• International Journal of Aeronautical and Space Sciences
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• 제17권4호
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• pp.491-500
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• 2016

This paper presents a highly efficient aeroelastic optimization method based on a surrogate model; the model is verified by considering the case of a high-aspect-ratio composite wing. Optimization frameworks using the Kriging model and genetic algorithm (GA), the Kriging model and improved particle swarm optimization (IPSO), and the back propagation neural network model (BP) and IPSO are presented. The feasibility of the method is verified, as the model can improve the optimization efficiency while also satisfying the engineering requirements. Moreover, the effects of the number of design variables and number of constraints on the optimization efficiency and objective function are analysed in detail. The accuracy of two surrogate models in aeroelastic optimization is also compared. The Kriging model is constructed more conveniently, and its predictive accuracy of the aeroelastic responses also satisfies the engineering requirements. According to the case of a high-aspect-ratio composite wing, the GA is better at global optimization.

• 한국CDE학회논문집
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• 제19권3호
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• pp.245-252
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• 2014

Engineering applications of global optimization techniques are recently abundant in the literature and it may be caused by both new methodologies arising and faster computers coming out. Many of the optimization techniques are based on natural or biological phenomena. This study put focus on enhancing the performace of Cuckoo Search (CS) among them since it has the least number of parameters to tune. The proposed enhancement can be achieved by applying surrogate-based optimization at every cycle of CS, which fortifies the exploitation capability of the original method. The enhanced algorithm has been applied several engineering design problems with constraints. The proposed method shows comparable or superior performance to the original method.

• Steel and Composite Structures
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• 제27권4호
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• pp.427-438
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• 2018

In this paper, the single and multi-objective optimization of thin-walled conical tubes with different types of indentations under axial impact has been investigated using surrogate models called metamodels. The geometry of tapered thin-walled tubes has been studied in order to achieve maximum specific energy absorption (SEA) and minimum peak crushing force (PCF). The height, radius, thickness, tapered angle of the tube, and the radius of indentation have been considered as design variables. Based on the design of experiments (DOE) method, the generated sample points are computed using the explicit finite element code. Different surrogate models including Kriging, Feed Forward Neural Network (FNN), Radial Basis Neural Network (RNN), and Response Surface Modelling (RSM) comprised to evaluate the appropriation of such models. The comparison study between surrogate models and the exploration of indentation shapes have been provided. The obtained results show that the RNN method has the minimum mean squared error (MSE) in training points compared to the other methods. Meanwhile, optimization based on surrogate models with lower values of MSE does not provide optimum results. The RNN method demonstrates a lower crashworthiness performance (with a lower value of 125.7% for SEA and a higher value of 56.8% for PCF) in comparison to RSM with an error order of $10^{-3}$. The SEA values can be increased by 17.6% and PCF values can be decreased by 24.63% by different types of indentation. In a specific geometry, higher SEA and lower PCF require triangular and circular shapes of indentation, respectively.

• 대한산업공학회지
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• 제35권4호
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• pp.257-265
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• 2009

This paper considers the hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. In hybrid flow shops, each job is processed through multiple production stages in series, each of which has multiple identical parallel machines. The problem is to determine the allocation of jobs to the parallel machines at each stage as well as the sequence of the jobs assigned to each machine. Due to the complexity of the problem, we suggest search heuristics, tabu search and simulated annealing algorithms with a new method to generate neighborhood solutions. In particular, to evaluate and select neighborhood solutions, three surrogate objectives are additionally suggested because not much difference in the number of tardy jobs can be found among the neighborhoods. To test the performances of the surrogate objective based search heuristics, computational experiments were performed on a number of test instances and the results show that the surrogate objective based search heuristics were better than the original ones. Also, they gave the optimal solutions for most small-size test instances.

• 아동학회지
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• 제28권6호
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• pp.53-72
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• 2007

The purpose of this study was to understand the meaning and nature of long term boarding care of children provided by grandparents in surrogate foster homes. Data were collected from 10 children 15 to 18 years of age by in depth interviews and observation from May 2007 to July 2007. Analysis of data was by the phenomenological analytic method of Giorgi(1970). Seven essential themes were extracted: (1) ambivalence about being labeled "family headed by a child," (2) recognition of the burden to grandparents with appreciation for their care, (3) resentment and yearning for parents, (4) economic hardship, (5) discord with grandparents, (6) maladjustment to school life, and (7) overcoming such obstacles as poor economic conditions and loneliness.

• Journal of the Korean Data and Information Science Society
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• 제24권6호
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• pp.1543-1550
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• 2013

In this paper, we study Bayesian estimation for the finite population proportion in binary data under selection bias. We use a Bayesian nonignorable selection model to accommodate the selection mechanism. We compare four possible estimators of the finite population proportions based on data analysis as well as Monte Carlo simulation. It turns out that nonignorable selection model might be useful for weekly biased samples.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2017년도 제48회 춘계학술대회논문집
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• pp.304-309
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• 2017

본 연구에서는 zonal hybrid RANS/LES 기법을 사용하여 모델 스크램제트 연소기 내에서의 비예혼합 연소 현상에 대한 연구를 수행하였다. 수치 계산을 위한 도메인은 RANS와 LES 영역으로 나누어져 있으며, 이 두 개 영역의 계면은 synthetic eddy method로 처리되었다. 본 연구에서는 독일 항공우주센터에서 실험한 모델 스크램제트 연소기가 사용되었다. 수소 연료를 사용한 실험 결과와 수치해석적 검증을 수행하였다. 크랙된 케로신 연료는 에틸렌과 메탄으로 구성되었으며, 크랙된 케로신 surrogate의 난류연소는 화염편 모델을 사용하여 모사되었다.

• 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.

• 한국대기환경학회지
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• 제23권5호
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• pp.515-525
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• 2007

In this study, various techniques for measurement and analysis of PAHs in the ambient air were verified in order to select a more reliable method. Sampling and analysis of PAHs were done by the EPA TO-13a method. QA/QC of the measurement was conducted to minimize errors in sampling and analyzing processes. The linearity of calibration curve of the PAH standards was good ($R^2{\geq}0.99$). Audit accuracy was evaluated using 5 internal standards of PAHs ($Naphthalene-d_8,\;Acenaphthene-d_{10},\;Phenanthrene-d_{10},\;Chrysene-d_{12},\;Perylene-d_{12}$). Relative standard deviations of the internal standard of the PAHs were ranged from 6.22% for $acenaphthene-d_{10}$ to 8.11% for $chrysene-d_{12}$. To evaluate the surrogate recoveries, two field surrogate standards of PAHs ($fluoranthene-d_{10},\;benzo(a)pyrene-d_{12}$) and two extract surrogate standards of the PAHs ($fluorene-d_{10},\;pyrene-d_{12}$) were spiked into all samples before field sampling and sample extraction, respectively. Recoveries of field the surrogate standards ranged from $80.4{\pm}12.2%$ for $fluoranthene-d_{10}$ to $66.2{\pm}12.8%$ for $benzo(a)pyrene-d_{12}$. Extraction recoveries of the surrogate standards ranged from $70.4{\pm}10.2%$ for $fluorene-d_{10}$ to $77.6{\pm}10.8%$ for $pyrene-d_{10}$. The detection limit of benzo(a)pyrene among 16 PAHs standards for quantitation was 20 pg.

• 상하수도학회지
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• 제28권2호
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• pp.171-179
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• 2014

In this study, a novel method was proposed to test the integrity of water treatment system specifically equipped with membrane filtration process. We applied the silica particles coated with a fluorescent agent (rhodamine B isothiocyanate) as a surrogate to detect a membrane process integrity and evaluate the reliability of effluent quality in the system. Additionally, a series of experiments was conducted to evaluate the sensitivity of the method through the laboratory scale experiment. The laboratory scale experiments showed that the feasibility of application of proposed method to detect a breach or damaged part on the membrane surface. However, the sensitivity on predicting the area of a breach was significantly influenced by the testing conditions such as a concentration of surrogate, filtration flux, and detection time. The lowest error of predicting the area of breach was 3.5% at the testing condition of surrogate concentration of 80 mg/L injected with flux of $20L/m^2/hr$ for 10 minutes of detection time for the breach having the actual area of $7.069mm^2$. However, the error of estimation was increased at the small breach with area less than $0.785mm^2$. A future study will be conducted to estimate a damaged area with more accuracy and precision.