• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.163-168
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• 2011

Robust optimization or reliability-based design optimization are some of the methodologies that are employed to take into account the uncertainties of a system at the design stage. For applying such methodologies to solve industrial problems, accurate and efficient methods for estimating statistical moments and failure probability are required, and further, the results of sensitivity analysis, which is needed for searching direction during the optimization process, should also be accurate. The aim of this study is to employ the function approximation moment method into the sensitivity analysis formulation, which is expressed as an integral form, to verify the accuracy of the sensitivity results, and to solve a typical problem of reliability-based design optimization. These results are compared with those of other moment methods, and the feasibility of the function approximation moment method is verified. The sensitivity analysis formula with integral form is the efficient formulation for evaluating sensitivity because any additional function calculation is not needed provided the failure probability or statistical moments are calculated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.575-584
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• 2014

In this study, the NREL 5 MW wind turbine tower model was optimized according to the multi-body dynamics and reliability-based design. The mathematical model was defined as a link-joint system including dynamic characteristics derived from Timoshenko's beam theory. For the optimization problem, the sensitivities to variations in the tower thicknesses and inner and outer diameters were acquired and arranged in terms of safety and efficiency according to bending stress and buckling standards. An optimal design was calculated with the advanced first-order second moment method and used to define a finite element model for validation. The finite element model was simulated by static analysis. The relationship between the multi-body dynamic and finite element method throughout the process was investigated, and the optimal model, which had high endurance despite its low mass, was determined.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1331-1332
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• 2015

본 논문은 CAN(Controller Area Network) 통신의 WCRT(Worst Case Response Time) 분석을 통해 IEEE1212 기반 RTU(Remote Terminal Unit)의 통신 신뢰성을 검증한다. RTU는 원격지에서 네트워크를 구성하여 각 모듈들로부터 획득한 정보를 서버로 전송하거나 원격지를 제어하는 역할을 한다. 본 논문에서 대상으로 하는 RTU의 네트워크는 물리계층과 데이터링크 계층은 CAN을 사용하고 응용계층은 IEEE1212 기반으로 통신한다. 즉, RTU를 구성하는 모듈은 각각메모리 영역을 가지고 있고, CAN ID에 메모리 주소를 포함하여 해당 영역을 쓰는 구조로 통신을 한다. 첫 번째로 이러한 응용계층을 고려하여 WCRT를 계산하는 방법을 제시하고, 두 번째로 CAN 메시지의 우선 순위를 최적화하는 방법을 고찰한다. 마지막으로 시험 환경을 구축하고 시뮬레이션을 통해 앞에서 선정한 우선순위에 따라 통신 신뢰성을 검증한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.589-595
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• 2019

Recently, the mobile social networks, which consider both social relationship between users and mobile communication networks, have been received great attention. In this paper, we consider the trust degree of node as the social relationship for the cooperative communication networks. In contrast to the existing works that consider the case of the perfect trust degree information, for the case that transmitter has an imperfect trust degree information, we propose an imperfect trust degree based cooperative communication technique that maximizes a throughput. We first model the imperfect trust degree information as a probability distribution and derive the outage probability using the probability distribution. Then, we propose the transmission scheme that maximizes the throughput, which consider both outage probability and transmission rate. The simulation results show that the proposed cooperative transmission scheme outperforms the conventional scheme in terms of the throughput.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.540-556
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• 2009

The hub and spoke network is a critical network-based infrastructure that is widely applied in current transportation and telecommunications systems, including Internets, air transportation networks and highway systems. This main idea of hub location models is to construct a network system which achieves the economy of scale of flows. The main purpose of this study is to introduce new hub location problems that take into account network reliability. Two standard models based on assignment schemes are proposed, and a minimum threshold model is provided as an extension in terms of hub network design. The reliability and interaction potentials of 15 nodes in the U.S. are used to examine model behaviors. According to the type of models and reliability, hubs, and minimum threshold levels, relationships among the flow economy of scale, network costs, and network resiliency are analyzed.

• Journal of Energy Engineering
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• v.20 no.2
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• pp.154-162
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• 2011

PMT(Preventive Maintenance Template) is a standardized maintenance program that describes maintenance items & period as operation condition to increase component reliability at the component level. The existing maintenance programs are focused on time based maintenance to inspect and repair component depend on fixed period. But recently, we have developed advanced maintenance program(named PMT) to increase reliability and optimize maintenance program of the plant significant component. This paper presents how to develop the PMT for nuclear power plant's static exciter.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.195-198
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• 2002

고농도오존이 발생되는 원인과 환경적 요인의 상호관계를 모델링하기 위해 신경회로 망과 같은 지능제어 기법들이 많이 적용되어 왔다 분석과 모델링을 위해 유전자 알고리즘과 같은 최적화 방법을 적용하기도 하지만, 고농도 오존이 발생되는 메커니즘이 매우 복잡하고, 비선형적이며, 패턴파악이 어렵기 때문에 고농도 오존의 예측 모델링에는 여전히 문제점이 있다 따라서 본 논문에서는 신뢰수준과 신뢰구간을 이용하여 초농도 오존을 예측할 수 있는 모델링 방법을 서술하였다 예측값의 신뢰수준의 평가는 예측에 대한 실측값을 구하여 신뢰구간내의 데이터의 개수를 파악함으로써 신뢰성을 평가할 수 있다. 또한 이 테스트는 우리가 가지고 있지 않은 데이터에 대한 유효성을 평가하는데 적용될 수 있다 그리고 본 논문에서는 GMDH(Group Method of data handling)의 전형적인 알고리즘에 바탕을 두고 있는 DPNN(Dynamic Polynomial Neural Network)를 이용하여 예측 모델을 구성하였다. DPNN은 데이터 해석이 용이하고 비선형적인 동적 시스템 예측에 유용하게 적용될 수 있는 장점을 가지고 있다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.3
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• pp.275-280
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• 2008

A technique for reliability-based design optimization(RBDO) is developed based on the Bayesian approach, which can deal with the epistemic uncertainty arising due to the limited number of data. Until recently, the conventional REDO was implemented mostly by assuming the uncertainty as aleatory which means the statistical properties are completely known. In practice, however, this is not the case due to the insufficient data for estimating the statistical information, which makes the existing RBDO methods less useful. In this study, a Bayesian reliability is introduced to take account of the epistemic uncertainty, which is defined as the lower confidence bound of the probability distribution of the original reliability. In this case, the Bayesian reliability requires double loop of the conventional reliability analyses, which can be computationally expensive. Kriging based dimension reduction method(KDRM), which is a new efficient tool for the reliability analysis, is employed to this end. The proposed method is illustrated using a couple of numerical examples.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.691-697
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• 2010

Reliability-based topology optimization (RBTO) is to get an optimal topology satisfying uncertainties of design variables. In this study, reliability-based topology optimization method is applied to the inner reinforcement of vehicle's hood based on BESO. A multi-objective topology optimization technique was implemented to obtain optimal topology of the inner reinforcement of the hood. considering the static stiffness of bending and torsion as well as natural frequency. Performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. To evaluate the obtained optimal topology by RBTO, it is compared with that of DTO of the inner reinforcement of the hood. It is found that the more suitable topology is obtained through RBTO than DTO even though the final volume of RBTO is a little bit larger than that of DTO. From the result, multiobjective optimization technique based on the BESO can be applied very effectively in topology optimization for vehicle's hood reinforcement considering the static stiffness of bending and torsion as well as natural frequency.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.4
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• pp.412-418
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• 2011

Reliability-based Topology optimization(RBTO) is to get an optimal design satisfying uncertainties of design variables. Although RBTO based on homogenization and density distribution method has been done, RBTO based on BESO has not been reported yet. This study presents a reliability-based topology optimization(RBTO) using bi-directional evolutionary structural optimization(BESO). Topology optimization is formulated as volume minimization problem with probabilistic displacement constraint. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., RIA, PMA, SLSV and ADL(adaptive-loop), are used. Reliability-based topology optimization design process is conducted to obtain optimal topology satisfying allowable displacement and target reliability index with the above four methods, and then each result is compared with respect to numerical stability and computing time. The results of this study show that the RBTO based on BESO using the four methods can effectively be applied for topology optimization. And it was confirmed that DLSV and ADL had better numerical efficiency than SLSV. ADL and SLSV had better time cost than DLSV. Consequently, ADL method showed the best time efficiency and good numerical stability.