scholarly journals Random Spheres and Operads

2012 ◽  
Author(s):  
Remi Leandre
Keyword(s):  
1973 ◽  
Vol 10 (02) ◽  
pp. 483-490 ◽  
Author(s):  
P. A. P. Moran

The distribution of the volume occupied by random spheres in a cube is considered, both when the number of spheres is fixed and when their centres form a Poisson field. The mean and variance are obtained and in the latter case the distribution is proved to converge to normality. The probability of complete coverage is also obtained heuristically.


2001 ◽  
Vol 115 (12) ◽  
pp. 5376-5380 ◽  
Author(s):  
Alexander M. Berezhkovskii ◽  
Yurii A. Makhnovskii ◽  
George H. Weiss

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.


2017 ◽  
Vol 31 (01) ◽  
pp. 1650431 ◽  
Author(s):  
Ning Sun ◽  
Dilip Gersappe

We use a Lattice Boltzmann Model (LBM) in order to simulate diffuse-charge dynamics in Electric Double Layer Capacitors (EDLCs). Simulations are carried out for both the charge and the discharge processes on 2D systems of complex random electrode geometries (pure random, random spheres and random fibers). The steric effect of concentrated solutions is considered by using a Modified Poisson–Nernst–Planck (MPNP) equations and compared with regular Poisson–Nernst–Planck (PNP) systems. The effects of electrode microstructures (electrode density, electrode filler morphology, filler size, etc.) on the net charge distribution and charge/discharge time are studied in detail. The influence of applied potential during discharging process is also discussed. Our studies show how electrode morphology can be used to tailor the properties of supercapacitors.


2011 ◽  
Vol 11 (7) ◽  
pp. 3159-3171 ◽  
Author(s):  
J. Um ◽  
G. M. McFarquhar

Abstract. The projections of small ice crystals (with maximum dimension <50 μm) appear quasi-circular when imaged by probes on aircraft flying through cloud. Therefore, idealized models constructed to calculate their single-scattering properties have included quasi-spherical models such as Chebyshev particles, Gaussian random spheres, and droxtals. Recently, an ice analogue grown from sodium fluorosilicate solution on a glass substrate, with several columns emanating from a common center of mass, was shown to be quasi-circular when imaged by state-of-the-art cloud probes. In this study, a new idealized model, called the budding Bucky ball (3B) that resembles the shape of the small ice analogue is developed. The corresponding single-scattering properties (scattering phase function P11 and asymmetry parameter g) are computed by a ray-tracing code. Compared with previously used models, 3B scatters less light in the forward and more light in the lateral and backward directions. The Chebyshev particles and Gaussian random spheres show smooth and featureless P11, whereas droxtals and 3Bs, which have a faceted structure, show several peaks in P11 associated with angles of minimum deviation. Overall, the difference in the forward (lateral; backward) scattering between models are up to 22% (994%; 132%), 20% (510%; 101%), and 16% (146%; 156%) for small ice crystals with respective area ratios of 0.85, 0.77, and 0.69. The g for different models varies by up to 25%, 23%, and 19% for particles with area ratios of 0.85, 0.77, and 0.69, respectively. Because the single-scattering properties of small ice crystals depend both on the choice of the idealized model and the area ratios used to characterize the small ice crystals, higher resolution observations of small ice crystals or direct observations of their single-scattering properties are required.


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