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  1. Article ; Online: Real-Time Prediction of Operating Parameter of TBM during Tunneling

    Hang-Lo Lee / Ki-Il Song / Chongchong Qi / Jin-Seop Kim / Kyoung-Su Kim

    Applied Sciences, Vol 11, Iss 2967, p

    2021  Volume 2967

    Abstract: With the increasing use of the tunnel boring machine (TBM), attempts have been made to predict TBM operating parameters. Prediction of operating parameters is still an important step in the adaptability of the TBM for the future. In this study, we employ ...

    Abstract With the increasing use of the tunnel boring machine (TBM), attempts have been made to predict TBM operating parameters. Prediction of operating parameters is still an important step in the adaptability of the TBM for the future. In this study, we employ a walk forward (WF) prediction method based on ARIMAX, which can consider time-varying features and geological conditions. This method is applied to two different TBM projects to evaluate its performance, and is then compared with WF based on ordinary least squares (OLS). The simulation results show that the ARIMAX predictor outperforms the OLS predictor in both projects. For practical applications, an additional analysis is carried out according to the real-time prediction distance. The results show that time series-based ARIMAX provides meaningful results in 8 rings (11 m) or less of real-time prediction distance. The WF based on ARIMAX can provide reasonable TBM operating conditions with time-varying data and can be utilized in decision-making to improve excavation performance.
    Keywords real-time prediction ; operating parameter ; TBM ; ARIMAX ; walk forward ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 006
    Language English
    Publishing date 2021-03-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Ensemble Learning Approach for the Prediction of Quantitative Rock Damage Using Various Acoustic Emission Parameters

    Hang-Lo Lee / Jin-Seop Kim / Chang-Ho Hong / Dong-Keun Cho

    Applied Sciences, Vol 11, Iss 4008, p

    2021  Volume 4008

    Abstract: Monitoring rock damage subjected to cracks is an important stage in underground spaces such as radioactive waste disposal repository, civil tunnel, and mining industries. Acoustic emission (AE) technique is one of the methods for monitoring rock damage ... ...

    Abstract Monitoring rock damage subjected to cracks is an important stage in underground spaces such as radioactive waste disposal repository, civil tunnel, and mining industries. Acoustic emission (AE) technique is one of the methods for monitoring rock damage and has been used by many researchers. To increase the accuracy of the evaluation and prediction of rock damage, it is required to consider various AE parameters, but this work is a difficult problem due to the complexity of the relationship between several AE parameters and rock damage. The purpose of this study is to propose a machine learning (ML)-based prediction model of the quantitative rock damage taking into account of combined features between several AE parameters. To achieve the goal, 10 granite samples from KAERI (Korea Atomic Energy Research Institute) in Daejeon were prepared, and a uniaxial compression test was conducted. To construct a model, random forest (RF) was employed and compared with support vector regression (SVR). The result showed that the generalization performance of RF is higher than that of SVR RBF . The R 2 , RMSE, and MAPE of the RF for testing data are 0.989, 0.032, and 0.014, respectively, which are acceptable results for application in laboratory scale. As a complementary work, parameter analysis was conducted by means of the Shapley additive explanations (SHAP) for model interpretability. It was confirmed that the cumulative absolute energy and initiation frequency were selected as the main parameter in both high and low-level degrees of the damage. This study suggests the possibility of extension to in-situ application, as subsequent research. Additionally, it provides information that the RF algorithm is a suitable technique and which parameters should be considered for predicting the degree of damage. In future work, we will extend the research to the engineering scale and consider the attenuation characteristics of rocks for practical application.
    Keywords rock damage ; acoustic emission ; random forest ; support vector regression ; SHAP ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Subject code 600
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  3. Article ; Online: Real-Time Location Tracking of Multiple Construction Laborers

    Jin-Sun Lim / Ki-Il Song / Hang-Lo Lee

    Sensors, Vol 16, Iss 11, p

    2016  Volume 1869

    Abstract: A real-time location (RTL) system was developed to improve safety for multiple laborers in confined construction sites. The RTL system can monitor the location and movement of multiple laborers in real time. A portable RTL system with a low-battery mode ... ...

    Abstract A real-time location (RTL) system was developed to improve safety for multiple laborers in confined construction sites. The RTL system can monitor the location and movement of multiple laborers in real time. A portable RTL system with a low-battery mode was developed to accommodate various constraints in the construction site. A conventional RTL system that uses radio signal strength indicators (RSSIs) has high error, so an accelerometer with Bluetooth Low Energy (BLE) was added, and a calculation process is suggested. Field tests were performed for validation in underground construction and bridge overlay sites. The results show that the accelerometer and BLE can be used as effective sensors to detect the movement of laborers. When the sensor is fixed, the average error ranges 0.2–0.22 m, and when the sensor is moving, the average error ranges 0.1–0.47 m.
    Keywords construction site ; RTL system ; radio signal strength indicator ; accelerometer ; Technology (General) ; T1-995 ; Technology ; T ; Analytical chemistry ; QD71-142 ; Chemistry ; QD1-999 ; Science ; Q ; Chemical technology ; TP1-1185
    Subject code 690
    Language English
    Publishing date 2016-11-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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