Ground vibration due to blasting is identified as a challenging issue in mining and civil activities. Peak particle velocity (PPV) is one of the blasting undesirable consequences, which is resulted during emission of vibration in blasted bench. This study focuses on the PPV prediction in the surface mines. In this regard, two ensemble systems, i.e., the ensemble of artificial neural networks and the ensemble of extreme gradient boosting (EXGBoosts) were developed for PPV prediction in one of the largest lead-zinc open-pit mines in the Middle East. For ensemble modeling, several ANN and XGBoost base models were separately designed with different architectures. Then, the validation indices such as coefficient determination (R2), root mean square error (RMSE), mean absolute error (MAE), the variance accounted for (VAF), and Accuracy were used to evaluate the performance of the base models. The five top base models with high accuracy were selected to construct an ensemble model for each of the methods, i.e., ANNs and XGBoosts. To combine the outputs of the top base models and achieve a single result stacked generalization technique, was employed. Findings showed ensemble models increase the accuracy of PPV predicting in comparison with the best individual models. The EXGBoosts was superior method for predicting of the PPV, which obtained values of R2, RMSE, MAE, VAF, and Accuracy corresponding to the EXGBoosts were (0.990, 0.391, 0.257, 99.013(%), 98.216), and (0.968, 0.295, 0.427, 96.674(%), 96.059), for training and testing datasets, respectively. However, the sensitivity analysis indicated that the spacing (r = 0.917) and number of blast-holes (r = 0.839) had the highest and lowest impact on the PPV intensity, respectively.
In the last decade, there has been an increase in research on ecologically benign, cost-effective, and socially useful cement alternative materials for concrete. Alternatives involve industrial and agriculture waste, the potential advantages of which may be recognized by recycling, repurposing, and recreating techniques. Important energy reserves and a decrease in Portland cement (PC) consumption may be attained by using these wastes as supplementary and substitute ingredients, contributing to a reduction in carbon dioxide (CO2) production. Consequently, the incorporation of marble dust powder (MDP) and calcined clay (CC) as supplementary cementitious material (SCM) in high strength concrete may lower the environmental effect and reduce the amount of PC in mixes. This study is conducted on concrete containing 0%, 5%, 10%, 15%, and 20% of MDP and CC as cementitious materials alone and in combination. The main objectives of this investigations are to examine the effect of MDP and CC as cementitious materials on the flowability and mechanical characteristics of high strength concrete. In order to examine the ecological effect of CC and MDP, the eco-strength efficiency and embodied carbon were considered. In this context, there are so many trial mixes were performed on cubical specimens for achieving targeted compressive strength about 60 MPa after 28 days. After getting it, a total of 273 concrete specimens (cubes, cylinders, and prisms) were used to test the compressive, splitting tensile, and flexural strength of high strength concrete correspondingly. Moreover, when the amount of MDP and CC as SCM in the mixture grows, the workability of green concrete decreases. In addition, the compressive strength, flexural strength, and splitting tensile strength are increased by 6.38 MPa, 67.66 MPa, and 4.88 MPa, respectively, at 10% SCM (5% MDP and 5% CC) over a period of 28 days. In addition, using ANOVA, response prediction models were generated and confirmed at a 95% level of significance. The R2 values of the models varied from 96 to 99%. Furthermore, increasing the amount of CC and MDP as SCM in concrete also reduces the amount of carbon embedded in the material. It is recommended that the utilization of 10% SCM (5% MDP and 5% CC) in high strength concrete is providing optimum outcomes for construction industry in the field of Civil Engineering.