• 대한토목학회논문집
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• 제43권2호
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• pp.165-173
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• 2023

교량에 발생하는 손상에 대한 관리 및 평가는 정기적인 점검으로 작성된 보고서와 외관조사망도 및 손상물량표를 포함한 점검 및 진단자료에 기초한다. 이러한 자료 대부분은 2D 기반의 문서형식으로 작성되어 있고, 표준화된 방식으로 디지털화하기 어려워 정해진 목적 외의 활용이 쉽지 않다. 이에 본 연구에서는 점검자료를 기반으로 손상을 포함한 BIM 기반 교량모델을 구축하는 방법을 제시하고, BIM 표준을 준용하는 유지관리용 건설정보교환표준인 COBie (Construction Operations Building Information Exchange)를 사용하여 모델로부터 도출한 스프레드시트 데이터 형식의 손상정보들을 교량모델과 연계하여 관리하고 활용하는 방법을 제시하였다. 또한 전술한 방법들을 이용해 손상이 발생한 교량 상부구조 각 부위별 상태등급을 디지털 데이터 기반으로 자동화된 방법으로 평가하는 방법을 제안하였다. 본 연구에서 제안된 방법들은 PSC I형 콘크리트 교량의 상부구조를 대상으로 검증이 이루어졌으며 그 실효성이 검증되었다.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.417-420
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• 2008

Solar electric systems have very little impact on environment, making them one of the cleanest power-generating technologies available. While they are operating, PV systems produce no air pollution, hazardous waste, or noise, and they require no transportable fuels. In PV system design, the selection and proper installation of appropriately-sized components directly affect system reliability, lifetime, and initial cost. In this research, we have studied the PWM(Pulse Width Modulation) signals. I proposed an efficient photovoltaic power interface circuit incorporated with a DC-DC converter and a sine-pwm control method full-bridge inverter. In grid-connected solar power systems, the DC-DC converter operates at high switching frequency to make the output current a sine wave, whereas the full-bridge inverter operates at low switching frequency which is determined by the ac frequency. Thus, it can reduce the switching losses incurred by the full-bridge inverter. Full-bridge converter is controlled by using microprocessor control method, and its operation is verified through computer aided simulations.

• Smart Structures and Systems
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• 제13권6호
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• pp.1015-1039
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• 2014

The widening project on Freeway No.1 in Taiwan has a total length of roughly 14 kilometers, and includes three special bridges, namely a 216 m long-span bridge crossing the original freeway, an F-bent double decked bridge in a co-constructed section, and a steel and prestressed concrete composite bridge. This study employed in-situ monitoring in conjunction with numerical modeling to establish a real-time monitoring system for the three bridges. In order to determine the initial static and dynamic behavior of the real bridges, forced vibration experiments, in-situ static load experiments, and dynamic load experiments were first carried out on the newly-constructed bridges before they went into use. Structural models of the bridges were then established using the finite element method, and in-situ vehicle load weight, arrangement, and speed were taken into consideration when performing comparisons employing data obtained from experimental measurements. The results showed consistency between the analytical simulations and experimental data. After determining a bridge's initial state, the proposed in-situ monitoring system, which is employed in conjunction with the established finite element model, can be utilized to assess the safety of a bridge's members, providing useful reference information to bridge management agencies.

• Steel and Composite Structures
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• 제27권3호
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• pp.327-335
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• 2018

This paper presents structural assessment of a steel railway bridge for current condition using modal parameter to upgrade finite element modeling in order to gather accurate result. An adequate monitoring, such as acceleration, displacement, strain monitoring, is important tool to understand behavior and to assess structural performance of the structure under surround vibration by means of the dynamic analysis. Evaluation of conditions of an existing steel railway bridge consist of 4 decks, three of them are 14 m, one of them is 9.7 m, was performed with a numerical analysis and a series of dynamic tests. Numerical analysis was performed implementing finite element model of the bridge using SAP2000 software. Dynamic tests were performed by collecting acceleration data caused by surrounding vibrations and dynamic analysis is performed by Operational Modal Analysis (OMA) using collected acceleration data. The acceleration response of the steel bridge is assumed to be governing response quantity for structural assessment and provide valuable information about the current statute of the structure. Modal identification determined based on response of the structure play significant role for upgrading finite element model of the structure and helping structural evaluation. Numerical and experimental dynamic properties are compared and finite element model of the bridge is updated by changing of material properties to reduce the differences between the results. In this paper, an existing steel railway bridge with four spans is evaluated by finite element model improved using operational modal analysis. Structural analysis performed for the bridge both for original and calibrated models, and results are compared. It is demonstrated that differences in natural frequencies are reduced between 0.2% to 5% by calibrating finite element modeling and stiffness properties.

• 한국BIM학회 논문집
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• 제9권4호
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• pp.41-50
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• 2019

Digital models for a cable-stayed bridge are defined considering data-driven engineering from design to construction. Algorithms for digital object generation of each component of the cable-stayed bridge were developed. Using these algorithms, Level-3 BIM practices can be realized from design stages. Based on previous practices, digital object library can be accumulated. Basic digital models are modified according to given design conditions by a designer. Once design models are planned, various applications using the models are linked the models such as estimation, drawings and mechanical properties. Federated bridge models are delivered to construction stages. In construction stage, the models can be efficiently revised according to the changed situations during construction phases. In this paper, measured coordinates are imported to the model generation algorithms and revised models are obtained. Augmented reality devices and their applications are proposed. AR simulations in construction site and in office condition are tested. From this pilot test of digital models, it can be said that Level-3 BIM practices can be realized by using in-house modeling algorithms according to different purposes.

• Smart Structures and Systems
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• 제5권4호
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• pp.427-442
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• 2009

In this paper, the acceptability of system identification results for health monitoring of instrumented bridges is addressed. This is conducted by comparing the confidence intervals of identified modal parameters for a bridge in California, namely Truckee I80/Truckee river bridge, with the change of these parameters caused by several damage scenarios. A challenge to the accuracy of the identified modal parameters involves consequences regarding the damage detection and health monitoring, as some of the identified modal information is essentially not useable for acquiring a reliable damage diagnosis of the bridge system. Use of strong motion data has limitations that should not be ignored. The results and conclusions underline these limitations while presenting the opportunities offered by system identification using strong motion data for better understanding and monitoring the health of bridge systems.

• 한국전산구조공학회논문집
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• 제25권4호
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• pp.307-314
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• 2012

모듈러 강교량 제작, 조립, 설계, 시공단계에서 상부모듈의 부품정보를 효율적으로 제공하고 교환하기 위하여 BIM(Building Information Modeling) 프로젝트에서 정보교환을 위하여 사용하는 국제표준인 IFC 모델을 활용한 부품정보 라이브러리 구축방법을 제시하였다. 모듈러 강교량의 상부모듈을 구성하는 부품정보를 IFC 모델로 표현하기 위하여 의미론적인 관점에서 기존 IFC 모델에서 부품정보를 표현할 수 있는 엔티티와 모듈러 강교량의 구성요소를 매칭하여 적용하였으며, 구성요소의 역할을 구분하기 위하여 매칭한 엔티티의 타입을 적용하거나 사용자정의 타입으로 정의하였다. 또한, 부품 정보 라이브러리에서 부품 및 조립품의 정보를 해당단계에서 효율적으로 제공하기 위하여 조립체계를 네 단계의 상세수준(LoD)으로 구분하여 정의하였으며, 이를 IFC 모델로 표현하기 위하여 새로운 속성정보를 정의하였다. 마지막으로, IFC 모델과 매칭하여 정의한 정보를 실제 모듈러 강교량 상부모듈에 적용하여 IFC 기반의 시범 라이브러리 정보를 생성하였다.

• Smart Structures and Systems
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• 제21권5호
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• 대한토목학회논문집
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• 제40권2호
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• pp.239-245
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• 2020

최근 BIM (Building Information Modeling)이 건설 산업계에서 폭넓게 활용되고 있다. 하지만 과거에 시공이 된 구조물에 경우 대부분 BIM이 구축되어 있지 않다. BIM이 구축되지 않은 구조물의 경우, 카메라로부터 얻은 2D 이미지에 SfM (Structure from Motion) 기법을 활용하면 3D 모델의 점군 데이터(Point cloud)를 생성하고 BIM을 구축할 수 있다. 하지만 이렇게 생성된 점군 데이터는 의미론적 정보가 포함되어 있지 않기 때문에, 수작업으로 구조물의 어떤 요소인지 분류해 주어야 한다. 따라서 본 연구에서는 구조물 구성요소를 분류하는 과정을 자동화하기 위하여 딥러닝을 적용하였다. 딥러닝 네트워크 구축에는 CNN (Convolutional Neural Network) 구조의 Inception-ResNet-v2를 사용하였고, 전이학습을 통하여 교량 구조물의 구성요소를 학습하였다. 개발된 시스템을 검증하기 위하여 수집한 데이터를 이용하여 구성요소를 분류한 결과, 교량의 구성요소를 96.13 %의 정확도로 분류할 수 있었다.

• 한국CDE학회논문집
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• 제11권3호
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• pp.183-196
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• 2006

A new operation strategy. which can guarantee the data consistency of engineering information among the various intelligent information systems, is presented for engineering information of bridges, and construction methodology of integrated database is developed to support the strategy. The two core standard techniques are adopted to construct the integrated database. One is the Standard for the Exchange of Product Model Data (STEP) for CAD/CAE information and the other is the Extensible Markup Language(XML) for engineering document information. The former enabler structural engineers to handle the structural details with three-dimensional geometry-based information of bridges, and ACIS solid modeling kernel is employed to develop AutoCAD based application modules. The latter can make document files into data type for web-based application modules which assist end-users to search and retrieve engineering document data. In addition, relaying algorithm is developed to integrate the two different information, e.g. CAD/CAE information and engineering document information. The pilot application modules are also developed, and a case study subjected to the Han-Nam bridge is presented at the end of the paper to illustrate the use of the developed application modules.