• Structural Engineering and Mechanics
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• 제17권2호
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• pp.267-279
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• 2004

This paper presents an improved Monte Carlo simulation for the probabilistic determination of initial cable forces of cable-stayed bridges under dead loads using the response surfaces method. A response surface (i.e. a quadratic response surface without cross-terms) is used to approximate structural response. The use of the response surface eliminates the need to perform a deterministic analysis in each simulation loop. In addition, use of the response surface requires fewer simulation loops than conventional Monte Carlo simulation. Thereby, the computation time is saved significantly. The statistics (e.g. mean value, standard deviation) of the structural response are calculated through conventional Monte Carlo simulation method. By using Monte Carlo simulation, it is possible to use the existing deterministic finite element code without modifying it. Probabilistic analysis of a truss demonstrates the proposed method' efficiency and accuracy; probabilistic determination of initial cable forces of a cable-stayed bridge under dead loads verifies the method's applicability.

• Journal of Electrochemical Science and Technology
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• 제10권3호
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• pp.276-283
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• 2019

Nitinol is an alloy of nickel and titanium. Nitinol is one of the shape memory alloys(SMA) that are restored to a remembered form, changing the crystal structure at a given temperature. Because of these unique features, it is used in medical devices, high precision sensors, and aerospace industries. However, the conventional method of mechanical machining for nitinol has problems of thermal and residual stress after processing. Therefore, the electrochemical machining(ECM), which does not produce residual stress and thermal deformation, has emerged as an alternative processing technique. In addition, to replace the existing experimental planning methods, this study used deep neural network(DNN), which is the basis for AI. This method was shown to be more useful than conventional method of design of experiments(RSM, Taguchi, Regression) by applying deep neural network(DNN) to electrochemical machining(ECM) and comparing root mean square errors(RMSE). Comparison with actual experimental values has shown that DNN is a more useful method than conventional method. (DOE - RSM, Taguchi, Regression). The result of the machining was accurately and efficiently predicted by applying electrochemical machining(ECM) and deep neural network(DNN) to the shape memory alloy(SMA), which is a hard-mechinability material.

• 한국안전학회지
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• 제32권2호
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• pp.92-97
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• 2017

This study deals with new application method of the connecting tuned mass damper (CTMD) system for efficient vibration control of adjacent twin structures which have the same dynamic properties such as natural frequency and damping characteristics to each other. In the existing research, the vibration control of the twin structures has a limit to the application of the conventional damper-connection method of the twin structures. Due to the same frequency characteristics leading to the equally vibrating behaviors, it is impossible to apply the conventional connection method of the adjacent structures. In order to overcome these limitations induced by the symmetry of the dynamic characteristics, we propose a new CTMD-based control system that adopts the conventional connection configuration but unbalances the symmetric system by arranging the control device asymmetrically and then can finally achieve the efficient control performance. In order to demonstrate the applicability of the proposed system, numerical simulations of the optimally designed proposed system have been performed in comparison with the optimal design results of the existing independent single tuned mass damper (STMD) control system and the another optimal control system previously proposed by the same author, hereafter called CTMD-OsTMD. The comparative results of the control performances among STMD, CTMD-OsTMD and the proposed CTMD systems verified that the newly proposed control system can be a control-efficient and cost-effective system for vibration suppression of the two adjacent twin structures.

• 대한교통학회지
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• 제29권4호
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• pp.125-138
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• 2011

도로상의 안개로 인한 시정감소는 교통사고를 유발하는 주된 원인으로 운전자에게 도로의 시정거리를 미리 알려주어 안전운행을 유도하기 위한 안개경고시스템에서는 대부분 안개센서와 같은 고가의 광학센서를 사용하고 있다. 최근 운전자의 시정감각과 유사하면서도 저렴한 카메라를 이용한 시정측정에 관한 연구가 이루어지고 있다. 그러나 기존의 연구는 별도의 표지나 ROI를 기반으로 하고 있으므로 설치가 어렵고 비용이 많이 들며 도로에 기 설치된 CCTV 시스템을 활용하기 어렵다는 문제점을 가지고 있다. 본 논문에서는 도로상에 설치된 카메라 영상을 이용하여 주야간 실시간 시정측정이 가능한 방법을 제안한다. 제안된 방법은 도로모델을 구축하고 카메라 영상으로부터 차량의 이동영역과 가시선을 검출한 후 도로모델에 적용함으로써 매우 쉽고 빠른 시정의 계산이 가능하다. 제안된 방법은 운전자의 시정감각과 유사한 주야간 시정측정이 가능할 뿐만 아니라 시정표지와 같은 부가적인 시설을 사용할 필요가 없고 기존의 CCTV 시스템에 바로 적용할 수 있다는 장점이 있다. 본 논문에서는 중부내륙고속도로에서 획득한 영상을 이용한 실험결과를 통해 본 연구의 현장적용 가능성과 활용방안을 제시하고 신뢰성 검증을 위한 향후 연구방향을 기술한다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.602-607
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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 RBDO 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.

• 한국지능시스템학회논문지
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• 제8권4호
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• pp.1-7
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• 1998

This paper describes a meshless of element-free method based on fuzzy knowledge processing. To efficiently simulate complicated physical phenomena with dynmics and non-linear ploblem using computational mechanics, special method is required such as parallel processing or adaptive analysis techniques. However, the conventional finite element method is too complicated to be employed in the above cases. In order to reduce the above complexity of the conventional finite element analysis systms, the so called meshles finite elements as an input information have been stuided. Node is generated if its distance form existing node points is similar to the node spacing fuction at the point. The node spacing function is well controlled by the fuzzy knowledge processing Practical performances of the present system are demonstrated through several three-dimensional(3D) problems.

• Journal of Mechanical Science and Technology
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• 제17권10호
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• pp.1552-1562
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• 2003

In this paper, we propose a new PIV methodology for obtaining a velocity field from a sequence of multiple image data based on a least-square principle (also known as MQD; minimum quadratic difference) for the grey level difference between two neighboring frames of image data. We investigated both the accuracy of the result and the time consumption in the computation. It turns out that the proposed method is not only accurate but fast compared with the conventional correlation PIV techniques. Our method is applied to the spin-up flows and the results show that the method can be a good substitution for the conventional algorithms employed in the existing commercial codes.

• Structural Monitoring and Maintenance
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• 제1권3호
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• pp.323-338
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• 2014

In this study a new innovative method of earthquake-resistant strengthening of reinforced concrete structures is presented for the first time. Strengthening according to this new method consists of the construction of steel fiber ultra-high-strength concrete jackets without conventional reinforcement which is usually applied in the construction of conventional reinforced concrete jackets. An innovative solution is proposed also for the first time that ensures a satisfactory seismic performance of existing reinforced concrete structures, strengthened by using composite materials. The weak point of the use of such materials in repairing and strengthening of old R/C structures is the area of beam-column joints. According to the proposed solution, the joints can be strengthened with a steel fiber ultra-high-strength concrete jacket, while strengthening of columns can be achieved by using CFRPs. The experimental results showed that the performance of the subassemblage strengthened with the proposed mixed solution was much better than that of the subassemblage retrofitted completely with CFRPs.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.575-577
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• 1998

In this paper, we propose a hybrid target tracking algorithm which combine the conventional Kalman filter algorithm and the fuzzy neural network. Conventional methods are degraded in the presence of uncertanties and the environmental noise. These problems can be resolved by the proposed method. The training data for the proposed target tracker is obtained by the off-line simulation. Unlike other target trackers usging fuzzy inference system, our method can be easily integrated into the existing system. A numerical simulation is included to show the effectiveness and the feasibility of the proposed method.

• Nuclear Engineering and Technology
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• 제40권5호
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• pp.375-386
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• 2008

Conventional static reliability analysis methods are inadequate for modeling dynamic interactions between components of a system. Various techniques such as dynamic fault tree, dynamic Bayesian networks, and dynamic reliability block diagrams have been proposed for modeling dynamic systems based on improvement of the conventional modeling methods. In this paper, we review these methods briefly and introduce dynamic nodes to the existing reliability graph with general gates (RGGG) as an intuitive modeling method to model dynamic systems. For a quantitative analysis, we use a discrete-time method to convert an RGGG to an equivalent Bayesian network and develop a software tool for generation of probability tables.