• Smart Structures and Systems
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• v.15 no.3
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• pp.505-522
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• 2015

Variation of temperature is a primary environmental factor that affects the behavior of structures. Therefore, understanding the mechanisms of normal temperature-induced variations of structural behavior would help in distinguishing them from anomalies. In this study, we used the structural health monitoring data of the Shanghai Yangtze River Bridge, a steel girder cable-stayed bridge, to investigate the mechanisms of thermally induced vertical deflection ($D_T$) at mid-span of such bridges. The $D_T$ results from a multisource combination of thermal expansion effects of the cable temperature ($T_{Cab}$), girder temperature ($T_{Gir}$), girder differential temperature ($T_{Dif}$), and tower temperature ($T_{Tow}$). It could be approximated by multiple linear superpositions under operational conditions. The sensitivities of $D_T$ of the Shanghai Yangtze River Bridge to the above temperatures were in the following order: $T_{Cab}$ > $T_{Gir}$ > $T_{Tow}$ > $T_{Dif}$. However, the direction of the effect of $T_{Cab}$ was observed to be opposite to that of the other three temperatures, and the magnitudes of the effects of $T_{Cab}$ and $T_{Gir}$ were found to be almost one order greater than those of $T_{Dif}$ and $T_{Tow}$. The mechanisms of the thermally induced vertical deflection variation at mid-span of a cable-stayed bridge as well as the analytical methodology adopted in this study could be applicable for other long-span cable-stayed bridges.

• Journal of the Korean Geotechnical Society
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• v.37 no.5
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• pp.19-31
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• 2021

Groundwater level (GWL) causes the stress state within soil and affects the bearing capacity and the settlement of foundation. In this study, the analyses of influencing factors on GWL fluctuation were performed. From the results, river stage and moving average of precipitation were main influence components for urban near large river and rural areas, respectively. In addition, the prediction performance of GWL using artificial neural network (ANN) was conducted with respect to the influence components. As a result, the effect of main component was significant on the prediction performance of GWL.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1911-1923
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• 2022

The availability of high-resolution satellite images provides precise information without direct observation of the research target. Korea Multi-Purpose Satellite (KOMPSAT), also known as the Arirang satellite, has been developed and utilized for earth observation. The machine learning model was continuously proven as a good classifier in classifying remotely sensed images. This study aimed to compare the performance of the support vector machine (SVM) model in classifying the land cover of the Delaware River port area on high and medium-resolution images. Three optical images, which are KOMPSAT-2, KOMPSAT-3A, and Sentinel-2B, were classified into six land cover classes, including water, road, vegetation, building, vacant, and shadow. The KOMPSAT images are provided by Korea Aerospace Research Institute (KARI), and the Sentinel-2B image was provided by the European Space Agency (ESA). The training samples were manually digitized for each land cover class and considered the reference image. The predicted images were compared to the actual data to obtain the accuracy assessment using a confusion matrix analysis. In addition, the time-consuming training and classifying were recorded to evaluate the model performance. The results showed that the KOMPSAT-3A image has the highest overall accuracy and followed by KOMPSAT-2 and Sentinel-2B results. On the contrary, the model took a long time to classify the higher-resolution image compared to the lower resolution. For that reason, we can conclude that the SVM model performed better in the higher resolution image with the consequence of the longer time-consuming training and classifying data. Thus, this finding might provide consideration for related researchers when selecting satellite imagery for effective and accurate image classification.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.185-199
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• 2023

This study aimed to predict the effects of water ecology on the supply of hydrothermal energy to model a housing complex in Eco Delta Smart Village in Busan. Based on the results, engineering measures were recommended to minimize problems due to possible temperature variations on the supply of hydrothermal energy from the river. The current distribution of fish, benthic macroinvertebrates, and phytoplankton in the Pyeonggang Stream was monitored to determine their effects on water ecology. In the research area, five species and three families of fish were observed. The dominant species was Lepomis macrochirus, and the subdominant species was Carassius auratus. Twenty-five species and 21 families of benthic macroinvertebrates were found. The distribution of aquatic insects was poor in this area. The dominant species were Chironomidae sp., Lymnaea auricularia, Appasus japonicus, and Caridina denticulata denticulata in February, May, July, and October. Dominant phytoplankton were Aulacoseira ambigua and Nitzschia palea in February and May. Microcystis sp. was dominant in July and October. The health of the ecology the Pyeonggang Stream was assessed as D (bad) according to the benthic macroinvertebrate index (BMI). Shifts in the location of the discharge point 150 m downstream from intake points and discharge through embedded rock layer after adding equal amounts of stream water as was taken at the beginning were suggested to minimize water temperature variations due to the application of hydrothermal energy. When the scenario (i.e., quantity of water intake and dilution water, 1,600 m³/d and water temp. difference ±5 ℃) was realized, variations in water temperature were assessed at -0.19 ℃ and 0.59 ℃ during cooling and heating, respectively, at a point 10 m downstream. Water temperatures recorded at -0.20 ℃ and 0.68 ℃ during cooling and heating, respectively, at a point 10 m upstream. All stream water temperatures after the application of hydrothermal energy recovered within 24 hours. Future work on the long-term monitoring of ecosystems is suggested, particularly to analyze the influence of the water environment on hydrothermal energy supply operations.

• Archives of design research
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• v.14 no.1
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• pp.83-92
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• 2001

Apartment exterior colors have an important effect on the images of cities and communities. Therefore planning the apartment exterior colors have to proceed systematically and synthetically based on the theoretical background. In this research, the first step is to investigate the apartment exterior colors which is located around the Han River in Seoul. And the second step is to survey the images of the S construction company in Korea. The results of this study are as follows: 1. The trends of apartment exterior colors on the basis of 1996 are showed differently. Bright and high saturation colors are more used after 1996, and divers color combinations are more tried than before. 2. Common customer Has positive images about the S construction company such as young, fresh, confidence and smart. Also they want the other images such as comfort, ease and coziness. 3. Two color combination palettes were proposed in this research. The first color combination is blue and yellow which is based on the dear and smart images. And the second color combination is green and orange which is based on the comfort and ease images.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.164-164
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• 2023

This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.30-30
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• 2023

This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.

• Smart Structures and Systems
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• v.22 no.1
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• pp.13-25
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• 2018

Pedro $G{\acute{o}}mez$ Bosque footbridge is a slender and lightweight structure that creates a pedestrian link over the Pisuerga River, Valladolid, Spain. This footbridge is a singular stress ribbon structure with one span of 85 m consisting on a steel plate and precast concrete slabs laying on it. Rubber pavement and a railing made of stainless steel and glass complete the footbridge. Because of its lively dynamics, prone to oscillate, a simple and affordable structural health monitoring system was installed in order to continuously evaluate its structural serviceability and to estimate its modal parameters. Once certain problems (conditioning and 3D orientation of the triaxial accelerometers) are overcome, the monitoring system is validated by comparison with a general purpose laboratory portable analyzer. Representative data is presented, including acceleration magnitudes and modal estimates. The evolution of these parameters has been analysed over one-year time.

• Smart Structures and Systems
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• v.3 no.3
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• pp.373-384
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• 2007

For structural health monitoring (SHM) of civil infrastructures, displacement is a good descriptor of the structural behavior under all the potential disturbances. However, it is not easy to measure displacement of civil infrastructures, since the conventional sensors need a reference point, and inaccessibility to the reference point is sometimes caused by the geographic conditions, such as a highway or river under a bridge, which makes installation of measuring devices time-consuming and costly, if not impossible. To resolve this issue, a visionbased real-time displacement measurement system using digital image processing techniques is developed. The effectiveness of the proposed system was verified by comparing the load carrying capacities of a steel-plate girder bridge obtained from the conventional sensor and the present system. Further, to simultaneously measure multiple points, a synchronized vision-based system is developed using master/slave system with wireless data communication. For the purpose of verification, the measured displacement by a synchronized vision-based system was compared with the data measured by conventional contact-type sensors, linear variable differential transformers (LVDT) from a laboratory test.

• Smart Structures and Systems
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• v.11 no.6
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• pp.637-662
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• 2013

The Jiangyin Bridge is a suspension bridge with a main span of 1385 m over the Yangtze River in Jiangsu Province, China. Being the first bridge with a main span exceeding 1 km in Chinese mainland, it had been instrumented with a structural health monitoring (SHM) system when completed in 1999. After operation for several years, it was found with malfunction in sensors and data acquisition units, and insufficient sensors to provide necessary information for structural health evaluation. This study reports the SHM system upgrade project on the Jiangyin Bridge. Although implementations of SHM system have been reported worldwide, few studies are available on the upgrade of SHM system so far. Recognizing this, the upgrade of original SHM system for the bridge is first discussed in detail. Especially, lessons learned from the original SHM system are applied to the design of upgraded SHM system right away. Then, performance assessment of the bridge, including: (i) characterization of temperature profiles and effects; (ii) recognition of wind characteristics and effects; and (iii) identification of modal properties, is carried out by making use of the long-term monitoring data obtained from the upgraded SHM system. Emphasis is placed on the verification of design assumptions and prediction of bridge behavior or extreme responses. The results may provide the baseline for structural health evaluation.