Blasting is a widely used technique for rock fragmentation in surface mines and tunneling projects. The ground vibrations produced by blasting operations are the main concern for the industries undertaking blasting operations, which can damage the surrounding structures, adjacent rock masses, roads and slopes in the vicinity. Therefore, proper prediction of blast-induced ground vibrations is essential to demarcate the safety area of blasting. In this research, classification and regression tree (CART) as a rule-based method was used to predict the peak particle velocity through a database comprising of 51 datasets with results of maximum charge per delay and distance from the blast face were fixed as model inputs. For comparison, the empirical and multiple regression (MR) models were also applied and proposed for peak particle velocity prediction. Performance of the proposed models were compared and evaluated using three statistical criteria, namely coefficient of correlation (R (2)), root mean square error (RMSE) and variance account for (VAF). Comparison of the obtained results demonstrated that the CART technique is more reliable for predicting the peak particle velocity than the MR and empirical models and it can be introduced as a new technique in this field.
This project investigates the feasibility of combining overburden (OB) produced from an open cut brown coal mine, rejected wood chip waste from a Kraft Paper Mill (KMR), and industrially derived compost. The outcome is an artificial soil that mitigates Acid Mine Drainage (AMD) and enhances soil heath and suitability for rehabilitation. The three separate industries are local to each other, facilitating economical transportation of waste streams. The study identified a suitable artificial soil mixing ratio that would ultimately neutralise AMD and amplify nutrient content (8 parts OB, 1 part KMR and 0.6 parts compost), based on net acid producing potential derived for each component. The pH of the mixtures increased compared with the raw materials eg. from pH 3.24 to pH 6.51, which was well within ideal conditions for plant growth and inhibition of acidophilic bacteria that catalyse AMD reactions. The artificial soil also demonstrated increased water retaining characteristics (field capacity) and enhanced vegetation growth, with an extreme example illustrated by one acid OB sample (pH 1.75, originally unable to support vegetation) effectively supporting grass growth after mixing. Synthetic Precipitation Leaching Procedure (SPLP) results showed no regulatory levels being breached in regards to metals leaching out of the artificial soils. However, in some samples, the artificial soil leachate exhibited higher concentrations of metals than the original samples. Electrical Conductivity values increased on average from 0.8 ds/m to 1.66 ds/m). These soils, once proven safe and effective for use, could be laid over the waste dumps in brown coal mines for reclamations purposes.