• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.3
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• pp.143-148
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• 2018

In this paper, the optimal fuzzy logic controller(FLC) for a hybrid renewable energy system(HRES) is proposed. Generally, hybrid renewable energy systems can consist of wind power, solar power, fuel cells and storage devices. The proposed FLC can effectively control the entire HRES by determining the output power of the fuel cell or the absorption power of the electrolyzer. In general, fuzzy logic controllers can be optimized by classical optimization algorithms such as genetic algorithms(GA) or particle swarm optimization(PSO). However, these FLC have a disadvantage in that their performance varies greatly depending on the control parameters of the optimization algorithms. Therefore, we propose a method to optimize the fuzzy logic controller using the teaching-learning based optimization(TLBO) algorithm which does not have the control parameters of the algorithm. The TLBO algorithm is an optimization algorithm that mimics the knowledge transfer mechanism in a class. To verify the performance of the proposed algorithm, we modeled the hybrid system using Matlab Tool and compare and analyze the performance with other classical optimization algorithms. The simulation results show that the proposed method shows better performance than the other methods.

• The Journal of the Acoustical Society of Korea
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• v.32 no.3
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• pp.237-246
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• 2013

This paper proposes a hydrophone array design optimization technique for cavitation tunnel noise measurements. The optimization technique comprises of design parameters, an objective function and an optimization algorithm. The design parameters are defined for circular, spiral and multi-spiral arrays. The objective function is defined so as to consider the mainlobe beamwidth and the maximum sidelobe level simultaneously. A global optimization scheme is applied to the array design using very fast simulated reannealing (VFSR). After applying the optimization technique to arrays respectively, the peak sidelobe level and the mainlobe beamwidth of optimum arrays are analyzed. Finally the array patterns considering multiple reflections in the cavitation tunnel are evaluated to validate the proposed method.

• Journal of Welding and Joining
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• v.34 no.3
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• pp.23-30
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• 2016

This paper discusses the optimization of friction stir spot welding (FSSW) process parameters for joining Aluminum alloy (AA6061-T6) with Magnesium alloy (AZ31B) sheets. Prior to optimization an empirical relationship was developed to predict the Tensile Shear Fracture Load (TSFL) incorporating the four most important FSSW parameters, i.e., tool rotational speed, plunge rate, dwell time and tool diameter ratio, using response surface methodology (RSM). The experiments were conducted based on four factor, five levels central composite rotatable design (CCD) matrix. The maximum TSFL obtained was 3.61kN, with the tool rotation of 1000 rpm, plunge rate of 16 mm/min, dwell time of 5 sec and tool diameter ratio of 2.5.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.1-10
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• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.71-90
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• 2016

Steel nitriding is a thermo-chemical process leading to surface hardening and improvement in fatigue properties. The process is strongly influenced by many different variables such as steel composition, nitrogen potential, temperature, time, and quenching media. In the present study, the influence of such parameters affecting physic-chemical and mechanical properties of nitride steels was evaluated. The aim was to streamline the process by numerical-experimental analysis allowing defining the optimal conditions for the success of the process. Input parameters-output results correlations were calculated through the employment of a multi-objective optimization software, modeFRONTIER (Esteco). The mechanical and microstructural results belonging to the nitriding process, performed with different processing conditions for various steels, are presented. The data were employed to obtain the analytical equations describing nitriding behavior as a function of nitriding parameters and steel composition. The obtained model was validated, through control designs, and optimized by taking into account physical and processing conditions.

• Journal of electromagnetic engineering and science
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• v.17 no.4
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• pp.208-220
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• 2017

This paper proposes an experimental optimization method for a wireless power transfer (WPT) system. The power transfer characteristics of a WPT system with arbitrary loads and various types of coupling and compensation networks can be extracted by frequency domain measurements. The various performance parameters of the WPT system, such as input real/imaginary/apparent power, power factor, efficiency, output power and voltage gain, can be accurately extracted in a frequency domain by a single passive measurement. Subsequently, the design parameters can be efficiently tuned by separating the overall design steps into two parts. The extracted performance parameters of the WPT system were validated with time-domain experiments.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.6 s.150
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• pp.693-699
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• 2006

This paper proposes a design optimization technique for ship RCS signature reductions using Taguchi method. The proposed technique comprises of i)evaluating initial RCS signatures, ii)defining critical areas which should be modified as design parameters, and threat factors which can't be controlled artificially as noise parameters, and finally iv)finding optimum parameters via analyzing signal to noise ratios for designated characteristics. We applied the technique to a model ship and found that it is suitable for radar stealth designs. In addition, the proposed technique is applicable to submarine designs against sonar threats.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.2
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• pp.229-239
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• 1998

The present paper examines the thermal and flow characteristics of a parallel flow heat exchanger and investigates the effects of the parameters on thermal performance by defining the flow nonuniformity. Thermal performance of a parallel flow heat exchanger is maximized by the optimization using Newton's searching method. The flow nonuniformity is chosen as an object function. The parameters such as the locations of separator, inlet, and outlet are expected to have a large influence on thermal performance of a parallel flow heat exchanger. The effect of these parameters are quantified by flow nonuniformity. The results show that the optimal locations of inlet and outlet are 19.73 mm and 10.9 mm, respectively. It is also shown that the heat transfer increases by 7.6% and the pressure drop decreases by 4.7%, compared to the reference model.

• The KSFM Journal of Fluid Machinery
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• v.11 no.3
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• pp.36-42
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• 2008

In this paper, the performance characteristics of the impeller in a centrifugal pump were investigated using DOE(Design of Experiment) with commercial CFD software. Geometric parameters of vane plane development were defined with the meridional shape and frontal view of the impeller. The incidence angles and the exit blade angle were selected as main parameters using 2k factorial and the influences of selected design parameters were examined through the optimization process using RSM.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.9
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• pp.139-145
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• 1997

This study is concerned with the optimizing method of control parameters for a hydraulic speed control system by using genetic algorithms which are general purpose search algorithms based on natural evolution and genetics. It is shown that the genetic altorithms satisfactorily oiptimized control gains of the PI speed control system of an electrohydraulic servomotor and that optimization of control para- meters can be achived without much experience and knowledge for tuning. It is also shown that optimal gains may be determined from fitness distribution curves plotted in given gain spaces.