• Environmental Engineering Research
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• 제23권2호
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• pp.175-180
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• 2018

Box-Behnken Design (BBD) under response surface methodology (RSM) was implemented to optimization the operating parameters and assess the removal and recovery efficiencies of crude oil from contaminated soil using subcritical water extraction. The effects of temperature, extraction time and water flow rate were explored, and the results indicate that temperature has a great impact on crude oil removal and recovery. The correlation coefficients for oil removal ($R^2=0.74$) and recovery ($R^2=0.98$) suggest that the proposed quadratic model is useful. When setting the target removal and recovery (>99%), BBD-RSM determined the optimum condition to be a temperature of $250^{\circ}C$, extraction time of 120 min, and water flow rate of 1 mL/min. An experiment was carried out to confirm the results, with removal and recovery efficiencies of 99.69% and 87.33%, respectively. This result indicates that BBD is a suitable method to optimize the process variables for crude oil removal and recovery from contaminated soil.

• 대한조선학회논문집
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• 제49권1호
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• pp.33-44
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• 2012

In this study, the optimal operating conditions for the dual mixed refrigerant(DMR) cycle were determined by considering the power efficiency. The DMR cycle consists of compressors, heat exchangers, seawater coolers, valves, phase separators, tees, and common headers, and the operating conditions include the equipment's flow rate, pressure, temperature, and refrigerant composition per flow. First, a mathematical model of the DMR cycle was formulated in this study by referring to the results of a past study that formulated a mathematical model of the single mixed refrigerant(SMR) cycle, which consists of compressors, heat exchangers, seawater coolers, and valves, and by considering as well the tees, phase separators, and common headers. Finally, in this study, the optimal operating conditions from the formulated mathematical model was obtained using a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP). Moreover, the required power at the obtained conditions was decreased by 1.4% compared with the corresponding value from the past relevant study of Venkatarathnam.

• 전자공학회논문지SC
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• 제39권6호
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• pp.59-70
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• 2002

본 논문에서는 최적 효율과 고성능으로 동작하는 SynRM(Synchronous Reluctance Motor)을 위한 위치 및 속도 센서리스 벡터제어를 제시한다. 제시한 제어 방법은 고정자 전압과 전류의 자속 추정에 기초한다. 그리고 동손과 철손을 최소화하는 효율 최적화의 전류각 조건은 SynRM의 등가회로를 기초로 유도한다. 폐루프 위치 및 속도 제어의 연구결과는 최적화 제어의 입증하였다.

• 한국산학기술학회논문지
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• 제19권7호
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• pp.337-342
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• 2018

도시유역에서 발생되는 내수침수를 방어하는 수단으로 구조적 대책인 빗물펌프장이 있으나 현실적 적용에 어려움이 있기 때문에 비구조적 대책 등이 보안되어야 한다. 본 연구에서는 빗물펌프장 실무운영 담당자의 의견을 반영한 최소의 월류량을 가지는 펌프의 최적운영수위를 결정하였다. 빗물펌프장의 최적운영수위를 산정하기 위해 최적화 기법인 GA(Genetic Algorithm)을 이용하였으며, 도시유역의 강우-유출 모형인 SWMM(Ver.5.1) DLL과 연계하였다. 제약조건으로는 펌프의 효율을 극대화하는데 까지의 걸리는 시간을 고려하였으며, 최적운영수위를 산정한 결과 전체적으로 기존운영수위보다 낮은 운영 수위에서 월류량이 감소하였다. 대부분 펌프의 경우 각 펌프 호기의 운영 범위에서 가장 낮은 운영 수위가 선정되었다. 초기 펌프의 운영하는 것이 월류량을 저감할 수 있는 것으로 판단되며 이 후 펌프 운영 조건 변경을 하여도 월류 저감에 변화는 없는 것으로 나타났다. 내수침수 저감정도는 약 1%~2%로 산출되었으며, 하류지역에서 발생되는 월류량을 저감하는 정도이지만, 펌프의 운영적 관점에서 기계적 및 실무적 관점의 접근에 따른 효과적인 운영이라 판단된다. 향후, 펌프의 운영조건 등을 고려한다면, 펌프의 효율을 증대하고 내수침수를 저감하는데 도움이 되리라 판단된다.

• 한국정밀공학회지
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• 제19권9호
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• pp.111-117
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• 2002

In most machining companies, operators decide the cutting condition, a pair of spindle speed (5) and table federate (F) by experience and subjective judgment. As cutting conditions are determined by operators' experience and ability, inconsistent cutting conditions are given in same operating conditions. The objective of this study is to develop the cutting condition decision system which utilizes shop data and predicts tool life by neural network and eventually leads to the optimal cutting condition. The production time per piece is considered for an optimization object. We will discuss the process of an optimal cutting condition decision by neural network. By this process, a series of shop data is stored. And neural network is constructed for prediction of tool life and the optimal cutting condition is recommended from a cutting condition decision system using the stored shop data. The results show that the developed system is rational in searching the optimal cutting conditions on job operations.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 추계학술대회 초록집
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• pp.97.1-97.1
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• 2011

Dimethyl ether (DME) is an attractive fuel as a hydrogen carrier for mobile PEMFC applications. However, its reforming technologies are rarely studied especially by using autothermal reforming (ATR) method. This work explored the impact of operating conditions to the performance of DME ATR. Temperature, Steam to carbon ratio(SCR), Oxygen to carbon ratio(OCR) and Gas hourly space velocity(GHSV) were considered as the operating conditions. As results, conversion efficiency was increased as the temperature increased, but saturated around $700^{\circ}C$. There was no significant effect of SCR on conversion efficiency, but high SCR led reactions in endothermic manner. High OCR substantially suppressed conversion efficiency, but it helped to sustain the temperature by stimulating exothermic reactions. Conversion efficiency was decreased as GHSV increased. The optimized operating conditions was suggested: $700^{\circ}C$, SCR of 1.5, OCR of 0.45 and GHSV below 15000/h and conversion efficiency was ~85% at the conditions.

• 실천공학교육논문지
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• 제15권2호
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• pp.419-427
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• 2023

In this study, optimal adhesion conditions to alleviate defects caused by heat shrinkage with FDM type 3D printers with machine learning are researched. Machine learning is one of the "statistical methods of extracting the law from data" and can be classified as supervised learning, unsupervised learning and reinforcement learning. Among them, a function model for adhesion between the bed and the output is presented using supervised learning specialized for optimization, which can be expected to reduce output defects with FDM type 3D printers by deriving conditions for optimum adhesion between the bed and the output. Machine learning codes prepared using Python generate a function model that predicts the effect of operating variables on adhesion using data obtained through adhesion testing. The adhesion prediction data and verification data have been shown to be very consistent, and the potential of this method is explained by conclusions.

• 한국국방경영분석학회지
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• 제7권1호
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• pp.118-138
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• 1981

In many response surface optimization problems for industrial processes, there are more than two responses of interest, and we want to find the optimal levels of the factors that influence the responses. This paper is to propose how to set up the desirability functions to find the optimum for a given set of data, and to propose how to analyse the data and the desirability functions to determine an optimal operating condition for the factors. To implement the proposed method in practice, a FORTRAN computer program was written and explained. Finally, an industrial example is illustrated to explain the proposed technique and the source list of the computer program is attached for the users.

• 품질경영학회지
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• 제8권1호
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• pp.3-7
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• 1980

In many industrial processes, there are more than two responses (i.e., yield, percent impurity, etc.) of interest, and it is desirable to determine the optimal levels of the factors (i.e., temperature, pressure, etc.) that influence the responses. Suppose the response relationships are assumed to be approximated by second-order polynomial regression models. The problems considered in this paper is, first, to propose how to select polynomial terms to fit the multivariate regression surfaces for a given set of data, and, second, to propose how to analyze the data to obtain an optimal operating condition for the factors. The proposed techniques were applied for empirical process optimization in a tire company in Korea. This case is presented as an illustration.

• 설비공학논문집
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• 제24권12호
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• pp.867-874
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• 2012

In the present study, three-dimensional transient numerical simulations were carried out to improve the performance of a vehicle paint drying process. In order to describe the movement of a vehicle, the techniques of moving boundary condition and multiple reference flames (MRF) were used. For the validation of the numerical analysis, the predicted temperature on the surface of a vehicle was compared to the experimental data, and a good agreement was achieved. With validated numerical procedure, various operating conditions of the temperature and the flow rate of the supply air were investigated to improve the drying performance of the facility. It is shown that the optimization of the operating condition can lead to energy savings and faster line speed of the production.