• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.291-295
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• 2022

This paper deal with the advanced thchnology of water supply line breakege detection system in singsan green city. the technology apply for construction eco oriented high-tech city to merge residant, industial, tour reasure parts for songsan green city furture direction achivement and response for a life style change of people in the city. Breakege detection system consist of smart prevention seat, pipeline breakege detection sensor, analysis software, server. etc.. Central control unit sent the data to hwa sung city water supply office by WCDMA in SKY. the data are states about water supply pipeline, Location.etc. This system maintain the long term life cycle of water supply plpeline by the prevention the leakege event through ackonwledge information of evnet occurrence locaion. and used to realtime sense method about demage information of the pipeline and prevent to brekege facilities during excavation work.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.463-481
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• 2020

Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R² of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.

• Tunnel and Underground Space
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• v.33 no.5
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• pp.339-347
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• 2023

As the jacks provide a thrust force on the inclined surface, bending deformations by a side force occur in the pedestal and rod parts. This can induce disorder or degradation of the thrust module, buckling stability on the inclined compression condition should be clarified to secure the reliability of shield TBM. For analyzing the stability, a buckling testing method for hydraulic cylinder was investigated and compression testing system was installed. Before the test, a numerical analysis was conducted to check the stress concentration parts. The maximum allowable force was loaded on the cylinder specimen at 0 degree surface condition as a preliminary test. After the test, plastic deformations or hydraulic leakage was not observed. The static stability of it was verified at 0 degree condition.

• Journal of the Korean Geotechnical Society
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• v.39 no.12
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• pp.103-114
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• 2023

Monitoring the site of an underground construction wall is crucial to confirm the stability of the supports and ground due to excavation. In particular, it is essential to maintain the accuracy of a load cell gauge, which identifies the load of the support transmitted from the excavated ground. However, research on verification methods and regulations that can identify the accuracy of load cell gauges at construction sites is inadequate, which is a problem as load cell gauges are installed without proper performance inspections. In this study, performance tests were conducted by a complete investigation of load cell gauges sold in Korea and comparing them with foreign products to determine defect causes. In addition, the criteria for selecting a load cell gauge were presented, and the results of this study were considered to help select a highly reliable load cell gauge.

• Geomechanics and Engineering
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• v.37 no.1
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• pp.49-64
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• 2024

Rocks undergoing repeated loading and unloading over an extended period, such as due to earthquakes, human excavation, and blasting, may result in the gradual accumulation of stress and deformation within the rock mass, eventually reaching an unstable state. In this study, a CNN-CCM is proposed to address the mechanical behavior. The structure and hyperparameters of CNN-CCM include Conv2D layers × 5; Max pooling2D layers × 4; Dense layers × 4; learning rate=0.001; Epoch=50; Batch size=64; Dropout=0.5. Training and validation data for deep learning include 71 rock samples and 122,152 data points. The AI Rock Constitutive Model learned by CNN-CCM can predict strain values(ε₁) using Mass (M), Axial stress (σ₁), Density (ρ), Cyclic number (N), Confining pressure (σ₃), and Young's modulus (E). Five evaluation indicators R², MAPE, RMSE, MSE, and MAE yield respective values of 0.929, 16.44%, 0.954, 0.913, and 0.542, illustrating good predictive performance and generalization ability of model. Finally, interpreting the AI Rock Constitutive Model using the SHAP explaining method reveals that feature importance follows the order N > M > σ₁ > E > ρ > σ₃.Positive SHAP values indicate positive effects on predicting strain ε₁ for N, M, σ₁, and σ₃, while negative SHAP values have negative effects. For E, a positive value has a negative effect on predicting strain ε₁, consistent with the influence patterns of conventional physical rock constitutive equations. The present study offers a novel approach to the investigation of the mechanical constitutive model of rocks under cyclic loading and unloading conditions.

• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.6-22
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• 2022

In this paper classifies the types of 228 anchor stones discharged from the west and south coasts, assumes a combined method by type, routes through discharge locations, and It attempted to estimate the burial site. Prior to classification of types, the weight, thickness, width, and length of the anchor stone were measured, and the largest Young in the tomb The scent weight was classified into I~V groups, and the shape of the anchor stone was classified into 1-6 types. All of these weight and shape correlations It was classified into 17 types. The combined method by type is 180kg or less depending on the morphological characteristics of the reference value of the extracted anchor stone, and the type An anchor of type 1 or 2 is used in combination with an anchor, and a anchor of type 3 or 6 weighs more than 180kg and is combined with an anchor The dragon was assumed to be an anchor. Along with this, the route and burial site are identified through past records and testimony of local residents It was checked against the data. The route was largely consistent with past records, but the new route was apparent in waters near the island or inland It was also drawn. In the case of burial sites, small and large in Taean Mado Sea and Jindo Byeokpajin Sea, where anchor stones are concentrated, Considering the pattern of the type anchor stones being discharged, it was consistent with the testimony that ships of various sizes were mysterious in the two seas. Based on this type classification, a study on the spatiality of the anchors was conducted. First, a comparison and analysis was done on whether actual real data, such as anchor stones, old ships, and relics, were identified on the Joun-ro route and international trade routes as recorded in the past literature. Where there was no record, the route was estimated based on real data. To this end, routes estimated based on the testimony of local residents and modern ship workers were analyzed as to whether ships traveled there in the past and whether they could actually sail. Next, the location of each seedling was estimated by ship size according to the weight of the anchor stone. In the case of the Taean Mado Sea and Jindo Byeokpajin Sea, both small and large anchor stones were discharged from the coastline and were far away.

• Journal of the Korean Geotechnical Society
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• v.15 no.4
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• pp.99-112
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• 1999

When there exists a fault zone ahead of the tunnel face and a tunnel is excavated without perceiving its existence, it will cause stress concentration in the region between the tunnel face and the fault zone because of the influence of the fault zone on the arching phenomena. Because the underground structure has many unreliable factors in the design stage, the prediction of a fault zone ahead of the tunnel face by monitoring plans during tunnel construction and the rapid establishment of appropriate support system are required for more economical and safer tunnel construction. Recent study shows that longitudinal displacement changes during excavation due to the change of rock property, and if longitudinal displacement and settlement, which are measured in the field, are considered together in displacement analysis, the prediction of change in rock mass property is possible. This study provided the method for the prediction of fault zones by analyzing the changes of L/C and (Ll-Lr)/C ratio (L= longitudinal displacement at crown, C = settlement at crown, Ll = longitudinal displacement at left sidewall, Lr = longitudinal displacement at right sidewall) and the stereographic projection of displacement vectors which were obtained from the 3-D numerical analysis of hybrid method in various initial stress conditions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.4
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• pp.327-343
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• 2004

During tunnel construction, ground failures often occur due to existence of weak zones, such as faults, joints, and cavities, ahead of tunnel face. It is hard to detect effectively weak zones, which can lead underground structure to fail after excavation and before supporting, by using conventional characterization methods. In this study, an enhanced analytical method of predicting weak zones ahead of tunnel face is developed to overcome some problems in the conventional geophysical exploration methods. The analytical method is based on Coulomb's and Gauss' laws with considering the characteristics of electric fields subjected to rock mass. Using the developed method, closed form solutions are obtained to detect a spherical shaped zone and an oriented fault ahead of tunnel face respectively. The analytical results suggest that the presence of weak zones and their sizes, location, and states can be accurately predicted by combining a proper inversion process with resistance measured from several electrodes on the tunnel face. It appears that the skin depth or resistivity in rock mass is affected by the diameter of tunnel face, natural electric potential and noises induced by experimental measurement and spatial distribution of uncertain properties. The developed analytical solution is verified through experimental tests. About 1800 concrete blocks of 5cm by 5cm by 5cm in size are prepared and used to model a joint rock mass around tunnel face. Weak zones are simulated ahead of tunnel face with a material which has relatively higher conductivity than concrete blocks. Experimental results on the model test show a good agreement with analytical results.

• Journal of the Korean GEO-environmental Society
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• v.19 no.3
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• pp.35-45
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• 2018

It is essential to predict ground conditions ahead of the tunnel face during tunnel excavation. Various studies on tunnel prediction method of the ground condition ahead of the tunnel face have already been done and applied to in mechanized tunnelling job sites. So, all the methods used in mechanized tunnelling to predict ground conditions ahead of the tunnel face were reviewed. A questionnaire surveying Tunnel Boring Machine (TBM) operators with at least 10 years' experience in TBM operation was used to determine the requirements for prediction methods as well as the distance from the tunnel face that must be assessed. Based on the result of questionnaire survey, the most feasible prediction methods applicable to mechanized tunnelling job-sites are suggested. One of the prediction methods applicable to mechanized tunnelling job-sites might be the electrical resistivity survey by utilizing the disk cutter on the cutterhead as electrode. So, in this study, laboratory tests were performed to evaluate the feasibility of prediction method utilizing electrical resistivity survey at mechanized tunnelling job-sites. It was found that geological condition ahead of 0.3 times of TBM's diameter from tunnel face could be predicted.

• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.1
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• pp.69-79
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• 2008

Prediction of ground condition ahead of tunnel face might be the most important factor to prevent collapse during tunnel excavation. In this study, a non-destructive method to evaluate the phase velocity in model rock mass using wavelet transform of surface wave was proposed aiming at ground condition assessment ahead of tunnel face. Model tests using gypsum as a rocklike material composed of two layers were performed. A Piezoelectric actuator with frequencies ranging from 150 Hz to 5 kHz was selected as a harmonic source. The acceleration history was measured with two accelerometers. Wavelet transform analysis was used to obtain the dispersion curves from the measured data. The experimental results showed that the near-field effects can be neglected if the distance between two receivers is chosen to be three times the wavelength. A simple inversion method using weighted factor based on the normal distribution was proposed. The inversion results showed that the predicted phase velocity agreed reasonably well with the measured one when the wavelength influence factor was 0.2. The depth of propagation of surface wave was from 0.42 to 0.63 times the wavelength. The range of wavelength varying with phase velocity in dispersion curve matched well with that estimated by inversion technique.