  This work presents a technique for particle size generation and placement in
arbitrary closed domains. Its main application is the simulation of granular
media described by disks. Particle size generation is based on the statistical
analysis of granulometric curves which are used as empirical cumulative
distribution functions to sample from mixtures of uniform distributions. The
desired porosity is attained by selecting a certain number of particles, and
their placement is performed by a stochastic point process. We present an
application analyzing different types of sand and clay, where we model the
grain size with the gamma, lognormal, Weibull and hyperbolic distributions. The
parameters from the resulting best fit are used to generate samples from the
theoretical distribution, which are used for filling a finite-size area with
non-overlapping disks deployed by a Simple Sequential Inhibition stochastic
point process. Such filled areas are relevant as plausible inputs for assessing
Discrete Element Method and similar techniques.
