• 한국자동차공학회논문집
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• 제12권3호
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• pp.51-58
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• 2004

Optimization of engine desist and operation parameters using a genetic algorithm was demonstrated for direct injection diesel engine combustion. A micro genetic algorithm and a modified KIVA-3V code were used for the analysis and optimization of the engine combustion. At each generation of the optimization step the micro genetic algorithm generated five groups of parameter sets, and the five cases of KIVA-3V analysis were to be performed either in series or in parallel. The micro genetic algorithm code was also parallelized by using MPI programming, and a multi-CPU parallel supercomputer was used to speed up the optimization process by four times. An example case for a fixed engine speed was performed with six parameters of intake swirl ratio, compression ratio, fuel injection included angle, injector hole number, SOI, and injection duration. A simultaneous optimization technique for the whole range of engine speeds would be suggested for further studies.

• 한국전자파학회논문지
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• 제14권5호
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• pp.499-505
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• 2003

이동 무선 통신 시스템을 설계할 때 기지국의 위치는 매우 중요한 파라미터 중 하나이다. 기지국 위치를 설계할 때 여러 가지 복잡한 변수들을 잘 조합하여 코스트가 최소가 되도록 설계해야 한다. 이러한 문제를 해결하는데 필요한 알고리즘이 조합 최적화 알고리즘이며, 지금까지 조합 최적화 기술로 Random Walk, Simulated Annealing, Tabu Search, Genetic Algorithm과 같은 전역 최적화 기술이 사용되어 왔다. 본 논문은 이동 통신시스템의 기지국 위치 최적화에 위의 4가지 알고리즘들을 적용하여 각 알고리즘의 결과를 비교 분석하며 알고리즘에 의한 최적화 과정을 보여준다.

• 한국자동차공학회논문집
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• 제19권1호
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• pp.66-72
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• 2011

Injection pressure is an important factor in filling procedure for injection molded parts. In addition, weldlines should be avoided to successfully produce injection molded parts. In this study, we optimally obtained injection molding process parameters that minimize injection pressure. Then, we determined the thickness of the part to avoid weldlines. To solve the optimization problem proposed, we employed MAPS-3D (Mold Analysis and Plastics Solution-3 Dimension), a commercial CAE tool for injection molding analysis, and PIAnO (Process Integration, Automation, and Optimization) as a commercial PIDO (Process Integration and Design Optimization) tool. We integrated MAPS-3D into PIAnO, automated the analysis and design procedure, and performed optimization by employing PQRSM (Progressive Quadratic Response Surface Method) equipped in PIAnO. We successfully obtained optimization results, which demonstrates the effectiveness of our design method.

• 소성∙가공
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• 제15권4호
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• pp.295-303
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• 2006

Optimization is carried out to determine process parameters which reduce the amount of springback and improve shape accuracy of a deep drawn product in sheet metal forming process. The study uses the amount of stress deviation along the thickness direction in the deep drawn product as an indicator of springback instead of springback simulation. The scheme incorporates with an explicit elasto-plastic finite element method for calculation of the final shape and the stress deviation The optimization method adopts the response surface method in order to seek for the optimum condition of process parameters such as the blank holding force and the draw-bead force. The present scheme is applied to design of the variable blank holding force in an U-draw bending process and the application is further extend ε d to the design of draw-bead force in a front side member formed with advanced high strength steel (AHSS) sheets of DP60. Results show that design of process parameter is well performed to decrease the stress deviation through the thickness and to reduce the amount of springback. The present analysis provides a guideline in a design stage for controlling the springback based on the finite element simulation of the complicated parts.

• 대한기계학회논문집A
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• 제31권11호
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• pp.1100-1107
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• 2007

In this study, a method to characterize material properties of adhesive that is used in a layered plates bonding process is developed by combined evaluation of experiment, simulation and optimization technique. A small bonded specimens of rectangular plate are prepared to this end, and put into a thermal loading conditions. $Moir{\acute{e}}$ interferomety is used to measure submicron displacements occurred during the process. The elevated temperature is chosen as control factors. FE analysis with constant values for the adhesive materials is also carried out to simulate the experiment. Significant differences are observed from the two results, in which the simulation predicts the monotonic increase of the bending displacement whereas the measurement shows decrease of the displacement at above $75^{\circ}C$. In order to minimize the difference of the two, material parameters of the adhesive at a number of different temperatures are posed as unknowns to be determined, and optimization is conducted. As a result, optimum material parameters are found that excellently matches the simulation and experiment, which are decreased with respect to the temperature.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1101-1106
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• 2005

The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Operating data (trace parameters) were collected on-line but quality data (measurement parameters) were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Thus, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were employed for data generation, and then modeling was accomplished, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to the control parameters. The dynamic polynomial neural network (DPNN) was used for data modeling that used the ingot fabrication data.

• 한국기계가공학회지
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• 제21권7호
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• pp.43-52
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• 2022

Design of a controller for a high-precision servo control system has been a popular topic while finding optimal parameters for multiple controllers is still a challenging subject. In this paper, we propose a practical scheme to optimize multi-parameters for the robust servo controller design by introducing a new cost function and optimization scheme. The proposed design method provides a simple and practical tool for the systematic servo design to reduce the control error with guaranteeing robust stability of the overall system. The reduction of the position error by 24% along with a faster convergence rate is demonstrated using a typical hard disk drive servo controller with 41 parameters.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.1611-1616
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• 2004

The objective of this study is to simulate the etching characteristics under different process parameters for the optimization of etching process. The etching characteristics such as the etching factor were investigated under different operating conditions and compared with the spray characteristics. The spray characteristics were measured by using Phase Doppler Anemometer. The correlation between the etching characteristics and the spray characteristics was analyzed to simulate the etching characteristics under the actual parameters of the etching process. The parameters were distance of nozzle tip and pipe pitch. To improve the uniformity and value of etching factor in the etching process, the process parameters should be designed optimally. The distribution of spray was simulated by the Monte-Carlo Method and the process parameters were optimized by the design of experiments(DOE).

• 대한수학회보
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• 제34권4호
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• pp.495-508
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• 1997

The problem of optimization in choosing of evasion parameters in differential games is considered. Existence of optimal parameters is proved and algorithm of their is shown. The example is cited. This work adjoins investigations [1-11].

• Structural Engineering and Mechanics
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• 제56권6호
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• pp.959-982
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• 2015

In this study, a non-stationary random earthquake Clough-Penzien model is used to describe earthquake ground motion. Using stochastic direct integration in combination with an equivalent linear method, a solution is established to describe the non-stationary response of lead-rubber bearing (LRB) system to a stochastic earthquake. Two parameters are used to develop an optimization method for bearing design: the post-yielding stiffness and the normalized yield strength of the isolation bearing. Using the minimization of the maximum energy response level of the upper structure subjected to an earthquake as an objective function, and with the constraints that the bearing failure probability is no more than 5% and the second shape factor of the bearing is less than 5, a calculation method for the two optimal design parameters is presented. In this optimization process, the radial basis function (RBF) response surface was applied, instead of the implicit objective function and constraints, and a sequential quadratic programming (SQP) algorithm was used to solve the optimization problems. By considering the uncertainties of the structural parameters and seismic ground motion input parameters for the optimization of the bearing design, convex set models (such as the interval model and ellipsoidal model) are used to describe the uncertainty parameters. Subsequently, the optimal bearing design parameters were expanded at their median values into first-order Taylor series expansions, and then, the Lagrange multipliers method was used to determine the upper and lower boundaries of the parameters. Moreover, using a calculation example, the impacts of site soil parameters, such as input peak ground acceleration, bearing diameter and rubber shore hardness on the optimization parameters, are investigated.