Результаты поиска по 'percolation cluster':
Найдено статей: 3
  1. Moskalev P.V.
    Estimates of threshold and strength of percolation clusters on square lattices with (1,π)-neighborhood
    Computer Research and Modeling, 2014, v. 6, no. 3, pp. 405-414

    In this paper we consider statistical estimates of threshold and strength of percolation clusters on square lattices. The percolation threshold pc and the strength of percolation clusters P∞ for a square lattice with (1,π)-neighborhood depends not only on the lattice dimension, but also on the Minkowski exponent d. To estimate the strength of percolation clusters P∞ proposed a new method of averaging the relative frequencies of the target subset of lattice sites. The implementation of this method is based on the SPSL package, released under GNU GPL-3 using the free programming language R.

    Keywords: site percolation, square lattice, non-metric Minkowski distance, Moore neighborhood, percolation threshold, strength of infinite clusters, R programming language, SPSL package.
    Views (last year): 4. Citations: 5 (RSCI).
  2. Fursov E.V., Kosilov A.T., Pryadilshchikov A.Y.
    Effect of the surface on characteristics of amorphization Ni-Ag system
    Computer Research and Modeling, 2014, v. 6, no. 2, pp. 263-269

    Molecular dynamics simulation using the embedded-atom method is applied to study the structural evolution of the particle diameter of 40 Å during the quenching process. Was carried comparative analysis of the structural reconstruction for the particle and the bulk models. Was a reduction in temperature of the beginning and end of the transformation of the particle. In formation of a percolation cluster from interpenetrating and contacting icosahedrons, for model of the particle, it is involved for 10 percent of atoms more, than for model of a bulk.

    Keywords: metal nanoparticle, molecular dynamics simulation, icosahedron.
    Views (last year): 1. Citations: 1 (RSCI).
  3. Moskalev P.V., Stebulyanin M.M., Myagkov A.S.
    Impact of spatial resolution on mobile robot path optimality in two-dimensional lattice models
    Computer Research and Modeling, 2025, v. 17, no. 6, pp. 1131-1148

    This paper examines the impact of the spatial resolution of a discretized (lattice) representation of the environment on the efficiency and correctness of optimal pathfinding in complex environments. Scenarios are considered that may include bottlenecks, non-uniform obstacle distributions, and areas of increased safety requirements in the immediate vicinity of obstacles. Despite the widespread use of lattice representations of the environment in robotics due to their compatibility with sensor data and support for classical trajectory planning algorithms, the resolution of these lattices has a significant impact on both goal reachability and optimal path performance. An algorithm is proposed that combines environmental connectivity analysis, trajectory optimization, and geometric safety refinement. In the first stage, the Leath algorithm is used to estimate the reachability of the target point by identifying a connected component containing the starting position. Upon confirmation of the target point’s reachability, the A* algorithm is applied to the nodes of this component in the second stage to construct a path that simultaneously minimizes both the path length and the risk of collision. In the third stage, a refined obstacle distance estimate is performed for nodes located in safety zones using a combination of the Gilbert – Johnson –Keerthi (GJK) and expanding polyhedron (EPA) algorithms. Experimental analysis revealed a nonlinear relationship between the probability of the existence and effectiveness of an optimal path and the lattice parameters. Specifically, reducing the spatial resolution of the lattice increases the likelihood of connectivity loss and target unreachability, while increasing its spatial resolution increases computational complexity without a proportional improvement in the optimal path’s performance.

    Keywords: mobile robot, optimal pathfinding, lattice percolation, percolation cluster, Leath algorithm, A* algorithm, Gilbert – Johnson –Keerthi algorithm, expanding polytope algorithm.

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