Analysis of loading and hauling equipment requirements with a comparison of Monte Carlo simulation methods, uniform distribution, normal distribution, and exponential distribution

2021 ◽  
Author(s):  
Anton Sudiyanto ◽  
Akhmad Al Faradcy ◽  
Tedy Agung Cahyadi ◽  
Dwi Poetranto W.A ◽  
Hendro Suryono
2006 ◽  
Vol 82 (3-4) ◽  
pp. 489-502 ◽  
Author(s):  
Antti Lauri ◽  
Joonas Merikanto ◽  
Evgeni Zapadinsky ◽  
Hanna Vehkamäki

2018 ◽  
Vol 46 (2) ◽  
pp. 902-912 ◽  
Author(s):  
Anthony J. Hardy ◽  
Maryam Bostani ◽  
Andrew M. Hernandez ◽  
Maria Zankl ◽  
Cynthia McCollough ◽  
...  

2011 ◽  
Vol 3 (3) ◽  
Author(s):  
John Howarth

AbstractAn important property of loess is a tendency to collapse on loading and wetting (hydroconsolidation) which can have serious consequences worldwide for civil engineering projects. Randomly generated particles are classified according to Zingg shape categories: disc, sphere, blade and rod. This paper differs from the previous by the same author [8] in that a uniform distribution is no longer assumed for the underlying spatial distribution. Randomly placed faults in the quartz mother-rock lead naturally to an exponential distribution for the linear dimension of the basic particle. Monte Carlo processes and analytical formulae are used to calculate the average dimensions for particles in the blade category, into which most loess has been shown to fall.


1991 ◽  
Vol 28 (3) ◽  
pp. 539-552 ◽  
Author(s):  
R. P. C. Rodgers ◽  
A. J. Baddeley

We consider two random sequential packing processes in which spheres of unit radius are randomly attached to the surface of a fixed unit sphere. Independent random spheres are generated and added successively, provided there is no overlap with previous spheres. In model 1, the process stops when a trial sphere intersects one of the previously-accepted spheres. In model 2, random sequential packing, any such overlapping trial sphere is discarded and the next random sphere is tried, until it is impossible to add any further spheres.Previous workers have conjectured convincingly that no exact analytical solution is possible for this type of problem. We use Monte Carlo simulation methods to estimate transition probabilities for the two models. Because some probabilities are extremely small, a simulation using independent repetitions of the model would be inefficient. We designed a branching process of conditionally binomial trials, and performed over 108 trials on a supercomputer.


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