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    ARTICLE

    A Modeling Method for Predicting the Strength of Cemented Paste Backfill Based on a Combination of Aggregate Gradation Optimization and LSTM

    Bo Zhang1,2, Keqing Li1,2, Siqi Zhang1,2, Yafei Hu1,2, Bin Han1,2,*

    Journal of Renewable Materials, Vol.10, No.12, pp. 3539-3558, 2022, DOI:10.32604/jrm.2022.021845

    Abstract Cemented paste backfill (CPB) is a sustainable mining technology that is widely used in mines and helps to improve the mine environment. To investigate the relationship between aggregate grading and different affecting factors and the uniaxial compressive strength (UCS) of the cemented paste backfill (CPB), Talbol gradation theory and neural networks is used to evaluate aggregate gradation to determine the optimum aggregate ratio. The mixed aggregate ratio with the least amount of cement (waste stone content river sand content = 7:3) is obtained by using Talbol grading theory and pile compactness function and combined with experiments. In addition, the response… More > Graphic Abstract

    A Modeling Method for Predicting the Strength of Cemented Paste Backfill Based on a Combination of Aggregate Gradation Optimization and LSTM

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