Machine-Learning Aided Design for Cemented Paste Backfill

Chongchong Qi

Research output: ThesisDoctoral Thesis

241 Downloads (Pure)

Abstract

Cemented paste backfill (CPB) technology is a promising way to substantially alter the way mine tailings are managed. At present, CPB design is mainly experiment-based, which is labour-intensive and time-consuming. Towards this end, a state­of-the-art concept for CPB design is proposed in this thesis, namely machine-learning aided design for CPB (MLAD_CPB). The methodology of MLAD_CPB is presented and its feasibility is validated through three example applications. This thesis presents a number of advances in CPB design, which, with further consolidation and refinement, may become important tools in predicting process parameters starting from constituent materials of CPB.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Award date3 Oct 2019
DOIs
Publication statusUnpublished - 2019

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