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We obtain asymptotic equalities for upper bounds of the deviations of the right-angled de la Vallee Poussin sums taken over classes of periodical functions of two variables of high smoothness. These equalities guarantee the solvability of the Kolmogorov–Nikol’skii problem for the right-angled de la Vallee Poussin sums on the specified classes of functions.

We obtain asymptotic equalities for upper bounds of the deviations of the right-angled de la Vallee Poussin sums taken over classes of periodical functions of many variables of high smoothness. These equalities guarantee the solvability of the Kolmogorov–Nikol’skii problem for the right-angled de la Vallee Poussin sums on the specified classes of functions.

Use of algorithms based on neural networks can be inefficient for small amounts of experimental data. Authors consider a solution of this problem in the context of modelling of properties of ceramic composite materials reinforced with carbon nanotubes using perceptron complex. This approach allowed us to obtain a mathematical description of the object of study with a minimal amount of input data (the amount of necessary experimental samples decreased 2–3.3 times). Authors considered different versions of perceptron complex structures. They found that the most appropriate structure has perceptron complex with breakthrough of two input variables. The relative error was only 6%. The selected perceptron complex was shown to be effective for predicting the properties of ceramic composites. The relative errors for output components were 0.3%, 4.2%, 0.4%, 2.9%, and 11.8%.

The article discusses the model of the anthropomorphic type of mechanism of the exoskeleton with links of variable length. Four models of parts of variable length are considered comprehensively: the model link of the exoskeleton of variable length with a resilient member and a rigid strong core; the model of the telescopic link; the model link with the masses in the hinge-joint between them; the link model with an arbitrary number of masses. The differential equations of motion in the form of Lagrange equations of the second kind are made. On the basis of analysis of differential equations of motion for multi-link rod of a mechanical system type, exoskeleton revealed their structure, which allowed us to represent them in vector-matrix form. The General pattern of building matrices are established for the first time and the generalization of the expressions for elements of matrices in two-dimensional case are obtained. New recursive and matrix methods of composing of differential equations of motion are given. A unified approach to constructing differential equations of motion of the exoskeleton based on the developed recursive and matrix methods write differential equations of motion of the proposed exoskeleton. Comparison of the time of writing the differential equations of motion proposed methods, in comparison with the Lagrange equations of the second kind, in the system of computer mathematics Mathematica conducted. An analytical study of the model of the exoskeleton carried out. It was found that for mechanisms with n movable links of the Cauchy problem for systems of differential equations of motion for any initial conditions there is no single and unlimited continue. Control of the exoskeleton is accomplished using the torques which are located in the hinge-joints in the joints of the links and simulating control actions. Numerical investigation of a model of the exoskeleton is made, a comparison of results of calculations for exoskeletons with various models of units is held. A numerical study of the empirical evidence about the man and his movements is used. It is established that the choice structure of the exoskeleton model with lumped masses is more preferable to a model with perfectly rigid strong core. As an exoskeleton, providing comfortable movement of people, and you should repeat the properties of the musculoskeletal system.

The system of linear hyperbolic kinetic equations with the relaxation term of Bhatnagar–Gross–Krook type for modelling of linear diffusion processes by the lattice Boltzmann method is considered. The coefficients of the equations depend on the discrete velocities from the pattern in velocity space. The system may be considered as an alternative mathematical model of the linear diffusion process. The cases of widely-used patterns on speed variables are considered. The case of parametric coefficients takes into account. By application of the method of Chapman–Enskog asymptotic expansion it is obtained, that the system may be reduced to the linear diffusion equation. The expression of the diffusion coefficient is obtained. As a result of the analysis of this expression, the existence of numerical diffusion in solutions obtained by application of lattice Boltzmann equations is demonstrated. Stability analysis is based on the investigation of wave modes defined by the solutions of hyperbolic system. In the cases of some one-dimensional patterns stability analysis may be realized analytically. In other cases the algorithm of numerical stability investigation is proposed. As a result of the numerical investigation stability of the solutions is shown for a wide range of input parameters. The sufficiency of the positivity of the relaxation parameter for the stability of solutions is demonstrated. The dispersion of the solutions, which is not realized for a linear diffusion equation, is demonstrated analytically and numerically for a wide range of the parameters. But the dispersive wave modes can be damped as an asymptotically stable solutions and the behavior of the solution is similar to the solution of linear diffusion equation. Numerical schemes, obtained from the proposed systems by various discretization techniques may be considered as a tool for computer modelling of diffusion processes, or as a solver for stationary problems and in applications of the splitting lattice Boltzmann method. Obtained results may be used for the comparison of the theoretical properties of the difference schemes of the lattice Boltzmann method for modelling of linear diffusion.

Currently, earthquake-resistant design of buildings based on the power calculation and presentation of effect of the earthquake static equivalent forces, which are calculated using elastic response spectra (linear-spectral method) that connects the law of motion of the soil with the absolute acceleration of the model in a nonlinear oscillator.

This approach does not directly take into account either the influence of the duration of strong motion or the plastic behavior of the structure. Frequency content and duration of ground vibrations directly affect the energy received by the building and causing damage to its elements. Unlike power or kinematic calculation of the seismic effect on the structure can be interpreted without considering separately the forces and displacements and to provide, as the product of both variables, i.e., the work or input energy (maximum energy that can be purchased building to the earthquake).

With the energy approach of seismic design, it is necessary to evaluate the input seismic energy in the structure and its distribution among various structural components.

The article provides substantiation of the energy approach in the design of earthquake-resistant buildings and structures instead of the currently used method based on the power calculation and presentation of effect of the earthquake static equivalent forces, which are calculated using spectra of the reaction.

Noted that interest in the use of energy concepts in earthquake-resistant design began with the works of Housner, which provided the seismic force in the form of the input seismic energy, using the range of speeds, and suggested that the damage in elastic-plastic system and elastic system causes one and the same input seismic energy.

The indices of the determination of the input energy of the earthquake, proposed by various authors, are given in this paper. It is shown that modern approaches to ensuring seismic stability of structures, based on the representation of the earthquake effect as a static equivalent force, do not adequately describe the behavior of the system during an earthquake.

In this paper, based on quantitative estimates of seismic risk analyzes developed in the NRU MSUCE Standard Organization (STO) “Seismic resistance structures. The main design provisions”. In the developed document a step forward with respect to the optimal design of earthquake-resistant structures.

The proposed concept of using the achievements of modern methods of calculation of buildings and structures on seismic effects, which are harmonized with the Eurocodes and are not contrary to the system of national regulations.

The paper studies the determination for one of the dynamic quality parameter (PDK) of railway vehicles — car body lateral acceleration — by using of computer simulation system for railway vehicles dynamic Simpack Rail. This provide the complex simulation environment with variable velocity depending on the train schedule. The rail vehicle model of typical 1520 mm gauge fright locomotive section used for simulation has been verified by means of the chair “Electric multiple unit cars and locomotives” in the Russian University of Transport (RUT (MIIT)). Due to this homologation the questions of model creating and verification in preprocessor are excluded in this paper. The paper gives the detail description of cartographic track modeling in situation plane, heights plane and superelevation plane based on the real operating data. The statistic parameters (moments) for the rail related track excitation and used cartographic track data of the specified track section in this simulation are given as a numeric and graphical results of reading the prepared data files. The measurement of the car body residual lateral acceleration occur under consideration of the earth gravity acceleration part like the accelerometer measurement in the real world. Finally the desired quality parameter determined by simulation is compared with the same one given by a test drive. The calculation method in both cases is based on the middle value of the absolute maximums picked up within the nonstationary realizations of this parameter. Compared results confirm that this quality factor all the first depends on the velocity and track geometry properties. The simulation of the track in this application uses the strong conformity original track data of the test ride track section. The accepted simplification in the rail vehicle model of fright electric locomotive section (body properties related to the center of gravity, small displacements between the bodies) by keeping the geometric and force law characteristics of the force elements and constraints constant allow in Simpack Rail the simulation with necessary validity of system behavior (reactions).

In this paper, a time-dependent natural convective heat transfer in a closed square cavity filled with non- Newtonian fluid was considered in the presence of an isothermal energy source located on the lower wall of the region under consideration. The vertical boundaries were kept at constant low temperature, while the horizontal walls were completely insulated. The behavior of a non-Newtonian fluid was described by the Ostwald de Ville power law. The process under study was described by transient partial differential equations using dimensionless non-primitive variables “stream function – vorticity – temperature”. This method allows excluding the pressure field from the number of unknown parameters, while the non-dimensionalization allows generalizing the obtained results to a variety of physical formulations. The considered mathematical model with the corresponding boundary conditions was solved on the basis of the finite difference method. The algebraic equation for the stream function was solved by the method of successive lower relaxation. Discrete analogs of the vorticity equation and energy equation were solved by the Thomas algorithm. The developed numerical algorithm was tested in detail on a class of model problems and good agreement with other authors was achieved. Also during the study, the mesh sensitivity analysis was performed that allows choosing the optimal mesh.

As a result of numerical simulation of unsteady natural convection of a non-Newtonian power-law fluid in a closed square cavity with a local isothermal energy source, the influence of governing parameters was analyzed including the impact of the Rayleigh number in the range 104–106, power-law index $n = 0.6–1.4$, and also the position of the heating element on the flow structure and heat transfer performance inside the cavity. The analysis was carried out on the basis of the obtained distributions of streamlines and isotherms in the cavity, as well as on the basis of the dependences of the average Nusselt number. As a result, it was established that pseudoplastic fluids $(n < 1)$ intensify heat removal from the heater surface. The increase in the Rayleigh number and the central location of the heating element also correspond to the effective cooling of the heat source.

This article studies a method of constructing a predictive neural network model of a time series based on determining the composition of input variables, constructing a training sample and training itself using the back propagation method. Traditional methods of constructing predictive models of the time series are: the autoregressive model, the moving average model or the autoregressive model — the moving average allows us to approximate the time series by a linear dependence of the current value of the output variable on a number of its previous values. Such a limitation as linearity of dependence leads to significant errors in forecasting.

Mining Technologies using neural network modeling make it possible to approximate the time series by a nonlinear dependence. Moreover, the process of constructing of a neural network model (determining the composition of input variables, the number of layers and the number of neurons in the layers, choosing the activation functions of neurons, determining the optimal values of the neuron link weights) allows us to obtain a predictive model in the form of an analytical nonlinear dependence.

The determination of the composition of input variables of neural network models is one of the key points in the construction of neural network models in various application areas that affect its adequacy. The composition of the input variables is traditionally selected from some physical considerations or by the selection method. In this work it is proposed to use the behavior of the autocorrelation and private autocorrelation functions for the task of determining the composition of the input variables of the predictive neural network model of the time series.

In this work is proposed a method for determining the composition of input variables of neural network models for stationary and non-stationary time series, based on the construction and analysis of autocorrelation functions. Based on the proposed method in the Python programming environment are developed an algorithm and a program, determining the composition of the input variables of the predictive neural network model — the perceptron, as well as building the model itself. The proposed method was experimentally tested using the example of constructing a predictive neural network model of a time series that reflects energy consumption in different regions of the United States, openly published by PJM Interconnection LLC (PJM) — a regional network organization in the United States. This time series is non-stationary and is characterized by the presence of both a trend and seasonality. Prediction of the next values of the time series based on previous values and the constructed neural network model showed high approximation accuracy, which proves the effectiveness of the proposed method.

The propagation of stable coherent entities of an electromagnetic field in nonlinear media with parameters varying in space can be described in the framework of iterations of nonlinear integral transformations. It is shown that for a set of geometries relevant to typical problems of nonlinear optics, numerical modeling by reducing to dynamical systems with discrete time and continuous spatial variables to iterates of local nonlinear Feigenbaum and Ikeda mappings and nonlocal diffusion-dispersion linear integral transforms is equivalent to partial differential equations of the Ginzburg–Landau type in a fairly wide range of parameters. Such nonlocal mappings, which are the products of matrix operators in the numerical implementation, turn out to be stable numerical- difference schemes, provide fast convergence and an adequate approximation of solutions. The realism of this approach allows one to take into account the effect of noise on nonlinear dynamics by superimposing a spatial noise specified in the form of a multimode random process at each iteration and selecting the stable wave configurations. The nonlinear wave formations described by this method include optical phase singularities, spatial solitons, and turbulent states with fast decay of correlations. The particular interest is in the periodic configurations of the electromagnetic field obtained by this numerical method that arise as a result of phase synchronization, such as optical lattices and self-organized vortex clusters.