Automatic selection of a subset size at vector fields construction

An algorithm for selection of the size of a correlation kernel at displacement vector field construction by the method of digital image correlation has been proposed. The algorithm has been tested on simulated and experimental optical images having different texture. The influence of the correlation kernel size and image texture on nose immunity at determining displacements has been studied. It is shown that the proposed algorithm allows to find this size providing the minimum error when determination of displacements and estimation of deformation

Fundamental role of local curvature of crystal structure in plastic deformation and fracture of solids

It is shown that strain-induced defects of all kinds are nucleated in local curvature zones of the interfaces between 3D-crystals and 2D-planar subsystem similar to a laser pumping mechanism. Mobile curvature solitons are generalized wave structural carriers of plastic flow. Fracture is the structural phase decay of a crystal in the zones of very high curvature

Search for glitches of gamma-ray pulsars with deep learning

The pulsar glitches are generally assumed to be an apparent manifestation of the superfluid interior of the neutron stars. Most of them were discovered and extensively studied by continuous monitoring in the radio wavelengths. The Fermi-LAT space telescope has made a revolution uncovering a large population of gamma-ray pulsars. In this paper we suggest to employ these observations for the searches of new glitches. We develop the method capable of detecting step-like frequency change associated with glitches in a sparse gamma-ray data. It is based on the calculations of the weighted H-test statistics and glitch identification by a convolutional neural network. The method demonstrates high accuracy on the Monte Carlo set and will be applied for searches of the pulsar glitches in the real gamma-ray data in the future works.Comment: 4 pages, 5 figure

Material fragmentation as dissipative process of micro rotation sequence formation: Hybrid model of excitable cellular automata

The authors have developed a multi-level model of energy propagation along interfaces between the various structural elements of a solid with taking into account mutual energy transformations of various kinds. They have also designed a computer simulation tool based on the excitable cellular automaton (ECA) method. An algorithm for calculating the local moments of forces has been developed for the case of material rotation and torsion. The relationship for the accumulated elastic energy is supplemented with a dissipation term. Numerical experiments have been carried out on high-energy impact on polycrystalline copper specimens with different grain sizes. The paper shows that during the nanostructuring of material surface layer, the dissipation of elastic energy gives rise to the rotation of structural elements. This makes it possible to prevent the occurrence of stress concentrators with peak values typical of coarse-grained specimens and reducing their mechanical properties

Dynamic recrystallization of Ti-based materials at crack surfaces at elevated temperatures –hybrid cellular automata simulation

In the study a Hybrid discrete-continuum Cellular Automata approach (HCA) based on coupling classical thermomechanics and logics of CA-switching to simulate new phase generation and grain growth is proposed. On the basis of the HCA the numerical experiments on thermal-activated recrystallization of pure titanium in the vicinity of crack edges were conducted. In doing so the 3D cellular automaton simulates the behavior of the V-notched specimen region that imitates the crack tip vicinity. Numerical experiments are aimed at calculating heat expansion in the material under study through taking into account thermal stresses accumulation and microrotation initiation. The latter gives rise to generation of new defects and increasing the local entropy