Seungheon Lee;Hyoung Jin Lee;Sangjo Kim;Gyujin Na;Jung Hoe Kim
Journal of the Korean Society of Propulsion Engineers
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v.27
no.1
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pp.37-48
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2023
In this study, performance analysis modeling of two spool mixed flow type turbofan engine according to steady-state and transient is performed. The target engine is selected as F100-PW-229 from Pratt & Whitney, and main engine components including fan, high pressure compressors, combustion, high pressure turbines, low pressure turbines, mixer, convergent-divergent nozzle are modeled. The cooling effect of turbine through secondary flow path are considered in engine simulation model. We develop in-house Matlab/Simulink-based engine performance analysis program capable of analyzing internal engine state and compare it with GASTURB which is generally used as a commercial engine analysis program.
Journal of the Computational Structural Engineering Institute of Korea
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v.36
no.4
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pp.259-264
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2023
In this study, we devised a parametric analysis workflow for efficiently analyzing the material properties of 3D woven materials. The parametric model uses wire spacing in the woven materials as a design parameter; we generated 2,500 numerical models with various combinations of these design parameters. Using MATLAB and ANSYS software, we obtained various material properties, such as bulk modulus, thermal conductivity, and fluid permeability of the woven materials, through a parametric batch analysis. We then used this large dataset of material properties to perform a regression analysis to validate the relationship between design variables and material properties, as well as the accuracy of numerical analysis. Furthermore, we constructed an artificial neural network capable of predicting the material properties of 3D woven materials on the basis of the obtained material database. The trained network can accurately estimate the material properties of the woven materials with arbitrary design parameters, without the need for numerical analyses.
Hexagonal boron nitride (h-BN), commonly referred to as Boron Nitride Nanoribbons (BNNRs), is an electrical insulator characterized by high thermal stability and a wide bandgap semiconductor property. This study delves into the electronic properties of two BNNR configurations: Armchair BNNRs (ABNNRs) and Zigzag BNNRs (ZBNNRs). Utilizing the nearest-neighbour tight-binding approach and numerical methods, the electronic properties of BNNRs were simulated. A simplifying assumption, the Hamiltonian matrix is used to compute the electronic properties by considering the self-interaction energy of a unit cell and the interaction energy between the unit cells. The edge perturbation is applied to the selected atoms of ABNNRs and ZBNNRs to simulate the electronic properties changes. This simulation work is done by generating a custom script using numerical computational methods in MATLAB software. When benchmarked against a reference study, our results aligned closely in terms of band structure and bandgap energy for ABNNRs. However, variations were observed in the peak values of the continuous curves for the local density of states. This discrepancy can be attributed to the use of numerical methods in our study, in contrast to the semi-analytical approach adopted in the reference work.
Ha-Seon Jeong;Ie-Jun Kim;Su-Bin Park;Suyeon Park;Yunji Oh;Woo-Seok Lee;Kang-Hyeon Seo;Youngjin Lee
Journal of radiological science and technology
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v.47
no.1
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pp.39-48
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2024
In this study, we optimized the FNLM algorithm through a simulation study and applied it to a phantom scanned by low-dose CT to evaluate whether the FNLM algorithm can be used to obtain improved image quality images. We optimized the FNLM algorithm with MASH phantom and FASH phantom, which the algorithm was applied with MATLAB, increasing the smoothing factor from 0.01 to 0.05 with increments of 0.001 and measuring COV, RMSE, and PSNR values of the phantoms. For both phantom, COV and RMSE decreased, and PSNR increased as the smoothing factor increased. Based on the above results, we optimized a smoothing factor value of 0.043 for the FNLM algorithm. Then we applied the optimized FNLM algorithm to low dose lung CT and lung CT under normal conditions. In both images, the COV decreased by 55.33 times and 5.08 times respectively, and we confirmed that the quality of the image of low dose CT applying the optimized FNLM algorithm was 5.08 times better than the image of lung CT under normal conditions. In conclusion, we found that the smoothing factor of 0.043 among the factors of the FNLM algorithm showed the best results and validated the performance by reducing the noise in the low-quality CT images due to low dose with the optimized FNLM algorithm.
Driven by both environmental and economic reasons, the development of small to medium scale GTL(gas-to-liquid) process for offshore applications and for utilizing other stranded or associated gas has recently been studied increasingly. Microchannel GTL reactors have been prefrered over the conventional GTL reactors for such applications, due to its compactness, and additional advantages of small heat and mass transfer distance desired for high heat transfer performance and reactor conversion. In this work, multi-microchannel reactor was simulated by using commercial CFD code, ANSYS FLUENT, to study the geometric effect of the microchannels on the heat transfer phenomena. A heat generation curve was first calculated by modeling a Fischer-Tropsch reaction in a single-microchannel reactor model using Matlab-ASPEN integration platform. The calculated heat generation curve was implemented to the CFD model. Four design variables based on the microchannel geometry namely coolant channel width, coolant channel height, coolant channel to process channel distance, and coolant channel to coolant channel distance, were selected for calculating three dependent variables namely, heat flux, maximum temperature of coolant channel, and maximum temperature of process channel. The simulation results were visualized to understand the effects of the design variables on the dependent variables. Heat flux and maximum temperature of cooling channel and process channel were found to be increasing when coolant channel width and height were decreased. Coolant channel to process channel distance was found to have no effect on the heat transfer phenomena. Finally, total heat flux was found to be increasing and maximum coolant channel temperature to be decreasing when coolant channel to coolant channel distance was decreased. Using the qualitative trend revealed from the present study, an appropriate process channel and coolant channel geometry along with the distance between the adjacent channels can be recommended for a microchannel reactor that meet a desired reactor performance on heat transfer phenomena and hence reactor conversion of a Fischer-Tropsch microchannel reactor.
In the case of satellite navigation positioning, the shielding of satellite signals is determined by the environment of the region at which a user is located, and the navigation performance is determined accordingly. The accuracy of user position determination varies depending on the dilution of precision (DOP) which is a measuring index for the geometric characteristics of visible satellites; and if the minimum visible satellites are not secured, position determination is impossible. Currently, the GLObal NAvigation Satellite system (GLONASS) of Russia is used to supplement the navigation performance of the Global Positioning System (GPS) in regions where GPS cannot be used. In addition, the European Satellite Navigation System (Galileo) of the European Union, the Chinese Satellite Navigation System (BeiDou) of China, the Quasi-Zenith Satellite System (QZSS) of Japan, and the Indian Regional Navigation Satellite System (IRNSS) of India are aimed to achieve the full operational capability (FOC) operation of the navigation system. Thus, the number of satellites available for navigation would rapidly increase, particularly in the Asian region; and when integrated navigation is performed, the improvement of navigation performance is expected to be much larger than that in other regions. To secure a stable and prompt position solution, GPS-GLONASS integrated navigation is generally performed at present. However, as available satellite navigation systems have been diversified, finding the minimum satellite constellation combination to obtain the best navigation performance has recently become an issue. For this purpose, it is necessary to examine and predict the navigation performance that could be obtained by the addition of the third satellite navigation system in addition to GPS-GLONASS. In this study, the current status of the integrated navigation performance for various satellite constellation combinations was analyzed based on 2014, and the navigation performance in 2020 was predicted based on the FOC plan of the satellite navigation system for each country. For this prediction, the orbital elements and nominal almanac data of satellite navigation systems that can be observed in the Korean Peninsula were organized, and the minimum elevation angle expecting signal shielding was established based on Matlab and the performance was predicted in terms of DOP. In the case of integrated navigation, a time offset determination algorithm needs to be considered in order to estimate the clock error between navigation systems, and it was analyzed using two kinds of methods: a satellite navigation message based estimation method and a receiver based method where a user directly performs estimation. This simulation is expected to be used as an index for the establishment of the minimum satellite constellation for obtaining the best navigation performance.
An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.
Journal of the Korea Society of Computer and Information
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v.24
no.12
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pp.51-57
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2019
In this paper, we analyzed the performance of IoT based smart wearable mine detection device. There are various mine detection methods currently used by the military. Still, in the general field, mine detection is performed by visual detection, probe detection, detector detection, and other detection methods. The detection method by the detector is using a GPR sensor on the detector, which is possible to detect metals, but it is difficult to identify non-metals. It is hard to distinguish whether the area where the detection was performed or not. Also, there is a problem that a lot of human resources and time are wasted, and if the user does not move the sensor at a constant speed or moves too fast, it is difficult to detect landmines accurately. Therefore, we studied the smart wearable mine detection device composed of human body antenna, main microprocessor, smart glasses, body-mounted LCD monitor, wireless data transmission, belt type power supply, black box camera, which is to improve the problem of the error of mine detection using unidirectional ultrasonic sensing signal. Based on the results of this study, we will conduct an experiment to confirm the possibility of detecting underground mines based on the Internet of Things (IoT). This paper consists of an introduction, experimental environment composition, simulation analysis, and conclusion. Introduction introduces the research contents such as mines, mine detectors, and research progress. It consists of large anti-personnel mine, M16A1 fragmented anti-mine, M15 and M19 antitank mines, plastic bottles similar to mines and aluminum cans. Simulation analysis is conducted by using MATLAB to analyze the mine detection device implementation performance, generating and transmitting IoT signals, and analyzing each received signal to verify the detection performance of landmines. Then we will measure the performance through the simulation of IoT-based mine detection algorithm so that we will prove the possibility of IoT-based detection landmine.
This paper presents an algorithm for multichannel slotted-ring topology medium access protocol (MAC) using in wavelength division multiplexing (WDM) networks. In multichannel ring, there are two main previously proposed architectures: Tunable Transmitter - Fixed Receiver (TTFR) and Fixed Transmitter - Tunable Receivers (FTTR). With TTFR, nodes can only receive packets on a fixed wavelength and can send packets on any wavelengths related to destination of packets. Disadvantage of this architecture is required as many wavelengths as there are nodes in the network. This is clearly a scalability limitation. In contrast, FTTR architecture has advantage that the number of nodes can be much larger than the number of wavelength. Source nodes send packet on a fixed channel (or wavelength) and destination nodes can received packets on any wavelength. If there are fewer wavelengths than there are nodes in the network, the nodes will also have to share all the wavelengths available for transmission. However the fixed wavelength approach of TTFR and FTTR bring low network utilization. Because source node with waiting data have to wait for an incoming empty slot on corresponding wavelength. Therefore this paper presents Tunable Transmitter - Tunable Receiver (TTTR) approach, in which the transmitting node can send a packet over any wavelengths and the receiving node can receive a packet from any wavelengths. Moreover, the self-similar distributed input traffic is used for evaluation of the performance of the proposed algorithm. The self-similar traffic performs better performance over long duration than short duration of the Poison distribution. In order to increase bandwidth efficiency, the Destination Stripping approach is used to mark the slot which has already reached the desired destination as an empty slot immediately at the destination node, so the slot does not need to go back to the source node to be marked as an empty slot as in the Source Stripping approach. MATLAB simulator is used to evaluate performance of FTTR, TTFR, and TTTR over 4 and 16 nodes ring network. From the simulation result, it is clear that the proposed algorithm overcomes higher network utilization and average throughput per node, and reduces the average queuing delay. With future works, mathematical analysis of those algorithms will be the main research topic.
The Transactions of The Korean Institute of Electrical Engineers
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v.67
no.11
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pp.1423-1433
/
2018
Recently, a permanent magnet synchronous motor of middle and small-capacity has high torque, high precision control and acceleration / deceleration characteristics. But existing control has several problems that include unpredictable disturbances and parameter changes in the high accuracy and rigidity control industry or nonlinear dynamic characteristics not considered in the driving part. In addition, in the drive method for the control of low-vibration and high-precision, the process of connecting the permanent magnet synchronous motor and the load may cause the response characteristic of the system to become very unstable, to cause vibration, and to overload the system. In order to solve these problems, various studies such as adaptive control, optimal control, robust control and artificial neural network have been actively conducted. In this paper, an incremental encoder of the permanent magnet synchronous motor is used to detect the position of the rotor. And the position of the detected rotor is used for low vibration and high precision position control. As the controller, we propose augmented state feedback control with a speed observer and first order deadbeat disturbance observer. The augmented state feedback controller performs control that the position of the rotor reaches the reference position quickly and precisely. The addition of the speed observer to this augmented state feedback controller compensates for the drop in speed response characteristics by using the previously calculated speed value for the control. The first order deadbeat disturbance observer performs control to reduce the vibration of the motor by compensating for the vibrating component or disturbance that the mechanism has. Since the deadbeat disturbance observer has a characteristic of being vulnerable to noise, it is supplemented by moving average filter method to reduce the influence of the noise. Thus, the new controller with the first order deadbeat disturbance observer can perform more robustness and precise the position control for the influence of large inertial load and natural frequency. The simulation stability and efficiency has been obtained through C language and Matlab Simulink. In addition, the experiment of actual 2.5[kW] permanent magnet synchronous motor was verified.
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