• Wind and Structures
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• v.20 no.6
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• pp.751-761
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• 2015

A multi-platform offshore wind farm is receiving the worldwide attention for the sake of maximizing the wind power capacity and the dynamic stability at sea. But, its wind power efficiency is inherently affected by the interference of wake disturbed by the rotating blades, so its layout should be appropriately designed to minimize such wake interference. In this context, the purpose of this paper is to introduce a layout optimization for multi-platform offshore wind farm consisted of 2.5MW spar-type floating wind turbines. The layout is characterized by the arrangement type of wind turbines, the spacing between wind turbines and the orientation of wind farm to the wind direction, but the current study is concerned with the spacing for a square-type wind farm oriented with the specific angle. The design variable and the objective function are defined by the platform length and the total material volume of the wind farm. The maximum torque loss and overlapping section area are taken as the constraints, and their meta-models expressed in terms of the design variable are approximated using the existing experimental data and the geometry interpretation of wake flow.

• Journal of the Korea Society for Simulation
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• v.16 no.2
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• pp.45-54
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• 2007

In this article, we propose a different modeling approach, which aims at the simulation optimization so as to meet the design specification. Generally, Multi objective optimization problem is formulated by dependent factors as objective functions and independent factors as constraints. However, this paper presents the critical(dependent) factors as objective function and design(independent) factors as constraints for the selection of design factors directly. The objective function is normalized far the generalization of design factors while the constraints are composed of the simulation-based regression metamodels fer the critical factors and design factor's domain. Then the effective and fast solution procedure based on the pareto optimal solution set is proposed. This paper provides a comprehensive framework for the system design using the simulation and metamodels. Therefore, the method developed for this research can be adopted for other enhancements in different but comparable situations.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.2
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• pp.1-12
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• 2019

Open space planners and designers should consider scientific and quantified functions of trees when they have to locate where to plant the tree. However, until now, most planners and designers could not consider them because of lack of tool for considering scientific and quantitative tree functions. This study introduces a tree location supporting tool which focuses on the multi-objective including scientific function using ACO (Ant colony optimization). We choose shading effect (scientific function), shielding, and openness as objectives for test application. The results show that when the user give a high weight to a particular objective, they can obtain the optimal results with high value of that objective. When we allocate higher weight for the shading effect, the tree plans provide larger shadow value. Even when compared with current tree plan, the study result has a larger shading effect plan. This result will reduce incident radiation to the ground and make thermal friendly open space in the summer. If planners and designers utilize this tool and control the objectives, they would get diverse optimal tree plans and it will allow them to make use of the many environmental benefits from trees.

• 한국전산유체공학회:학술대회논문집
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• 1999.11a
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• pp.77-84
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• 1999

Numerical design optimization techniques are implemented for the improvement of the ram accelerator performance. The design object is to find the minimum ram tube length required to accelerate projectile from initial velocity $V_0$ to target velocity $V_e$. The premixture is composed of $H_2,\;O_2,\;N_2$ and the mole numbers of these species are selected as design variables. The objective function and the constraints are linearized during the optimization process and gradient-based Simplex method and SLP(Sequential Linear Programming) have been employed. With the assumption of two dimensional inviscid flow for internal flow field, the analyses of the nonequilibrium chemical reactions for 8 steps 7 species lave been performed. To determined the tube length, ram tube internal flow field is assumed to be in a quasi-steady state and the flow velocity is divided into several subregions with equal interval. Hence the thrust coefficients and accelerations for corresponding subregions are obtained and integrated for the whole velocity region. With the proposed design optimization techniques, the total ram tube length had been reduced $19\%$ within 7 design iterations. This optimization procedure can be directly applied to the multi-stage, multi-premixture ram accelerator design optimization problems.

• Journal of the Semiconductor & Display Technology
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• v.20 no.4
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• pp.38-43
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• 2021

Permanent magnet linear synchronous motor (PMLSM) is suitable for use in cleanroom environments and have advantages such as high speed, high thrust, and high precision. If the stators are arranged in the entire moving path of the mover, there is a problem in that the installation cost increases. To solve this problem, discontinuous armature arrangement PMLSM has been proposed. In this case, the mover receives a greater detent force in the section where the stator is not arranged. When a large detent force occurs, it appears as a ripple component of the thrust during PMLSM operation. If the shape of the stator is changed to reduce the detent force, the characteristics of the back EMF are changed. Therefore, in this paper, the detent force and the harmonic components of back EMF were reduced through multi-purpose shape optimization. To this end, the FEA model was constructed and main effect analysis was performed on the major shape variables affecting each objective function. Then, the optimal shape that minimizes the objective function was derived through the response surface analysis method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.95-104
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• 2017

This paper deals with solution methods for discrete and multi-valued optimization problems. The objective function of the problem incorporates noise effects generated in case that fitness evaluation is accomplished by computer based experiments such as Monte Carlo simulation or discrete event simulation. Meta heuristics including Genetic Algorithm (GA) and Discrete Particle Swarm Optimization (DPSO) can be used to solve these simulation based multi-valued optimization problems. In applying these population based meta heuristics to simulation based optimization problem, samples size to estimate the expected fitness value of a solution and population (particle) size in a generation (step) should be carefully determined to obtain reliable solutions. Under realistic environment with restriction on available computation time, there exists trade-off between these values. In this paper, the effects of sample and population sizes are analyzed under well-known multi-modal and multi-dimensional test functions with randomly generated noise effects. From the experimental results, it is shown that the performance of DPSO is superior to that of GA. While appropriate determination of population sizes is more important than sample size in GA, appropriate determination of sample size is more important than particle size in DPSO. Especially in DPSO, the solution quality under increasing sample sizes with steps is inferior to constant or decreasing sample sizes with steps. Furthermore, the performance of DPSO is improved when OCBA (Optimal Computing Budget Allocation) is incorporated in selecting the best particle in each step. In applying OCBA in DPSO, smaller value of incremental sample size is preferred to obtain better solutions.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.138-139
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• 2007

This research provides machine designers with some intuition to consider both, magnetic and heat transfer effects. A topological multi-objective function includes magnetic energy and heat inflow rate to the system, which equals to the total heat dissipation by conduction and convection. For the thermal field regarding the heat inflow, introduced as a reaction force, topology design sensitivity is derived by employing discrete equations. The adjoint variable method is used to avoid numerous sensitivity evaluations. As a numerical example, a C-core design excited by winding current demonstrates the strength of the multi-physical approach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.141-147
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• 2019

In this paper, a systematic beam splitter design for multi-beam forming is proposed. The objective of this research is to a design beam splitter that splits and focuses scattering microwaves into intense beams in multiple directions. It is difficult to split multi-beam to non-specific directions with theoretical approaches. Therefore, instead of using transformation optics(TO), which is a widely used process for controlling electromagnetic wave propagation, we used a systematic design process called the phase field design method to obtain an optimal topological structure of beam splitter. The objective function is to maximize the norm of electric field of the target areas of each direction. To avoid island structure and obtain the structure in one body, volume constraint is added to the optimization problem by using augmented Lagrangian. Target frequency is set to X-band 10GHz. The optimal beam splitter performed well in multi-beam forming and the transported electric energy of target areas improved. A frequency dependency test was conducted in the X-band to determine effective frequency range.

• Knowledge Management Research
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• v.21 no.1
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• pp.27-40
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• 2020

Response surface methodology (RSM) empirically studies the relationship between a response variable and input variables in the product or process development phase. The ultimate goal of RSM is to find an optimal condition of the input variables that optimizes (maximizes or minimizes) the response variable. RSM can be seen as a knowledge management tool in terms of creating and utilizing data, information, and knowledge about a product production and service operations. In the field of product or process development, most real-world problems often involve a simultaneous consideration of multiple response variables. This is called a multiple response surface (MRS) problem. Various approaches have been proposed for MRS optimization, which can be classified into loss function approach, priority-based approach, desirability function approach, process capability approach, and probability-based approach. In particular, the loss function approach is divided into univariate and multivariate approaches at large. This paper focuses on the univariate approach. The univariate approach first obtains the mean square error (MSE) for individual response variables. Then, it aggregates the MSE's into a single objective function. It is common to employ the weighted sum or the Tchebycheff metric for aggregation. Finally, it finds an optimal condition of the input variables that minimizes the objective function. When aggregating, the relative weights on the MSE's should be taken into account. However, there are few studies on how to determine the weights systematically. In this study, we propose an interactive procedure to determine the weights through considering a decision maker's preference. The proposed method is illustrated by the 'colloidal gas aphrons' problem, which is a typical MRS problem. We also discuss the extension of the proposed method to the weighted MSE (WMSE).

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.68-78
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• 2012

A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.