• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.423-428
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• 2007

The 21st century is that both human and environment live together. The advancing knowledge concerning our environment instigates a change in understanding about the physical surroundings. The construction field particularly induces significant improvements that are environmental-friendly. To convene this demand, several manuals and guidelines related to the environmental issues have been enacted and amended. Especially the manuals and guidelines issued from Ministry of Environment (MOC) and Ministry of Construction and Transportation (MOCT) is requiring the addition of environmental knowledge in construction technology. Recently, environmental assessments and advanced environmental measures in various kinds of construction are persuasively been carried out. The policy of Total Maximum Daily Load is the one more reason for the revisions of the manual and guideline, which is really requiring the addition of the environmental knowledge in construction technology. Therefore, this research is focusing on revising the manuals and guidelines related to road construction and maintenance works issued from MOCT.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.6
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• pp.447-456
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• 2014

In this paper, a new damage-detection method based on structural vibration is proposed. The essence of the proposed method is the detection of abrupt changes in rotation. Damage-induced rotation (DIR), which is determined from the modal flexibility of the structure, initially occurs only at a specific damaged location. Therefore, damage can be localized by evaluating abrupt changes in rotation. We conducted numerical simulations of two damage scenarios using a 10-story cantilever-type building model. Measurement noise was also considered in the simulation. We compared the sensitivity of the proposed method to localize damage to that of two conventional modal-flexibility-based damage-detection methods, i.e., uniform load surface (ULS) and ULS curvature. The proposed method was able to localize damage in both damage scenarios for cantilever structures, but the conventional methods could not.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.211-218
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• 2015

The analysis of remote sensing data depends on sensor specifications that provide accurate and consistent measurements. However, it is not easy to establish confidence and consistency in data that are analyzed by different sensors using various radiometric scales. For this reason, the cross-calibration method is used to calibrate remote sensing data with reference image data. In this study, we used an airborne hyperspectral image in order to calibrate a multispectral image. We presented an automatic cross-calibration method to calibrate a multispectral image using hyperspectral data and spectral mixture analysis. The spectral characteristics of the multispectral image were adjusted by linear regression analysis. Optimal endmember sets between two images were estimated by spectral mixture analysis for the linear regression analysis, and bands of hyperspectral image were aggregated based on the spectral response function of the two images. The results were evaluated by comparing the Root Mean Square Error (RMSE), the Spectral Angle Mapper (SAM), and average percentage differences. The results of this study showed that the proposed method corrected the spectral information in the multispectral data by using hyperspectral data, and its performance was similar to the manual cross-calibration. The proposed method demonstrated the possibility of automatic cross-calibration based on spectral mixture analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.331-341
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• 2019

With the popularity of sensor-rich environments, smartphones have become one of the major platforms for obtaining and sharing information. Since it is difficult to utilize GNSS (Global Navigation Satellite System) inside the area with many buildings, the localization of smartphone in this case is considered as a challenging task. To resolve problem of localization using smartphone a four step image-based localization method and procedure is proposed. To improve the localization accuracy of smartphone datasets, MMS (Mobile Mapping System) and Google Street View were utilized. In our approach first, the searching for candidate matching image is performed by the query image of smartphone's using GNSS observation. Second, the SURF (Speed-Up Robust Features) image matching between the smartphone image and reference dataset is done and the wrong matching points are eliminated. Third, the geometric transformation is performed using the matching points with 2D affine transformation. Finally, the smartphone location and attitude estimation are done by PnP (Perspective-n-Point) algorithm. The location of smartphone GNSS observation is improved from the original 10.204m to a mean error of 3.575m. The attitude estimation is lower than 25 degrees from the 92.4% of the adjsuted images with an average of 5.1973 degrees.

• Journal of the Korean GEO-environmental Society
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• v.20 no.12
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• pp.27-32
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• 2019

Disaster Safety Management Information standardization and harmonization simplifies the process of disaster management (prevention, preparedness, response and recovery) to increase the efficiency of disaster management, it is necessary to minimize the people's life and property damage. Disaster safety standardization is to standardize disaster safety information in the past to respond to an uncertain future and systematically manage disaster safety accordingly. This study developed a standard code system to utilize disaster safety information such as earthquake, fire, and fine dust, which are of social interest among various and complex environmental disasters. It aims to support practitioners to conduct efficient disaster tasks in the event of a disaster.

• Journal of the Korean GEO-environmental Society
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• v.22 no.11
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• pp.39-47
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• 2021

Tunneling is widely increased in rail-road construction due to the large portion of mountainous regions in Korea as well as the improving running performance of train. Tunneling under poor rock condition, shallow overburden, or existing fault zone has high risk for collapse. Therefore, this study presents the stability of tunnel under unfavorable geological conditions using finite element methods.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.861-872
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• 2021

An efficient cost management is important for the domestic social overhead capital(SOC) based on a long lifecycle after 30 years since completion. Maintenance in South Korea have had the restrictions of consistency and suitability of decision-making by the establishment of a budget plan based on the company estimate and repair and reinforcement methods determined by the inspection and diagnosis engineers' subjective determination for each facility. To resolve this issue, the Korea Institute of Civil Engineering and Building Technology is currently in development of a methodology to propose an optimum maintenance method according to the damage of components by artificial intelligence. This study has deduced the primary factors by analyzing information generated during bridge maintenance and management as a prior step for the development of technologies, and conducted a preliminary analysis to select the optimum artificial intelligence technology.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.3
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• pp.93-102
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• 2021

The dynamic characterization of a three-story auxiliary building in a nuclear power plant (NPP) constructed with a monolithic reinforced concrete shear wall is investigated in this study. The shear wall is subjected to a joint-research, round-robin analysis organized by the Korea Atomic Energy Research Institute, South Korea, to predict seismic responses of that auxiliary building in NPP through a shake table test. Five different intensity measures of the base excitation are applied to the shaking table test to get the acceleration responses from the different building locations for one horizontal direction (front-back). Simultaneously to understand the global damage scenario of the structure, a frequency search test is conducted after each excitation. The primary motivation of this study is to develop a nonlinear numerical model considering the multi-layered shell element and compare it with the test result to validate through the modal parameter identification and floor responses. In addition, the acceleration amplification factor is evaluated to judge the dynamic behavior of the shear wall with the existing standard, thus providing theoretical support for engineering practice.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.6
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• pp.573-581
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• 2018

The purpose of this study is to evaluate the fixed wing type domestic UAV for monitoring of algae bloom in aquatic environment. The UAV used in this study is operated automatically in-flight using an automatic navigation device, and flies along a path targeting preconfigured GPS coordinates of desired measurement sites input by a flight path controller. The sensors used in this study were Sequoia multi-spectral cameras. The photographed images were processed using orthomosaics, georeferenced digital surface models, and 3D mapping software such as Pix4D. In this study, NDVI(Normalized distribution vegetation index) was used for estimating the concentration of chlorophyll-a in river. Based on the NDVI analysis, the distribution areas of chlorophyll-a could be analyzed. The UAV image was compared with a airborne image at a similar time and place. UAV images were found to be effective for monitoring of chlorophyll-a in river.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.277-292
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• 2018

This paper presents the development and implementation of an artificial intelligence (AI)-based deep excavation induced wall and ground displacements and wall support member forces prediction program (ANN-EXCAV). The program has been developed in a C# environment by using the well-known AI technique artificial neural network (ANN). Program used ANN to predict the induced displacement, groundwater drawdown and wall and support member forces parameters for deep excavation project and run the stability check by comparing predict values to the calculated allowable values. Generalised ANNs were trained to predict the said parameters through databases generated by numerical analysis for cases that represented real field conditions. A practical example to run the ANN-EXCAV is illustrated in this paper. Results indicate that the program efficiently performed the calculations with a considerable accuracy, so it can be handy and robust tool for preliminary design of wall and support members for deep excavation project.