• Tunnel and Underground Space
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• v.27 no.4
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• pp.243-252
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• 2017

Since the failure behavior of transversely isotropic rocks is significantly different from that of isotropic rocks, it is necessary to develop a transversely isotropic rock failure function in order to evaluate the stability of rock structures constructed in transversely isotropic rock masses. In this study, a spatial distribution function for strength parameters of transversely isotropic rocks is proposed, which is based on the Cassini oval curve proposed by 17th century astronomer Giovanni Domenico Cassini to model the orbit of the Sun around the Earth. The proposed distribution function consists of two model parameters which could be identified through triaxial compression tests on transversely isotropic rock samples. The original Mohr-Coulomb (M-C) failure function is extended to a three-dimensional transversely isotropic M-C failure function by employing the proposed strength parameter distribution function for the spatial distributions of the friction angle and cohesion. In order to verify the suitability of the transversely isotropic M-C failure function, both the conventional triaxial compression and true triaxial compression tests of transversely isotropic rock samples are simulated. The predicted results from the numerical experiments are consistent with the failure behavior of transversely isotropic rocks observed in the actual laboratory tests. In addition, the simulated result of true triaxial compression tests hints that the dependence of rock strength on intermediate principal stress may be closely related to the distribution of the microstructures included in the rock samples.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.763-774
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• 2020

Wind data forecasted from the numerical weather prediction (NWP) model is generally used as the first-guess of the target tracking process to obtain the atmospheric motion vectors(AMVs) because it increases tracking accuracy and reduce computational time. However, there is a contradiction that the NWP model used as the first-guess is used again as the reference in the AMVs verification process. To overcome this problem, model-independent first guesses are required. In this study, we propose the AMVs derivation from Lucas and Kanade optical flow method and then using it as the first guess. To retrieve AMVs, Himawari-8/AHI geostationary satellite level-1B data were used at 00, 06, 12, and 18 UTC from August 19 to September 5, 2015. To evaluate the impact of applying the optical flow method on the AMV derivation, cross-validation has been conducted in three ways as follows. (1) Without the first-guess, (2) NWP (KMA/UM) forecasted wind as the first-guess, and (3) Optical flow method based wind as the first-guess. As the results of verification using ECMWF ERA-Interim reanalysis data, the highest precision (RMSVD: 5.296-5.804 ms^-1) was obtained using optical flow based winds as the first-guess. In addition, the computation speed for AMVs derivation was the slowest without the first-guess test, but the other two had similar performance. Thus, applying the optical flow method in the target tracking process of AMVs algorithm, this study showed that the optical flow method is very effective as a first guess for model-independent AMVs derivation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.1
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• pp.80-87
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• 2016

In this work, we conduct a thermal pointing error analysis of the observation satellites considering seasonal and daily temperature variation with interpolated temperature based on prescribed average temperature (PAT) method. Maximum 200 degree temperature excursion is applied to the observation satellites during on-orbit operation, which cause the line of sight (LOS) to deviate from the designated pointing direction due to thermo-elastic deformation. To predict and adjust such deviation, the thermo-elastic deformation analysis with a fine structural finite element model is accomplished with interpolated thermal maps calculated from the results of on-station thermal analysis with a coarse thermal model. After verifying the interpolated temperatures by PAT with two benchmark problems, we evaluate the thermal pointing error.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.427-438
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• 2022

With the recent growing importance over safety management the need for advanced and technical approaches for on-site safety inspection methods has increased. Railway construction is subject to its own particular set of temporal and spatial challenges due to its unique facilities and equipment. This study aimed to investigate the field characteristics of railway infrastructure and improve the conventional field safety management methods by identifying the most appropriate features of AR technology. Group interviews and surveys were conducted with field safety experts to derive the major problems and inspection needs. Subsequently, various features of AR, such as BIM model projection, and remote conferencing, were investigated to determine their applicability to address safety issues. As a result, four problems in the current safety management process, such as 'lack of time due to the conventional inspection method and inspection of areas that are difficult to access', and three major inspection types, such as 'observance of work procedures, status of installation, adequate dimensional spacing', were identified to be improved when adopting AR based techniques. Furthermore, AR technology utilizing plans to solve safety inspection problems and effectively manage major inspection types were proposed, and a follow up survey was conducted with the same field safety experts to derive the priority of technology development.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.107-123
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• 2020

With stabilization of the recent multi-GNSS infrastructure, and as multi-GNSS has been proven to be effective in improving the accuracy of the positioning performance in various industrial sectors. In this study, in view that SF(Single frequency) GNSS receivers are widely used due to the low costs, evaluate effectiveness of SF Real Time Point Positioning(SF-RT-PP) based on four multi-GNSS surveying methods with RTCM-SSR correction streams in static and kinematic modes, and also derive response challenges. Results of applying SSR correction streams, CNES presented good results compared to other SSR streams in 2D coordinate. Looking at the results of the SF-RT-PP surveying using SF signals from multi-GNSS, were able to identify the common cause of large deviations in the altitude components, as well as confirm the importance of signal bias correction according to combinations of different types of satellite signals and ionospheric delay compensation algorithm using undifferenced and uncombined observations. In addition, confirmed that the improvement of the infrastructure of Multi-GNSS allows SF-RT-SPP surveying with only one of the four GNSS satellites. In particular, in the case of code-based SF-RT-SPP measurements using SF signals from GPS satellites only, the difference in the application effect between broadcast ephemeris and SSR correction for satellite orbits/clocks was small, but in the case of ionospheric delay compensation, the use of SBAS correction information provided more than twice the accuracy compared to result of the Klobuchar model. With GPS and GLONASS, both the BDS and GALILEO constellations will be fully deployed in the end of 2020, and the greater benefits from the multi-GNSS integration can be expected. Specially, If RT-ionospheric correction services reflecting regional characteristics and SSR correction information reflecting atmospheric characteristics are carried out in real-time, expected that the utilization of SF-RT-PPP survey technology by multi-GNSS and various demands will be created in various industrial sectors.