• 국제초고층학회논문집
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• 제4권1호
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• pp.9-25
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• 2015

Field measurements of various structures have been conducted for many purposes. Measurement data obtained by field measurement is very useful to determine vibration characteristics including dynamic characteristics such as the damping ratio, natural frequency, and mode shape of a structure. In addition, results of field measurements and modal identification can be used for modal updating of FEM analysis, for checking the efficiency of damping devices and so on. This paper shows some examples of field measurements and modal identification for structural health monitoring. As the first example, changes of dynamic characteristics of a 15-story office building in four construction stages from the foundation stage to completion are described. The dynamic characteristics of each construction stage were modeled as accurately as possible by FEM, and the stiffness of the main structural frame was evaluated and the FEM results were compared with measurements performed on non-load-bearing elements. Simple FEM modal updating was also applied. As the next example, full-scale measurements were also carried out on a high-rise chimney, and the efficiency of the tuned mass damper was investigated by using two kinds of modal identification techniques. Good correspondence was shown with vibration characteristics obtained by the 2DOF-RD technique and the Frequency Domain Decomposition method. As the last example, the wind-induced response using RTK-GPS and the feasibility of hybrid use of FEM analysis and RTK-GPS for confirming the integrity of structures during strong typhoons were shown. The member stresses obtained by hybrid use of FEM analysis and RTK-GPS were close to the member stresses measured by strain gauges.

• Structural Monitoring and Maintenance
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• 제5권2호
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• pp.231-242
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• 2018

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

• 대한환경공학회지
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• 제32권4호
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• pp.369-378
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• 2010

폐기물매립장의 안정화에는 미생물이 중요한 역할을 수행한다. 폐기물매립장에서 미생물군집 변화 모니터링에 말단 제한절편다형성(Terminal Restriction Fragment Length Polymorphism; T-RFLP)법의 활용 가능성을 평가하고자 박테리아의 16S rDNA 서열에 기초한 T-RFLP법으로 4개의 폐기물매립장 내부에서 채취한 침출수의 미생물군집 구조를 조사하였다. T-RFLP법을 사용하여 해석한 침출수 내 우점 미생물군집 구조와 일반적으로 널리 사용되고 있는 16S rDNA 클론 해석법에 의한 우점 미생물군집구조는 유사하였다. 또한, T-RFLP법을 이용하여 폐기물매립장의 구조, 매립 폐기물 종류, 운영기간이 다른 폐기물매립장 침출수의 우점 미생물군집 구조가 서로 다르게 나타나는 것을 확인 할 수 있었다. 따라서 T-RFLP법을 사용하여 폐기물매립장 침출수내 미생물군집 구조를 장기적으로 모니터링 한다면 많은 비용과 시간이 소요되는 클론해석법의 반복적인 수행 없이도 비교적 간단하게 폐기물매립장의 안정화 정도를 평가할 수 있을 것으로 기대한다.

• Steel and Composite Structures
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• 제29권4호
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• pp.527-544
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• 2018

The paper presents the study on a change in modal parameters and structural stiffness of cable-stayed Fiberline Bridge made entirely of Glass Fiber Reinforced Polymer (GFRP) composite used for 20 years in the fjord area of Kolding, Denmark. Due to this specific location the bridge structure was subjected to natural aging in harsh environmental conditions. The flexural properties of the pultruded GFRP profiles acquired from the analyzed footbridge in 1997 and 2012 were determined through three-point bending tests. It was found that the Young's modulus increased by approximately 9%. Moreover, the influence of the temperature on the storage and loss modulus of GFRP material acquired from the Fiberline Bridge was studied by the dynamic mechanical analysis. The good thermal stability in potential real temperatures was found. The natural vibration frequencies and mode shapes of the bridge for its original state were evaluated through the application of the Finite Element (FE) method. The initial FE model was created using the real geometrical and material data obtained from both the design data and flexural test results performed in 1997 for the intact composite GFRP material. Full scale experimental investigations of the free-decay response under human jumping for the experimental state were carried out applying accelerometers. Seven natural frequencies, corresponding mode shapes and damping ratios were identified. The numerical and experimental results were compared. Based on the difference in the fundamental natural frequency it was again confirmed that the structural stiffness of the bridge increased by about 9% after 20 years of service life. Data collected from this study were used to validate the assumed FE model. It can be concluded that the updated FE model accurately reproduces the dynamic behavior of the bridge and can be used as a proper baseline model for the long-term monitoring to evaluate the overall structural response under service loads. The obtained results provided a relevant data for the structural health monitoring of all-GFRP bridge.

• Smart Structures and Systems
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• 제18권3호
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• pp.405-423
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• 2016

In this study, the feasibility of using telecommunication single-mode optical fiber (SMF) as a distributed fiber optic strain and crack sensor was evaluated in concrete pavement monitoring. Tensile tests on various sensors indicated that the $SMF-28e^+$ fiber revealed linear elastic behavior to rupture at approximately 26 N load and 2.6% strain. Six full-scale concrete panels were prepared and tested under truck and three-point loads to quantify the performance of sensors with pulse pre-pump Brillouin optical time domain analysis (PPP-BOTDA). The sensors were protected by precast mortar from brutal action during concrete casting. Once air-cured for 2 hours after initial setting, half a mortar cylinder of 12 mm in diameter ensured that the protected sensors remained functional during and after concrete casting. The strains measured from PPP-BOTDA with a sensitivity coefficient of $5.43{\times}10^{-5}GHz/{\mu}{\varepsilon}$ were validated locally by commercial fiber Bragg grating (FBG) sensors. Unlike the point FBG sensors, the distributed PPP-BOTDA sensors can be utilized to effectively locate multiple cracks. Depending on their layout, the distributed sensors can provide one- or two-dimensional strain fields in pavement panels. The width of both micro and major cracks can be linearly related to the peak strain directly measured with the distributed fiber optic sensor.

• Computers and Concrete
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• 제33권4호
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• pp.341-348
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• 2024

Ultra-high-performance concrete (UHPC) has received remarkable attentions in civil infrastructure due to its unique mechanical characteristics and durability. UHPC gains increasingly dominant in essential structural elements, while its unique properties pose challenges for traditional inspection methods, as damage may not always manifest visibly on the surface. As such, the need for robust inspection techniques for detecting cracks in UHPC members has become imperative as traditional methods often fall short in providing comprehensive and timely evaluations. In the era of artificial intelligence, computer vision has gained considerable interest as a powerful tool to enhance infrastructure condition assessment with image and video data collected from sensors, cameras, and unmanned aerial vehicles. This paper presents a computer vision-based approach employing deep learning to detect cracks in UHPC beams, with the aim of addressing the inherent limitations of traditional inspection methods. This work leverages computer vision to discern intricate patterns and anomalies. Particularly, a convolutional neural network architecture employing transfer learning is adopted to identify the presence of cracks in the beams. The proposed approach is evaluated with image data collected from full-scale experiments conducted on UHPC beams subjected to flexural and shear loadings. The results of this study indicate the applicability of computer vision and deep learning as intelligent methods to detect major and minor cracks and recognize various damage mechanisms in UHPC members with better efficiency compared to conventional monitoring methods. Findings from this work pave the way for the development of autonomous infrastructure health monitoring and condition assessment, ensuring early detection in response to evolving structural challenges. By leveraging computer vision, this paper contributes to usher in a new era of effectiveness in autonomous crack detection, enhancing the resilience and sustainability of UHPC civil infrastructure.

• Wind and Structures
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• 제23권4호
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• pp.313-350
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• 2016

Taipei 101 Tower, which has 101 stories with height of 508 m, is located in Taipei where typhoons and earthquakes commonly occur. It is currently the second tallest building in the world. Therefore, the dynamic performance of the super-tall building under strong wind actions requires particular attentions. In this study, Large Eddy Simulation (LES) integrated with a new inflow turbulence generator and a new sub-grid scale (SGS) model was conducted to simulate the wind loads on the super-tall building. Three-dimensional finite element model of Taipei 101 Tower was established and used to evaluate the wind-induced responses of the high-rise structure based on the simulated wind forces. The numerical results were found to be consistent with those measured from a vibration monitoring system installed in the building. Furthermore, the equivalent static wind loads on the building, which were computed by the time-domain and frequency-domain analysis, respectively, were in satisfactory agreement with available wind tunnel testing results. It has been demonstrated through the validation studies that the numerical framework presented in this paper, including the recommended SGS model, the inflow turbulence generation technique and associated numerical treatments, is a useful tool for evaluation of the wind loads and wind-induced responses of tall buildings.

• 한국농공학회논문집
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• 제58권5호
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• pp.81-90
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• 2016

Due to droughts and water shortages causing severe damage to crops and other vegetations, much attention has been given to efficient irrigation for upland farming. However, little information has been known to measure soil moisture levels in a field scale and apply their spatial variability for proper irrigation scheduling. This study aimed to characterize the spatial variability and temporal stability of soil water contents at depths of 10 cm, 20 cm and 30 cm on flat (loamy soil) and hill-slope fields (silt-loamy soil). Field monitoring of soil moisture contents was used for variogram analysis using GS+ software. Kriging produced from the structural parameters of variogram was applied for the means of spatial prediction. The overall results showed that the surface soil moisture presented a strong spatial dependence at the sampling time and space in the field scale. The coefficient variation (CV) of soil moisture was within 7.0~31.3 % in a flat field and 8.3~39.4 % in a hill-slope field, which was noticeable in the dry season rather than the rainy season. The drought assessment analysis showed that only one day (Dec. 21st) was determined as dry (20.4 % and 24.5 % for flat and hill-slope fields, respectively). In contrary to a hill-slope field where the full irrigation was necessary, the centralized irrigation scheme was appeared to be more effective for a flat field based on the spatial variability of soil moisture contents. The findings of this study clearly showed that the geostatistical analysis of soil moisture contents greatly contributes to proper irrigation scheduling for water-efficient irrigation with maximal crop productivity and environmental benefits.

• 한국심리학회지:학교
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• 제17권2호
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• pp.165-180
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• 2020

본 연구의 목적은 다층적 행동지원 모형을 적용하고 있는 학교차원 긍정적 행동지원(School-Wide Positive Behavior Supports, SWPBS)을 국내 학교현장에서 근거기반 실천으로 보급하기 위해 개별화지원에 해당하는 3차 지원의 실행충실도 평가도구를 개발해 타당화하는 것이었다. 3차 지원 실행충실도 평가도구를 개발하기 위해 문헌 개관 및 전문가 내용 타당도 검증을 통해 핵심 평가요소 6개 요인으로 구성된 37개의 예비문항을 선정하였다. 이후 학교차원 긍정적 행동지원 실행 경험이 있는 현직 교사 185명(남 52명, 여 133명)을 대상으로 3차 지원 실행충실도 척도, 개별화지원 척도, 학교풍토 척도, 학생지도 척도, 긍정적 행동지원 효과성 척도로 구성된 설문지를 배포해 자료를 수집하였다. 탐색적 요인분석에서 각 하위요인에 4문항으로 구성된 5요인 구조(요인 1: 개별화지원 계획의 점검 및 평가, 요인 2: 정신건강 서비스 연계를 통한 지원, 요인 3: 위기관리 계획, 요인 4: 문제행동 평가, 요인 5: 개별화지원 팀구성)의 총 20문항이 최종 문항으로 선정되었다. 또한 내적 합치도는 전체 문항 α=.950, 하위요인은 α=.888 ~ .954로 모두 양호하였다. 상관분석에서 3차 지원 실행충실도 척도는 개별화지원 척도, 학교풍토 척도, 학생지도 척도, 긍정적 행동지원 효과성 척도와 각각 유의미한 상관을 나타내면서 양호한 수렴타당도를 나타내었다. 마지막으로, 확인적 요인분석에서 5요인 구조의 모형 적합도는 양호하였고, 신뢰도 및 타당도가 안정적인 것으로 나타났다. 따라서 SWPBS의 실행충실도를 점검하고 평가하는 데 본 척도가 신뢰롭고 타당하게 사용될 수 있을 것으로 보인다. 또한 한국형 3차 지원 실행충실도 척도가 국내 학교현장에서 SWPBS를 근거기반의 행동적 개입으로 활용하는 데 기여할 수 있을 것이다.

• 대한전자공학회논문지SD
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• 제42권11호
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• pp.1-8
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• 2005

본 논문은 MEMS (Micro-Mechanical-Electronic System) 기술을 이용한 온도, 압력, 습도 복합 센서의 설계와 제작, 그리고 평가에 관한 것이다. 이러한 MEMS 복합 센서는 휴대 전화나 PDA와 같이 가정용 제품에 사용되어 환경을 모니터링하는 건강 측정용 센서로서 사용될 것이다. 이 연구의 범위는 이러한 개별 센서의 연구 및 모든 센서를 하나의 실리콘 웨이퍼 상에서 집적할 수 있는 구조에 관한 연구, 그리고 복합 센서를 MEMS 공정에서 제작할 수 있는 공정 호환성에 대한 연구와 얻어진 센서 prototype의 측정, 평가로 이루어져 있다. 이 연구에서 우리는 온도와 압력 센서의 경우에는 선형성과 이력특성이 $1\%FS$안에 들어오는 특성을 얻었으며 단지 습도 센서의 경우에는 $5\%FS$에 해당하는 선형성과 이력 특성을 얻었다. 다만 원리적으로 습도 센서의 동작 특성은 비선형적이며 우리가 3차로 근사화할 경우에 보다 낳은 결과를 얻을 것을 기대할 수 있다. 이러한 특성을 더욱 개선하기 위한 것은 추후의 연구 영역이 될 것이다.