Abstract
In order to achieve a successful cemented paste backfill (CPB) mixture design, multiple project requirements such as strength, flowability and cost should be met. For this achievement, the key design parameters, solid content (SD) and cement percentage (C), should be well adjusted. With increasing the amount of cement in the mixture, CPB strength and production cost increase together, whereas the workability decreases. In order to reduce the cost, more tailings can be added while keeping the cement amount the same but this will reduce both strength and workability. Therefore, CPB design is in fact a multi-objective optimisation problem. In this study, the particle swarm optimisation (PSO) algorithm is used to design CPB mixture meeting multiple objectives. PSO identifies the optimum set of SD and C yielding in desired strength and workability with a minimum cost. The proposed workflow can be a useful and practical for multiple decision making where CPB designers face strength-workability-cost paradox. In addition to reducing the number of trial experiments, the multi objective mixture design of CPB also provides the optimum use of materials to reduce the incurred costs and ensure cleaner and more sustainable production.
| Original language | English |
|---|---|
| Article number | 106385 |
| Journal | Minerals Engineering |
| Volume | 153 |
| DOIs | |
| Publication status | Published - 1 Jul 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 12 Responsible Consumption and Production
Fingerprint
Dive into the research topics of 'Multi-objective mixture design of cemented paste backfill using particle swarm optimisation algorithm'. Together they form a unique fingerprint.Research output
- 55 Citations
- 1 Doctoral Thesis
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The design optimisation of cementitious mixtures using artificial intelligence algorithms for sustainable mining and construction projects
Sadrossadat, E., 2022, (Unpublished)Research output: Thesis › Doctoral Thesis
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