption rate in the pipe material as a function of absorption time. The arrangements for positioning12-electrode sensor parameters such as capacitance, capacitance change and change rate of capacitance are analyzed by ANSYS and MATLAB to plot the mass of water absorption curve against absorption time (t). An analytical model based on a Fickian diffusion model is conducted to predict the saturation level of water absorption ($M_S$) from the obtained mass of water absorption curve. The FE results are in excellent agreement with the analytical results and experimental results available in the literature, thus, validating the accuracy and reliability of the proposed expert system.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.623-640
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• 2017

The full nonlinear equations of an unmanned aerial vehicle ground taxiing mathematical dynamic model are built based on a type of unmanned aerial vehicle data in LMS Virtual.Lab Motion. The flexible landing gear model is considered to make the aircraft ground motion more accurate. The electric braking control system is established in MATLAB/Simulink and the experiment of it verifies that the electric braking model with the pressure sensor is fitted well with the actual braking mechanism and it ensures the braking response speediness. The direction rectification control law combining the differential brake and the rudder with 30% anti-skid brake is built to improve the directional stability. Two other rectifying control laws are demonstrated to compare with the designed control law to verify that the designed control is of high directional stability and high braking efficiency. The lateral displacement increases by 445.45% with poor rectification performance under the only rudder rectifying control relative to the designed control law. The braking distance rises by 36m and the braking frequency increases by 85.71% under the control law without anti-skid brake. Different landing conditions are simulated to verify the good robustness of the designed rectifying control.

• Progress in Superconductivity and Cryogenics
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• v.17 no.2
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• pp.41-44
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• 2015

Critical current of high-temperature superconducting (HTS) coil is influenced by its own self magnetic field. Direction and density distribution of the magnetic field around the coil are fixed after the shape of the coil is decided. If the entire part of the HTS tape has homogeneous $I_c$ distribution characteristic, quench would be initiated in fixed location on the coil. However, the actual HTS tape has inhomogeneous $I_c$ distribution along the length. If the $I_c$ distribution of the HTS tape is known, we can expect the spot within the HTS coil that has the highest probability to initiate the quench. In this paper, $I_c$ distribution within the HTS coil under self-field effect is simulated by MATLAB. In the simulation procedure, $I_c$ distribution of the entire part of the HTS tape is assume d to follow Gaussian-distribution by central limit theorem. The HTS coil model is divided into several segments, and the critical current of each segment is calculated based on the-generalized Kim model. Single pancake model is simulated and self-field of HTS coil is calculated by Biot-Savart's law. As a result of simulation, quench-initiating spot in the actual HTS coil can be predicted statistically. And that statistical analysis can help detect or protect the quench of the HTS coil.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.1
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• pp.80-88
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• 2013

In currently developed engine condition monitoring systems, most field engine maintenance engineers have difficulties to use them in fields due to complexity, unpractical use, lack of understanding, etc. Therefore a practical usable engine condition monitoring system must be needed. This work proposes a practical performance condition monitoring of a small turbojet engine through comparing between the on-line performance monitoring data and the initial clean performance data calculated by the base engine performance model. Moreover the proposed monitoring system checks the gas path components' on-line health condition through comparing the component performance characteristics between the running engine represented as a deteriorated engine or a degraded engine and the base engine performance model represented as a clean engine. The proposed condition monitoring system is coded in a friendly GUI type program for easy practical application by a commercial tool, MATLAB/SIMULINK and LabVIEW.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.69-77
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• 2017

The amount of solar irradiation obtained by a photovoltaic (PV) solar panel is the major factor determining the power generated by a PV system, and the array tilt angle is critical for maximizing panel radiation acquisition. There are three types of PV systems based on the manner of setting the array tilt angle: fixed, semi-fixed, and tracking systems. A fixed system cannot respond to seasonal solar altitude angle changes, and therefore cannot absorb the maximum available solar radiation. The tracking system continually adjusts the tilt angle to absorb the maximum available radiation, but requires additional cost for equipment, installation, operation, and maintenance. The semi-fixed system is only adjusted periodically (usually seasonally) to obtain more energy than a fixed system at an overall cost that is less than a tracking system. To maximize semi-fixed system efficiency, determining the optimal tilt angle adjustment schedule are required. In this research, we conducted a simulation to derive an optimal operation schedule for a semi-fixed system in Seoul, Korea (latitude $37.5^{\circ}$). We implemented a solar radiation acquisition model and PV genereation model on MATLAB. The optimal operation schedule was derived by changing the number of tilt angle adjustments throughout a year using a Dynamic Algorithm. The results show that adjusting the tilt angle 4 times a year was the most appropriate. and then, generation amount of PV system increased 2.80% compared with the fixed system. This corresponds to 99% compared to daily adjustment model. This increase would be quite valid as the PV system installation area increased.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1044-1053
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• 2010

Transmitting correct train control information is important in a train control system which demands safety. The train control information includes the maximum speed of trains, position of preceding trains, incline of tracks and curve sections etc. A radio frequency-communication based train control system is influenced by the noise and interference because the train control information is transmitted by wireless between a on-board system and wayside system. The radio frequency-communication based train control system is a mobile communication system due to moving trains. The inter symbol interference(ISI) occurs by the multipath fading in the mobile ommunication system. As signal-to-noise ratio(SNR) is decreased by the ISI, the train control information is not received correctly. In case of tunnel section, numerous reflected waves exist. Therefore, the power density of receiver is decreased by difference among the received times, magnitudes, phases through the multipath. So, the train suddenly is stopped by the fail-safe operation in the train control system on account of decreasing the power density of receiver. In this paper, a line of sight model-(Additive White Gaussian noise(AWGN) channel), rayleigh and rician fading model are presented. Probability density functions which are related to the SNR are derived from the models. The fading phenomenon severely occurs as a result of analyzing the probability density functions. So, the space diversity method is used in order to reduce the fading effect and it is demonstrated by using Matlab program.

• Journal of the Korean Solar Energy Society
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• v.37 no.3
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• pp.47-59
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• 2017

As the global warming threats to humanity, renewable energy is considered the key solution to overcome the climate change. In this circumstance, distributed PV systems are being expanded significantly its market share in the renewable energy industry. The performance of inverter is the most important component at PV system and numerous researches are focusing on it. In order to improve the inverter, PV simulator is an essential device to experiment under various load and conditions. This paper proposes the PV Power-Hardware-In-Loop simulator (PHILS) with real-time processing converted electrical and mathematical models to improve computation speed. Single-diode PV model is used in MATLAB/SIMULINK for the PV PHILS to boosting computation speed and dynamic model accuracy. In addition, control algorithms for sub-components such as DC amplifier, measurement device and several interface functions are implemented in the model. The proposed PV PHILS is validated by means of experiments with commercial PV module parameters.