All issues

The process of heat conduction, accompanied by the first order phase transitions is discussed in this article. Using cellular automates simulation was investigated class of problems that have broad application in practice. In this paper we calculate the temperature distribution in the depth of the soil at different times for a problem of freezing of moist soil. Another task — zone growing — has been modeled by cellular automates too. The coincidence of real and modeling parameters of the system confirms the feasibility of using the selected method of modeling of physical processes.

We now review the main points of mean-field approximation (MFA) in its application to multicomponent stochastic reaction-diffusion systems.

We present the chemical reaction model under study — brusselator. We write the kinetic equations of reaction supplementing them with terms that describe the diffusion of the intermediate components and the fluctuations of the concentrations of the initial products. We simulate the fluctuations as random Gaussian homogeneous and spatially isotropic fields with zero means and spatial correlation functions with a non-trivial structure. The model parameter values correspond to a spatially-inhomogeneous ordered state in the deterministic case.

In the MFA we derive single-site two-dimensional nonlinear self-consistent Fokker–Planck equation in the Stratonovich's interpretation for spatially extended stochastic brusselator, which describes the dynamics of probability distribution density of component concentration values of the system under consideration. We find the noise intensity values appropriate to two types of Fokker–Planck equation solutions: solution with transient bimodality and solution with the multiple alternation of unimodal and bimodal types of probability density. We study numerically the probability density dynamics and time behavior of variances, expectations, and most probable values of component concentrations at various noise intensity values and the bifurcation parameter in the specified region of the problem parameters.

Beginning from some value of external noise intensity inside the ordered phase disorder originates existing for a finite time, and the higher the noise level, the longer this disorder “embryo” lives. The farther away from the bifurcation point, the lower the noise that generates it and the narrower the range of noise intensity values at which the system evolves to the ordered, but already a new statistically steady state. At some second noise intensity value the intermittency of the ordered and disordered phases occurs. The increasing noise intensity leads to the fact that the order and disorder alternate increasingly.

Thus, the scenario of the noise induced order–disorder transition in the system under study consists in the intermittency of the ordered and disordered phases.

We present a simulation methodology for the prediction of ЃgunexpectedЃh bottlenecks, i.e., the bottlenecks that occur suddenly and unexpectedly for drivers on a highway. Such unexpected bottlenecks can be either a moving bottleneck (MB) caused by a slow moving vehicle or a motionless bottleneck caused by a stopped vehicle (SV). Based on simulations of a stochastic microscopic traffic flow model in the framework of KernerЃfs three-phase traffic theory, we show that through the use of a small share of probe vehicles (FCD) randomly distributed in traffic flow the reliable prediction of ЃgunexpectedЃh bottlenecks is possible. We have found that the time dependence of the probability of MB and SV prediction as well as the accuracy of the estimation of MB and SV location depend considerably on sequences of phase transitions from free flow (F) to synchronized flow (S) (F→S transition) and back from synchronized flow to free flow (S→F transition) as well as on speed oscillations in synchronized flow at the bottleneck. In the simulation approach, the identification of F→S and S→F transitions at an unexpected bottleneck has been made in accordance with Kerner's three-phase traffic theory. The presented simulation methodology allows us both the prediction of the unexpected bottleneck that suddenly occurs on a highway and the distinguishing of the origin of the unexpected bottleneck, i.e., whether the unexpected bottleneck has occurred due to a MB or a SV.

One of the promising technologies for enhanced oil recovery in the development of unconventional oil reservoirs is the thermo-gas method. The method is based on the injection of an oxygen-containing mixture into the formation and its transformation into a highly efficient displacing agent miscible with the formation of oil due to spontaneous in-situ oxidative processes. In some cases, this method has great potential compared to other methods of enhanced oil recovery. This paper discusses some issues of the propagation of in-situ combustion waves. Depending on the parameters of the reservoir and the injected mixture, such waves can propagate in different modes. In this paper, only the direct-flow inverse propagation mode is considered. In this mode, the combustion wave propagates in the direction of the oxidant flow and the reaction front lags behind the heatwave, in which the substance (hydrocarbon fractions, porous skeleton, etc.) is heated to temperatures sufficient for the oxidation reaction to occur. The paper presents the results of an analytical study and numerical simulation of the structure of the inverse wave of in-situ combustion. in two-phase flow in a porous layer. Some simplifying assumptions about the thermal properties of fluid phases was accepted, which allow, on the one hand, to modify the in-situ combustion model observable for analysis, and with another is to convey the main features of this process. The solution of the “running wave” type is considered and the conditions of its implementation are specified. Selected two modes of reaction trailing front regime in-situ combustion waves: hydrodynamic and kinetic. Numerical simulation of the in-situ combustion wave propagation was carried out with using the thermohydrodynamical simulator developed for the numerical integration of non-isothermal multicomponent filtration flows accompanied by phase transitions and chemical reaction.

For the production of purified final product in chemical engineering used the process of desublimation. For this purpose, the tank is cooled by liquid nitrogen or cold air. The mixture of gases flows inside the tank and is cooled to the condensation or desublimation temperature some components of the gas mixture. The condensed components are deposited on the walls of the tank. The article presents a mathematical model to calculate the cooling air tanks for desublimation of vapours. A mathematical model based on equations of gas dynamics and describes the movement of cooled air in the duct and the heat exchanger with heat exchange and friction. The heat of the phase transition is taken into account in the boundary condition for the heat equation by setting the heat flux. Heat transfer in the walls of the pipe and in the tank wall is described by the nonstationary heat conduction equations. The solution of the system of equations is carried out numerically. The equations of gas dynamics are solved by the method of S. K. Godunov. The heat equation are solved by an implicit finite difference scheme. The article presents the results of calculations of the cooling of two successively installed tanks. The initial temperature of the tanks is equal to 298 K. Cold air flows through the tubing, through the heat exchanger of the first tank, then through conduit to the heat exchanger second tank. During the 20 minutes of tank cool down to operating temperature. The temperature of the walls of the tanks differs from the air temperature not more than 1 degree. The flow of cooling air allows to maintain constant temperature of the walls of the tank in the process of desublimation components from a gas mixture. The results of analytical evaluation of the time of cooling tank and temperature difference between the tank walls and air with the vapor desublimation. Analytical assessment is based on determining the time of heat relaxation temperature of the tank walls. The results of evaluations are satisfactorily coincide with the results of calculations by the present model. The proposed approach allows calculating the cooling tanks with a flow of cold air supplied via the pipeline system.

Mathematical models of gas dynamics and its computational industry, in our opinion, are far from perfect. We will look at this problem from the point of view of a clear probabilistic micro-model of a gas from hard spheres, relying on both the theory of random processes and the classical kinetic theory in terms of densities of distribution functions in phase space, namely, we will first construct a system of nonlinear stochastic differential equations (SDE), and then a generalized random and nonrandom integro-differential Boltzmann equation taking into account correlations and fluctuations. The key feature of the initial model is the random nature of the intensity of the jump measure and its dependence on the process itself.

Briefly recall the transition to increasingly coarse meso-macro approximations in accordance with a decrease in the dimensionalization parameter, the Knudsen number. We obtain stochastic and non-random equations, first in phase space (meso-model in terms of the Wiener — measure SDE and the Kolmogorov – Fokker – Planck equations), and then — in coordinate space (macro-equations that differ from the Navier – Stokes system of equations and quasi-gas dynamics systems). The main difference of this derivation is a more accurate averaging by velocity due to the analytical solution of stochastic differential equations with respect to the Wiener measure, in the form of which an intermediate meso-model in phase space is presented. This approach differs significantly from the traditional one, which uses not the random process itself, but its distribution function. The emphasis is placed on the transparency of assumptions during the transition from one level of detail to another, and not on numerical experiments, which contain additional approximation errors.

The theoretical power of the microscopic representation of macroscopic phenomena is also important as an ideological support for particle methods alternative to difference and finite element methods.

The paper formulates a mathematical model for hydroelastic oscillations of a plate resting on a nonlinear hardening elastic foundation and interacting with a pulsating fluid layer. The main feature of the proposed model, unlike the wellknown ones, is the joint consideration of the elastic properties of the plate, the nonlinearity of elastic foundation, as well as the dissipative properties of the fluid and the inertia of its motion. The model is represented by a system of equations for a twodimensional hydroelasticity problem including dynamics equation of Kirchhoff’s plate resting on the elastic foundation with hardening cubic nonlinearity, Navier – Stokes equations, and continuity equation. This system is supplemented by boundary conditions for plate deflections and fluid pressure at plate ends, as well as for fluid velocities at the bounding walls. The model was investigated by perturbation method with subsequent use of iteration method for the equations of thin layer of viscous fluid. As a result, the fluid pressure distribution at the plate surface was obtained and the transition to an integrodifferential equation describing bending hydroelastic oscillations of the plate is performed. This equation is solved by the Bubnov –Galerkin method using the harmonic balance method to determine the primary hydroelastic response of the plate and phase response due to the given harmonic law of fluid pressure pulsation at plate ends. It is shown that the original problem can be reduced to the study of the generalized Duffing equation, in which the coefficients at inertial, dissipative and stiffness terms are determined by the physical and mechanical parameters of the original system. The primary hydroelastic response and phases response for the plate are found. The numerical study of these responses is performed for the cases of considering the inertia of fluid motion and the creeping fluid motion for the nonlinear and linearly elastic foundation of the plate. The results of the calculations showed the need to jointly consider the viscosity and inertia of the fluid motion together with the elastic properties of the plate and its foundation, both for nonlinear and linear vibrations of the plate.

Intersections present a very demanding environment for all the parties involved. Challenges arise from complex vehicle trajectories; occasional absence of lane markings to guide vehicles; split phases that prevent determining who has the right of way; invisible vehicle approaches; illegal movements; simultaneous interactions among pedestrians, bicycles and vehicles. Unsurprisingly, most demonstrations of AVs are on freeways; but the full potential of automated vehicles — personalized transit, driverless taxis, delivery vehicles — can only be realized when AVs can sense the intersection environment to efficiently and safely maneuver through intersections.

AVs are equipped with an array of on-board sensors to interpret and suitably engage with their surroundings. Advanced algorithms utilize data streams from such sensors to support the movement of autonomous vehicles through a wide range of traffic and climatic conditions. However, there exist situations, in which additional information about the upcoming traffic environment would be beneficial to better inform the vehicles’ in-built tracking and navigation algorithms. A potential source for such information is from in-pavement sensors at an intersection that can be used to differentiate between motorized and non-motorized modes and track road user movements and interactions. This type of information, in addition to signal phasing, can be provided to the AV as it approaches an intersection, and incorporated into an improved prior for the probabilistic algorithms used to classify and track movement in the AV’s field of vision.

This paper is concerned with the situation in which there are objects that are not visible to the AV. The driving context is that of an intersection, and the lack of visibility is due to other vehicles that obstruct the AV’s view, leading to the creation of blind zones. Such obstruction is commonplace in intersections.

Our objective is:

1) inform a vehicle crossing the intersection about its potential blind zones;

2) inform the vehicle about the presence of agents (other vehicles, bicyclists or pedestrians) in those blind zones.

Corrosion damage to metals and alloys is one of the main problems of strength and durability of metal structures and products operated in contact with chemically aggressive environments. Recently, there has been a growing interest in computer modeling of the evolution of corrosion damage, especially pitting corrosion, for a deeper understanding of the corrosion process, its impact on the morphology, physical and chemical properties of the surface and mechanical strength of the material. This is mainly due to the complexity of analytical and high cost of experimental in situ studies of real corrosion processes. However, the computing power of modern computers allows you to calculate corrosion with high accuracy only on relatively small areas of the surface. Therefore, the development of new mathematical models that allow calculating large areas for predicting the evolution of corrosion damage to metals is currently an urgent problem.

In this paper, the evolution of the corrosion front in the interaction of a polycrystalline metal surface with a liquid aggressive medium was studied using a computer model based on a cellular automat. A distinctive feature of the model is the specification of the solid body structure in the form of Voronoi polygons used for modeling polycrystalline alloys. Corrosion destruction was performed by setting the probability function of the transition between cells of the cellular automaton. It was taken into account that the corrosion strength of the grains varies due to crystallographic anisotropy. It is shown that this leads to the formation of a rough phase boundary during the corrosion process. Reducing the concentration of active particles in a solution of an aggressive medium during a chemical reaction leads to corrosion attenuation in a finite number of calculation iterations. It is established that the final morphology of the phase boundary has a fractal structure with a dimension of 1.323 ± 0.002 close to the dimension of the gradient percolation front, which is in good agreement with the fractal dimension of the etching front of a polycrystalline aluminum-magnesium alloy AlMg6 with a concentrated solution of hydrochloric acid. It is shown that corrosion of a polycrystalline metal in a liquid aggressive medium is a new example of a topochemical process, the kinetics of which is described by the Kolmogorov–Johnson– Meil–Avrami theory.

The repressilator is the first genetic regulatory network in synthetic biology, which was artificially constructed in 2000. It is a closed network of three genetic elements $lacI$, $\lambda cI$ and $tetR$, which have a natural origin, but are not found in nature in such a combination. The promoter of each of the three genes controls the next cistron via the negative feedback, suppressing the expression of the neighboring gene. In our previous paper [Bratsun et al., 2018], we proposed a mathematical model of a delayed repressillator and studied its properties within the framework of a deterministic description. We assume that delay can be both natural, i.e. arises during the transcription / translation of genes due to the multistage nature of these processes, and artificial, i.e. specially to be introduced into the work of the regulatory network using gene engineering technologies. In this work, we apply the stochastic description of dynamic processes in a delayed repressilator, which is an important addition to deterministic analysis due to the small number of molecules involved in gene regulation. The stochastic study is carried out numerically using the Gillespie algorithm, which is modified for time delay systems. We present the description of the algorithm, its software implementation, and the results of benchmark simulations for a onegene delayed autorepressor. When studying the behavior of a repressilator, we show that a stochastic description in a number of cases gives new information about the behavior of a system, which does not reduce to deterministic dynamics even when averaged over a large number of realizations. We show that in the subcritical range of parameters, where deterministic analysis predicts the absolute stability of the system, quasi-regular oscillations may be excited due to the nonlinear interaction of noise and delay. Earlier, we have discovered within the framework of the deterministic description, that there exists a long-lived transient regime, which is represented in the phase space by a slow manifold. This mode reflects the process of long-term synchronization of protein pulsations in the work of the repressilator genes. In this work, we show that the transition to the cooperative mode of gene operation occurs a two order of magnitude faster, when the effect of the intrinsic noise is taken into account. We have obtained the probability distribution of moment when the phase trajectory leaves the slow manifold and have determined the most probable time for such a transition. The influence of the intrinsic noise of chemical reactions on the dynamic properties of the repressilator is discussed.