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A variant of the inverse method of characteristics (IMH) is presented, in whose algorithm an additional fractional time step is introduced, which makes it possible to increase the accuracy of calculations due to a more accurate approximation of the characteristics. The calculation formulas of the modified method for the equations of the one-velocity model of a gas-liquid mixture are given, with the help of which one-dimensional and also flat test problems with self-similar solutions are calculated. When solving multidimensional problems, the original system of equations is split into a number of one-dimensional subsystems, for the calculation of which the inverse method of characteristics with a fractional time step is used. Using the proposed method, the following were calculated: the one-dimensional problem of the decay of an arbitrary discontinuity in a dispersed medium; a twodimensional problem of the interaction of a homogeneous gas-liquid flow with an obstacle with an attached shock wave, as well as a flow with a centered rarefaction wave. The results of numerical calculations of these problems are compared with self-similar solutions and their satisfactory agreement is noted. On the example of the Riemann problem with a shock wave, a comparison is made with a number of conservative, non-conservative, first and higher orders of accuracy schemes, from which, in particular, it follows that the presented calculation method, i. e. MIMC, quite competitive. Despite the fact that the application of MIMC requires many times more time than the original inverse method of characteristics (IMC), calculations can be carried out with an increased time step and, in some cases, more accurate results can be obtained. It is noted that the method with a fractional time step has advantages over the IMC in cases where the characteristics of the system are significantly curvilinear. For this reason, the use of MIMC, for example, for the Euler equations is inappropriate, since for the latter the characteristics within the time step differ little from straight lines.

In various applications, i. e., astronomical imaging, electron microscopy, and tomography, images are often damaged by Poisson noise. At the same time, the thermal motion leads to Gaussian noise. Therefore, in such applications, the image is usually corrupted by mixed Poisson – Gaussian noise.

In this paper, we propose a novel method for recovering images corrupted by mixed Poisson – Gaussian noise. In the proposed method, we develop a total variation-based model connected with the nonconvex function and the total generalized variation regularization, which overcomes the staircase artifacts and maintains neat edges.

Numerically, we employ the primal-dual method combined with the classical iteratively reweighted $l_1$ algorithm to solve our minimization problem. Experimental results are provided to demonstrate the superiority of our proposed model and algorithm for mixed Poisson – Gaussian removal to state-of-the-art numerical methods.

When a supersonic air flow interacts with a transverse secondary jet injected into this flow through an orifice on a flat wall, a special flow structure is formed. This flow takes place during fuel injection into combustion chambers of supersonic aircraft engines; therefore, in recent years, various approaches to intensifying gas mixing in this type of flow have been proposed and studied in several countries. The approach proposed in this work implies using spark discharges for pulsed heating of the gas and generating the instabilities in the shear layer at the boundary of the secondary jet. Using simulation in the software package FlowVision 3.13, the characteristics of this flow were obtained in the absence and presence of pulsed-periodic local heat release on the wall on the windward side of the injector opening. A comparison was made of local characteristics at different periodicities of pulsed heating (corresponding to the values of the Strouhal number 0.25 and 0.31). It is shown that pulsed heating can stimulate the formation of perturbations in the shear layer at the jet boundary. For the case of the absence of heating and for two modes of pulsed heating, the values of an integral criterion for mixing efficiency were calculated. It is shown that pulsed heating can lead both to a decrease in the average mixing efficiency and to its increase (up to 9% in the considered heating mode). The calculation method used (unsteady Reynolds-averaged Navier – Stokes equations with a modified $k-\varepsilon$ turbulence model) was validated by considering a typical case of the secondary transverse jet interaction with a supersonic flow, which was studied by several independent research groups and well documented in the literature. The grid convergence was shown for the simulation of this typical case in FlowVision. A quantitative comparison was made of the results obtained from FlowVision calculations with experimental data and calculations in other programs. The results of this study can be useful for specialists dealing with the problems of gas mixing and combustion in a supersonic flow, as well as the development of engines for supersonic aviation.

The work investigates the search for inefficient edges in the model of stable dynamics by Nestrov – de Palma (2003). For this purpose, we prove several general theorems about equilibrium properties, including the condition of equal costs for all used routes that can be extended to all paths involving edges from equilibrium routes. The study demonstrates that the standard problem formulation of finding edges whose removal reduces the cost of travel for all participants has no practical significance because the same edge can be both efficient and inefficient depending on the network’s load. In the work, we introduce the concept of an inefficient edge based on the sensitivity of total driver costs to the costs on the edge. The paper provides an algorithm for finding inefficient edges and presents the results of numerical experiments for the transportation network of the city of Anaheim.

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.

The work analyzes known classes of convolutional neural network models and studies selected from them promising models for detecting flying objects in images. Object detection here refers to the detection, localization in space and classification of flying objects. The work conducts a comprehensive study of selected promising convolutional neural network models in order to identify the most effective ones from them for creating mobile real-time computer vision systems. It is shown that the most suitable models for detecting flying objects in images, taking into account the formulated requirements for mobile real-time computer vision systems, are models of the YOLO family, and five models from this family should be considered: YOLOv4, YOLOv4-Tiny, YOLOv4-CSP, YOLOv7 and YOLOv7-Tiny. An appropriate dataset has been developed for training, validation and comprehensive research of these models. Each labeled image of the dataset includes from one to several flying objects of four classes: “bird”, “aircraft-type unmanned aerial vehicle”, “helicopter-type unmanned aerial vehicle”, and “unknown object” (objects in airspace not included in the first three classes). Research has shown that all convolutional neural network models exceed the specified threshold value by the speed of detecting objects in the image, however, only the YOLOv4-CSP and YOLOv7 models partially satisfy the requirements of the accuracy of detection of flying objects. It was shown that most difficult object class to detect is the “bird” class. At the same time, it was revealed that the most effective model is YOLOv7, the YOLOv4-CSP model is in second place. Both models are recommended for use as part of a mobile real-time computer vision system with condition of additional training of these models on increased number of images with objects of the “bird” class so that they satisfy the requirement for the accuracy of detecting flying objects of each four classes.

In this work, we use analytical and numerical methods to consider the problem of the structure and dynamics of coupled localized nonlinear waves in the sine-Gordon model with three identical attractive extended “impurities”, which are modeled by spatial inhomogeneity of the periodic potential. Two possible types of coupled nonlinear localized waves are found: breather and soliton. The influence of system parameters and initial conditions on the structure, amplitude, and frequency of localized waves was analyzed. Associated oscillations of localized waves of the breather type as in the case of point impurities, are the sum of three harmonic oscillations: in-phase, in-phase-antiphase and antiphase type. Frequency analysis of impurity-localized waves that were obtained during a numerical experiment was performed using discrete Fourier transform. To analyze localized breather-type waves, the numerical finite difference method was used. To carry out a qualitative analysis of the obtained numerical results, the problem was solved analytically for the case of small amplitudes of oscillations localized on impurities. It is shown that, for certain impurity parameters (depth and width), it is possible to obtain localized solitontype waves. The ranges of values of the system parameters in which localized waves of a certain type exist, as well as the region of transition from breather to soliton types of oscillations, have been found. The values of the depth and width of the impurity at which a transition from the breather to the soliton type of localized oscillations is observed were determined. Various scenarios of soliton-type oscillations with negative and positive amplitude values for all three impurities, as well as mixed cases, were obtained and considered. It is shown that in the case when the distance between impurities much less than one, there is no transition region where which the nascent breather, after losing energy through radiation, transforms into a soliton. It is shown that the considered model can be used, for example, to describe the dynamics of magnetization waves in multilayer magnets.

A numerical method is proposed that approximates the equations of the dynamics of a weakly compressible viscous flow in the presence of a polymer component of the flow. The behavior of the flow under the influence of a static external periodic force in a periodic square cell is investigated. The methodology is based on a hybrid approach. The hydrodynamics of the flow is described by a system of Navier – Stokes equations and is numerically approximated by the linearized Godunov method. The polymer field is described by a system of equations for the vector of stretching of polymer molecules $\bf R$, which is numerically approximated by the Kurganov – Tedmor method. The choice of model relationships in the development of a numerical methodology and the selection of modeling parameters made it possible to qualitatively model and study the regime of elastic turbulence at low Reynolds $Re \sim 10^{-1}$. The polymer solution flow dynamics equations differ from the Newtonian fluid dynamics equations by the presence on the right side of the terms describing the forces acting on the polymer component part. The proportionality coefficient $A$ for these terms characterizes the backward influence degree of the polymers number on the flow. The article examines in detail how the flow and its characteristics change depending on the given coefficient. It is shown that with its growth, the flow becomes more chaotic. The flow energy spectra and the spectra of the polymers stretching field are constructed for different values of $A$. In the spectra, an inertial sub-range of the energy cascade is traced for the flow velocity with an indicator $k \sim −4$, for the cascade of polymer molecules stretches with an indicator $−1.6$.

The semiclassical approximation method is applied for solution construction of the Fokker–Planck equation with quadratic nonlocal nonlinearity and various coefficients in models of asset returns estimation. Analitical expressions determining nonlinear evolution operator are obtained in semiclasical approximation.

Modern GPUs are massively-parallel processors, offering substantial amount of computational power in energy-efficient package. We discuss the benefits of utilizing this computing power for modeling problems in bio-informatics, such as molecular dynamics, quantum chemistry and sequence analysis.