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This article represents numerical simulation technique for determining effective spectral electromagnetic properties (effective electrical conductivity and relative dielectric permittivity) of saturated porous media. Information about these properties is vastly applied during the interpretation of petrophysical exploration data of boreholes and studying of rock core samples. The main feature of the present paper consists in the fact, that it involves three-dimensional saturated digital rock models, which were constructed based on the combined data considering microscopic structure of the porous media and the information about capillary equilibrium of oil-water mixture in pores. Data considering microscopic structure of the model are obtained by means of X-ray microscopic tomography. Information about distributions of saturating fluids is based on hydrodynamic simulations with density functional technique. In order to determine electromagnetic properties of the numerical model time-domain Fourier transform of Maxwell equations is considered. In low frequency approximation the problem can be reduced to solving elliptic equation for the distribution of complex electric potential. Finite difference approximation is based on discretization of the model with homogeneous isotropic orthogonal grid. This discretization implies that each computational cell contains exclusively one medium: water, oil or rock. In order to obtain suitable numerical model the distributions of saturating components is segmented. Such kind of modification enables avoiding usage of heterogeneous grids and disregards influence on the results of simulations of the additional techniques, required in order to determine properties of cells, filled with mixture of media. Corresponding system of differential equations is solved by means of biconjugate gradient stabilized method with multigrid preconditioner. Based on the results of complex electric potential computations average values of electrical conductivity and relative dielectric permittivity is calculated. For the sake of simplicity, this paper considers exclusively simulations with no spectral dependence of conductivities and permittivities of model components. The results of numerical simulations of spectral dependence of effective characteristics of heterogeneously saturated porous media (electrical conductivity and relative dielectric permittivity) in broad range of frequencies and multiple water saturations are represented in figures and table. Efficiency of the presented approach for determining spectral electrical properties of saturated rocks is discussed in conclusion.

Efficiency of production directly depends on quality of the management of technology which, in turn, relies on the accuracy and efficiency of the processing of control and measuring information. Development of the mathematical methods of research of the system communications and regularities of functioning and creation of the mathematical models taking into account structural features of object of researches, and also writing of the software products for realization of these methods are an actual task. Practice has shown that the list of parameters that take place in the study of complex object of modern production, ranging from a few dozen to several hundred names, and the degree of influence of each factor in the initial time is not clear. Before working for the direct determination of the model in these circumstances, it is impossible — the amount of the required information may be too great, and most of the work on the collection of this information will be done in vain due to the fact that the degree of influence on the optimization of most factors of the original list would be negligible. Therefore, a necessary step in determining a model of a complex object is to work to reduce the dimension of the factor space. Most industrial plants are hierarchical group processes and mass volume production, characterized by hundreds of factors. (For an example of realization of the mathematical methods and the approbation of the constructed models data of the Moldavian steel works were taken in a basis.) To investigate the systemic linkages and patterns of functioning of such complex objects are usually chosen several informative parameters, and carried out their sampling. In this article the sequence of coercion of the initial indices of the technological process of the smelting of steel to the look suitable for creation of a mathematical model for the purpose of prediction is described. The implementations of new types became also creation of a basis for development of the system of automated management of quality of the production. In the course of weak correlation the following stages are selected: collection and the analysis of the basic data, creation of the table the correlated of the parameters, abbreviation of factor space by means of the correlative pleiads and a method of weight factors. The received results allow to optimize process of creation of the model of multiple-factor process.

The article deals with the development of the noise-reduction algorithm based on anisotropic nonlinear data filtering of computed tomography (CT). Analysis of domestic and foreign literature has shown that the most effective algorithms for noise reduction of CT data use complex methods for analyzing and processing data, such as bilateral, adaptive, three-dimensional and other types of filtrations. However, a combination of such techniques is rarely used in practice due to long processing time per slice. In this regard, it was decided to develop an efficient and fast algorithm for noise-reduction based on simplified bilateral filtration method with three-dimensional data accumulation. The algorithm was developed on C ++11 programming language in Microsoft Visual Studio 2015. The main difference of the developed noise reduction algorithm is the use an improved mathematical model of CT noise, based on the distribution of Poisson and Gauss from the logarithmic value, developed earlier by our team. This allows a more accurate determination of the noise level and, thus, the threshold of data processing. As the result of the noise reduction algorithm, processed CT data with lower noise level were obtained. Visual evaluation of the data showed the increased information content of the processed data, compared to original data, the clarity of the mapping of homogeneous regions, and a significant reduction in noise in processing areas. Assessing the numerical results of the algorithm showed a decrease in the standard deviation (SD) level by more than 6 times in the processed areas, and high rates of the determination coefficient showed that the data were not distorted and changed only due to the removal of noise. Usage of newly developed context dynamic threshold made it possible to decrease SD level on every area of data. The main difference of the developed threshold is its simplicity and speed, achieved by preliminary estimation of the data array and derivation of the threshold values that are put in correspondence with each pixel of the CT. The principle of its work is based on threshold criteria, which fits well both into the developed noise reduction algorithm based on anisotropic nonlinear filtration, and another algorithm of noise-reduction. The algorithm successfully functions as part of the MultiVox workstation and is being prepared for implementation in a single radiological network of the city of Moscow.

We consider a model of spontaneous formation of a computational structure in the human brain for solving a given class of tasks in the process of performing a series of similar tasks. The model is based on a special definition of a numerical measure of the complexity of the solution algorithm. This measure has an informational property: the complexity of a computational structure consisting of two independent structures is equal to the sum of the complexities of these structures. Then the probability of spontaneous occurrence of the structure depends exponentially on the complexity of the structure. The exponential coefficient requires experimental determination for each type of problem. It may depend on the form of presentation of the source data and the procedure for issuing the result. This estimation method was applied to the results of a series of experiments that determined the strategy for solving a series of similar problems with a growing number of initial data. These experiments were described in previously published papers. Two main strategies were considered: sequential execution of the computational algorithm, or the use of parallel computing in those tasks where it is effective. These strategies differ in how calculations are performed. Using an estimate of the complexity of schemes, you can use the empirical probability of one of the strategies to calculate the probability of the other. The calculations performed showed a good match between the calculated and empirical probabilities. This confirms the hypothesis about the spontaneous formation of structures that solve the problem during the initial training of a person. The paper contains a brief description of experiments, detailed computational schemes and a strict definition of the complexity measure of computational structures and the conclusion of the dependence of the probability of structure formation on its complexity.

The work is devoted to the structural analysis of complex technical systems. Mechanical structures are considered, the properties of which affect the behavior of products during assembly, repair and operation. The main source of data on parts and mechanical connections between them is a hypergraph. This model formalizes the multidimensional basing relation. The hypergraph correctly describes the connectivity and mutual coordination of parts, which is achieved during the assembly of the product. When developing complex products in CAD systems, an engineer often makes serious design mistakes: overbasing of parts and non-sequential assembly operations. Effective ways of identifying these structural defects have been proposed. It is shown that the property of independent assembly can be represented as a closure operator whose domain is the boolean of the set of product parts. The images of this operator are connected and coordinated subsets of parts that can be assembled independently. A lattice model is described, which is the state space of the product during assembly, disassembly and decomposition into assembly units. The lattice model serves as a source of various structural information about the project. Numerical estimates of the cardinality of the set of admissible alternatives in the problems of choosing an assembly sequence and decomposition into assembly units are proposed. For many technical operations (for example, control, testing, etc.), it is necessary to mount all the operand parts in one assembly unit. A simple formalization of the technical conditions requiring the inclusion (exclusion) of parts in the assembly unit (from the assembly unit) has been developed. A theorem that gives an mathematical description of product decomposition into assembly units in exact lattice terms is given. A method for numerical evaluation of the robustness of the mechanical structure of a complex technical system is proposed.

Finding the global minimum of a nonconvex function is one of the key and most difficult problems of the modern optimization. In this paper we consider special classes of nonconvex problems which have a clear and distinct global minimum.

In the first part of the paper we consider two classes of «good» nonconvex functions, which can be bounded below and above by a parabolic function. This class of problems has not been widely studied in the literature, although it is rather interesting from an applied point of view. Moreover, for such problems first-order and higher-order methods may be completely ineffective in finding a global minimum. This is due to the fact that the function may oscillate heavily or may be very noisy. Therefore, our new methods use only zero-order information and are based on grid search. The size and fineness of this grid, and hence the guarantee of convergence speed and oracle complexity, depend on the «goodness» of the problem. In particular, we show that if the function is bounded by fairly close parabolic functions, then the complexity is independent of the dimension of the problem. We show that our new methods converge with a linear convergence rate $\log(1/\varepsilon)$ to a global minimum on the cube.

In the second part of the paper, we consider the nonconvex optimization problem from a different angle. We assume that the target minimizing function is the sum of the convex quadratic problem and a nonconvex «noise» function proportional to the distance to the global solution. Considering functions with such noise assumptions for zero-order methods is new in the literature. For such a problem, we use the classical gradient-free approach with gradient approximation through finite differences. We show how the convergence analysis for our problems can be reduced to the standard analysis for convex optimization problems. In particular, we achieve a linear convergence rate for such problems as well.

Experimental results confirm the efficiency and practical applicability of all the obtained methods.

Newton and quasi-Newton methods of absolute optimization based on Cholesky factorization with adaptive step and finite difference approximation of the first and the second derivatives. In order to raise effectiveness of the quasi-Newton methods a modified version of Cholesky decomposition of quasi-Newton matrix is suggested. It solves the problem of step scaling while descending, allows approximation by non-quadratic functions, and integration with confidential neighborhood method. An approach to raise Newton methods effectiveness with finite difference approximation of the first and second derivatives is offered. The results of numerical research of algorithm effectiveness are shown.

Road network infrastructure is the basis of any urban area. This article compares the structural characteristics (meshedness coefficient, clustering coefficient) road networks of Moscow center (Old Moscow), formed as a result of self-organization and roads near Leninsky Prospekt (postwar Moscow), which was result of cetralized planning. Data for the construction of road networks in the form of graphs taken from the Internet resource OpenStreetMap, allowing to accurately identify the coordinates of the intersections. According to the characteristics of the calculated Moscow road networks areas the cities with road network which have a similar structure to the two Moscow areas was found in foreign publications. Using the dual representation of road networks of centers of Moscow and St. Petersburg, studied the information and cognitive features of navigation in these tourist areas of the two capitals. In the construction of the dual graph of the studied areas were not taken into account the different types of roads (unidirectional or bi-directional traffic, etc), that is built dual graphs are undirected. Since the road network in the dual representation are described by a power law distribution of vertices on the number of edges (scale-free networks), exponents of these distributions were calculated. It is shown that the information complexity of the dual graph of the center of Moscow exceeds the cognitive threshold 8.1 bits, and the same feature for the center of St. Petersburg below this threshold, because the center of St. Petersburg road network was created on the basis of planning and therefore more easy to navigate. In conclusion, using the methods of statistical mechanics (the method of calculating the partition functions) for the road network of some Russian cities the Gibbs entropy were calculated. It was found that with the road network size increasing their entropy decreases. We discuss the problem of studying the evolution of urban infrastructure networks of different nature (public transport, supply , communication networks, etc.), which allow us to more deeply explore and understand the fundamental laws of urbanization.

The results of verification carried out for investigations of hydrodynamic effect on reentry conicalsegmental space vehicle are presented in the paper. The program complex Flow Vision is used for this analysis. The purpose of the study is verification of using Flow Vision program complex for problem solving mentioned above on the base of comparison between calculated and experimental data, obtained on the Apollo landing models and new development reentry spacecraft of manned transporting spaceship designed by RSC Energia. The comparison was carried out through the data of pressure values on spacecraft model surfaces during its water landing and inertia center motion parameters.

The results of study show good agreement between experimental and calculated data of force effects on vehicle construction during water landing and its motion parameters in the water medium. Computer simulation sufficiently well reproduces influence of initial velocities & water entry angles variations on water landing process.

Using of computer simulation provides simultaneous acquisition of all data information needed for investigation of water landing peculiarities during construction design, notably, hydrodynamic effects for structural strength calculations, parameters and dynamics of center mass motion and vehicle revolution around center mass for estimation water landing conditions, as well as vehicle stability after landing.

Obtained results confirm suitability of using Flow Vision program complex for water landing vehicle investigations and investigations of influence of different landing regimes through wide initial condition change range, that permits considerably decrease extent of expensive experimental tests and realize landing conditions which are sufficiently complicated for realizing in model physical experiments.

The paper develops a new mathematical method of the joint signal and noise parameters determination at the Rice statistical distribution by method of moments based upon the analysis of data for the 1-st and the 3-rd raw moments of the random rician value. The explicit equations’ system have been obtained for required parameters of the signal and noise. In the limiting case of the small value of the signal-to-noise ratio the analytical formulas have been derived that allow calculating the required parameters without the necessity of solving the equations numerically. The technique having been elaborated in the paper ensures an efficient separation of the informative and noise components of the data to be analyzed without any a-priori restrictions, just based upon the processing of the results of the signal’s sampled measurements. The task is meaningful for the purposes of the rician data processing, in particular in the systems of magnetic-resonance visualization, in ultrasound visualization systems, at the optical signals’ analysis in range measuring systems, in radio location, etc. The results of the investigation have shown that the two parameter task solution of the proposed technique does not lead to the increase in demanded volume of computing resources compared with the one parameter task being solved in approximation that the second parameter of the task is known a-priori There are provided the results of the elaborated technique’s computer simulation. The results of the signal and noise parameters’ numerical calculation have confirmed the efficiency of the elaborated technique. There has been conducted the comparison of the accuracy of the sought-for parameters estimation by the technique having been developed in this paper and by the previously elaborated method of moments based upon processing the measured data for lower even moments of the signal to be analyzed.