• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.6
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• pp.60-65
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• 2004

Numerical simulations and experiments have been carried out to investigate the effect of fuel injection nozzles on the combustion and NOx formation processes in a medium-speed marine diesel engine. Spray visualization experiment was performed in the constant-volume high-pressure chamber to verify the numerical results on the spray characteristics such as spray angle and spray tip penetration. Time-resolved spray behaviors were captured by high-speed digital camera and analyzed to extract the information on the spray parameters. Spray and combustion phenomena were examined numerically using FIRE code. Wave breakup and Zeldovich models were adopted to describe the atomization characteristics and NOx formation processes. Numerical results were verified with experimental data such as cylinder pressure, heat release rate and NOx emission. Finally, the effects of fuel injection nozzles on the engine performance were investigated numerically to find the optimum nozzle parameters such as fuel injection angle, nozzle hole diameter and number of nozzle holes. From this study, the optimum fuel injection nozzle (nozzle hole diameter, 0.32 mm, number of nozzle holes, 8 and fuel injection angle, $148^{\circ}$) was selected to reduce both the fuel consumption and NOx emission. The reason for this selection could be explained from the highest fuel-air mixing in the early phase of injection due to the longest spray tip penetration and the highest heat release rate after $19^{\circ}$ ATDC due to the increased injection duration.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.9
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• pp.81-92
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• 1998

A new hybrid technique using several sub-populations having completely different evolutionary behaviors is proposed to increase the possibility to quickly find the global optimum of continuous optimization problem. It has three sub-populations. Two NPOSA algorithms showing good performance in the problem having a rugged fitness function are applied to two sub-populations and a self-adaptive evolutionary algorithm to the other sub-population. Sub-populations evolve in different manners and the interaction among these sub-populations lead to the global optimum quickly. The efficiency of this technique is verified through benchmark test functions. Finally, the algorithm with three sub-populations has been applied to seek for the optimal camera calibration parameters. After an error function has been defined using measured feature points of a calibration block, it has been shown that the algorithm searches for the camera parameters that minimize the error function.

• Journal of the Korean Society of Safety
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• v.25 no.6
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• pp.115-122
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• 2010

The importance of the life cycle cost (LCC) analysis for bridges has been recognized over the last decade. However, it is difficult to predict LCC precisely since the costs occurring throughout the service life of the bridge depend on various parameters such as design, construction, maintenance, and environmental conditions. This paper presents a methodology for the optimal life cycle cost design of a bridge. Total LCC for the service life is calculated as the sum of initial cost, damage cost, maintenance cost, repair and rehabilitation cost, user cost, and disposal cost. The optimization method is applied to design of a bridge structure with minimal cost, in which the objective function is set to LCC and constraints are formulated on the basis of Korean Bridge Design Code. Initial cost is calculated based on standard costs of the Korea Construction Price Index and damage cost on damage probabilities to consider the uncertainty of load and resistance. Repair and rehabilitation cost is determined using load carrying capacity curves and user cost includes traffic operation costs and time delay costs. The optimal life cycle cost design of a bridge is performed and the effects of parameters are investigated.

• Coupled systems mechanics
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• v.9 no.2
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• pp.111-123
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• 2020

Wastewater treatment plants (WWTPs) with activated sludge system are widely used throughout the most common technologies in the world. Most treatment plants require optimization of certain treatment processes using dynamic modeling. A lot of examples of dynamic simulations require reliable data base of diurnal variation of the inflow and typical concentrations of parameters such as Chemical Oxygen Demand (COD), Total Kjeldahl Nitrogen (TKN), etc. Such detailed data are not available, which leads to problemsin the application of dynamic simulations. In many examples of plants, continuous flow measurements are only performed after the primary clarifier, whereas measurements from influent to the plant are missing, as is the case with the examples in this paper. In some cases, a simpler, faster and cheaper way can be applied to determine influent variations, such as the "HSG-Sim" method ("Hochschulgruppe Simulation"). "Hochschulgruppe Simulation" is a group of researchers from Germany, Austria, Switzerland, Luxembourg, Netherlands and Poland (see http://www.hsgsim.org). This paper presents a model for generating daily variations of inflow and concentration of municipal wastewater quality parameters, applied to several existing WWTPs in Bosnia and Herzegovina (B&H). The main goal of the applied method is to generate realistic influent data of the existing plants in B&H, in terms of flow and quality, without any prior comprehensive survey and measurements at the site. The examples of plants show the influence of overflow facilities on the dynamics of input flow and quality of wastewater, and a strong influence of the problems of the sewerage systems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.50-61
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• 1999

\In this paper, we consider the optimal scheduling of detection and tracking parameters in phased array radars to minimize the radar energy required for track maintenance in a cluttered environment. We develop a mathematical model of target detection induced by a search process in phased array radars. In the mathematical development, we take into account the effect of unwanted measurements that may have originated from clutter or false alarms in the detection process. We use and analytic approximation of the modified Riccati equation of the probabilistic data association (PDA) filter to take into account the effect of clutter interference in tracking. Based on the search process and the tracking models, we formulate the optimal scheduling problem into a nonlinear optimal control problem. We solve a constrained nonlinear optimization problem to obtain the solution of the optimal control problem.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.6 s.40
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• pp.73-80
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• 2004

A nonlinear time-domain system identification algorithm using measured acceleration data is developed for structural damage assessment. To take account of nonlinear behavior of structural systems, an output error between measured and computed acceleration increments has been defined and a constrained nonlinear optimization problem is solved for optimal structural parameters. The algorithm estimates time-varying properties of stiffness and damping parameters. Nonlinear response of restoring force of a structural system is recovered by using the estimated time-varying structural properties and computed displacement by Newmark-$\beta$ method. In the recovery, no pre-defined model for inelastic behavior has been assumed. In developing the algorithm, noise and incomplete measurement in space and state have been considered. To examine the developed algorithm, numerical simulation and laboratory experimental studies on a three-story shear building have been carried out.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.4
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• pp.231-238
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• 2014

In the buildings, the systems of structures are influenced by the gravity load changes due to room alteration or construction stage. This paper proposes a system identification method establishing mass as well as stiffness to parameters in model updating process considering mass change in the buildings. In this proposed method, modified genetic algorithm, which is optimization technique, is applied to search those parameters while minimizing the difference of dynamic characteristics between measurement and FE model. To search more global solution, the proposed modified genetic algorithm searches in the wider search space. It is verified that the proposed method identifies the system of structure appropriately through the analytical study on a steel beam structure in the building. The comparison for performance of modified genetic algorithm and existing simple genetic algorithm is carried out. Furthermore, the existing model updating method neglecting mass change is performed to compare with the proposed method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.12
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• pp.502-508
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• 2016

An optimized PI controller design method is presented to promote the control performance of an oil cooler system for high precision machine tools. First, a transfer function model of the oil cooler system with a variable rotating speed compressor was obtained by the perturbation method as the first order system with a negligible dead time. Then, the closed-loop control system was described as the second order system with a zero. Its dynamic behaviors are mostly governed by characteristic parameters, the damping ratio, and the natural frequency which is incorporated in PI gains. Next, an optimum integral of the time-weighted absolute error (ITAE) criterion was applied to the second order system. The characteristic parameters can be determined by the given design specifications, percent overshoots and settling times and comparisons with the ITAE criterion. Hence, the PI gains were plainly identified in a deterministic way. Finally, the PI gains were fine-tuned to obtain desirable dynamics in real systems, considering the zero effect and parameter variations. The validity of the proposed method was proven by computer simulations and real experiments for selected cases.

• Journal of the Korean Institute of Gas
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• v.8 no.4 s.25
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• pp.30-35
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• 2004

In this paper, the metal seal for a pressure vessel has been analyzed using the Daguchi method. This method may efficiently optimize the design parameters for a cantilever sealing device of a pressure vessel in terms of dimensions and angles. The computed results indicate that the optimized design parameters can only be drawn by sixteen experimental numbers of iterations when the Daguchi design technique has been employed. This means that the Daguchi design method is very useful for the optimization design of the curved design of the structure. Based on the computed results by the Daguchi design technique, the dimension and angle of the metal seal structure are given as $d_1=50mm,\;d_2=60mm,\;a_1=20^{\circ},\;a_2=8^{\circ},\;a_3=5^{\circ}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.602-610
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• 2018

The model predictive control is an effective method to optimize the current control input that predicts the current control state and the future error using the predictive model of the control system when the reference trajectory is known. Since the control input can not have a physically infinitely large value, a predictive controller design with constraints should be considered. In addition, the reference model $A_r$ and the weight matrices Q, R that determine the control performance of the predictive controller are not optimized as arbitrarily designated should be considered in the controller design. In this study, we construct a predictive controller of a mobile robot by transforming it into a quadratic programming problem with constraints, The control performance of the mobile robot can be improved by optimizing the control parameters of the predictive controller that determines the control performance of the mobile robot using genetic algorithm. Through the computer simulation, the superiority of the proposed method is confirmed by comparing with the existing method.