• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.2
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• pp.64-73
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• 2014

This study proposes a load identification for the safety monitoring of the steel structure based on measured strain data. Instead of parameterizing the stiffness of structure in the existing system identification researches, the loads on a structure and a matrix (the unit strain matrix) defined by the relationship between strain and load on structure are parameterized in this study. The error function is defined by the difference between measured strain and strain estimated by parameters. In order to minimize this error function, the genetic algorithm which is one of the optimization algorithm is applied and the parameters are found. The loads on the structure can be identified through the founded parameters and measured strain data. When the loads are changed, the unmeasured strains are estimated based on founded parameters and measured strains on changed state of structure. To verify the load identification algorithm in this paper, the static experimental test for 3 dimensional steel frame structure was implemented and the loads were exactly identified through the measured strain data. In case of loading changes, the unmeasured strains which are monitoring targets on the structure were estimated in acceptable error range (0.17~3.13%). It is expected that the identification method in this study is applied to the safety monitoring of steel structures more practically.

• Proceedings of the Optical Society of Korea Conference
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• 2002.11a
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• pp.120-121
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• 2002

• Computational Structural Engineering
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• v.4 no.3
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• pp.23-26
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• 1991

본 고에서는 막구조의 설계, 시공, 유지관리에 대해 개략적으로 기술하였다. 막구조는 그 여러가지 특성이 아직 규명이 안된 부분이 많고 시공오차가 비교적 큰 편이므로 막 재료의 역학적, 재료적 특성에 대한 연구와 형상해석 모델의 공식화, 막재단의 컴퓨터화가 필요하며 초기장력 도입에 따른 시공과정의 해석이 더욱 필요하다. 따라서 설계, 형상해석, 재단에서 시공 및 유지관리에 이르는 일괄적인 System의 개발이 시급하다 하겠다.

• Computational Structural Engineering
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• v.27 no.4
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• pp.68-71
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• 2014

본 학술기사에서는 최근 구조공학에 응용이 활성화되고 있는 퍼지 이론에 대하여 간단히 설명을 하였다. 그리고 퍼지이론의 구조공학 적용 예로, 본 저자가 수행한 퍼지이론을 이용한 원형 CFT의 구속응력 평가 과정을 간략히 소개하였다. 이 예에서도 알 수 있듯이 퍼지이론은 부정확성, 지식의 부족, 애매함에 기인하는 불확실성을 다루는데 있어 적합한 것을 알 수 있으며, 여러 불확성에 인하여 발생하는 오차를 줄이는데 적합한 것으로 판단된다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.255-262
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• 2021

In this study, a jointless bridge that integrates the superstructure and abutment without installing an expansion joint was analyzed. An example of a jointless bridge that has been introduced in Korea since 2009. Owing to the short period of use and lack of experience in design, construction, and maintenance, there is insufficient information regarding the long-term behavior of jointless bridges. When analyzing numerous bridges, the numerical analysis model must maintain the numerical values used and ensure the convenience of model construction. In this study, sensitivity analysis was performed to select a numerical model for various types of jointless bridges using commercial finite element programs, MIDAS Civil and ABAQUS 2018. According to a solid element-based model, we analyzed the mean and maximum relative errors between structural models. Consequently, it was found that the beam element-based model exhibits a significantly small relative error in comparison to the shell element, where a relatively large error was recorded. Therefore, the optimal numerical analysis model, a practical model that maintains the similarity and precision of the displacement shape cause by relative error, was judged to be the most suitable for jointless bridges based on the shell element.

• The Journal of the Acoustical Society of Korea
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• v.13 no.4
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• pp.60-68
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• 1994

In this paper we propose a new Hybrid learning rule applied to multilayer feedforward neural networks, which is constructed by combining Hebbian learning rule that is a good feature extractor and Back-Propagation(BP) learning rule that is an excellent classifier. Unlike the BP rule used in multi-layer perceptron(MLP), the proposed Hybrid learning rule is used for uptate of all connection weights except for output connection weigths becase the Hebbian learning in output layer does not guarantee learning convergence. To evaluate the performance, the proposed hybrid rule is applied to classifier problems in two dimensional space and shows better performance than the one applied only by the BP rule. In terms of learning speed the proposed rule converges faster than the conventional BP. For example, the learning of the proposed Hybrid can be done in 2/10 of the iterations that are required for BP, while the recognition rate of the proposed Hybrid is improved by about $0.778\%$ at the peak.

• Environmental and Resource Economics Review
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• v.24 no.4
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• pp.679-708
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• 2015

Almost all of natural gas demand in Korea is currently met by overseas LNG imports. More than 80% of LNG is imported through the mid to long-term contracts with oil-linked pricing. Despite LNG price estimation provides valuable information with various interested parties, an empirical study as well as an econometric model on LNG price hasn't yet been available in Korea. This paper therefore, aims at analyzing not only whether the long-run equilibrium relationship between oil prices and Korean LNG prices exists but also whether structural change occurred in such relationship. Further, it aims at building a conditional VECM taking account of a structural change. According to the final model, an oil price shock is passed through to the LNG prices in nonlinear and different manner from the past.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.9
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• pp.781-786
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• 2015

An aeroelastic stability can be degraded due to an aeroelastic modeling error and a structural uncertainty. Therefore it is necessary to predict the aeroelastic stability boundary considering an aeroelastic modeling error and a structural uncertainty. Robust aeroelastic analysis was proposed to predict the aeroelastic stability boundary considering these error and uncertainty. In the present study, the robust aeroelastic modeling and analysis were performed by using the ${\mu}$ analysis technique and the aeroelastic model of the control fin with modal approach and MSA. The computer program for the robust aeroelastic analysis was developed and verified by comparing its results with those of conventional aeroelastic analysis methods.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.2
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• pp.121-130
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• 2023

Finite element analysis is widely used to predict the structural stability and tooth contact performance of gears. This study focused on the effect of finite element modeling conditions of a spur gear on the simulation result and the model simplification. The gear body and teeth, teeth width, configuration of mesh, frictional coefficient, and simulation time interval (gear mesh cycle division) were selected for model simplification for gear analysis. The static transmission error during a single-gear mesh cycle was calculated to represent the performance of the gear, and the elapsed time was measured as a simplification factor. Contact stress distribution was also checked. The differences in maximum transmission error and elapsed time depending on the model simplification methods were analyzed. After all simplification methods were estimated, an optimal combination of the methods was defined, and the result was compared with that of the most detailed modeling methods.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.2
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• pp.169-177
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• 2017

In this paper, classification of spall and crack faults of gear teeth is studied by applying the ensemble empirical mode decomposition(EEMD) for the gear transmission error(TE). Finite element models of the gears with the two faults are built, and TE is obtained by simulation of the gears under loaded contact. EEMD is applied to the residuals of the TE which are the difference between the normal and faulty signal. From the result, the difference of spall and crack faults are clearly identified by the intrinsic mode functions(IMF). A simple test bed is installed to illustrate the approach, which consists of motor, brake and a pair of spur gears. Two gears are employed to obtain the TE for the normal, spalled, and cracked gears, and the type of the faults are separated by the same EEMD application process. In order to quantify the results, crest factors are applied to each IMF. Characteristics of spall and crack are well represented by the crest factors of the first and the third IMF, which are used as the feature signals. The classification is carried out using the Bayes decision theory using the feature signals acquired through the experiments.