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This paper addresses the problem of the plane-parallel motion of an elliptic foil with an attached point vortex of constant strength in an ideal fluid. It is assumed that the position of the vortex relative to the foil remains unchanged during motion. The flow of the fluid outside the body is assumed to be potential (except for the singularity corresponding to a point vortex), and the flow around the body is noncirculatory. Special attention is given to the general position case in which the point vortex does not lie on the continuations of the semiaxes of the ellipse. The problem under consideration is described by a system of six first-order differential equations. After reduction by the motion group of the plane E(2) it reduces to a system of three differential equations. An analysis of this reduced system is made. It is shown that this system admits one to five fixed points which correspond to motions of the ellipse in various circles. By numerically investigating the phase flow of the reduced system near fixed points, it is shown that, in the general case, the system admits no invariant measure with a smooth positive definite density. Parameter values are found for which one of the fixed points of the reduced system is an unstable node-focus. It is shown that, as the variation of the parameters is continued, an unstable limit cycle can arise from an unstable fixed point via an Andronov – Hopf bifurcation. An analysis is made of bifurcations of this limit cycle for the case where the position of the point vortex relative to the ellipse changes. By constructing a parametric bifurcation diagram, it is shown that, as the system’s parameters are varied, the limit cycle undergoes a cascade of period-doubling bifurcations, giving rise to a chaotic repeller (a reversed-time attractor). To carry out a numerical analysis of the problem, the method of constructing a twodimensional Poincaré map is used. The search for and analysis of simple and strange repellers were performed backward in time.

The paper provides a review of the existing methods of signals’ processing within the conditions of the Rice statistical model applicability. There are considered the principle development directions, the existing limitations and the improvement possibilities concerning the methods of solving the tasks of noise suppression and analyzed signals’ filtration by the example of magnetic-resonance visualization. A conception of a new approach to joint calculation of Rician signal’s both parameters has been developed based on the method of moments in two variants of its implementation. The computer simulation and the comparative analysis of the obtained numerical results have been conducted.

The technique of simplification of mathematical model of a chemical reaction by reducing the number of steps of the reaction scheme, based on an analysis of sensitivity to changes in the objective function of the model parameters, is proposed. The reduced scheme of model reaction of formaldehyde oxidation is received. Functional characterizes the measure of proximity to the calculated values for the initial kinetic reaction scheme and the scheme resulting disturbance of its parameters. The advantage of this technique is the ability to analyze complex kinetic schemes and reduction of kinetic models to a size suitable for practical use. The results of computational experiments under different reaction conditions can be included in the functional and thus to receive the reduce scheme, which is consistent the detailed scheme for the desired range of conditions. Sensitivity analysis of the functional model allows to identify those parameters, which provide the largest (or smallest) the contribution to the result of the process simulation. The mathematical model can contain parameters, which change of values do not affect the qualitative and quantitative description of the process. The contribution of these parameters in the functional value won’t be of great importance. Thus it can be eliminated from consideration, which do not serve for modeling kinetic curves substances. The kinetic scheme of formaldehyde oxidation, the detailed mechanism which includes 25 stages and 15 substances, were investigated using this method. On the basis of the local and global sensitivity analysis, the most important stage of the process that affect the overall dynamics of the target concentrations of the reaction. The reduced scheme of model reaction of formaldehyde oxidation is received. This scheme also describes the behavior of the main substances, as detailed scheme, but has a much smaller number of reaction stages. The results of the comparative analysis of modeling of formaldehyde oxidation on detailed and reduced schemes are given. Computational aspects of the problems of chemical kinetics by Sobol’ global method an example of this reaction are specified. The comparison results are local, global and total sensitivity indices are given.

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.

Nowadays the random search became a widespread and effective tool for solving different complex optimization and adaptation problems. In this work, the problem of an average duration of a random search for one object by another is regarded, depending on various factors on a square field. The problem solution was carried out by holding total experiment with 4 factors and orthogonal plan with 54 lines. Within each line, the initial conditions and the cellular automaton transition rules were simulated and the duration of the search for one object by another was measured. As a result, the regression model of average duration of a random search for an object depending on the four factors considered, specifying the initial positions of two objects, the conditions of their movement and detection is constructed. The most significant factors among the factors considered in the work that determine the average search time are determined. An interpretation is carried out in the problem of random search for an object from the constructed model. The important result of the work is that the qualitative and quantitative influence of initial positions of objects, the size of the lattice and the transition rules on the average duration of search is revealed by means of model obtained. It is shown that the initial neighborhood of objects on the lattice does not guarantee a quick search, if each of them moves. In addition, it is quantitatively estimated how many times the average time of searching for an object can increase or decrease with increasing the speed of the searching object by 1 unit, and also with increasing the field size by 1 unit, with different initial positions of the two objects. The exponential nature of the growth in the number of steps for searching for an object with an increase in the lattice size for other fixed factors is revealed. The conditions for the greatest increase in the average search duration are found: the maximum distance of objects in combination with the immobility of one of them when the field size is changed by 1 unit. (that is, for example, with $4 \times 4$ at $5 \times 5$) can increase the average search duration in $e^{1.69} \approx 5.42$. The task presented in the work may be relevant from the point of view of application both in the landmark for ensuring the security of the state, and, for example, in the theory of mass service.

A hierarchical method of mathematical and computer modeling of interval-stochastic thermal processes in complex electronic systems for various purposes is developed. The developed concept of hierarchical structuring reflects both the constructive hierarchy of a complex electronic system and the hierarchy of mathematical models of heat exchange processes. Thermal processes that take into account various physical phenomena in complex electronic systems are described by systems of stochastic, unsteady, and nonlinear partial differential equations and, therefore, their computer simulation encounters considerable computational difficulties even with the use of supercomputers. The hierarchical method avoids these difficulties. The hierarchical structure of the electronic system design, in general, is characterized by five levels: Level 1 — the active elements of the ES (microcircuits, electro-radio-elements); Level 2 — electronic module; Level 3 — a panel that combines a variety of electronic modules; Level 4 — a block of panels; Level 5 — stand installed in a stationary or mobile room. The hierarchy of models and modeling of stochastic thermal processes is constructed in the reverse order of the hierarchical structure of the electronic system design, while the modeling of interval-stochastic thermal processes is carried out by obtaining equations for statistical measures. The hierarchical method developed in the article allows to take into account the principal features of thermal processes, such as the stochastic nature of thermal, electrical and design factors in the production, assembly and installation of electronic systems, stochastic scatter of operating conditions and the environment, non-linear temperature dependencies of heat exchange factors, unsteady nature of thermal processes. The equations obtained in the article for statistical measures of stochastic thermal processes are a system of 14 non-stationary nonlinear differential equations of the first order in ordinary derivatives, whose solution is easily implemented on modern computers by existing numerical methods. The results of applying the method for computer simulation of stochastic thermal processes in electron systems are considered. The hierarchical method is applied in practice for the thermal design of real electronic systems and the creation of modern competitive devices.

We consider a model of spontaneous formation of a computational structure in the human brain for solving a given class of tasks in the process of performing a series of similar tasks. The model is based on a special definition of a numerical measure of the complexity of the solution algorithm. This measure has an informational property: the complexity of a computational structure consisting of two independent structures is equal to the sum of the complexities of these structures. Then the probability of spontaneous occurrence of the structure depends exponentially on the complexity of the structure. The exponential coefficient requires experimental determination for each type of problem. It may depend on the form of presentation of the source data and the procedure for issuing the result. This estimation method was applied to the results of a series of experiments that determined the strategy for solving a series of similar problems with a growing number of initial data. These experiments were described in previously published papers. Two main strategies were considered: sequential execution of the computational algorithm, or the use of parallel computing in those tasks where it is effective. These strategies differ in how calculations are performed. Using an estimate of the complexity of schemes, you can use the empirical probability of one of the strategies to calculate the probability of the other. The calculations performed showed a good match between the calculated and empirical probabilities. This confirms the hypothesis about the spontaneous formation of structures that solve the problem during the initial training of a person. The paper contains a brief description of experiments, detailed computational schemes and a strict definition of the complexity measure of computational structures and the conclusion of the dependence of the probability of structure formation on its complexity.

The influence of solar activity on various processes on Earth has long been the subject of close study, which resulted in the appearance of the term “space weather”. The most striking manifestation of solar activity are the so-called “solar flares”, which are explosive releases of energy in the solar atmosphere, resulting in a flow of photons and charged particles reaching the Earth with a slight delay. After two or three days, a plasma flow reaches the Earth. Thus, a solar flare is an event stretched out in time for several days. The impact of solar flares on human health and the technosphere is a popular subject for discussion and scientific research. This article provides a quantitative assessment of the trigger effect of solar flares on the release of energy as a result of seismic events. The article provides an estimate in the form of a “percentage” of the released seismic energy of the trigger effect of solar flares on the release of seismic energy worldwide and in 8 areas of the Pacific Fire Ring. The initial data are a time series of solar flares from July 31, 1996 to the end of 2024. The time points of the greatest local extremes of solar flare intensity and released seismic energy were studied in successive time intervals of 1 day. For each pair of time sequences in sliding time windows, the “lead measures” of each time sequence relative to the other were estimated using a parametric model of the intensity of interacting point processes. The difference between the “direct” lead measure of the time points of local extremes of solar flare intensity relative to the moments of maximum released seismic energy and the “reverse” lead measure was calculated. The average value of the difference in lead measures provides an estimate of the share of the intensity of seismic events for which solar flares are a trigger.

The approach given in this work helps to organize the operative control over action intensity of pollution emissions in atmosphere. The approach allows to sequential estimate of unknown intensity of atmospheric pollution source on the base of concentration measurements of impurity in several stationary control points is offered in the work. The inverse problem was solved by means of the step-by-step regularization and the sequential function specification method. The solution is presented in the form of the digital filter in terms of Hamming. The fitting algorithm of regularization parameter r for function specification method is described.

Тhe new test-signals forming method for correlation identification of a nonlinear system based on Lee–Shetzen cross-correlation approach is developed and tested. Numerical Gauss–Newton algorithm is applied to correct autocorrelation functions of test signals. The achieved test-signals have length less than 40 000 points and allow to measure the 2nd order Wiener kernels with a linear resolution up to 32 points, the 3rd order Wiener kernels with a linear resolution up to 12 points and the 4th order Wiener kernels with a linear resolution up to 8 points.