Abstract
Failure evolution of cemented paste backfill (CPB) is crucial to the stope stability in the mining industry. While many effects have been done on the strength requirement and macroscopic deformation behaviors of CPB, the mesoscopic failure mechanism is not yet well understood. In this work, a uniaxial compressive test on the CPB sample from Lilou iron mining was conducted under topographic monitoring using a 450-kV industrial X-ray computed tomography (CT). A specific self-developed loading device was used to match the CT machine to realize the real-time CT scanning. A series of 2D CT images were obtained by carrying out CT scanning at seven stages throughout sample deformation and from different positions in the sample. Clear CT images, CT value analysis, and void identification and extraction reveal that the sample experiences compression, damage, crack initiation, crack propagation, crack coalescence, and collapse stages. Besides, a damage constitutive equation is proposed first using the CT data, which can be used to predict the stress strain response of CPB. What is more, volumetric dilatancy characteristics caused by the damage and cracking behavior are investigated from the stress strain curve and the CT images, the result reveals the influence of localization deformation on the failure evolution of CPB. Through a series of meso-structural changes analysis, the meso-mechanisms of failure evolution in CPB have been first documented.
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Acknowledgements
The authors would like to thank the editors and the anonymous reviewers for their helpful and constructive comments.
Funding
This study was supported by the National Key Technologies Research & Development Program (2018YFC0808402, 2018YFC0604601), the Fundamental Research Funds for the Central Universities (2302017FRF-TP-17-027A1), and National Natural Science Foundation of China (Grants Nos. 41502294).
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Wang, Y., Liu, D. & Hu, Y. Monitoring of internal failure evolution in cemented paste backfill under uniaxial deformation using in-situ X-ray computed tomography. Arab J Geosci 12, 138 (2019). https://doi.org/10.1007/s12517-019-4285-4
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DOI: https://doi.org/10.1007/s12517-019-4285-4