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The article covered results of three-dimensional modeling of ecologic situation of shallow water on the example of the Azov Sea with using schemes of increased order of accuracy on multiprocessor computer system of Southern Federal University. Discrete analogs of convective and diffusive transfer operators of the fourth order of accuracy in the case of partial occupancy of cells were constructed and studied. The developed scheme of the high (fourth) order of accuracy were used for solving problems of aquatic ecology and modeling spatial distribution of polluting nutrients, which caused growth of phytoplankton, many species of which are toxic and harmful. The use of schemes of the high order of accuracy are improved the quality of input data and decreased the error in solutions of model tasks of aquatic ecology. Numerical experiments were conducted for the problem of transportation of substances on the basis of the schemes of the second and fourth orders of accuracy. They’re showed that the accuracy was increased in 48.7 times for diffusion-convection problem. The mathematical algorithm was proposed and numerically implemented, which designed to restore the bottom topography of shallow water on the basis of hydrographic data (water depth at individual points or contour level). The map of bottom relief of the Azov Sea was generated with using this algorithm. It’s used to build fields of currents calculated on the basis of hydrodynamic model. The fields of water flow currents were used as input data of the aquatic ecology models. The library of double-layered iterative methods was developed for solving of nine-diagonal difference equations. It occurs in discretization of model tasks of challenges of pollutants concentration, plankton and fish on multiprocessor computer system. It improved the precision of the calculated data and gave the possibility to obtain operational forecasts of changes in ecologic situation of shallow water in short time intervals.

It is known that the sound speed in medium that contain highly compressible inclusions, e.g. air pores in an elastic medium or gas bubbles in the liquid may be significantly reduced compared to a homogeneous medium. Effective nonlinear parameter of medium, describing the manifestation of nonlinear effects, increases hundreds and thousands of times because of the large differences in the compressibility of the inclusions and the medium. Spatial change in the concentration of such inclusions leads to the variable local sound speed, which in turn calls the spatial-temporal redistribution of acoustic energy in the wave and the distortion of its temporal profiles and cross-section structure of bounded beams. In particular, focal areas can form. Under certain conditions, the sound channel is formed that provides waveguide propagation of acoustic signals in the medium with similar inclusions. Thus, it is possible to control spatial-temporal structure of acoustic waves with the introduction of highly compressible inclusions with a given spatial distribution and concentration. The aim of this work is to study the propagation of acoustic waves in a rubberlike material with non-uniform spatial air cavities. The main objective is the development of an adequate theory of such structurally inhomogeneous media, theory of propagation of nonlinear acoustic waves and beams in these media, the calculation of the acoustic fields and identify the communication parameters of the medium and inclusions with characteristics of propagating waves. In the work the evolutionary self-consistent equation with integro-differential term is obtained describing in the low-frequency approximation propagation of intense acoustic beams in a medium with highly compressible cavities. In this equation the secondary acoustic field is taken into account caused by the dynamics of the cavities oscillations. The method is developed to obtain exact analytical solutions for nonlinear acoustic field of the beam on its axis and to calculate the field in the focal areas. The obtained results are applied to theoretical modeling of a material with non-uniform distribution of strongly compressible inclusions.

The paper considers the problem of estimating the parameters of time series described by regression models with Markov switching of two regimes at random instants of time with independent Gaussian noise. For the solution, we propose a variant of the EM algorithm based on the iterative procedure, during which an estimation of the regression parameters is performed for a given sequence of regime switching and an evaluation of the switching sequence for the given parameters of the regression models. In contrast to the well-known methods of estimating regression parameters in the models with Markov switching, which are based on the calculation of a posteriori probabilities of discrete states of the switching sequence, in the paper the estimates are calculated of the switching sequence, which are optimal by the criterion of the maximum of a posteriori probability. As a result, the proposed algorithm turns out to be simpler and requires less calculations. Computer modeling allows to reveal the factors influencing accuracy of estimation. Such factors include the number of observations, the number of unknown regression parameters, the degree of their difference in different modes of operation, and the signal-to-noise ratio which is associated with the coefficient of determination in regression models. The proposed algorithm is applied to the problem of estimating parameters in regression models for the rate of daily return of the RTS index, depending on the returns of the S&P 500 index and Gazprom shares for the period from 2013 to 2018. Comparison of the estimates of the parameters found using the proposed algorithm is carried out with the estimates that are formed using the EViews econometric package and with estimates of the ordinary least squares method without taking into account regimes switching. The account of regimes switching allows to receive more exact representation about structure of a statistical dependence of investigated variables. In switching models, the increase in the signal-to-noise ratio leads to the fact that the differences in the estimates produced by the proposed algorithm and using the EViews program are reduced.

We consider “predator – prey” model taking into account the competition of prey, predator for different from the prey resources, and their interaction described by the second type Holling trophic function. An analysis of the attractors is carried out depending on the coefficient of competition of predators. In the deterministic case, this model demonstrates the complex behavior associated with the local (Andronov –Hopf and saddlenode) and global (birth of a cycle from a separatrix loop) bifurcations. An important feature of this model is the disappearance of a stable cycle due to a saddle-node bifurcation. As a result of the presence of competition in both populations, parametric zones of mono- and bistability are observed. In parametric zones of bistability the system has either coexisting two equilibria or a cycle and equilibrium. Here, we investigate the geometrical arrangement of attractors and separatrices, which is the boundary of basins of attraction. Such a study is an important component in understanding of stochastic phenomena. In this model, the combination of the nonlinearity and random perturbations leads to the appearance of new phenomena with no analogues in the deterministic case, such as noise-induced transitions through the separatrix, stochastic excitability, and generation of mixed-mode oscillations. For the parametric study of these phenomena, we use the stochastic sensitivity function technique and the confidence domain method. In the bistability zones, we study the deformations of the equilibrium or oscillation regimes under stochastic perturbation. The geometric criterion for the occurrence of such qualitative changes is the intersection of confidence domains and the separatrix of the deterministic model. In the zone of monostability, we evolve the phenomena of explosive change in the size of population as well as extinction of one or both populations with minor changes in external conditions. With the help of the confidence domains method, we solve the problem of estimating the proximity of a stochastic population to dangerous boundaries, upon reaching which the coexistence of populations is destroyed and their extinction is observed.

The paper uses methods of mathematical modeling to estimate a zooplankton influence on the dynamics of phytoplankton abundance. We propose a three-component model of the “phytoplankton–zooplankton” community with discrete time, considering a heterogeneity of zooplankton according to the developmental stage and type of feeding; the model takes into account cannibalism in zooplankton community, during which mature individuals of some of its species consume juvenile ones. Survival rates at the early stages of zooplankton life cycle depend explicitly on the interaction between zooplankton and phytoplankton. Loss of phytoplankton biomass because of zooplankton consumption is explicitly considered. We use the Holling functional response of type II to describe saturation during biomass consumption. The dynamics of the phytoplankton community is represented by the Ricker model, which allows to take into account the restriction of phytoplankton biomass growth by the availability of external resources (mineral nutrition, oxygen, light, etc.) implicitly.

The study analyzed scenarios of the transition from stationary dynamics to fluctuations in the size of phytoand zooplankton for various values of intrapopulation parameters determining the nature of the dynamics of the species constituting the community, and the parameters of their interaction. The focus is on exploring the complex modes of community dynamics. In the framework of the model used for describing dynamics of phytoplankton in the absence of interspecific interaction, phytoplankton dynamics undergoes a series of perioddoubling bifurcations. At the same time, with zooplankton appearance, the cascade of period-doubling bifurcations in phytoplankton and the community as a whole is realized earlier (at lower reproduction rates of phytoplankton cells) than in the case when phytoplankton develops in isolation. Furthermore, the variation in the cannibalism level in zooplankton can significantly change both the existing dynamics in the community and its bifurcation; e.g., with a certain structure of zooplankton food relationships the realization of Neimark–Sacker bifurcation scenario in the community is possible. Considering the cannibalism level in zooplankton can change due to the natural maturation processes and achievement of the carnivorous stage by some individuals, one can expect pronounced changes in the dynamic mode of the community, i.e. abrupt transitions from regular to quasiperiodic dynamics (according to Neimark–Sacker scenario) and further cycles with a short period (the implementation of period halving bifurcation).

The Lipschitz continuous property has been used for a long time to solve the global optimization problem and continues to be used. Here we can mention the work of Piyavskii, Yevtushenko, Strongin, Shubert, Sergeyev, Kvasov and others. Most papers assume a priori knowledge of the Lipschitz constant, but the derivation of this constant is a separate problem. Further still, we must prove that an objective function is really Lipschitz, and it is a complicated problem too. In the case where the Lipschitz continuity is established, Strongin proposed an algorithm for global optimization of a satisfying Lipschitz condition on a compact interval function without any a priori knowledge of the Lipschitz estimate. The algorithm not only finds a global extremum, but it determines the Lipschitz estimate too. It is known that every function that satisfies the Lipchitz condition on a compact convex set is uniformly continuous, but the reverse is not always true. However, there exist models (Arutyunova, Dulliev, Zabotin) whose study requires a minimization of the continuous but definitely not Lipschitz function. One of the algorithms for solving such a problem was proposed by R. J. Vanderbei. In his work he introduced some generalization of the Lipchitz property named $\varepsilon$-Lipchitz and proved that a function defined on a compact convex set is uniformly continuous if and only if it satisfies the $\varepsilon$-Lipchitz condition. The above-mentioned property allowed him to extend Piyavskii’s method. However, Vanderbei assumed that for a given value of $\varepsilon$ it is possible to obtain an associate Lipschitz $\varepsilon$-constant, which is a very difficult problem. Thus, there is a need to construct, for a function continuous on a compact convex domain, a global optimization algorithm which works in some way like Strongin’s algorithm, i.e., without any a priori knowledge of the Lipschitz $\varepsilon$-constant. In this paper we propose an extension of Strongin’s global optimization algorithm to a function continuous on a compact interval using the $\varepsilon$-Lipchitz conception, prove its convergence and solve some numerical examples using the software that implements the developed method.

In this paper we consider mathematical model to control water quality. We study a system with two-level hierarchy: one environmental organization (supervisor) at the top level and a few industrial enterprises (agents) at the lower level. The main goal of the supervisor is to keep water pollution level below certain value, while enterprises pollute water, as a side effect of the manufacturing process. Supervisor achieves its goal by charging a penalty for enterprises. On the other hand, enterprises choose how much to purify their wastewater to maximize their income.The fee increases the budget of the supervisor. Moreover, effulent fees are charged for the quantity and/or quality of the discharged pollution. Unfortunately, in practice, such charges are ineffective due to the insufficient tax size. The article solves the problem of determining the optimal size of the charge for pollution discharge, which allows maintaining the quality of river water in the rear range.

We describe system members goals with target functionals, and describe water pollution level and enterprises state as system of ordinary differential equations. We consider the problem from both supervisor and enterprises sides. From agents’ point a normal-form game arises, where we search for Nash equilibrium and for the supervisor, we search for Stackelberg equilibrium. We propose numerical algorithms for finding both Nash and Stackelberg equilibrium. When we construct Nash equilibrium, we solve optimal control problem using Pontryagin’s maximum principle. We construct Hamilton’s function and solve corresponding system of partial differential equations with shooting method and finite difference method. Numerical calculations show that the low penalty for enterprises results in increasing pollution level, when relatively high penalty can result in enterprises bankruptcy. This leads to the problem of choosing optimal penalty, which requires considering problem from the supervisor point. In that case we use the method of qualitatively representative scenarios for supervisor and Pontryagin’s maximum principle for agents to find optimal control for the system. At last, we compute system consistency ratio and test algorithms for different data. The results show that a hierarchical control is required to provide system stability.

A simplified implicit Euler method was analyzed as an alternative to the explicit Euler method, which is a commonly used method in numerical modeling in electrophysiology. The majority of electrophysiological models are quite stiff, since the dynamics they describe includes a wide spectrum of time scales: a fast depolarization, that lasts milliseconds, precedes a considerably slow repolarization, with both being the fractions of the action potential observed in excitable cells. In this work we estimate stiffness by a formula that does not require calculation of eigenvalues of the Jacobian matrix of the studied ODEs. The efficiency of the numerical methods was compared on the case of typical representatives of detailed and conceptual type models of excitable cells: Hodgkin–Huxley model of a neuron and Aliev–Panfilov model of a cardiomyocyte. The comparison of the efficiency of the numerical methods was carried out via norms that were widely used in biomedical applications. The stiffness ratio’s impact on the speedup of simplified implicit method was studied: a real gain in speed was obtained for the Hodgkin–Huxley model. The benefits of the usage of simple and high-order methods for electrophysiological models are discussed along with the discussion of one method’s stability issues. The reasons for using simplified instead of high-order methods during practical simulations were discussed in the corresponding section. We calculated higher order derivatives of the solutions of Hodgkin-Huxley model with various stiffness ratios; their maximum absolute values appeared to be quite large. A numerical method’s approximation constant’s formula contains the latter and hence ruins the effect of the other term (a small factor which depends on the order of approximation). This leads to the large value of global error. We committed a qualitative stability analysis of the explicit Euler method and were able to estimate the model’s parameters influence on the border of the region of absolute stability. The latter is used when setting the value of the timestep for simulations a priori.

One of problems in developing the gas condensate fields lies on the fact that the condensed hydrocarbons in the gas-bearing layer can get stuck in the pores of the formation and hence cannot be extracted. In this regard, research is underway to increase the recoverability of hydrocarbons in such fields. This research includes a wide range of studies on mathematical simulations of the passage of gas condensate mixtures through a porous medium under various conditions.

In the present work, within the classical approach based on the Darcy law and the law of continuity of flows, we formulate an initial-boundary value problem for a system of nonlinear differential equations that describes a depletion of a multicomponent gas-condensate mixture in porous reservoir. A computational scheme is developed on the basis of the finite-difference approximation and the fourth order Runge .Kutta method. The scheme can be used for simulations both in the spatially one-dimensional case, corresponding to the conditions of the laboratory experiment, and in the two-dimensional case, when it comes to modeling a flat gas-bearing formation with circular symmetry.

The computer implementation is based on the combination of C++ and Maple tools, using the MPI parallel programming technique to speed up the calculations. The calculations were performed on the HybriLIT cluster of the Multifunctional Information and Computing Complex of the Laboratory of Information Technologies of the Joint Institute for Nuclear Research.

Numerical results are compared with the experimental data on the pressure dependence of output of a ninecomponent hydrocarbon mixture obtained at a laboratory facility (VNIIGAZ, Ukhta). The calculations were performed for two types of porous filler in the laboratory model of the formation: terrigenous filler at 25 .„R and carbonate one at 60 .„R. It is shown that the approach developed ensures an agreement of the numerical results with experimental data. By fitting of numerical results to experimental data on the depletion of the laboratory reservoir, we obtained the values of the parameters that determine the inter-phase transition coefficient for the simulated system. Using the same parameters, a computer simulation of the depletion of a thin gas-bearing layer in the circular symmetry approximation was carried out.

The article presents the numerical modeling and study of the kinetic model of propane pyrolysis. The study of the reaction kinetics is a necessary stage in modeling the dynamics of the gas flow in the reactor.

The kinetic model of propane pyrolysis is a nonlinear system of ordinary differential equations of the first order with parameters, the role of which is played by the reaction rate constants. Math modeling of processes is based on the use of the mass conservation law. To solve an initial (forward) problem, implicit methods for solving stiff ordinary differential equation systems are used. The model contains 60 input kinetic parameters and 17 output parameters corresponding to the reaction substances, of which only 9 are observable. In the process of solving the problem of estimating parameters (inverse problem), there is a question of non-uniqueness of the set of parameters that satisfy the experimental data. Therefore, before solving the inverse problem, the possibility of determining the parameters of the model is analyzed (analysis of identifiability).

To analyze identifiability, we use the orthogonal method, which has proven itself well for analyzing models with a large number of parameters. The algorithm is based on the analysis of the sensitivity matrix by the methods of differential and linear algebra, which shows the degree of dependence of the unknown parameters of the models on the given measurements. The analysis of sensitivity and identifiability showed that the parameters of the model are stably determined from a given set of experimental data. The article presents a list of model parameters from most to least identifiable. Taking into account the analysis of the identifiability of the mathematical model, restrictions were introduced on the search for less identifiable parameters when solving the inverse problem.

The inverse problem of estimating the parameters was solved using a genetic algorithm. The article presents the found optimal values of the kinetic parameters. A comparison of the experimental and calculated dependences of the concentrations of propane, main and by-products of the reaction on temperature for different flow rates of the mixture is presented. The conclusion about the adequacy of the constructed mathematical model is made on the basis of the correspondence of the results obtained to physicochemical laws and experimental data.