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An approach to numerical analysis of thermo-hydraulic processes proceeding in a fast-neutron reactor is described in the given article. The description covers physical models, numerical schemes and geometry simplifications accepted in the computational model. Steady-state and dynamic regimes of reactor operation are considered. The steady-state regimes simulate the reactor operation at nominal power. The dynamic regimes simulate the shutdown reactor cooling by means of the heat-removal system.

Simulation of thermo-hydraulic processes is carried out in the FlowVision CFD software. A mathematical model describing the coolant flow in the first loop of the fast-neutron reactor was developed on the basis of the available geometrical model. The flow of the working fluid in the reactor simulator is calculated under the assumption that the fluid density does not depend on pressure, with use a $k–\varepsilon$ turbulence model, with use of a model of dispersed medium, and with account of conjugate heat exchange. The model of dispersed medium implemented in the FlowVision software allowed taking into account heat exchange between the heat-exchanger lops. Due to geometric complexity of the core region, the zones occupied by the two heat exchangers were modeled by hydraulic resistances and heat sources.

Numerical simulation of the coolant flow in the FlowVision software enabled obtaining the distributions of temperature, velocity and pressure in the entire computational domain. Using the model of dispersed medium allowed calculation of the temperature distributions in the second loops of the heat exchangers. Besides that, the variation of the coolant temperature along the two thermal probes is determined. The probes were located in the cool and hot chambers of the fast-neutron reactor simulator. Comparative analysis of the numerical and experimental data has shown that the developed mathematical model is correct and, therefore, it can be used for simulation of thermo-hydraulic processes proceeding in fast-neutron reactors with sodium coolant.

The paper proposes an approach to simulation of a sport game, consisting of a discrete set of separate competitions. According to this approach, such a competition is considered as a random processes, generally — a non-Markov’s one. At first we treat the flow of the game as a Markov’s process, obtaining recursive relationship between the probabilities of achieving certain states of score in a tennis match, as well as secondary indicators of the game, such as expectation and variance of the number of serves to finish the game. Then we use a simulation system, modeling the match, to allow an arbitrary change of the probabilities of the outcomes in the competitions that compose the match. We, for instance, allow the probabilities to depend on the results of previous competitions. Therefore, this paper deals with a modification of the model, previously proposed by the authors for sports games with continuous time.

The proposed approach allows to evaluate not only the probability of the final outcome of the match, but also the probabilities of reaching each of the possible intermediate results, as well as secondary indicators of the game, such as the number of separate competitions it takes to finish the match. The paper includes a detailed description of the construction of a simulation system for a game of a tennis match. Then we consider simulating a set and the whole tennis match by analogy. We show some statements concerning fairness of tennis serving rules, understood as independence of the outcome of a competition on the right to serve first. We perform simulation of a cancelled ATP series match, obtaining its most probable intermediate and final outcomes for three different possible variants of the course of the match.

The main result of this paper is the developed method of simulation of the match, applicable not only to tennis, but also to other types of sports games with discrete time.

In case of vessel wall damage or contact of blood plasma with a foreign surface, the chain of chemical reactions called coagulation cascade is launched that leading to the formation of a fibrin clot. A key enzyme of the coagulation cascade is thrombin, which catalyzes formation of fibrin from fibrinogen. The distribution of thrombin concentration in blood plasma determines spatio-temporal dynamics of clot formation. Contact pathway of blood coagulation triggers the production of thrombin in response to the contact with a negatively charged surface. If the concentration of thrombin generated at this stage is large enough, further production of thrombin takes place due to positive feedback loops of the coagulation cascade. As a result, thrombin propagates in plasma cleaving fibrinogen that results in the clot formation. The concentration profile and the speed of propagation of thrombin are constant and do not depend on the type of the initial activator.

Such behavior of the coagulation system is well described by the traveling wave solutions in a system of “reaction – diffusion” equations on the concentration of blood factors involved in the coagulation cascade. In this study, we carried out detailed analysis of the mathematical model describing the main reaction of the intrinsic pathway of coagulation cascade.We formulate necessary and sufficient conditions of the existence of the traveling wave solutions. For the considered model the existence of such solutions is equivalent to the existence of the wave solutions in the simplified one-equation model describing the dynamics of thrombin concentration derived under the quasi-stationary approximation.

Simplified model also allows us to obtain analytical estimate of the thrombin propagation rate in the considered model. The speed of the traveling wave for one equation is estimated using the narrow reaction zone method and piecewise linear approximation. The resulting formulas give a good approximation of the velocity of propagation of thrombin in the simplified, as well as in the original model.

Financial mathematics is one of the most natural applications for the statistical analysis of time series. Financial time series reflect simultaneous activity of a large number of different economic agents. Consequently, one expects that methods of statistical physics and the theory of random processes can be applied to them.

In this paper, we provide a statistical analysis of time series of the FOREX currency market. Of particular interest is the comparison of the time series behavior depending on the way time is measured: physical time versus trading time measured in the number of elementary price changes (ticks). The experimentally observed statistics of the time series under consideration (euro–dollar for the first half of 2007 and for 2009 and British pound – dollar for 2007) radically differs depending on the choice of the method of time measurement. When measuring time in ticks, the distribution of price increments can be well described by the normal distribution already on a scale of the order of ten ticks. At the same time, when price increments are measured in real physical time, the distribution of increments continues to differ radically from the normal up to scales of the order of minutes and even hours.

To explain this phenomenon, we investigate the statistical properties of elementary increments in price and time. In particular, we show that the distribution of time between ticks for all three time series has a long (1-2 orders of magnitude) power-law tails with exponential cutoff at large times. We obtained approximate expressions for the distributions of waiting times for all three cases. Other statistical characteristics of the time series (the distribution of elementary price changes, pair correlation functions for price increments and for waiting times) demonstrate fairly simple behavior. Thus, it is the anomalously wide distribution of the waiting times that plays the most important role in the deviation of the distribution of increments from the normal. As a result, we discuss the possibility of applying a continuous time random walk (CTRW) model to describe the FOREX time series.

The paper proposes a mathematical model for the therapy of glioma, taking into account the blood-brain barrier, radiotherapy and antibody therapy. The parameters were estimated from experimental data and the evaluation of the effect of parameter values on the effectiveness of treatment and the prognosis of the disease were obtained. The possible variants of sequential use of radiotherapy and the effect of antibodies have been explored. The combined use of radiotherapy with intravenous administration of $mab$ $Cx43$ leads to a potentiation of the therapeutic effect in glioma.

Radiotherapy must precede chemotherapy, as radio exposure reduces the barrier function of endothelial cells. Endothelial cells of the brain vessels fit tightly to each other. Between their walls are formed so-called tight contacts, whose role in the provision of BBB is that they prevent the penetration into the brain tissue of various undesirable substances from the bloodstream. Dense contacts between endothelial cells block the intercellular passive transport.

The mathematical model consists of a continuous part and a discrete one. Experimental data on the volume of glioma show the following interesting dynamics: after cessation of radio exposure, tumor growth does not resume immediately, but there is some time interval during which glioma does not grow. Glioma cells are divided into two groups. The first group is living cells that divide as fast as possible. The second group is cells affected by radiation. As a measure of the health of the blood-brain barrier system, the ratios of the number of BBB cells at the current moment to the number of cells at rest, that is, on average healthy state, are chosen.

The continuous part of the model includes a description of the division of both types of glioma cells, the recovery of BBB cells, and the dynamics of the drug. Reducing the number of well-functioning BBB cells facilitates the penetration of the drug to brain cells, that is, enhances the action of the drug. At the same time, the rate of division of glioma cells does not increase, since it is limited not by the deficiency of nutrients available to cells, but by the internal mechanisms of the cell. The discrete part of the mathematical model includes the operator of radio interaction, which is applied to the indicator of BBB and to glial cells.

Within the framework of the mathematical model of treatment of a cancer tumor (glioma), the problem of optimal control with phase constraints is solved. The patient’s condition is described by two variables: the volume of the tumor and the condition of the BBB. The phase constraints delineate a certain area in the space of these indicators, which we call the survival area. Our task is to find such treatment strategies that minimize the time of treatment, maximize the patient’s rest time, and at the same time allow state indicators not to exceed the permitted limits. Since the task of survival is to maximize the patient’s lifespan, it is precisely such treatment strategies that return the indicators to their original position (and we see periodic trajectories on the graphs). Periodic trajectories indicate that the deadly disease is translated into a chronic one.

The short-term prediction of road traffic condition is one of the main tasks of transportation modelling. The main purpose of which are traffic control, reporting of accidents, avoiding traffic jams due to knowledge of traffic flow and subsequent transportation planning. A number of solutions exist — both model-driven and data driven had proven to be successful in capturing the dynamics of traffic flow. Nevertheless, most space-time models suffer from high mathematical complexity and low efficiency. Artificial Neural Networks, one of the prominent datadriven approaches, show promising performance in modelling the complexity of traffic flow. We present a neural network architecture for traffic flow prediction on a real-world road network graph. The model is based on the combination of a recurrent neural network and graph convolutional neural network. Where a recurrent neural network is used to model temporal dependencies, and a convolutional neural network is responsible for extracting spatial features from traffic. To make multiple few steps ahead predictions, the encoder-decoder architecture is used, which allows to reduce noise propagation due to inexact predictions. To model the complexity of traffic flow, we employ multilayered architecture. Deeper neural networks are more difficult to train. To speed up the training process, we use skip-connections between each layer, so that each layer teaches only the residual function with respect to the previous layer outputs. The resulting neural network was trained on raw data from traffic flow detectors from the US highway system with a resolution of 5 minutes. 3 metrics: mean absolute error, mean relative error, mean-square error were used to estimate the quality of the prediction. It was found that for all metrics the proposed model achieved lower prediction error than previously published models, such as Vector Auto Regression, LSTM and Graph Convolution GRU.

The conjugate problem of disk movement into gas-filled volume of the spring-type safety valve is solved. The questions of determining the physically correct value of the disk initial lift are considered. The review of existing approaches and methods for solving of such type problems is conducted. The formulation of the problem about the valve actuation when the vessel pressure rises and the mathematical model of the actuation processes are given. A special attention to the binding of physical subtasks is paid. Used methods, numerical schemes and algorithms are described. The mathematical modeling is performed on basе the fundamental system of differential equations for viscous gas movement with the equation for displacement of disk valve. The solution of this problem in the axe symmetric statement is carried out numerically using the finite volume method. The results obtained by the viscous and inviscid models are compared. In an inviscid formulation this problem is solved using the Godunov scheme, and in a viscous formulation is solved using the Kurganov – Tadmor method. The dependence of the disk displacement on time was obtained and compared with the experimental data. The pressure distribution on the disk surface, velocity profiles in the cross sections of the gap for different disk heights are given. It is shown that a value of initial drive lift it does not affect on the gas flow and valve movement part dynamic. It can significantly reduce the calculation time of the full cycle of valve work. Immediate isotahs for various elevations of the disk are presented. The comparison of jet flow over critical section is given. The data carried out by two numerical experiments are well correlated with each other. So, the inviscid model can be applied to the numerical modeling of the safety valve dynamic.

This article solves the problem of constructing a neuro-fuzzy model of fuzzy rules formation and using them for objects state evaluation in conditions of uncertainty. Traditional mathematical statistics or simulation modeling methods do not allow building adequate models of objects in the specified conditions. Therefore, at present, the solution of many problems is based on the use of intelligent modeling technologies applying fuzzy logic methods. The traditional approach of fuzzy systems construction is associated with an expert attraction need to formulate fuzzy rules and specify the membership functions used in them. To eliminate this drawback, the automation of fuzzy rules formation, based on the machine learning methods and algorithms, is relevant. One of the approaches to solve this problem is to build a fuzzy neural network and train it on the data characterizing the object under study. This approach implementation required fuzzy rules type choice, taking into account the processed data specificity. In addition, it required logical inference algorithm development on the rules of the selected type. The algorithm steps determine the number and functionality of layers in the fuzzy neural network structure. The fuzzy neural network training algorithm developed. After network training the formation fuzzyproduction rules system is carried out. Based on developed mathematical tool, a software package has been implemented. On its basis, studies to assess the classifying ability of the fuzzy rules being formed have been conducted using the data analysis example from the UCI Machine Learning Repository. The research results showed that the formed fuzzy rules classifying ability is not inferior in accuracy to other classification methods. In addition, the logic inference algorithm on fuzzy rules allows successful classification in the absence of a part of the initial data. In order to test, to solve the problem of assessing oil industry water lines state fuzzy rules were generated. Based on the 303 water lines initial data, the base of 342 fuzzy rules was formed. Their practical approbation has shown high efficiency in solving the problem.

This paper studies electromagnetic fields, frequencies of lasing, and emission thresholds of a drop-shaped microcavity laser. From the mathematical point of view, the original problem is a nonstandard two-parametric eigenvalue problem for the Helmholtz equation on the whole plane. The desired positive parameters are the lasing frequency and the threshold gain, the corresponding eigenfunctions are the amplitudes of the lasing modes. This problem is usually referred to as the lasing eigenvalue problem. In this study, spectral characteristics are calculated numerically, by solving the lasing eigenvalue problem on the basis of the set of Muller boundary integral equations, which is approximated by the Nystr¨om method. The Muller equations have weakly singular kernels, hence the corresponding operator is Fredholm with zero index. The Nyström method is a special modification of the polynomial quadrature method for boundary integral equations with weakly singular kernels. This algorithm is accurate for functions that are well approximated by trigonometric polynomials, for example, for eigenmodes of resonators with smooth boundaries. This approach leads to a characteristic equation for mode frequencies and lasing thresholds. It is a nonlinear algebraic eigenvalue problem, which is solved numerically by the residual inverse iteration method. In this paper, this technique is extended to the numerical modeling of microcavity lasers having a more complicated form. In contrast to the microcavity lasers with smooth contours, which were previously investigated by the Nyström method, the drop has a corner. We propose a special modification of the Nyström method for contours with corners, which takes also the symmetry of the resonator into account. The results of numerical experiments presented in the paper demonstrate the practical effectiveness of the proposed algorithm.

The article is devoted to the numerical study of shock-wave flows in inhomogeneous media–gas mixtures. In this work, a two-speed two-temperature model is used, in which the dispersed component of the mixture has its own speed and temperature. To describe the change in the concentration of the dispersed component, the equation of conservation of “average density” is solved. This study took into account interphase thermal interaction and interphase pulse exchange. The mathematical model allows the carrier component of the mixture to be described as a viscous, compressible and heat-conducting medium. The system of equations was solved using the explicit Mac-Cormack second-order finite-difference method. To obtain a monotone numerical solution, a nonlinear correction scheme was applied to the grid function. In the problem of shock-wave flow, the Dirichlet boundary conditions were specified for the velocity components, and the Neumann boundary conditions were specified for the other unknown functions. In numerical calculations, in order to reveal the dependence of the dynamics of the entire mixture on the properties of the solid component, various parameters of the dispersed phase were considered — the volume content as well as the linear size of the dispersed inclusions. The goal of the research was to determine how the properties of solid inclusions affect the parameters of the dynamics of the carrier medium — gas. The motion of an inhomogeneous medium in a shock duct divided into two parts was studied, the gas pressure in one of the channel compartments is more important than in the other. The article simulated the movement of a direct shock wave from a high-pressure chamber to a low–pressure chamber filled with a dusty medium and the subsequent reflection of a shock wave from a solid surface. An analysis of numerical calculations showed that a decrease in the linear particle size of the gas suspension and an increase in the physical density of the material from which the particles are composed leads to the formation of a more intense reflected shock wave with a higher temperature and gas density, as well as a lower speed of movement of the reflected disturbance reflected wave.