Investigation of Failed Slopes Based on a New Method of Back Analysis in Rock Masses: A Case Study

Geotechnical and Geological Engineering - Small variation in shear strength parameters results in remarkable changes in the safety factor (SF) of a rock slope. In this regard, rock mass strength of...     

A Risk-Based Technique to Analyze Flyrock Results Through Rock Engineering System

Flyrock is an adverse effect produced by blasting in open-pit mines and tunneling projects. So, it seems that the precise estimations and risk level assessment of flyrock are essential in minimizing environmental effects induced by blasting. The first aim of this research is to model the risk level associated with flyrock through rock engineering systems (RES) methodology. In this regard, 62 blasting were investigated in Ulu Tiram quarry, Malaysia, and the most effective parameters of flyrock were measured. Using the most influential parameters on flyrock, the overall risk of flyrock was obtained as 32.95 which is considered as low to medium degree of vulnerability. Moreover, the second aim of this research is to estimate flyrock based on RES and multiple linear regression (MLR). To evaluate performance prediction of the models, some statistical criteria such as coefficient of determination (R²) were computed. Comparing the values predicted by the models demonstrated that the RES has more suitable performance than MLR for predicting the flyrock and it could be introduced as a powerful technique in this field.     

A Combination of Fuzzy Delphi Method and ANN-based Models to Investigate Factors of Flyrock Induced by Mine Blasting

Natural Resources Research - The identification of parameters that affect mining is one of the requirements in executive work in this field. Due to the dangers of flyrock, studying the role of the...     

Use of Intelligent Methods to Design Effective Pattern Parameters of Mine Blasting to Minimize Flyrock Distance

Flyrock is one of the most important environmental issues in mine blasting, which can affect equipment, people and could cause fatal accidents. Therefore, minimization of this environmental issue of blasting must be considered as the ultimate objective of many rock removal projects. This paper describes a new minimization procedure of flyrock using intelligent approaches, i.e., artificial neural network (ANN) and particle swarm optimization (PSO) algorithms. The most effective factors of flyrock were used as model inputs while the output of the system was set as flyrock distance. In the initial stage, an ANN model was constructed and proposed with high degree of accuracy. Then, two different strategies according to ideal and engineering condition designs were considered and implemented using PSO algorithm. The two main parameters of PSO algorithm for optimal design were obtained as 50 for number of particle and 1000 for number of iteration. Flyrock values were reduced in ideal condition to 34 m; while in engineering condition, this value was reduced to 109 m. In addition, an appropriate blasting pattern was proposed. It can be concluded that using the proposed techniques and patterns, flyrock risks in the studied mine can be significantly minimized and controlled.