• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2000년도 가을 학술발표회논문집(I)
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• pp.199-204
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• 2000

In this study, an optimum design algorithm using efficient reanalysis is proposed for seismic design of RC Piers. The proposed algorithm for optimization of RC Piers is based on efficient reanalysis technique. Considering structural behavior of RC Piers, several other approximation techniques, such as artificial constraint deletion is introduced to increase the efficiency of optimization. The efficiency and robustness of the proposed algorithm increase the proposed reanalysis technique is demonstrated by comparing it with a conventional optimization algorithm. A few of design examples are optimized to show the applicability of the proposed algorithm.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1406-1420
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• 2017

Artificial neural networks (ANNs) play an important role in the fields of function approximation, prediction, and classification. ANN performance is critically dependent on the input parameters, including the number of neurons in each layer, and the optimal values of weights and biases assigned to each neuron. In this study, we apply the particle swarm optimization method, a popular optimization algorithm for determining the optimal values of weights and biases for every neuron in different layers of the ANN. Several regression models, including general linear regression, Fourier regression, smoothing spline, and polynomial regression, are conducted to evaluate the proposed method's prediction power compared to multiple linear regression (MLR) methods. In addition, residual analysis is conducted to evaluate the optimized ANN accuracy for both training and test datasets. The experimental results demonstrate that the proposed method can effectively determine optimal values for neuron weights and biases, and high accuracy results are obtained for prediction applications. Evaluations of the proposed method reveal that it can be used for prediction and estimation purposes, with a high accuracy ratio, and the designed model provides a reliable technique for optimization. The simulation results show that the optimized ANN exhibits superior performance to MLR for prediction purposes.

• Smart Structures and Systems
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• 제18권6호
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• pp.1233-1250
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• 2016

Cracks in plate-like structures are some of the main reasons for destruction of the entire structure. In this study, a novel two-stage methodology is proposed for damage detection of flexural plates using an optimized artificial neural network. In the first stage, location of damages in plates is investigated using curvature-moment and curvature-moment derivative concepts. After detecting the damaged areas, the equations for damage severity detection are solved via Bat Algorithm (BA). In the second stage, in order to efficiently reduce the computational cost of model updating during the optimization process of damage severity detection, multiple damage location assurance criterion index based on the frequency change vector of structures are evaluated using properly trained cascade feed-forward neural network (CFNN) as a surrogate model. In order to achieve the most generalized neural network as a surrogate model, its structure is optimized using binary version of BA. To validate this proposed solution method, two examples are presented. The results indicate that after determining the damage location based on curvature-moment derivative concept, the proposed solution method for damage severity detection leads to significant reduction of computational time compared with direct finite element method. Furthermore, integrating BA with the efficient approximation mechanism of finite element model, maintains the acceptable accuracy of damage severity detection.

• 한국유체기계학회 논문집
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• 제16권1호
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• pp.40-46
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• 2013

Recently, the duct system with a cross flow fan was used to improve the ventilation in various industrial fields. For the efficient ventilation, it is necessary to design the duct system based on the flow characteristics around the cross flow fan. In the present study, the flow characteristics around a cross flow fan in the ventilation duct were predicted by using the moving mesh and sliding interface techniques for the rotation of blades. To design the duct system with the high performance of ventilation, the CFD simulations were repeated with the revised duct model based on the DOE. With the numerical results of flow rate through the ventilation duct with various geometric parameters, the optimized geometry of ventilation duct to maximize the flow rate was obtained by using the Kriging approximation method. From the performance curves of cross flow fan in the original and optimized models of ventilation duct, it was observed that the flow rate through the optimized model is about 16 percent larger than that through the original model.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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• pp.444-449
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• 1998

A modal transducer in two-dimensional structure can be implemented by varying the distributed transducer's gain spatially. In this paper, a method based on finite element method is developed for optimizing spatial gain distribution of PVDF transducer to create the modal transducer for specific modes. Using this concept, one can design the modal transducer in two-dimensional structure having arbitrary geometry and boundary conditions. As a practical means for implementing this continuous gain distribution without repoling die PVDF film, the gain distribution is approximated by optimizing gain-weights of interface circuit. The whole spatial area of the PVDF film is divided into several electrode segments and the signals from each segment are properly weighted and summed by interface circuit. This corresponds to the approximation of a continuous function using discrete values. The electrode partition is optimized using the genetic algorithm. Gain-weights are optimized using the simplex search method. A modal sensor for first to fourth modes of aluminum plate is designed using PVDF film with gain-weighted interface circuit. Various lamination angles of PVDF film are taken into consideration to utilize the anisotropy of the PVDF film. Performance of the optimized' PVDF sensor is demonstrated by numerical simulations..

• 대한기계학회논문집A
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• 제28권3호
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• pp.267-273
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• 2004

The purpose of this paper is to develop a systematic design method for the suspension system hard points and compliance elements, which have great influence on the handling stability of a vehicle. In this paper, a method to optimize J-turn responses is presented based on the principles of design of experiments, multi-body dynamic analysis and optimum design technique. The design variables associated with the J-turn maneuver are selected through the experimental design sensitivity analysis using the perturbation method. An objective function is defined as an approximate function for the J-turn characteristics using the TSA(Taylor series approximation). The values of the design variables, which make the optimized J-turn characteristics, are obtained using the conjugate gradient method. The result of the J-turn simulation shows that the optimized vehicle has more improved handling stability than the optimized vehicle.

• 대한토목학회논문집
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• 제9권1호
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• pp.33-40
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• 1989

철근 콘크리트 뼈대구조는 설계변수가 많고, 목적함수의 제약조건이 복잡하여 주로 반복적인 재해석에 의하여 최적해에 접근하는 방법이 사용되고 있다. 본 연구에서는 다단계분할(multilevel decomposition)에 의하여 최적화 문제를 형성하여 재해석과정을 줄이고 효과적으로 설계변수를 취할 수 있도록 하였다. 최적화의 단계는 첫째 단계에서 비선형거동에 의한 재분배모멘트의 설계공간을 계산하여 설계모멘트에 대한 제약조건식을 형성하고, 둘째 단계에서는 재분배 모멘트를 최적화하였으며, 셋째 단계에서는 설계단면을 최적화하였다. 이때 재분배 모멘트의 최적화에 따른 첫째 단계의 모멘트의 설계공간의 변화는 부재력 변화량 추정(force approximation technique)에 의하여 수정하도록 하며, 변수를 단계별로 줄여 수렴을 가속화시킬 수 있도록 하였다. 최적화 문제의 목적함수로는 경비함수를 취하였으며 영국 CP110의 한계상태설계법을 이용하여 부재의 응력제약조건식을 유도하고, 설계예를 통하여 본 연구의 타당성과 효율성을 구명하였다.

• International Journal of Fluid Machinery and Systems
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• 제3권2호
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• pp.150-159
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• 2010

Laidback fan shaped film-cooling hole is formulated numerically and optimized with the help of three-dimensional numerical analysis, surrogate methods, and the multi-objective evolutionary algorithm. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by four geometric design variables, the injection angle of the hole, the lateral expansion angle of the diffuser, the forward expansion angle of the hole, and the ratio of the length to the diameter of the hole, to maximize the film-cooling effectiveness compromising with the aerodynamic loss. The objective function values are numerically evaluated through Reynolds- averaged Navier-Stokes analysis at the designs that are selected through the Latin hypercube sampling method. Using these numerical simulation results, the Response Surface Approximation model are constructed for each objective function and a hybrid multi-objective evolutionary algorithm is applied to obtain the Pareto optimal front. The clustered points from Pareto optimal front were evaluated by flow analysis. These designs give enhanced objective function values in comparison with the experimental designs.

• 한국유체기계학회 논문집
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• 제14권5호
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• pp.63-68
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• 2011

This paper presents an optimization procedure for performance improvement of a tunnel ventilation jet fan. Optimization techniques based on response surface approximation (RSA) are employed to improve the aerodynamic performance of a tunnel ventilation jet fan. For numerical analysis, three-dimensional Renolds- averaged Navier-Stokes (RANS) equations with shear stress transport turbulence model are discretized by using finite volume approximations and solved on hexahedral grids to evaluate the total efficiency at the operating condition as the objective function. Four geometric variables defining the meridional length and the thickness profile at the hub and shroud in the jet fan rotor are selected as design variables for the numerical optimization. The results of the numerical optimization show that the total efficiency of the optimized model is significantly improved in comparison with the base model.

• 한국정보과학회논문지:데이타베이스
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• 제31권1호
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• pp.13-22
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• 2004

멀티미디어 데이타의 사용이 증가함에 따라 고차원 이미지 데이타에 대한 효율적인 색인과 검색 기법이 크게 요구되고 있다. 그러나 많은 노력에도 불구하고 현재의 다차원 색인 기법들은 고차원 데이타 공간에서 만족할 만한 성능을 보여주지 못하고 있다. 이러한 소위 차원의 저주를 해결하기 위해 최근에 차원을 줄이거나 근사 해를 구하는 둥의 접근법이 시도되고 있지만 이러한 방법들은 근본적으로 정확도의 상실이라는 문제를 갖고 있다. 정확도의 보존을 위해 VA-file, LPC-file둥과 같이 벡터 근사에 기반 한 기법들이 최근에 개발되었다. 그러나 이 기법은 검색 성능이 색인 파일의 크기에 큰 영향을 받으며, 한번에 큰 검색 공간을 줄이는 계층 색인 구조의 장점을 상실한다. 본 논문에서는 이미지 데이터베이스에서 유사성 질의를 위한 새로운 계층 색인 구조인 GC-트리를 제안한다. GC-트리는 밀도 함수에 기초하여 데이타 공간을 적응적으로 분할하고, 색인 구조를 동적으로 생성한다. 이러한 특성을 갖는 GC-트리는 군집화 된 고차원 이미지 데이타 검색에 훌륭한 성능을 나타낸다.