A Novel Prediction Model of Strength of Paste Backfill Prepared from Waste-Unclassified Tailings

• Published in: Advances in materials science and engineering 2019, Vol.2019 (2019), p.1-10
• Main Authors: Li, Junhong, Zhang, Xiaoqiang, Wu, Shunchuan, Cheng, Haiyong
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Backfill; Cement; Chemical elements; Clay; Concrete; Experiments; Filling; Hydration; Mining engineering; Packing density; Particle size; Physical properties; Rheology; Slurries; Strength; Sustainable development; Tailings; Water-cement ratio
• ISSN: 1687-8434; 1687-8442
• DOI: 10.1155/2019/3574190

Paste backfilling is an important support for the development of green mines and deep mining. It can effectively reduce a series of risks of underground goaf and surface tailings ponds. Reasonable strength of backfill is an effective guarantee for controlling ground stress and realizing safe mining function. Under the combination of complex materials and local conditions, ensuring the optimal design and effective proportion for paste backfill strength is the bottleneck problem that restricts the safety, economy, and efficiency of filling mining. The strength developing trend of paste backfilling prepared from waste rock and unclassified tailings has been studied. Different levels of cement contents, tailings-waste ratios, and slurry concentrations were investigated through orthogonal design to obtain the relationship between the UCS and the multi-influential factors. Combined with the experimental results and the previous strength prediction models, the waste rock-unclassified tailings paste strength prediction model was proposed. Introducing the water-cement ratio, the cement-tailings ratio, the amount of cement, and the packing density that characterizing the overall gradation of unclassified tailings and waste rock, as well as the curing time, a strength prediction model of multifactors was developed. Moreover, the microscopic structure of the paste prepared from waste-unclassified tailings was analyzed with an Environment Scanning Electron Microscope (ESEM), and the influence mechanism was ascertained. The weight coefficient of strength development is carded in this paper, and the strength model of unclassified tailings-waste paste considering five factors is obtained, which is of great significance to guide the mining engineering.