Techno Press
You logged in as Techno Press

Geomechanics and Engineering
  Volume 26, Number 3, August10 2021 , pages 235-251

Data-driven framework for predicting ground temperature during ground freezing of a silty deposit
Khanh Pham, Sangyeong Park, Hangseok Choi and Jongmuk Won

    Predicting the frozen zone near the freezing pipe in artificial ground freezing (AGF) is critical in estimating the efficiency of the AGF technique. However, the complexity and uncertainty of many factors affecting the ground temperature cause difficulty in developing a reliable physical model for predicting the ground temperature. This study proposed a data-driven framework to accurately predict the ground temperature during the operation of AGF. Random forest (RF) and extreme gradient boosting (XGB) techniques were employed to develop the prediction model using the dataset of a field experiment in the silty deposit. The developed ensemble models showed relatively good performance (R2 > 0.96), yet the XGB model showed higher accuracy than the RF model. In addition, the evaluated mutual information and importance score revealed that the environmental attributes (ambient temperature, surface temperature, humidity, and wind speed) can be critical in predicting ground temperature during the AFG operation. The prediction models presented in this study can be utilized in evaluating freezing efficiency at the range of geotechnical and environmental attributes.
Key Words
    artificial ground freezing; data-driven framework; extreme gradient boosting; mutual information; random forest
Khanh Pham: 1.) Department of Civil Engineering, International University, Ho Chi Minh City, Vietnam
2.) Vietnam National University, Ho Chi Minh City, Vietnam

Sangyeong Park and Hangseok Choi: School of Civil, Environmental, & Architectural Engineering, Korea University, Seoul, 02841, Republic of Korea

Jongmuk Won: Department of Civil and Environmental Engineering, University of Ulsan, Ulsan, 44610, Republic of Korea

Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2023 Techno Press
P.O. Box 33, Yuseong, Daejeon 305-600 Korea, Tel: +82-42-828-7996, Fax : +82-42-828-7997, Email: