对数正态分布
蒙特卡罗方法
随机变量
统计
变量(数学)
振动
概率逻辑
数据集
经验模型
算法的概率分析
数学
工程类
模拟
物理
数学分析
量子力学
作者
Sunny Murmu,Piyush Maheshwari,Harsh Kumar Verma
标识
DOI:10.1016/j.ijrmms.2018.01.038
摘要
An attempt has been made to include an additional blast design parameter, burden, in obtaining the vector peak particle velocity, VPPV. A large set of about 640 blast data pertaining to different rock types from ten different sites in India and Turkey has been collected from the literature. Analysis of these data has been carried out resulting in the proposal of an empirical model for peak particle velocity with due consideration to the burden along with monitoring distance and maximum charge per delay. The performance of the proposed model has been compared with existing models, and the proposed model has been found to serve the purpose of predicting VPPV with greater accuracy. Further, probabilistic analysis of VPPV has been conducted by performing Monte-Carlo (MC) simulation on proposed empirical model. Typical results corresponding to Chittorgarh limestone mines in India are presented. The input parameters namely monitoring distance and maximum charge per delay have been assumed as lognormally distributed random variables, while the burden has been assumed as discreet variable. The analysis of results of MC simulations revealed that output or the state variable, VPPV follows a lognormal distribution. It was possible to take into account the variability in the blast parameters and therefore to study its influence on VPPV.
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