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We study the class of first order differential equations in partial derivatives of the Clairaut-type, which are a multidimensional generalization of the ordinary differential Clairaut equation to the case when the unknown function depends on many variables. It is known that the general solution of the Clairaut-type partial differential equation is a family of integral (hyper-) planes. In addition to the general solution, there can be particular solutions, and in some cases a special (singular) solution can be found.

The aim of the paper is to find a singular solution of the Clairaut-type equation in partial derivatives of the first order with a special right-hand side. In the paper, we formulate a criterion for the existence of a special solution of a differential equation of Clairaut type in partial derivatives for the case, when the function of the derivatives is a function of a linear combination of partial derivatives of unknown function. We obtain the singular solution for this type of differential equations with trigonometric functions of a linear combination of $n$-independent variables with arbitrary coefficients. It is shown that the task of finding a special solution is reduced to solving a system of transcendental equations containing initial trigonometric functions. The article describes the procedure for evaluation of a singular solution of Clairaut-type equation; the main idea is to find not partial derivatives of the unknown function, as functions of independent variables, but linear combinations of partial derivatives with some coefficients. This method can be used to find special solutions of Clairaut-type equations, for which this structure is preserved.

The work is organized as follows. The Introduction contains a brief review of some modern results related to the topic of the study of Clairaut-type equations. The Second part is the main one and it includes a formulation of the main task of the work and describes a method of evaluation of singular solutions for the Clairaut-type equations in partial derivatives with a special right-hand side. The main result of the work is to find singular solutions of the Clairaut-type equations containing trigonometric functions. These solutions are given in the main part of the work as an illustrating example for the method described earlier. In Conclusion, we formulate the results of the work and describe future directions of the research.

We present the iterative algorithm that solves numerically both Urysohn type Fredholm and Volterra nonlinear one-dimensional nonsingular integral equations of the second kind to a specified, modest user-defined accuracy. The algorithm is based on descending recursive sequence of quadratures. Convergence of numerical scheme is guaranteed by fixed-point theorems. Picard’s method of integrating successive approximations is of great importance for the existence theory of integral equations but surprisingly very little appears on numerical algorithms for its direct implementation in the literature. We show that successive approximations method can be readily employed in numerical solution of integral equations. By that the quadrature algorithm is thoroughly designed. It is based on the explicit form of fifth-order embedded Runge–Kutta rule with adaptive step-size self-control. Since local error estimates may be cheaply obtained, continuous monitoring of the quadrature makes it possible to create very accurate automatic numerical schemes and to reduce considerably the main drawback of Picard iterations namely the extremely large amount of computations with increasing recursion depth. Our algorithm is organized so that as compared to most approaches the nonlinearity of integral equations does not induce any additional computational difficulties, it is very simple to apply and to make a program realization. Our algorithm exhibits some features of universality. First, it should be stressed that the method is as easy to apply to nonlinear as to linear equations of both Fredholm and Volterra kind. Second, the algorithm is equipped by stopping rules by which the calculations may to considerable extent be controlled automatically. A compact C++-code of described algorithm is presented. Our program realization is self-consistent: it demands no preliminary calculations, no external libraries and no additional memory is needed. Numerical examples are provided to show applicability, efficiency, robustness and accuracy of our approach.

This work is dedicated to application of bicompact schemes to numerical solution of evolutionary hyperbolic equations. The main advantage of this class of schemes lies in combination of two beneficial properties: the first one is spatial approximation of high even order on a stencil that always occupies only one mesh cell; the second one is spectral resolution which is better in comparison to classic compact finite-difference schemes of the same order of spatial approximation. One feature of bicompact schemes is considered: their spatial approximation is rigidly tied to Cartesian meshes (with parallelepiped-shaped cells in three-dimensional case). This feature makes rather challenging any application of bicompact schemes to problems with complex computational domains as treated in the framework of unstructured meshes. This problem is proposed to be solved using well-known methods for treating complex-shaped boundaries and their corresponding boundary conditions on Cartesian meshes. The generalization of bicompact schemes on problems in geometrically complex domains is made in case of gas dynamics problems and Euler equations. The free boundary method is chosen as a particular tool to introduce the influence of arbitrary-shaped solid boundaries on gas flows on Cartesian meshes. A brief description of this method is given, its governing equations are written down. Bicompact schemes of fourth order of approximation in space with locally one-dimensional splitting are constructed for equations of the free boundary method. Its compensation flux is discretized with second order of accuracy. Time stepping in the obtained schemes is done with the implicit Euler method and the third order accurate $L$-stable stiffly accurate three-stage singly diagonally implicit Runge–Kutta method. The designed bicompact schemes are tested on three two-dimensional problems: stationary supersonic flows with Mach number three past one circular cylinder and past three circular cylinders; the non-stationary interaction of planar shock wave with a circular cylinder in a channel with planar parallel walls. The obtained results are in a good agreement with other works: influence of solid bodies on gas flows is physically correct, pressure in control points on solid surfaces is calculated with the accuracy appropriate to the chosen mesh resolution and level of numerical dissipation.

The using of determining the measure of interaction between channels when choosing the configuration structure of a control system for complex dynamic objects is considered in the work. The main methods for determining the measure of interaction between subsystems of complex control systems based on the methods RGA (Relative Gain Array), Dynamic RGA, HIIA (Hankel Interaction Index Array), PM (Participation matrix) are presented. When choosing a control configuration, simple configurations are preferable, as they are simple in design, maintenance and more resistant to failures. However, complex configurations provide higher performance control systems. Processes in large dynamic objects are characterized by a high degree of interaction between process variables. For the design of the control structure interaction measures are used, namely, the selection of the control structure and the decision on the configuration of the controller. The choice of control structure is to determine which dynamic connections should be used to design the controller. When a structure is selected, connections can be used to configure the controller. For large systems, it is proposed to pre-group the components of the vectors of input and output signals of the actuators and sensitive elements into sets in which the number of variables decreases significantly in order to select a control structure. A quantitative estimation of the decentralization of the control system based on minimizing the sum of the off-diagonal elements of the PM matrix is given. An example of estimation the measure of interaction between components of strong coupled subsystems and the measure of interaction between components of weak coupled subsystems is given. A quantitative estimation is given of neglecting the interaction of components of weak coupled subsystems. The construction of a weighted graph for visualizing the interaction of the subsystems of a complex system is considered. A method for the formation of the controllability gramian on the vector of output signals that is invariant to state vector transformations is proposed in the paper. An example of the decomposition of the stabilization system of the components of the flying vehicle angular velocity vector is given. The estimation of measures of the mutual influence of processes in the channels of control systems makes it possible to increase the reliability of the systems when accounting for the use of analytical redundancy of information from various devices, which reduces the mass and energy consumption. Methods for assessing measures of the interaction of processes in subsystems of control systems can be used in the design of complex systems, for example, motion control systems, orientation and stabilization systems of vehicles.

The work is dedicated to investigation of possibility to increase the efficiency of solving external aerodynamic problems. Methodical questions of using locally-adaptive grids and wall functions for numerical simulation of turbulent flows past flying vehicles are studied. Reynolds-averaged Navier–Stokes equations are integrated. The equations are closed by standard $k–\varepsilon$ turbulence model. Subsonic turbulent flow of perfect compressible viscous gas past airfoil RAE 2822 is considered. Calculations are performed in CFD software FlowVision. The efficiency of using the technology of smoothing diffusion fluxes and the Bradshaw formula for turbulent viscosity is analyzed. These techniques are regarded as means of increasing the accuracy of solving aerodynamic problems on locally-adaptive grids. The obtained results show that using the technology of smoothing diffusion fluxes essentially decreases the discrepancy between computed and experimental values of the drag coefficient. In addition, the distribution of the skin friction coefficient over the curvilinear surface of the airfoil becomes more regular. These results indicate that the given technology is an effective way to increase the accuracy of calculations on locally-adaptive grids. The Bradshaw formula for the dynamic coefficient of turbulent viscosity is traditionally used in the SST $k–\omega$ turbulence model. The possibility to implement it in the standard $k–\varepsilon$ turbulence model is investigated in the present article. The calculations show that this formula provides good agreement of integral aerodynamic characteristics and the distribution of the pressure coefficient over the airfoil surface with experimental data. Besides that, it essentially augments the accuracy of simulation of the flow in the boundary layer and in the wake. On the other hand, using the Bradshaw formula in the simulation of the air flow past airfoil RAE 2822 leads to under-prediction of the skin friction coefficient. For this reason, the conclusion is made that practical use of the Bradshaw formula requires its preliminary validation and calibration on reliable experimental data available for the considered flows. The results of the work as a whole show that using the technologies discussed in numerical solution of external aerodynamic problems on locally-adaptive grids together with wall functions provides the computational accuracy acceptable for quick assessment of the aerodynamic characteristics of a flying vehicle. So, one can deduce that the FlowVision software is an effective tool for preliminary design studies, for conceptual design, and for aerodynamic shape optimization.

The simplest and most desirable method of traffic signal control is precalculated regulation, when the parameters of the traffic light object operation are calculated in advance and activated in accordance to a schedule. This work proposes a method of forming a signal plan that allows one to calculate the control programs and set the period of their activity. Preparation of initial data for the calculation includes the formation of a time series of daily traffic intensity with an interval of 15 minutes. When carrying out field studies, it is possible that part of the traffic intensity measurements is missing. To fill up the missing traffic intensity measurements, the spline interpolation method is used. The next step of the method is to calculate the daily set of signal plans. The work presents the interdependencies, which allow one to calculate the optimal durations of the control cycle and the permitting phase movement and to set the period of their activity. The present movement control systems have a limit on the number of control programs. To reduce the signal plans' number and to determine their activity period, the clusterization using the $k$-means method in the transport phase space is introduced In the new daily signal plan, the duration of the phases is determined by the coordinates of the received cluster centers, and the activity periods are set by the elements included in the cluster. Testing on a numerical illustration showed that, when the number of clusters is 10, the deviation of the optimal phase duration from the cluster centers does not exceed 2 seconds. To evaluate the effectiveness of the developed methodology, a real intersection with traffic light regulation was considered as an example. Based on field studies of traffic patterns and traffic demand, a microscopic model for the SUMO (Simulation of Urban Mobility) program was developed. The efficiency assessment is based on the transport losses estimated by the time spent on movement. Simulation modeling of the multiprogram control of traffic lights showed a 20% reduction in the delay time at the traffic light object in comparison with the single-program control. The proposed method allows automation of the process of calculating daily signal plans and setting the time of their activity.

A hyperbolic model of a viscous heat-conducting gas is presented, in which the Maxwell – Cattaneo approach is used to hyperbolize the equations, which provides finite wave propagation velocities. In the modified model, instead of the original Stokes and Fourier laws, their relaxation analogues were used and it is shown that when the relaxation times $\tau_\sigma^{}$ и $\tau_w^{}$ tend to The hyperbolized equations are reduced to zero to the classical Navier – Stokes system of non-hyperbolic type with infinite velocities of viscous and heat waves. It is noted that the hyperbolized system of equations of motion of a viscous heat-conducting gas considered in this paper is invariant not only with respect to the Galilean transformations, but also with respect to rotation, since the Yaumann derivative is used when differentiating the components of the viscous stress tensor in time. To integrate the equations of the model, the hybrid Godunov method (HGM) and the multidimensional nodal method of characteristics were used. The HGM is intended for the integration of hyperbolic systems in which there are equations written both in divergent form and not resulting in such (the original Godunov method is used only for systems of equations presented in divergent form). A linearized solver’s Riemann is used to calculate flow variables on the faces of adjacent cells. For divergent equations, a finitevolume approximation is applied, and for non-divergent equations, a finite-difference approximation is applied. To calculate a number of problems, we also used a non-conservative multidimensional nodal method of characteristics, which is based on splitting the original system of equations into a number of one-dimensional subsystems, for solving which a one-dimensional nodal method of characteristics was used. Using the described numerical methods, a number of one-dimensional problems on the decay of an arbitrary rupture are solved, and a two-dimensional flow of a viscous gas is calculated when a shock jump interacts with a rectangular step that is impermeable to gas.

The article describes an improved paired comparison method, which systematizes in tables the rules of logical conclusions and formulas of checking indices for comparison of technical systems. To achieve this goal, the authors formulate rational rules of logical conclusions in making a paired comparison of the systems. In addition, for the purpose of consistency check of the results of the assessment, the authors introduce parameters such as «the number of scores gained by one system» and «systems’ quality index»; moreover, they design corresponding calculation formulas. For the purposes of practical application of this method to design computer programs, the authors propose to use formalized variants of interconnected tables: a table for processing and systematization of expert information, a table of possible logical conclusions based on the results of comparison of a set number of technical systems and a table of check values in the paired comparison method used in quality assessment of a definite number of technical systems. These tables allow one to organize procedures of the information processing in a more rational way and to predominantly exclude the influence of mistakes on the results of quality assessment of technical systems at the stage of data input. The main positive effect from the implementation of the paired comparison method is observed in a considerable reduction of time and resources needed to organize experts work, process expert information, and to prepare and conduct distant interviews with experts (on the Internet or a local computer network of an organization). This effect is achieved by a rational use of input data of the quality of the systems to be assessed. The proposed method is applied to computer programs used in assessing the effectiveness and stability of large technical systems.

Recently, saddle point problems have received much attention due to their powerful modeling capability for a lot of problems from diverse domains. Applications of these problems occur in many applied areas, such as robust optimization, distributed optimization, game theory, and many applications in machine learning such as empirical risk minimization and generative adversarial networks training. Therefore, many researchers have actively worked on developing numerical methods for solving saddle point problems in many different settings. This paper is devoted to developing a numerical method for solving saddle point problems in the nonconvex uniformly-concave setting. We study a general class of saddle point problems with composite structure and H\"older-continuous higher-order derivatives. To solve the problem under consideration, we propose an approach in which we reduce the problem to a combination of two auxiliary optimization problems separately for each group of variables, the outer minimization problem w.r.t. primal variables, and the inner maximization problem w.r.t the dual variables. For solving the outer minimization problem, we use the Adaptive Gradient Method, which is applicable for nonconvex problems and also works with an inexact oracle that is generated by approximately solving the inner problem. For solving the inner maximization problem, we use the Restarted Unified Acceleration Framework, which is a framework that unifies the high-order acceleration methods for minimizing a convex function that has H\"older-continuous higher-order derivatives. Separate complexity bounds are provided for the number of calls to the first-order oracles for the outer minimization problem and higher-order oracles for the inner maximization problem. Moreover, the complexity of the whole proposed approach is then estimated.

In this study we discuss methods to solve optimal control problems based on neural network techniques. We study hierarchical dynamical two-level system for surface water quality control. The system consists of a supervisor (government) and a few agents (enterprises). We consider this problem from the point of agents. In this case we solve optimal control problem with constraints. To solve this problem, we use Pontryagin’s maximum principle, with which we obtain optimality conditions. To solve emerging ODEs, we use feedforward neural network. We provide a review of existing techniques to study such problems and a review of neural network’s training methods. To estimate the error of numerical solution, we propose to use defect analysis method, adapted for neural networks. This allows one to get quantitative error estimations of numerical solution. We provide examples of our method’s usage for solving synthetic problem and a surface water quality control model. We compare the results of this examples with known solution (when provided) and the results of shooting method. In all cases the errors, estimated by our method are of the same order as the errors compared with known solution. Moreover, we study surface water quality control problem when no solutions is provided by other methods. This happens because of relatively large time interval and/or the case of several agents. In the latter case we seek Nash equilibrium between agents. Thus, in this study we show the ability of neural networks to solve various problems including optimal control problems and differential games and we show the ability of quantitative estimation of an error. From the numerical results we conclude that the presence of the supervisor is necessary for achieving the sustainable development.