Cement Take Evaluation and Prediction based on Empirical Relationships and Support Vector Regression
- DOI
- 10.2991/iceep-16.2016.120How to use a DOI?
- Keywords
- Cement take, Permeability, Transmissivity, Rock quality classification, Support vector regression (SVR)
- Abstract
Cement grouting is a common method to improve the dam foundation, however, the cement take needed for improvement is difficult to evaluate because of the complexity of the rock foundation and the uncertainty of the influence factors. Although grouting design depends largely on the permeability of the dam foundation, due to the anisotropy of the hydraulic paths and various flow properties of water and grout, it is difficult to obtain a direct relationship between the Lugeon values and the cement takes. In this paper, the cement take is evaluated by considering rock quality classification, Lugeon value and transmissivity as the influencing parameters. Simple and multivariate regression analysis are used to research the correlation of the cement take and the parameters, results indicate general correlations but low or moderate correlative coefficients. Additionally, support vector regression method is utilized to predict the cement take, the correlative coefficients become higher than the previous results, but the goodness of fitting is not very high. It seems that more research need to understanding the influencing mechanism of the cement takes.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Guichao Fan AU - Denghua Zhong AU - Jiajun Wang AU - Bingyu Ren PY - 2016/11 DA - 2016/11 TI - Cement Take Evaluation and Prediction based on Empirical Relationships and Support Vector Regression BT - Proceedings of the 2016 5th International Conference on Energy and Environmental Protection (ICEEP 2016) PB - Atlantis Press SP - 699 EP - 704 SN - 2352-5401 UR - https://doi.org/10.2991/iceep-16.2016.120 DO - 10.2991/iceep-16.2016.120 ID - Fan2016/11 ER -