Impact of cross-section CENTERS estimation on the accuracy of the Point cloud spatial expansion using robust m-estimation and monte carlo simulation

Measurement ◽  
2021 ◽  
pp. 110436
Author(s):  
Paweł S. Dąbrowski ◽  
Marek Hubert Zienkiewicz
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Cross Section ◽  
Point Cloud ◽  
Spatial Expansion ◽  
M Estimation

Fuzzy Monte Carlo Simulation using point-cloud-based probability–possibility transformation

SIMULATION ◽  
2013 ◽  
Vol 89 (7) ◽  
pp. 860-875 ◽  
Author(s):  
A M M Sharif Ullah ◽  
M Shamsuzzaman
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Point Cloud

scholarly journals Monte Carlo Simulation of the Formation of Snowflakes

2005 ◽  
Vol 62 (5) ◽  
pp. 1529-1544 ◽  
Author(s):  
Ken-ichi Maruyama ◽  
Yasushi Fujiyoshi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Standard Deviation ◽  
Cross Section ◽  
Collision Cross Section ◽  
Initial Distribution ◽  
Sphere Model ◽  
Aggregate Model ◽  
Mean Diameter ◽  
The Mean

Abstract A stochastic microphysical model of snow aggregation that combines a simple aggregation model with a Monte Carlo method was developed. Explicit treatment of the shape of individual snowflakes in the new model facilitates examination of the structure of snowflakes and the relationships between the parameters of the generated snowflakes, such as mass versus diameter, in addition to comparisons with observations. In this study, complexities in the shape of snowflakes are successfully simulated, and the understanding of the evolution of their size distribution is advanced. The mean diameter of snow particles evolves more rapidly in the aggregate model than in the sphere model. However, growth rates of the aggregates greatly depend on the collision section of particles in aggregation. The mean mass of snowflakes in the aggregate model grows more slowly than the mass in the sphere model when the sum of the particle cross section is used as the collision cross section. The mean mass grows more quickly when a circle is used whose radius is the sum of the radii of two particles. Sensitivity experiments showed that aggregation also depends on the mean and standard deviation of the initial distribution, and on the density of constituent particles.

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