对煅烧硬质高岭土对铅锌矿溢流尾砂胶结膏体充填材料抗压强度的影响进行了研究。研究结果表明:当胶结剂中煅烧硬质高岭土(Calcined Hard Kaolin,CHK)取代水泥率从0增加到30%时,胶结膏体充填材料(Cemented Paste Backfill,CPB)28d抗压强...对煅烧硬质高岭土对铅锌矿溢流尾砂胶结膏体充填材料抗压强度的影响进行了研究。研究结果表明:当胶结剂中煅烧硬质高岭土(Calcined Hard Kaolin,CHK)取代水泥率从0增加到30%时,胶结膏体充填材料(Cemented Paste Backfill,CPB)28d抗压强度基本保持不变;当CHK取代水泥率从30%增加到80%时,CPB的28d抗压强度急剧降低;当CHK取代水泥率低于50%的CPB养护到28d或56d后,其抗压强度大幅度降低;当CHK取代水泥率为50%的CPB养护到180d时,其抗压强度呈增长趋势。CPB抗压强度损失与其内部形成膨胀性物质(石膏)有关。当CHK取代水泥率为50%时,由于降低了胶结剂中水泥熟料的量,CHK中偏高岭土(Metakaolin,MK)和水泥水化产物氢氧化钙的火山灰反应解除或减少了膨胀性二水石膏的形成,结果CPB的180d抗压强度呈增长趋势。展开更多
To reduce the difficulty of obtaining the unconfined compressive strength(UCS) value of fiber-reinforced cemented paste backfill(CPB) and analyze the comprehensive impact of conventional and fiber variables on the com...To reduce the difficulty of obtaining the unconfined compressive strength(UCS) value of fiber-reinforced cemented paste backfill(CPB) and analyze the comprehensive impact of conventional and fiber variables on the compressive property, a new artificial intelligence model was proposed by combining a newly invented meta-heuristics algorithm(salp swarm algorithm, SSA) and extreme learning machine(ELM) technology. Aiming to test the reliability of that model, 720 UCS tests with different cement-to-tailing mass ratio, solid mass concentration, fiber content, fiber length, and curing time were carried out, and a strength evaluation database was collected. The obtained results show that the optimized SSA-ELM model can accurately predict the uniaxial compressive strength of the fiber-reinforced CPB, and the model performance of SSA-ELM model is better than ANN, SVR and ELM models. Variable sensitivity analysis indicates that fiber content and fiber length have a significant effect on the UCS of fiber-reinforced CPB.展开更多
文摘对煅烧硬质高岭土对铅锌矿溢流尾砂胶结膏体充填材料抗压强度的影响进行了研究。研究结果表明:当胶结剂中煅烧硬质高岭土(Calcined Hard Kaolin,CHK)取代水泥率从0增加到30%时,胶结膏体充填材料(Cemented Paste Backfill,CPB)28d抗压强度基本保持不变;当CHK取代水泥率从30%增加到80%时,CPB的28d抗压强度急剧降低;当CHK取代水泥率低于50%的CPB养护到28d或56d后,其抗压强度大幅度降低;当CHK取代水泥率为50%的CPB养护到180d时,其抗压强度呈增长趋势。CPB抗压强度损失与其内部形成膨胀性物质(石膏)有关。当CHK取代水泥率为50%时,由于降低了胶结剂中水泥熟料的量,CHK中偏高岭土(Metakaolin,MK)和水泥水化产物氢氧化钙的火山灰反应解除或减少了膨胀性二水石膏的形成,结果CPB的180d抗压强度呈增长趋势。
基金financial supports from the National Natural Science Foundation of China (51874350,41807259)the National Key Research and Development Program of China (2017YFC0602902)+1 种基金the Fundamental Research Funds for the Central Universities of Central South University of China (2018zzts217)the Innovation-Driven Project of Central South University of China (2020CX040)。
文摘To reduce the difficulty of obtaining the unconfined compressive strength(UCS) value of fiber-reinforced cemented paste backfill(CPB) and analyze the comprehensive impact of conventional and fiber variables on the compressive property, a new artificial intelligence model was proposed by combining a newly invented meta-heuristics algorithm(salp swarm algorithm, SSA) and extreme learning machine(ELM) technology. Aiming to test the reliability of that model, 720 UCS tests with different cement-to-tailing mass ratio, solid mass concentration, fiber content, fiber length, and curing time were carried out, and a strength evaluation database was collected. The obtained results show that the optimized SSA-ELM model can accurately predict the uniaxial compressive strength of the fiber-reinforced CPB, and the model performance of SSA-ELM model is better than ANN, SVR and ELM models. Variable sensitivity analysis indicates that fiber content and fiber length have a significant effect on the UCS of fiber-reinforced CPB.