arXiv subjects

Alexey A. Tsukanov

Publications and source records attributed to Alexey A. Tsukanov.

4 recordsLinked to original sources

arXiv2026

Fast and accurate quasi-atom method for simultaneous atomistic and continuum simulation of solids

We report a novel hybrid method of simultaneous atomistic simulation of solids in critical regions (contacts surfaces, cracks areas, etc.), along with continuum modeling of other parts. The continuum is treated in terms of quasi-atoms of different size, comprising composite medium. The parameters of interaction potential between the quasi-atoms are optimized to match elastic properties of the composite medium to those of the atomic one. The optimization method coincides conceptually with the online Machine Learning (ML) methods, making it computationally very efficient. Such an approach allows a straightforward application of standard software packages for molecular dynamics (MD), supplemented by the ML-based optimizer. The new method is applied to model systems with a simple, pairwise Lennard-Jones potential, as well with multi-body Tersoff potential, describing covalent bonds. Using LAMMPS software we simulate collision of particles of different size. Comparing simulation results, obtained by the novel method, with full-atomic simulations, we demonstrate its accuracy, validity and overwhelming superiority in computational speed. Furthermore, we compare our method with other hybrid methods, specifically, with the closest one -- AtC (Atomic to Continuum) method. We demonstrate a significant superiority of our approach in computational speed and implementation convenience. Finally, we discuss a possible extension of the method for modeling other phenomena.

cond-mat.mtrl-sci↗

arXiv2025

An effective control of large systems of active particles: An application to evacuation problem

Manipulation of large systems of active particles is a serious challenge across diverse domains, including crowd management, control of robotic swarms, and coordinated material transport. The development of advanced control strategies for complex scenarios is hindered, however, by the lack of scalability and robustness of the existing methods, in particular, due to the need of an individual control for each agent. One possible solution involves controlling a system through a leader or a group of leaders, which other agents tend to follow. Using such an approach we develop an effective control strategy for a leader, combining reinforcement learning (RL) with artificial forces acting on the system. To describe the guidance of active particles by a leader we introduce the generalized Vicsek model. This novel method is then applied to the problem of the effective evacuation by a robot-rescuer (leader) of large groups of people from hazardous places. We demonstrate, that while a straightforward application of RL yields suboptimal results, even for advanced architectures, our approach provides a robust and efficient evacuation strategy. The source code supporting this study is publicly available at: https://github.com/cinemere/evacuation.

cs.RO↗

arXiv2023

Atomistic mechanism of friction force independence on the normal load and other friction laws for dynamic structural superlubricity

We explore dynamic structural superlubricity for the case of a relatively large contact area, where the friction force is proportional to the area (exceeding $\sim 100\,nm^2$) experimentally, numerically, and theoretically. We use a setup comprised of two molecular smooth incommensurate surfaces -- graphene-covered tip and substrate. The experiments and MD simulations demonstrate independence of the friction force on the normal load, for a wide range of normal loads and relative surface velocities. We propose an atomistic mechanism of this phenomenon, associated with synchronic out-of-plane surface fluctuations of thermal origin, and confirm it by numerical experiments. Based on this mechanism, we develop a theory for this type of superlubricity and show that friction force increases linearly with increasing temperature and relative velocity, for velocities, larger than a threshold velocity. The MD results are in a fair agreement with predictions of the theory.

physics.comp-ph↗

arXiv2021

Collision of nanoparticles of covalently bound atoms. Impact of stress-dependent adhesion

The impact of nanoparticles (NPs) comprised of atoms with covalent bonding is investigated numerically and theoretically. We use recent models of covalent bonding of carbon atoms and elaborate a numerical model of amorphous carbon (a-C) NPs, which may be applied for modelling soot particles. We compute the elastic moduli of the a-C material which agree well with the available data. We reveal an interesting novel phenomenon - stress dependent adhesion, which refers to stress-enhanced formation of covalent bonds between contacting surfaces. We observe that the effective adhesion coefficient linearly depends on the maximal stress between the surfaces and explain this dependence. We compute the normal restitution coefficient for colliding NPs and explore the dependence of the critical velocity, demarcating bouncing and aggregative collisions, on the NP radius. Using the obtained elastic and stress-dependent adhesive coefficients we develop a theory for the critical velocity. The predictions of the theory agree very well with the simulation results.

cond-mat.mes-hall↗