| Issue |
E3S Web Conf.
Volume 350, 2022
International Conference on Environment, Renewable Energy and Green Chemical Engineering (EREGCE 2022)
|
|
|---|---|---|
| Article Number | 01013 | |
| Number of page(s) | 8 | |
| Section | Green Chemical Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202235001013 | |
| Published online | 09 May 2022 | |
Ae-Based Failure Warning Mechanism During Cemented Paste Backfilling: Experimental Investigation
1
School of Resources and Safety Engineering, Central South University, Changsha 410083, Hunan, China
2
Center for Advanced Studies, Central South University, Changsha 410083, Hunan, China
* Corresponding author: csuwangzihe@163.com
To research the AE warning mechanism of cemented paste backfilling (CPB), the uniaxial compression test with AE monitoring was carried out on CPB. The effects of different moisture content, cement proportion, and loading rate on AE characteristics of CPB were analyzed. And a damage model based on AE is established. The results show that the increase of water content, gypsum content, and loading rate can enhance the ductility of CPB and lengthen the AE warning area. However, the increase of moisture content will lead to the delay of AE signal peak, which is bad for the early warning. With the increase of loading rate, the failure mode of specimens gradually changes from splitting failure to shear failure. The cracks produced under different failure modes can correspond to the peaks of AE signals. The damage model based on AE shows that the damage process of CPB samples can be divided into three stages, linear-exponential-linear. The experimental results can further research the optimal conditions for ae monitoring of backfill, and provide a theoretical basis for ae monitoring and warning of backfill.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.