Optimal Backfilling Materials with High Compressive Strength Based on Multiple Linear Regression - Mining, Metallurgy & Exploration (2023)
- Organization:
- Society for Mining, Metallurgy & Exploration
- Pages:
- 9
- File Size:
- 698 KB
- Publication Date:
- Oct 3, 2023
Abstract
Backfilling material such as tailing (mine wastes) mixing with cement or gypsum has grown throughout the world’s underground
mines. However, despite their growing popularity, the typical hydraulic and mechanical fill types utilized in many
mines still exist. Deep underground mining has increased due to the lack of commercial minerals nearby. Mine wastes were
considered the main part of backfilling to prevent environmental pollution, ground subsidence after mine abandonment, and
mine collapse during deeper extraction phases. The cemented backfill technique is the principal technique used in underground
mines, which include cement with fly ash and/or filter dust, cement with tailing material and fly ash, gypsum with
fly ash, and synthetic anhydrite with fly ash and have been reviewed. It has concluded that a backfilling material must be
selected based on further goals, available material near the mine site, and economic factors. This paper analyzes different
backfill material mixtures to create a technique that will increase safety in underground mining conditions and foresees an
appropriate formula that gives high uniaxial compressive strength. The multiple linear regression (MLR) on the collected
data from the experimental works to construct the relationship between the uniaxial compressive strength (UCS) of the mixture
and the components of the backfilling and the prediction formula for expected compressive strength was obtained. The
results revealed that the predicted regression equation was robust and reliable to predict the (UCS) for the new components
of the filling (cement (CE), filter dust (FD), water content (WC), and time (T)).
Citation
APA: (2023) Optimal Backfilling Materials with High Compressive Strength Based on Multiple Linear Regression - Mining, Metallurgy & Exploration (2023)
MLA: Optimal Backfilling Materials with High Compressive Strength Based on Multiple Linear Regression - Mining, Metallurgy & Exploration (2023). Society for Mining, Metallurgy & Exploration, 2023.