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In this paper, using our bifurcation-geometric approach, we study global dynamics and solve the problem of the maximum number and distribution of limit cycles (self-oscillating regimes corresponding to states of dynamical equilibrium) in a planar polynomial mechanical system of the Euler–Lagrange–Liйnard type. Such systems are also used to model electrical, ecological, biomedical and other systems, which greatly facilitates the study of the corresponding real processes and systems with complex internal dynamics. They are used, in particular, in mechanical systems with damping and stiffness. There are a number of examples of technical systems that are described using quadratic damping in second-order dynamical models. In robotics, for example, quadratic damping appears in direct-coupled control and in nonlinear devices, such as variable impedance (resistance) actuators. Variable impedance actuators are of particular interest to collaborative robotics. To study the character and location of singular points in the phase plane of the Euler–Lagrange–Liйnard polynomial system, we use our method the meaning of which is to obtain the simplest (well-known) system by vanishing some parameters (usually, field rotation parameters) of the original system and then to enter sequentially these parameters studying the dynamics of singular points in the phase plane. To study the singular points of the system, we use the classical Poincarй index theorems, as well as our original geometric approach based on the application of the Erugin twoisocline method which is especially effective in the study of infinite singularities. Using the obtained information on the singular points and applying canonical systems with field rotation parameters, as well as using the geometric properties of the spirals filling the internal and external regions of the limit cycles and applying our geometric approach to qualitative analysis, we study limit cycle bifurcations of the system under consideration.

The work is devoted to modeling the processes of disassembling complex products in CADsystems. The ability to dismantle a product in a given sequence is formed at the early design stages, and is implemented at the end of the life cycle. Therefore, modern CAD-systems should have tools for assessing the complexity of dismantling parts and assembly units of a product. A hypergraph model of the mechanical structure of the product is proposed. It is shown that the mathematical description of coherent and sequential disassembly operations is the normal cutting of the edge of the hypergraph. A theorem on the properties of normal cuts is proved. This theorem allows us to organize a simple recursive procedure for generating all cuts of the hypergraph. The set of all cuts is represented as an AND/OR-tree. The tree contains information about plans for disassembling the product and its parts. Mathematical descriptions of various types of disassembly processes are proposed: complete, incomplete, linear, nonlinear. It is shown that the decisive graph of the AND/OR-tree is a model of disassembling the product and all its components obtained in the process of dismantling. An important characteristic of the complexity of dismantling parts is considered — the depth of nesting. A method of effective calculation of the estimate from below has been developed for this characteristic.

This article presents the results of an analytical and computer study of the collective dynamic properties of a chain of self-oscillating systems (conditionally — oscillators). It is assumed that the couplings of individual elements of the chain are non-reciprocal, unidirectional. More precisely, it is assumed that each element of the chain is under the influence of the previous one, while the reverse reaction is absent (physically insignificant). This is the main feature of the chain. This system can be interpreted as an active discrete medium with unidirectional transfer, in particular, the transfer of a matter. Such chains can represent mathematical models of real systems having a lattice structure that occur in various fields of natural science and technology: physics, chemistry, biology, radio engineering, economics, etc. They can also represent models of technological and computational processes. Nonlinear self-oscillating systems (conditionally, oscillators) with a wide “spectrum” of potentially possible individual self-oscillations, from periodic to chaotic, were chosen as the “elements” of the lattice. This allows one to explore various dynamic modes of the chain from regular to chaotic, changing the parameters of the elements and not changing the nature of the elements themselves. The joint application of qualitative methods of the theory of dynamical systems and qualitative-numerical methods allows one to obtain a clear picture of all possible dynamic regimes of the chain. The conditions for the existence and stability of spatially-homogeneous dynamic regimes (deterministic and chaotic) of the chain are studied. The analytical results are illustrated by a numerical experiment. The dynamical regimes of the chain are studied under perturbations of parameters at its boundary. The possibility of controlling the dynamic regimes of the chain by turning on the necessary perturbation at the boundary is shown. Various cases of the dynamics of chains comprised of inhomogeneous (different in their parameters) elements are considered. The global chaotic synchronization (of all oscillators in the chain) is studied analytically and numerically.

The article provides approaches to evolutionary modelling of synthesis of organised systems and analyses methodological problems of evolutionary computations of this kind. Based on the analysis of works on evolutionary cybernetics, evolutionary theory, systems theory and synergetics, we conclude that there are open problems in formalising the synthesis of organised systems and modelling their evolution. The article emphasises that the theoretical basis for the practice of evolutionary modelling is the principles of the modern synthetic theory of evolution. Our software project uses a virtual computing environment for machine synthesis of problem solving algorithms. In the process of modelling, we obtained the results on the basis of which we conclude that there are a number of conditions that fundamentally limit the applicability of genetic programming methods in the tasks of synthesis of functional structures. The main limitations are the need for the fitness function to track the step-by-step approach to the solution of the problem and the inapplicability of this approach to the problems of synthesis of hierarchically organised systems. We note that the results obtained in the practice of evolutionary modelling in general for the whole time of its existence, confirm the conclusion the possibilities of genetic programming are fundamentally limited in solving problems of synthesizing the structure of organized systems. As sources of fundamental difficulties for machine synthesis of system structures the article points out the absence of directions for gradient descent in structural synthesis and the absence of regularity of random appearance of new organised structures. The considered problems are relevant for the theory of biological evolution. The article substantiates the statement about the biological specificity of practically possible ways of synthesis of the structure of organised systems. As a theoretical interpretation of the discussed problem, we propose to consider the system-evolutionary concept of P.K.Anokhin. The process of synthesis of functional structures in this context is an adaptive response of organisms to external conditions based on their ability to integrative synthesis of memory, needs and information about current conditions. The results of actual studies are in favour of this interpretation. We note that the physical basis of biological integrativity may be related to the phenomena of non-locality and non-separability characteristic of quantum systems. The problems considered in this paper are closely related to the problem of creating strong artificial intelligence.

This paper presents algorithm for modeling set of trajectories of non-stationary time series, based on a numerical scheme for approximating the sample density of the distribution function in a problem with fixed ends, when the initial distribution for a given number of steps transforms into a certain final distribution, so that at each step the semigroup property of solving the Liouville equation is satisfied. The model makes it possible to numerically construct evolving densities of distribution functions during random switching of states of the system generating the original time series.

The main problem is related to the fact that with the numerical implementation of the left-hand differential derivative in time, the solution becomes unstable, but such approach corresponds to the modeling of evolution. An integrative approach is used while choosing implicit stable schemes with “going into the future”, this does not match the semigroup property at each step. If, on the other hand, some real process is being modeled, in which goal-setting presumably takes place, then it is desirable to use schemes that generate a model of the transition process. Such model is used in the future in order to build a predictor of the disorder, which will allow you to determine exactly what state the process under study is going into, before the process really went into it. The model described in the article can be used as a tool for modeling real non-stationary time series.

Steps of the modeling scheme are described further. Fragments corresponding to certain states are selected from a given time series, for example, trends with specified slope angles and variances. Reference distributions of states are compiled from these fragments. Then the empirical distributions of the duration of the system’s stay in the specified states and the duration of the transition time from state to state are determined. In accordance with these empirical distributions, a probabilistic model of the disorder is constructed and the corresponding trajectories of the time series are modeled.

Computer-aided assembly planning for complex products is an important engineering and scientific problem. The assembly sequence and content of assembly operations largely depend on the mechanical structure and geometric properties of a product. An overview of geometric modeling methods that are used in modern computer-aided design systems is provided. Modeling geometric obstacles in assembly using collision detection, motion planning, and virtual reality is very computationally intensive. Combinatorial methods provide only weak necessary conditions for geometric reasoning. The important problem of minimizing the number of geometric tests during the synthesis of assembly operations and processes is considered. A formalization of this problem is based on a hypergraph model of the mechanical structure of the product. This model provides a correct mathematical description of coherent and sequential assembly operations. The key concept of the geometric situation is introduced. This is a configuration of product parts that requires analysis for freedom from obstacles and this analysis gives interpretable results. A mathematical description of geometric heredity during the assembly of complex products is proposed. Two axioms of heredity allow us to extend the results of testing one geometric situation to many other situations. The problem of minimizing the number of geometric tests is posed as a non-antagonistic game between decision maker and nature, in which it is required to color the vertices of an ordered set in two colors. The vertices represent geometric situations, and the color is a metaphor for the result of a collision-free test. The decision maker’s move is to select an uncolored vertex; nature’s answer is its color. The game requires you to color an ordered set in a minimum number of moves by decision maker. The project situation in which the decision maker makes a decision under risk conditions is discussed. A method for calculating the probabilities of coloring the vertices of an ordered set is proposed. The basic pure strategies of rational behavior in this game are described. An original synthetic criterion for making rational decisions under risk conditions has been developed. Two heuristics are proposed that can be used to color ordered sets of high cardinality and complex structure.

The process of heat conduction, accompanied by the first order phase transitions is discussed in this article. Using cellular automates simulation was investigated class of problems that have broad application in practice. In this paper we calculate the temperature distribution in the depth of the soil at different times for a problem of freezing of moist soil. Another task — zone growing — has been modeled by cellular automates too. The coincidence of real and modeling parameters of the system confirms the feasibility of using the selected method of modeling of physical processes.

The paper considers hereditarity oscillator which is characterized by oscillation equation with derivatives of fractional order $\beta$ and $\gamma$, which are defined in terms of Gerasimova-Caputo. Using Laplace transform were obtained analytical solutions and the Green’s function, which are determined through special functions of Mittag-Leffler and Wright generalized function. It is proved that for fixed values of $\beta = 2$ and $\gamma = 1$, the solution found becomes the classical solution for a harmonic oscillator. According to the obtained solutions were built calculated curves and the phase trajectories hereditarity oscillatory process. It was found that in the case of an external periodic influence on hereditarity oscillator may occur effects inherent in classical nonlinear oscillators.

In present paper we reexamine the properties of CABARET numerical scheme formulated for a weakly compressible fluid flow basing the results of free shear layer modeling. Kelvin–Helmholtz instability and successive generation of two-dimensional turbulence provide a wide field for a scheme analysis including temporal evolution of the integral energy and enstrophy curves, the vorticity patterns and energy spectra, as well as the dispersion relation for the instability increment. The most part of calculations is performed for Reynolds number $\text{Re} = 4 \times 10^5$ for square grids sequentially refined in the range of $128^2-2048^2$ nodes. An attention is paid to the problem of underresolved layers generating a spurious vortex during the vorticity layers roll-up. This phenomenon takes place only on a coarse grid with $128^2$ nodes, while the fully regularized evolution pattern of vorticity appears only when approaching $1024^2$-node grid. We also discuss the vorticity resolution properties of grids used with respect to dimensional estimates for the eddies at the borders of the inertial interval, showing that the available range of grids appears to be sufficient for a good resolution of small–scale vorticity patches. Nevertheless, we claim for the convergence achieved for the domains occupied by large-scale structures.

The generated turbulence evolution is consistent with theoretical concepts imposing the emergence of large vortices, which collect all the kinetic energy of motion, and solitary small-scale eddies. The latter resemble the coherent structures surviving in the filamentation process and almost noninteracting with other scales. The dissipative characteristics of numerical method employed are discussed in terms of kinetic energy dissipation rate calculated directly and basing theoretical laws for incompressible (via enstrophy curves) and compressible (with respect to the strain rate tensor and dilatation) fluid models. The asymptotic behavior of the kinetic energy and enstrophy cascades comply with two-dimensional turbulence laws $E(k) \propto k^{−3}, \omega^2(k) \propto k^{−1}$. Considering the instability increment as a function of dimensionless wave number shows a good agreement with other papers, however, commonly used method of instability growth rate calculation is not always accurate, so some modification is proposed. Thus, the implemented CABARET scheme possessing remarkably small numerical dissipation and good vorticity resolution is quite competitive approach compared to other high-order accuracy methods

One- and two-dimensional hydrodynamic models of turbulent transfer within the atmospheric surface layer under neutral thermal stratification are considered. Both models are based on the solution of system of the timeaveraged equations of Navier – Stokes and continuity using a 1.5-order closure scheme as well as equations for turbulent kinetic energy and the rate of its dissipation. The influence of the upper and lower boundary conditions on vertical profiles of wind speed and turbulence parameters within the atmospheric surface layer was derived using an one-dimensional model usually applied in case of an uniform ground surface. The boundary conditions in the model were prescribed in such way that the vertical wind and turbulence patterns were well agreed with widely used logarithmic vertical profile of wind speed, linear dependence of turbulent exchange coefficient on height above ground surface level and constancy of turbulent kinetic energy within the atmospheric surface layer under neutral atmospheric conditions. On the basis of the classical one-dimensional model it is possible to obtain a number of relationships which link the vertical wind speed gradient, turbulent kinetic energy and the rate of its dissipation. Each of these relationships can be used as a boundary condition in our hydrodynamic model. The boundary conditions for the wind speed and the rate of dissipation of turbulent kinetic energy were selected as parameters to provide the smallest deviations of model calculations from classical distributions of wind and turbulence parameters. The corresponding upper and lower boundary conditions were used to define the initial and boundary value problem in the two-dimensional hydrodynamic model allowing to consider complex topography and horizontal vegetation heterogeneity. The two-dimensional model with selected optimal boundary conditions was used to describe the spatial pattern of turbulent air flow when it interacted with the forest edge. The dynamics of the air flow establishment depending on the distance from the forest edge was analyzed. For all considered initial and boundary value problems the unconditionally stable implicit finite-difference schemes of their numerical solution were developed and implemented.