• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.12
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• pp.1141-1150
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• 2012

This paper describes the shape optimization of impeller blades for an anti-heeling bidirectional axial flow pump used in ships. In general, a bidirectional axial pump has efficiency much lower than that of a classical unidirectional pump because of the symmetry of the blade type. In this study, by focusing on a pump impeller, the shape of the blades is redesigned to develop a bidirectional axial pump with higher efficiency. The commercial code employed in this simulation is CFX v.13. The CFD result of the pump torque, head, and hydraulic efficiency was compared. The orthogonal array (OA) and analysis of variance (ANOVA) techniques and surrogate-model-based optimization using orthogonal polynomials are employed to determine the main effects and their optimal design variables. According to the optimal design, we confirm an effective design variable for impeller blades and explain the optimal solution as well as the usefulness of satisfying the constraints of the pump torque and head.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.40-48
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• 2009

In this article, scheduling of a casting sequence is studied in a casting foundry which must deliver products according to the Just-in-time(JIT) production policy of a customer. When a foundry manufactures a variety of casts with an identical alloy simultaneously, it frequently faces the task of production scheduling. An optimal casting schedule should be emphasized in order to maximize the production rate and raw material efficiency under the constraints of limited resources; melting furnaces and operation time for a casting machine. To solve this practical problem-fulfilling the objectives of casting the assigned mixed orders for the highest raw material efficiency in a way specified by the customer's JIT schedule, we implement simple integer programming. A simulation to solve a real production problem in a typical casting plant proves that the proposed method provides a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Employing this simple methodology, a casting foundry having an automated casting machine can produce a mixed order of casts with a maximum furnace utilization within the due date, and provide them according to their customer's JIT inventory policy.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1851-1864
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• 1997

This paper presents an algorithm simplifying the ESOP function by several rules. The algorithm is repeatedly performing operations based on the state of each terms by the product transformation operation of two functions and thus it is simplifying the ESOP function through the reduction of the product terms. Through the minimization of the product terms of the multi-valued input binary multi-output function, an optimization of the input has been done using EXOR PLA with input decoder. The algorithm when applied to four valued arithmetic circuit has been used for a EXOR logic circuit design and the two bits input decoder has been used for a EXOR-PLA design. It has been found from a computer simulation(IBM PC486) that the suggested algorithm can reduce the product terms of the output function remarkably regardless of the number of input variables when the variable AND-EXOR PLA is applied to the poperation circuit.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.5
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• pp.572-581
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• 2008

The performance of a barrel stave flextensional transducer is determined by the properties of its constituent materials and the effects of many structural parameters. In this study, with the finite element method, the structure of a barrel stave flextensional transducer was optimized to achieve the widest bandwidth while satisfying the requirements on pressure and center frequency. The optimization was carried out with the SQP-PD method for multi-variable minimization. The optimized barrel stave flextensional transducer satisfied all the required specifications.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.106-108
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• 1987

Until now, inflow has been handled an independent log-normal random variable in the problem of planning the long-term operation of a multi-reservoir hydrothermal electric power generation system. This paper introduces the detail study for making rule curve by applying weekly time interval for handling inflows. The hydro system model consists of a set of reservoirs and ponds. Thermal units are modeld by one equivalent thermal unit. Objective is minimizing the total cost that the summation of the fuel cost of equivalent thermal unit at each time interval. For optimization, stochastic dynamic programming(SDP) algorithm using successive approximations is used.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.1
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• pp.1-12
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• 1995

In order to seek various relationships among many design parameters employed in the design of the axial-flow fans the program which generates acoustic spectrum has been developed and its validity verified. Outputs of the program, with other outputs from a formerly developed performance prediction program, have been used to form a multi-objective function, for which an optimal design process was carried out. The present analysis shows that overall noise level and efficiency has contrasting trends, and the chord length turns out to be the most critical design variable. In the chosen design case of requirements $Q=2000m^2/min$, ${\Delta}P_s=67mmAq$, D=1.4m, the chord length of 0.2059m minimizes the overall noise level, while chord length of 0.1254m maximizes the efficiency. The resulting chord length in the balanced optimization is 0.1809m.

• Computers and Concrete
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• v.26 no.4
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• pp.309-316
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• 2020

The application of multi-variable adaptive regression spline (MARS) in predicting he long-term compressive strength of a concrete with various admixtures has been investigated in this study. The compressive strength of concrete specimens, which were made based on 24 different mix designs using various mineral and chemical admixtures in different curing ages have been obtained. First, The values of fly ash (FA), micro-silica (MS), water-reducing admixture (WRA), coarse and fine aggregates, cement, water, age of samples and compressive strength were defined as inputs to the model, and MARS analysis was used to model the compressive strength of concrete and to evaluate the most important parameters affecting the estimation of compressive strength of the concrete. Next, the proposed equation by the MARS method using particle swarm optimization (PSO) algorithm has been optimized to have more efficient equation from the economical point of view. The proposed model in this study predicted the compressive strength of the concrete with various admixtures with a correlation coefficient of R=0.958 rather than the measured compressive strengths within the laboratory. The final model reduced the production cost and provided compressive strength by reducing the WRA and increasing the FA and curing days, simultaneously. It was also found that due to the use of the liquid membrane-forming compounds (LMFC) for its lower cost than water spraying method (SWM) and also for the longer operating time of the LMFC having positive mechanical effects on the final concrete, the final product had lower cost and better mechanical properties.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.258-264
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• 2018

This paper presents application of a differential search (DS) meta-heuristic optimization algorithm for optimal operation of a micro grid system. The DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. The micro grid system consists of a wind turbine, a diesel generator, a fuel cell, and a photovoltaic system. The wind turbine generator is modeled by considering the characteristics of variable output. Optimization is aimed at minimizing the cost function of the system, including fuel costs and maximizing fuel efficiency to generate electric power. The simulation was applied to a micro grid system only. This study applies the DS algorithm with excellence and efficiency in terms of coding simplicity, fast convergence speed, and accuracy in the optimal operation of micro grids based on renewable energy resources, and we compared its optimum value to other algorithms to prove its superiority.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.191-200
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• 2017

A robust parameter set (ROPS) selection framework for an unsteady flow model was developed by combining Pareto optimums obtained by outcomes of model calibration using multi-site observations with the minimax regret approach (MRA). The multi-site calibration problem which is a multi-objective problem was solved by using an aggregation approach which aggregates the weighted criteria related to different sites into one measure, and then performs a large number of individual optimization runs with different weight combinations to obtain Pareto solutions. Roughness parameter structure which can describe the variation of Manning's n with discharges and sub-reaches was proposed and the related coefficients were optimized as model parameters. By applying the MRA which is a decision criterion, the Pareto solutions were ranked based on the obtained regrets related to each Pareto solution, and the top-rated one due to the lowest aggregated regrets of both calibration and validation was determined as the only ROPS. It was found that the determination of variable roughness and the corresponding standardized RMSEs at the two gauging stations varies considerably depending on the combinations of weights on the two sites. This method can provide the robust parameter set for the multi-site calibration problems in hydrologic and hydraulic models.