Flyrock is one of the major disturbances induced by blasting which may cause severe damage to nearby structures. This phenomenon has to be precisely predicted and subsequently controlled through the changing in the blast design to minimize potential risk of blasting. The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA) and artificial neural network (ANN). For this purpose, the parameters of 113 blasting operations were accurately recorded and flyrock distances were measured for each operation. By applying the sensitivity analysis, maximum charge per delay and powder factor were determined as the most influential parameters on flyrock. In the light of this analysis, two new empirical predictors were developed to predict flyrock distance. For a comparison purpose, a predeveloped backpropagation (BP) ANN was developed and the results were compared with those of the proposed ICA-ANN model and empirical predictors. The results clearly showed the superiority of the proposed ICA-ANN model in comparison with the proposed BP-ANN model and empirical approaches.
Blast operations in the vicinity of residential areas usually produce significant environmental problems which may cause severe damage to the nearby areas. Blast-induced air overpressure (AOp) is one of the most important environmental impacts of blast operations which needs to be predicted to minimize the potential risk of damage. This paper presents an artificial neural network (ANN) optimized by the imperialist competitive algorithm (ICA) for the prediction of AOp induced by quarry blasting. For this purpose, 95 blasting operations were precisely monitored in a granite quarry site in Malaysia and AOp values were recorded in each operation. Furthermore, the most influential parameters on AOp, including the maximum charge per delay and the distance between the blast-face and monitoring point, were measured and used to train the ICA-ANN model. Based on the generalized predictor equation and considering the measured data from the granite quarry site, a new empirical equation was developed to predict AOp. For comparison purposes, conventional ANN models were developed and compared with the ICA-ANN results. The results demonstrated that the proposed ICA-ANN model is able to predict blast-induced AOp more accurately than other presented techniques.
Jurong Formation underlies part of Southern Johor Bahru which comprises well cemented and consolidated volcanic-sedimentary rocks. The study aims to assess quality and hydrogeochemistry of rock aquifer in Jurong Formation at Southern Johor Bahru which is mainly overlain by rhyolitic tuff. It also evaluates the differences in quality and hydrogeochemistry of rhyolitic tuff aquifer found in source and floodplain zones of South-West Johor Rivers Basin. In this study, a total of nine samples from four wells, namely TW1-TW4, were collected at foothills of Gunung Pulai (TW1) and Iskandar Puteri (TW2-TW4) in Southern Johor Bahru. The samples were examined for physiochemical parameters. The groundwater in the study area is fresh and non-saline with hardness of soft to hard. The pH of groundwater in source zone is significantly higher than in floodplain zone. Meanwhile, the hardness of groundwater in source zone is significantly lower than in other deep wells in floodplain zone as more calcite mineral is present. The concentration of manganese, iron and zinc is lower at source zone than floodplain zone. Three facies of water types were encountered during the study such as CaNaHCO3 in TW2, CaHCO3 in TW1 and TW3 and CaCl2 in TW4. The deep wells in floodplain zone are susceptible to saline intrusion. Finally, the groundwater quality in the study area is found to control by rock weathering especially silicates and carbonates, rainfall and proximity to seawater. This suggests the major control on groundwater chemistry is due to leaching of volcanic rocks and dissolution on calcite infillings. In conclusion, the groundwater is clean and safe in general although pH value is slightly acidic closer to straits and magnesium's presence in higher concentration at TW2.