• Journal of Conservation Science
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• v.35 no.2
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• pp.99-115
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• 2019

The Royal Tombs at Songsanri is one of the most important historic site for ancient historical study in Korean Peninsula. Since the excavation of the tombs, continuous exposure to the outside environment and the negative effects of the artificial air conditioning system have caused significant threats to the thermal environment stability of the tombs. Unlike the outside temperature that shows significant differences according to seasonal changes, the burial chamber of the tombs had a relatively stable temperature range of 11.4 to $22.2^{\circ}C$ throughout the year, and the standard deviation of temperature was within 3.5. It was revealed that major factors affecting the microclimate of the tombs were inflow of outdoor air, wind direction and speed, and all of them had closely related to airtightness of the tombs. The solar radiation was in inverse proportion to the thickness of burial mounds, and thus Royal Tomb of King Muryeong, which has the thickest burial mound, was least affected by solar radiation. Especially, microclimate of the tombs caused to the highest influence with artificial environmental changes due to access by people, which varied in proportion to the number of accessed people and time of stay. Currently, the inside of the tombs are sealed and always in saturated condition, it is very vulnerable to dew condensation. As a result of analyzing the possibility of condensation in each tomb, all the tomb No. 5, tomb No. 6 and Royal Tomb of King Muryeong had condensation most of the time throughout the year. It is required to make a proper conservation environment for the Royal Tombs at Songsanri.

• Explosives and Blasting
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• v.38 no.4
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• pp.16-25
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• 2020

Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.262-269
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• 2005

Since the buried cultural relics are three-dimensional (3-D) objects in nature, 3-D survey is more preferable in archeological exploration. 3-D Ground Penetrating Radar (GPR) survey based on very dense data in principle, however, might need much higher cost and longer time of exploration than other geophysical methods commonly used for the archeological exploration, such as magnetic and electromagnetic methods. We developed a small-scale continuous data acquisition system which consists of two sets of GPR antennas and the precise positioning device tracking the moving-path of GPR antenna automatically and continuously. Since the high cost of field work may be partly attributed to establishing many profile lines, we adopted a concept of data acquisition at arbitrary locations not along the pre-established profile lines. Besides this hardware system, we also developed several software packages in order to effectively process and visualize the 3-D data obtained by the developed system and the data acquisition concept. Using the developed system, we performed 3-D GPR survey to investigate the possible historical remains of Baekje Kingdom at Buyeo city, South Korea, prior to the excavation. Owing to the newly devised system, we could obtain 3-D GPR data of this survey area having areal extent over about $17,000m^2$ within only six-hours field work. Although the GPR data were obtained at random locations not along the pre-established profile lines, we could obtain high-resolution 3-D images showing many distinctive anomalies, which could be interpreted as old agricultural lands, waterways, and artificial structures or remains. This cast: history led us to the conclusion that 3-D GPR method is very useful not only to examine a small anomalous area but also to investigate the wider region of the archeological interests.

• Journal of Conservation Science
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• v.34 no.5
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• pp.333-343
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• 2018

This study was conducted to evaluate the conservation environment by monitoring temperature and humidity for two years and mapping the remaining pigments of mural paintings to diagnose the conservation state of mural paintings of Royal Tombs in Neungsan-ri. We evaluated the characteristics of condensation in the tomb. Compared with the results of a 2008 survey, we conducted state change of mural paintings in the tomb. The temperature in the main room, which has an annual average soil temperature distribution at 5 m depth in Korea, is maintained at $13{\sim}18^{\circ}C$. The temperature range of the main room was between less than $0.1^{\circ}C$ to $0.5^{\circ}C$, and the diurnal variation of temperature between summer (June to September) and winter (December to January) is the greatest. Condensation is more concentrated in the summer because the outdoor air was typically at higher temperatures than the main room inflows in the tomb. Mapping the remaining pigment composition and particle distribution of mural paintings showed that it was in the range of 36.72~39.53% of the wall area. The pigment range was confirmed to be the same as it was in 2008, through ultraviolet fluorescence reaction and infrared ray investigation. Therefore, the underground environment that receives dew condensation in the summer has been stable since 2008. However, continuous monitoring is needed because the deterioration of mural painting proceeds considerably after excavation and only a small percentage of the pigments survive.