• Tunnel and Underground Space
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• v.16 no.3 s.62
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• pp.259-276
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• 2006

In rock mass subject to high in-situ stresses, the failure process of rock is dominated by the stress-induced fractures growing parallel to the excavation boundary. When the ratio of in situ stresses compared to rock strength is greater than a certain value, progressive brittle failure which is characterized by popping and spatting of rock debris occurs due to stress concentration. Traditional constitutive model like Mohr-Coulomb usually assume that the normal stress dependent frictional strength component and the cohesion strength component are constant, therefore modelling progressive brittle failure will be very difficult. In this study, a series of numerical analyses were conducted for surrounding rock mass near crude oil storage cavern using CW-FS model which was known to be efficient for modelling brittle failure and the results were compared with those of linear Mohr-Coulomb model. Further analyses were performed by varying plastic shear strain limits on cohesion and internal friction angle to find the proper values which yield the matching result with the observed failure in the oil storage caverns. The obtained results showed that CW-FS model could be a proper method to characterize essential behavior of progressive brittle failure in competent rock mass.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.69-80
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• 2022

Drone photogrammetry generally acquires images vertically or obliquely from above, so when photographing for the purpose of three-dimensional modeling, image matching for the ground of a building and spatial accuracy of point cloud data are poor, resulting in poor 3D mesh completeness. Therefore, to overcome this, this study analyzed the spatial accuracy of each drone image by acquiring smartphone images from the ground, and evaluated the accuracy improvement and completeness of 3D mesh when the smartphone image is not combined with the drone image. As a result of the study, the horizontal (x,y) accuracy of drone photogrammetry was about 1/200,000, similar to that of traditional photogrammetry. In addition, it was analyzed that the accuracy according to the photographing method was more affected by the photographing angle of the object than the increase in the number of photos. In the case of the smartphone image combination, the accuracy was not significantly affected, but the completeness of the 3D mesh was able to obtain a 3D mesh of about LoD3 that satisfies the digital twin city standard. Therefore, it is judged that it can be sufficiently used to build a 3D model for digital twin city by combining drone images and smartphones or DSLR images taken on the ground.

• Membrane Journal
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• v.32 no.4
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• pp.253-263
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• 2022

This study suggests a guideline for designing unit process of wastewater reuse in terms of a maintenance of the process based on critical parameters to draw a high quality performance of RO unit. Defining the parameters was done by applying membrane integrity test (MIT) in pretreatment process utilizing lab-scale MF. SDI is utilized for judging whether permeate is suitable to RO unit. However, result said TOC concentration matching with particle count analysis is better for judging the permeate condition. When membrane test pressure (P_test) was measured to derive log removal value in PDT, virgin state of membrane fiber was used to measure dynamic contact angle utilizing surface tension of the membrane fiber. Actually, foulant affects to the state of membrane surface, and it decreases the P_test value along with time elapsed. Consequently, LRV_DIT is also affected by P_test value. Thus, sensitivity of direct integrity test descends with result of P_test value change, so P_test value should be considered not the virgin state of the membrane but its current state. Overall, this study focuses on defining design parameters suitable to MF pretreatment for RO process in wastewater reuse by assessing its impact. Therefore, utilities can acknowledge that the membrane surface condition must be considered when users conduct the direct integrity test so that P_test and other relative parameter used to calculate LRV_DIT are adequately measured.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.175-185
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• 2020

Three-dimensional registration is a process of matching data with or without a coordinate system to a reference coordinate system, which is used in various fields such as the absolute orientation of photogrammetry and data combining for producing precise road maps. Three-dimensional registration is divided into a method using points and a method using linear features. In the case of using points, it is difficult to find the same conjugate point when having different spatial resolutions. On the other hand, the use of linear feature has the advantage that the three-dimensional registration is possible by using not only the case where the spatial resolution is different but also the conjugate linear feature that is not the same starting point and ending point in point cloud type data. In this study, we proposed a method to determine the scale and the three-dimensional translation after determining the three-dimensional rotation angle between two data using quaternion to perform three-dimensional registration using linear features. For the verification of the proposed method, three-dimensional registration was performed using the linear features constructed an indoor and the linear features acquired through the terrestrial mobile mapping system in an outdoor environment. The experimental results showed that the mean square root error was 0.001054m and 0.000936m, respectively, when the scale was fixed and if not fixed, using indoor data. The results of the three-dimensional transformation in the 500m section using outdoor data showed that the mean square root error was 0.09412m when the six linear features were used, and the accuracy for producing precision maps was satisfied. In addition, in the experiment where the number of linear features was changed, it was found that nine linear features were sufficient for high-precision 3D transformation through almost no change in the root mean square error even when nine linear features or more linear features were used.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.