• Journal of the Society of Naval Architects of Korea
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• 제55권1호
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• pp.45-55
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• 2018

Concerns are emerging in marine industry on the additional fatigue damages induced by hydroelasticity, and large container carriers, among others, are considered to be susceptible to this hydroelastic response due to its large size, deck openings and high speed. This study focuses on the fatigue damage estimation of 9,400TEU container carrier based on the full scale measurement data via long-base strain gage installed on the ship. Some correlation analyses have been also done to check whether there was significant torsional response during the voyage. Direct cycle counting method was used to derive stress histogram and the long-term fatigue damage was estimated based upon that analyzed data. It turned out that the fatigue damage of this particular ship during the measurement period increased by more than 60% due to the hydroelastic response of the hull, and main contribution is considered to come from vertical bending mode.

• The Korean Journal of Applied Statistics
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• 제26권2호
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• pp.237-252
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• 2013

An estimation model for premiums and components is essential to determine reasonable insurance premiums. In this study, we introduce diverse models for the estimation of property damage premiums(premium, depth and frequency) that include a regression model using a dummy variable, additive independent variable model, autoregressive error model, seasonal ARIMA model and intervention model. In addition, the actual property damage premium data was used to estimate the premium, depth and frequency for each model. The estimation results of the models are comparatively examined by comparing the RMSE(Root Mean Squared Errors) of estimates and actual data. Based on real data analysis, we found that the autoregressive error model showed the best performance.

• Proceedings of the Korea Multimedia Society Conference
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• 한국멀티미디어학회 2003년도 춘계학술발표대회논문집
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• pp.624-627
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• 2003

• Proceedings of the Korean Nuclear Society Conference
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• 한국원자력학회 1999년도 추계학술발표회요약집
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• pp.238.2-238
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• 1999

• 한국방재학회:학술대회논문집
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• 한국방재학회 2009년도 정기 학술발표대회
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• pp.100.1-100.1
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• 2009

• Journal of Korean Association for Spatial Structures
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• 제10권4호
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• pp.16-22
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• 2010

• 한국도로학회:학술대회논문집
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• 한국도로학회 2005년도 학술발표회 논문집
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• pp.255-258
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• 2005

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2002년도 학술발표회 논문집(II)
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• pp.799-804
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• 2002

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.779-788
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• 2017

System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.

• Earthquakes and Structures
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• 제7권4호
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• pp.449-462
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• 2014

Seismically induced structural damage, as well as any damage caused by a natural catastrophic event, covers a wide area. This suggests to supervise the event consequences by vision tools. This paper reports the evolution from the results obtained by the project RADATT (RApid Damage Assessment Telematics Tool) funded by the European Commission within FP4. The aim was to supply a rapid and reliable damage detector/estimator for an area where a catastrophic event had occurred. Here, a general open-source methodology for the detection and the estimation of the damage caused by natural catastrophes is developed. The suitable available hazard and vulnerability data and satellite pictures covering the area of interest represent the required bits of information for updated telematics tools able to manage it. As a result the global damage is detected by the simple use of open source software. A case-study to a highly dense agglomerate of buildings is discussed in order to provide the main details of the proposed methodology.