Using large-scale numerical simulations, we analyze the statistical properties of fracture in the two-dimensional random spring model and compare it with its scalar counterpart: the random fuse model. We first consider the process of crack localization measuring the evolution of damage as the external load is raised. We find that, as in the fuse model, damage is initially uniform and localizes ...

We generate Voronoi meshes over three dimensional domains with prescribed boundaries. Voronoi cells are clipped at one-sided domain boundaries. The seeds of Voronoi cells are generated by maximal Poisson-disk sampling. In contrast to centroidal Voronoi tessellations, our seed locations are unbiased. The exception is some bias near concave features of the boundary to ensure well-shaped cells. Th...

A novel and rather simple method is presented to describe the physics of space-charge region in a planar diode. The method deals with the issue in the time domain and as a consequence transient time behavior can be achieved. Potential distributions and currents obtained using this technique, supposing zero initial velocity for electrons, reveal absolute agreement with Child's results. Moreover,...

In typical stochastic simulations, randomness is produced by generating a sequence of independent uniform variates (usually real-valued between 0 and 1, or integer-valued in some interval) and transforming them in an appropriate way. In this paper, we examine practical ways of generating (deterministic approximations to) such uniform variates on a computer. We compare them in terms of ease of i...

Given εi ∈ [0,1) for each 1 < i < n, a particle performs the following random walk on {1,2, . . . ,n}: If the particle is at n, it chooses a point uniformly at random (u.a.r.) from {1, . . . ,n− 1}. If the current position of the particle is m (1 < m < n), with probability εm it decides to go back, in which case it chooses a point u.a.r. from {m + 1, . . . ,n}. With probability 1− εm it decides...

A fundamental question in Computer Science is understanding when a specific class of problems go from being computationally easy to hard. Because of its generality and applications, the problem of Boolean Satisfiability (aka SAT) is often used as a vehicle for these studies. A signal result from these studies is that the hardness of SAT problems exhibits a dramatic easy-to-hard phase transition...