Prediction of roadheader performance plays a significant role in the plan of tunnel construction, which is influenced by different key parameters, including rock strength, discontinuity in rock mass, type and specific...Prediction of roadheader performance plays a significant role in the plan of tunnel construction, which is influenced by different key parameters, including rock strength, discontinuity in rock mass, type and specifications of roadheader machine, and brittleness. The main aim of this study is to build a robust empirical equation based on rock mass properties for the roadheader performance prediction. For achieving the aim, a dataset composed of roadheader performance rate and rock properties is established using the dataset compiled from an underground coal mine located in a remote rugged desert environment some 85 km south of Tabas City in mid east Iran. By using gathered data, the statistical analyses are conducted between rock mass properties and roadheader performance to find whether there is a significant relationship between input variables and roadheader performance. The results show that rock mass properties have a considerable impact on the rate of the roadheader performance. It is demonstrated that the proposed model can accurately predict the roadheader performance as a function of rock mass properties.展开更多
文摘Prediction of roadheader performance plays a significant role in the plan of tunnel construction, which is influenced by different key parameters, including rock strength, discontinuity in rock mass, type and specifications of roadheader machine, and brittleness. The main aim of this study is to build a robust empirical equation based on rock mass properties for the roadheader performance prediction. For achieving the aim, a dataset composed of roadheader performance rate and rock properties is established using the dataset compiled from an underground coal mine located in a remote rugged desert environment some 85 km south of Tabas City in mid east Iran. By using gathered data, the statistical analyses are conducted between rock mass properties and roadheader performance to find whether there is a significant relationship between input variables and roadheader performance. The results show that rock mass properties have a considerable impact on the rate of the roadheader performance. It is demonstrated that the proposed model can accurately predict the roadheader performance as a function of rock mass properties.
