Prediction of casted muck pile profiles using discrete element modeling and the Monte Carlo approach

作     者：Lamont, R. Schafrik, S. Diddle, B. Silva, J. Calnan, J. Agioutantis, Z. 

作者机构：Dyno Nobel SALT LAKE CITY UT USA Univ Kentucky Dept Min Engn Lexington KY 40506 USA Dyno Consult Salt Lake City UT USA 

出 版 物：《SIMULATION MODELLING PRACTICE AND THEORY》 (Simul. Model. Pract. Theory)

年 卷 期：2025年第140卷

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Cast blasting Discrete element modeling Monte Carlo approach Predictive modeling 

摘      要：In applicable orebodies, well-designed cast blasting has proven to be a more efficient method of material transportation than traditional options. Cast blast design has historically been based upon the modification of previous field observations. More recently, numerical models have been developed to predict blasting effects such as vibration and sound, among many. The Discrete Element Modeling method, which creates a large quantity of individual particles, has experienced successful application in modeling blasted rock movement. This work examined several potential improvements to the prediction of muck pile profiles and evaluated their effect based on measured results. Model element shapes, sizes, and distributions were found to have little effect on predictive ability. A stochastic approach was taken to simplify the effect of several pre-blast variables into only initial velocity, which proved to be a valid assumption. A modest central portion of the bench was found to represent the entire bench accurately. Several factors were found to have a high impact on final muck pile profiles, including friction, pit floor variation, and timing. The results illuminate the effects of several parameters crucial to increasing the ability of operators to optimize cast blasts.