• Environmental Analysis Health and Toxicology
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• 제20권4호통권51호
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• pp.333-341
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• 2005

In order to know whether polychaetes could be used as an appropriate organism for the detection of genotoxicity, DNA strand breaks were evaluated in blood cells of a nereidae worm (Perinereis aibuhitensis) exposed to various aquatic chemical pollutants (e.g. Cd, Pb, Pyrene, Benaor[a]pyrene). Hydrogen peroxide increased DNA strand breaks up to the highest concentration (10 $\mu$M). Higher concentration than 0.1 $\mu$M showed a significantly more DNA damage than control. Cadmium and lead also showed higher DNA damage than control, over 1.0 and 1 $\mu$g/L, respectively. In case of pyrene, DNA damage was detected even at 0.001 $\mu$g/L. However, DNA damage decreased due to apoptosis at the highest concentration of pyrene and Pb. This study suggested that the polythaetous blood cells could be used effectively for screening genotoxic contaminants in the environment.

• Steel and Composite Structures
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• 제42권4호
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• pp.501-511
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• 2022

Earthquake Resistant Design Philosophy seeks (a) no damage, (b) no significant structural damage, and (c) significant structural damage but no collapse of normal buildings, under minor, moderate and severe levels of earthquake shaking, respectively. A procedure is proposed for seismic design of low-rise reinforced concrete special moment frame buildings, which is consistent with this philosophy; buildings are designed to be ductile through appropriate sizing and reinforcement detailing, such that they resist severe level of earthquake shaking without collapse. Nonlinear analyses of study buildings are used to determine quantitatively (a) ranges of design parameters required to assure the required deformability in normal buildings to resist the severe level of earthquake shaking, (b) four specific limit states that represent the start of different structural damage states, and (c) levels of minor and moderate earthquake shakings stated in the philosophy along with an extreme level of earthquake shaking associated with the structural damage state of no collapse. The four limits of structural damage states and the three levels of earthquake shaking identified are shown to be consistent with the performance-based design guidelines available in literature. Finally, nonlinear analyses results are used to confirm the efficacy of the proposed procedure.

• Biotechnology and Bioprocess Engineering:BBE
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• 제8권2호
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• pp.101-105
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• 2003

Recombinant bioluminescent bacteria were used to monitor and classify the to xicity of azo dyes. Two constitutive bioluminescent bacteria, Photobacterium phosphoreum and Es-Cherichia coli, E, coli GC2 (lac::luxCOABE), were used to detect the cellular toxicity of the azo dyes. In addition, four stress-inducible bioluminestent E. coli, DPD2794 (recA::luxCDABE), a DNA damage Sensitive strain; DPD2540 (fabA::luxCDABE), a membrane damage sensitive strain; DPD2511 (katG::luxCDABE), an oxidative damage sensitive strain; and TV1061 (grpE::luxCDABE), a protein damage sensitive strain, were used to provide information about the type of toxicity caused by crystal violet, the most toxic dye of the 16 azo dyes tested. These results suggest that azo dyes result in serious cellular toxicity in bacteria, and that toxicity monitoring and classific ation of some azo dyes, In the field, may be possible using these recombinant bioluminescent bacteria.

• Nuclear Engineering and Technology
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• 제45권4호
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• pp.553-564
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• 2013

This study evaluates the local damage of a turbine in an auxiliary building of a nuclear power plant due to an external impact by using the LS-DYNA finite element program. The wall of the auxiliary building is SC structure and the material of the SC wall plate is high manganese steel, which has superior ductility and energy absorbance compared to the ordinary steel used for other SC wall plates. The effects of the material of the wall, collision speed, and angle on the magnitude of the local damage were evaluated by local collision analysis. The analysis revealed that the SC wall made of manganese steel had significantly less damage than the SC wall made of ordinary steel. In conclusion, an SC wall made of manganese steel can have higher effective resistance than an SC wall made of ordinary steel against the local collision of an airplane engine or against a turbine impact.

• Steel and Composite Structures
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• 제44권2호
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• pp.241-254
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• 2022

The cables in a cable-stayed bridge are critical load-carrying parts. The potential damage to cables should be identified early to prevent disasters. In this study, an efficient deep learning model is proposed for the damage identification of cables using both a multi-layer perceptron (MLP) and a graph neural network (GNN). Datasets are first generated using the practical advanced analysis program (PAAP), which is a robust program for modeling and analyzing bridge structures with low computational costs. The model based on the MLP and GNN can capture complex nonlinear correlations between the vibration characteristics in the input data and the cable system damage in the output data. Multiple hidden layers with an activation function are used in the MLP to expand the original input vector of the limited measurement data to obtain a complete output data vector that preserves sufficient information for constructing the graph in the GNN. Using the gated recurrent unit and set2set model, the GNN maps the formed graph feature to the output cable damage through several updating times and provides the damage results to both the classification and regression outputs. The model is fine-tuned with the original input data using Adam optimization for the final objective function. A case study of an actual cable-stayed bridge was considered to evaluate the model performance. The results demonstrate that the proposed model provides high accuracy (over 90%) in classification and satisfactory correlation coefficients (over 0.98) in regression and is a robust approach to obtain effective identification results with a limited quantity of input data.

• Smart Structures and Systems
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• 제31권4호
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.651-656
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• 2007

Changes in measured structural responses induced by a damage could be significantly smaller than those by environmental effects such as temperature and temperature gradients. It is highly desirable to develop a methodology to distinguish the changes due to the structural damage from those by the environmental variations. In this study, a novel method to extract the damage-induced deflection under temperature variations is presented using the outlier analysis on the deflections obtained using the modal flexibility matrices. The main idea is that temperature change in a bridge would produce global increase or decrease in deflections over the whole bridge while structural damages may cause local variations in deflections near the damage locations. Hence, the correlation between the deflection measurements may show high abnormality near the damage locations. A series of laboratory tests were carried out on a bridge model with a steel box-girder for 14 days. It has been found that the damage existence assessment and localization can carried out for a case with relatively small damage under the temperature variations

• Smart Structures and Systems
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• 제4권6호
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• pp.759-777
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• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

• 한국수자원학회논문집
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• 제50권6호
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• pp.397-405
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• 2017

인구와 자산이 밀집된 도시에서 침수가 발생할 경우 농촌과 달리 관거월류에 의한 건축물 피해가 지배적이기 때문에 이를 고려한 피해액산정기법의 적용이 필요하다. 본 연구는 도림천 유역의 도림1 배수분구를 대상으로 침수예측을 다차원 홍수피해산정방법을 통한 침수피해액 분석을 실시하였다. 과거 침수가 발생한 강우사상을 활용하여 XP-SWMM 모형을 통한 도시유출해석 및 침수해석을 실시하였고, 침수구역의 행정구역별 기초자료와 유출해석 결과를 활용하여 건물 피해액을 산정하였다. 침수범위를 예측하기 위한 XP-SWMM모형 구동 결과, 관거 월류에 의한 침수 발생 4시간 후인 16시 30분에 침수면적이 가장 넓게 나타났고, 계산된 침수심 별 침수면적을 다차원법과 연계하여 건물 피해액을 산정하였다. 연구결과, 최대 침수면적은 $305,955m^2$으로 나타났으며, 0~0.5 m의 경우 $305,190m^2$, 0.5 m 이상은 $765m^2$으로 나타났으며, 침수해석 결과를 활용한 도림1 배수분구의 건물피해액은 약 155억 원, 건물 내용물 피해액은 약 70억 원으로 산정되었고, 0~0.5 m 이하의 건물 및 건물 내용물 피해액은 약 224억 원, 0.5 m 이상 약 1억 원으로 산정되었다. 본 연구결과를 토대로 할 때, 도시지역의 침수피해액 산정을 위해 침수심 및 침수시간과 같은 다양한 피해양상에 따라 세분화된 피해액 산정기법이 필요할 것으로 판단된다.

• 환경정책연구
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• 제8권2호
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• pp.1-23
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• 2009

본 연구는 레이더 위성영상을 활용한 침수피해 지역 파악 및 그 완화방안의 도출을 위해 실제 침수지역을 대상으로 레이더 위성 영상의 침수피해에의 활용가능성을 살펴보았다. 이를 위하여 시계열 레이더 위성영상 자료를 활용하여 홍수에 취약한 침수 지역을 추출하고, 동일지역의 토지이용도에 대한 GIS 중첩분석을 통하여 토지이용 현황별 침수피해를 분석하였다. 사례 분석지역의 경우 침수피해가 심한 토지이용 형태는 농경지와 숲으로 나타났다. 본 연구는 레이더 위성영상을 활용하여 구축 가능한 침수피해 지도를 바탕으로 침수피해 완화를 위한 대응정책도 함께 논의하였다. 침수가 발생할 경우 긴급복구와 같은 위기대응적 접근도 중요하지만 무엇보다도 침수피해 지도와 같은 자료를 기반으로 위험한 지역에 건물의 입지를 제한하는 등 상습 침수피해 지역이 개발되지 않도록 예방적 차원에서의 토지 이용적 접근을 하여야 할 것이다. 본 연구에서 제안한 방안은 레이더 위성 영상의 환경 분야 활용과 침수피해를 최소화하는 방안의 일부이며, 레이더 위성영상은 대규모 홍수와 같은 재해문제 이외에도 다양한 환경 분야에 있어 활용 잠재력이 높으므로 향후 다양한 지역을 대상으로 레이더 위성영상을 여러 환경문제에 적용하는 연구가 계속되어야 할 것이다.