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The paper considers the possibility of comparing and classifying dynamical systems based on topological data analysis. Determining the measures of interaction between the channels of dynamic systems based on the HIIA (Hankel Interaction Index Array) and PM (Participation Matrix) methods allows you to build HIIA and PM graphs and their adjacency matrices. For any linear dynamic system, an approximating directed graph can be constructed, the vertices of which correspond to the components of the state vector of the dynamic system, and the arcs correspond to the measures of mutual influence of the components of the state vector. Building a measure of distance (proximity) between graphs of different dynamic systems is important, for example, for identifying normal operation or failures of a dynamic system or a control system. To compare and classify dynamic systems, weighted directed graphs corresponding to dynamic systems are preliminarily formed with edge weights corresponding to the measures of interaction between the channels of the dynamic system. Based on the HIIA and PM methods, matrices of measures of interaction between the channels of dynamic systems are determined. The paper gives examples of the formation of weighted directed graphs for various dynamic systems and estimation of the distance between these systems based on topological data analysis. An example of the formation of a weighted directed graph for a dynamic system corresponding to the control system for the components of the angular velocity vector of an aircraft, which is considered as a rigid body with principal moments of inertia, is given. The method of topological data analysis used in this work to estimate the distance between the structures of dynamic systems is based on the formation of persistent barcodes and persistent landscape functions. Methods for comparing dynamic systems based on topological data analysis can be used in the classification of dynamic systems and control systems. The use of traditional algebraic topology for the analysis of objects does not allow obtaining a sufficient amount of information due to a decrease in the data dimension (due to the loss of geometric information). Methods of topological data analysis provide a balance between reducing the data dimension and characterizing the internal structure of an object. In this paper, topological data analysis methods are used, based on the use of Vietoris-Rips and Dowker filtering to assign a geometric dimension to each topological feature. Persistent landscape functions are used to map the persistent diagrams of the method of topological data analysis into the Hilbert space and then quantify the comparison of dynamic systems. Based on the construction of persistent landscape functions, we propose a comparison of graphs of dynamical systems and finding distances between dynamical systems. For this purpose, weighted directed graphs corresponding to dynamical systems are preliminarily formed. Examples of finding the distance between objects (dynamic systems) are given.

The dual task of integral geometry – to define for a given averaging operator the function class where inversion of that operator is possible – is solved. Those classes are defined ambiguously. Full description of those classes is given in the form of minimal complimentary information necessary to know about the function. The possible to give a constructive description of the class is researched and in the case of a finite averaging system the inversion formulas are given.

In the paper we construct the adjoint problem for the explicit and implicit parabolic quazi-linear grid boundary-value problems with one spatial variable; the coefficients of the problems depend on the solution at the same time and earlier times. Dependence on the history of the solution is via the state vector; its evolution is described by the differential equation. Many models of diffusion mass transport are reduced to such boundary-value problems. Having solutions to the direct and adjoint problems, one can obtain the exact value of the gradient of a functional in the space of parameters the problem also depends on. We present solving algorithms, including the parallel one.

Efficiency of production directly depends on quality of the management of technology which, in turn, relies on the accuracy and efficiency of the processing of control and measuring information. Development of the mathematical methods of research of the system communications and regularities of functioning and creation of the mathematical models taking into account structural features of object of researches, and also writing of the software products for realization of these methods are an actual task. Practice has shown that the list of parameters that take place in the study of complex object of modern production, ranging from a few dozen to several hundred names, and the degree of influence of each factor in the initial time is not clear. Before working for the direct determination of the model in these circumstances, it is impossible — the amount of the required information may be too great, and most of the work on the collection of this information will be done in vain due to the fact that the degree of influence on the optimization of most factors of the original list would be negligible. Therefore, a necessary step in determining a model of a complex object is to work to reduce the dimension of the factor space. Most industrial plants are hierarchical group processes and mass volume production, characterized by hundreds of factors. (For an example of realization of the mathematical methods and the approbation of the constructed models data of the Moldavian steel works were taken in a basis.) To investigate the systemic linkages and patterns of functioning of such complex objects are usually chosen several informative parameters, and carried out their sampling. In this article the sequence of coercion of the initial indices of the technological process of the smelting of steel to the look suitable for creation of a mathematical model for the purpose of prediction is described. The implementations of new types became also creation of a basis for development of the system of automated management of quality of the production. In the course of weak correlation the following stages are selected: collection and the analysis of the basic data, creation of the table the correlated of the parameters, abbreviation of factor space by means of the correlative pleiads and a method of weight factors. The received results allow to optimize process of creation of the model of multiple-factor process.

Calculations of radiation transport in the shockwave layer of a descent space vehicle cause essential difficulties due to complex multi-resonance dependence of the absorption macroscopic cross sections from the photon energy. The convergence of two approximate spectrum averaging methods to the results of exact pointwise spectrum calculations is investigated. The first one is the well known multigroup method, the second one is the Lebesgue averaging method belonging to methods of the reduction of calculation points by means of aggregation of spectral points which are characterized by equal absorption strength. It is shown that convergence of the Lebesgue averaging method is significantly faster than the multigroup approach as the number of groups is increased. The only 100–150 Lebesgue groups are required to achieve the accuracy of pointwise calculations even in the shock layer at upper atmosphere with sharp absorption lines. At the same time the number of calculations is reduced by more than four order. Series of calculations of the radiation distribution function in 2D shock layer around a sphere and a blunt cone were performed using the local flat layer approximation and the Lebesgue averaging method. It is shown that the shock wave radiation becomes more significant both in value of the energy flux incident on the body surface and in the rate of energy exchange with the gas-dynamic flow in the case of increasing of the vehicle’s size.

Mathematical models of many natural processes are described by partial differential equations with singular solutions. Classical numerical methods for determination of approximate solution to such problems are inefficient. In the present paper a boundary value problem for vector wave equation in L-shaped domain is considered. The presence of reentrant corner of size $3\pi/2$ on the boundary of computational domain leads to the strong singularity of the solution, i.e. it does not belong to the Sobolev space $H^1$ so classical and special numerical methods have a convergence rate less than $O(h)$. Therefore in the present paper a special weighted set of vector-functions is introduced. In this set the solution of considered boundary value problem is defined as $R_ν$-generalized one.

For numerical determination of the $R_ν$-generalized solution a weighted vector finite element method is constructed. The basic difference of this method is that the basis functions contain as a factor a special weight function in a degree depending on the properties of the solution of initial problem. This allows to significantly raise a convergence speed of approximate solution to the exact one when the mesh is refined. Moreover, introduced basis functions are solenoidal, therefore the solenoidal condition for the solution is taken into account precisely, so the spurious numerical solutions are prevented.

Results of numerical experiments are presented for series of different type model problems: some of them have a solution containing only singular component and some of them have a solution containing a singular and regular components. Results of numerical experiment showed that when a finite element mesh is refined a convergence rate of the constructed weighted vector finite element method is $O(h)$, that is more than one and a half times better in comparison with special methods developed for described problem, namely singular complement method and regularization method. Another features of constructed method are algorithmic simplicity and naturalness of the solution determination that is beneficial for numerical computations.

The purpose of the paper is a research of a 2nd order finite difference scheme based on the Z-scheme. This research is the numerical solution of several two-dimensional differential equations simulated the incompressible medium convection.

One of real tasks for similar equations solution is the numerical simulating of strongly non-stationary midscale processes in the Earth ionosphere. Because convection processes in ionospheric plasma are controlled by magnetic field, the plasma incompressibility condition is supposed across the magnetic field. For the same reason, there can be rather high velocities of heat and mass convection along the magnetic field.

Ionospheric simulation relevant task is the research of plasma instability of various scales which started in polar and equatorial regions first of all. At the same time the mid-scale irregularities having characteristic sizes 1–50 km create conditions for development of the small-scale instabilities. The last lead to the F-spread phenomenon which significantly influences the accuracy of positioning satellite systems work and also other space and ground-based radio-electronic systems.

The difference schemes used for simultaneous simulating of such multi-scale processes must to have high resolution. Besides, these difference schemes must to be high resolution on the one hand and monotonic on the other hand. The fact that instabilities strengthen errors of difference schemes, especially they strengthen errors of dispersion type is the reason of such contradictory requirements. The similar swing of errors usually results to nonphysical results at the numerical solution.

At the numerical solution of three-dimensional mathematical models of ionospheric plasma are used the following scheme of splitting on physical processes: the first step of splitting carries out convection along, the second step of splitting carries out convection across. The 2nd order finite difference scheme investigated in the paper solves approximately convection across equations. This scheme is constructed by a monotonized nonlinear procedure on base of the Z-scheme which is one of 2nd order schemes. At this monotonized procedure a nonlinear correction with so-called “oblique differences” is used. “Oblique differences” contain the grid nodes relating to different layers of time.

The researches were conducted for two cases. In the simulating field components of the convection vector had: 1) the constant sign; 2) the variable sign. Dissipative and dispersive characteristics of the scheme for different types of the limiting functions are in number received.

The results of the numerical experiments allow to draw the following conclusions.

1. For the discontinuous initial profile the best properties were shown by the SuperBee limiter.

2. For the continuous initial profile with the big spatial steps the SuperBee limiter is better, and at the small steps the Koren limiter is better.

3. For the smooth initial profile the best results were shown by the Koren limiter.

4. The smooth F limiter showed the results similar to Koren limiter.

5. Limiters of different type leave dispersive errors, at the same time dependences of dispersive errors on the scheme parameters have big variability and depend on the scheme parameters difficulty.

6. The monotony of the considered differential scheme is in number confirmed in all calculations. The property of variation non-increase for all specified functions limiters is in number confirmed for the onedimensional equation.

7. The constructed differential scheme at the steps on time which are not exceeding the Courant's step is monotonous and shows good exactness characteristics for different types solutions. At excess of the Courant's step the scheme remains steady, but becomes unsuitable for instability problems as monotony conditions not satisfied in this case.

Verification of the physical-statistical approach within reliability theory for the simplest cases was carried out, which showed its validity. An analytical solution of the one-dimensional basic equation of the physicalstatistical approach is presented under the assumption of a stationary degradation rate. From a mathematical point of view this equation is the well-known continuity equation, where the role of density is played by the density distribution function of goods in its characteristics phase space, and the role of fluid velocity is played by intensity (rate) degradation processes. The latter connects the general formalism with the specifics of degradation mechanisms. The cases of coordinate constant, linear and quadratic degradation rates are analyzed using the characteristics method. In the first two cases, the results correspond to physical intuition. At a constant rate of degradation, the shape of the initial distribution is preserved, and the distribution itself moves equably from the zero. At a linear rate of degradation, the distribution either narrows down to a narrow peak (in the singular limit), or expands, with the maximum shifting to the periphery at an exponentially increasing rate. The distribution form is also saved up to the parameters. For the initial normal distribution, the coordinates of the largest value of the distribution maximum for its return motion are obtained analytically.

In the quadratic case, the formal solution demonstrates counterintuitive behavior. It consists in the fact that the solution is uniquely defined only on a part of an infinite half-plane, vanishes along with all derivatives on the boundary, and is ambiguous when crossing the boundary. If you continue it to another area in accordance with the analytical solution, it has a two-humped appearance, retains the amount of substance and, which is devoid of physical meaning, periodically over time. If you continue it with zero, then the conservativeness property is violated. The anomaly of the quadratic case is explained, though not strictly, by the analogy of the motion of a material point with an acceleration proportional to the square of velocity. Here we are dealing with a mathematical curiosity. Numerical calculations are given for all cases. Additionally, the entropy of the probability distribution and the reliability function are calculated, and their correlation is traced.

An essential class of problems describes physical processes occurring in non-convex domains containing a corner greater than 180 degrees on the boundary. The solution in a neighborhood of a corner is singular and its finding using classical approaches entails a loss of accuracy. In the paper, we consider stationary, linearized by Picard’s iterations, Navier – Stokes equations governing the flow of a incompressible viscous fluid in the convection form in $L$-shaped domain. An $R_\nu$-generalized solution of the problem in special sets of weighted spaces is defined. A special finite element method to find an approximate $R_\nu$-generalized solution is constructed. Firstly, functions of the finite element spaces satisfy the law of conservation of mass in the strong sense, i.e. at the grid nodes. For this purpose, Scott – Vogelius element pair is used. The fulfillment of the condition of mass conservation leads to the finding more accurate, from a physical point of view, solution. Secondly, basis functions of the finite element spaces are supplemented by weight functions. The degree of the weight function, as well as the parameter $\nu$ in the definition of an $R_\nu$-generalized solution, and a radius of a neighborhood of the singularity point are free parameters of the method. A specially selected combination of them leads to an increase almost twice in the order of convergence rate of an approximate solution to the exact one in relation to the classical approaches. The convergence rate reaches the first order by the grid step in the norms of Sobolev weight spaces. Thus, numerically shown that the convergence rate does not depend on the corner value.

An important role in the construction of mathematical models of dynamic systems is played by inverse problems, which in particular include the problem of parametric identification. Unlike classical models that operate with point values, interval models give upper and lower boundaries on the quantities under study. The paper considers an interpolation approach to solving interval problems of parametric identification of dynamic systems for the case when experimental data are represented by external interval estimates. The purpose of the proposed approach is to find such an interval estimate of the model parameters, in which the external interval estimate of the solution of the direct modeling problem would contain experimental data or minimize the deviation from them. The approach is based on the adaptive interpolation algorithm for modeling dynamic systems with interval uncertainties, which makes it possible to explicitly obtain the dependence of phase variables on system parameters. The task of minimizing the distance between the experimental data and the model solution in the space of interval boundaries of the model parameters is formulated. An expression for the gradient of the objectivet function is obtained. On a representative set of tasks, the effectiveness of the proposed approach is demonstrated.