ORCID Profile
0000-0003-4064-2158
Current Organisation
Inha University
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Publisher: Elsevier BV
Date: 08-2018
Publisher: Hindawi Limited
Date: 2018
DOI: 10.1155/2018/4751612
Abstract: To investigate the mechanical properties and energy evolution characteristics of sandstone depending on the water contents and confining pressure, the uniaxial and triaxial tests were conducted. The test results show that the strain energy was stored in the sandstone s les at the prepeak stage, and that is suddenly released when the failure occurred, and energy dissipation is sharply increased at the postpeak stage. The damage and energy dissipation characteristics of the s les are observed clearly under the stepwise loading and unloading process. The critical strain energy and energy dissipation show a clear exponential relationship. The critical elastic energy decreases linearly as the water content increases. As the confining pressure increases, the critical elastic energy of the s les transforms from linear to exponential. The concept of energy enhancement factor is proposed to characterize the strengthening effect induced by the confining pressure on the energy storage capacity of the rock s les. The energy evolution of the sandstone s les is more sensitive to the confining pressure than that of the water content.
Publisher: Elsevier BV
Date: 06-2019
Publisher: Elsevier BV
Date: 03-2020
Publisher: Elsevier BV
Date: 07-2019
Publisher: MDPI AG
Date: 26-03-2021
DOI: 10.3390/APP11072967
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.
Location: Korea, Republic of
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