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A mathematical model for the numerical study of thermal destruction of the "Chelyabinsk" meteorite when entering the Earth’s atmosphere is presented in the article. The study was conducted in the framework of an integrated approach, including the calculation of the meteorite trajectory associated with the physical processes connected with the meteorite motion. Together with the trajectory the flow field and radiation-convective heat
transfer were determined as well as warming and destruction of the meteorite under the influence of the calculated heat load. An integrated approach allows to determine the trajectories of space objects more precisely, predict the area of their fall and destruction.

In the context of problems of hydrogen and thermonuclear power engineering intensive research of the hydrogen isotopes properties is being conducted. Mathematical models help to specify physical-chemical ideas about the interaction of hydrogen isotopes with structural materials, to discover the limiting factors. Classical diffusion models are often insufficient. The paper is devoted to the models and numerical solution of the boundary-value problems of hydrogen thermodesorption and permeability taking into account nonlinear sorption-desorption dynamics on the surface and reversible capture of hydrogen atoms in the bulk. Algorithms based on difference approximations. The results of computer simulation of the hydrogen flux from a structural material sample are presented.

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.

In the last decades, the development of methods for increasing the efficiency of hydrocarbon extraction in fields with unconventional reserves containing large amounts of gas condensate is of great importance. This makes important the development of methods of mathematical modeling that realistically describe physical processes in a gas-condensate mixture in a porous medium.

In the paper, a mathematical model which describes the dynamics of the pressure, velocity and concentration of the components of a two-component two-phase mixture entering a laboratory model of plast filled with a porous substance with known physicochemical properties is considered. The mathematical model is based on a system of nonlinear spatially one-dimensional partial differential equations with the corresponding initial and boundary conditions. Laboratory experiments show that during a finite time the system stabilizes, what gives a basis to proceed to the stationary formulation of the problem.

The numerical solution of the formulated system of ordinary differential equations is realized in the Maple environment on the basis of the Runge–Kutta procedure. It is shown that the physical parameters of the gascondensate mixture, which characterize the modeled system in the stabilization regime, obtained on this basis, are in good agreement with the available experimental data. This confirms the correctness of the chosen approach and the validity of its further application and development for computer modeling of physical processes in gas-condensate mixtures in a porous medium. The paper presents a mathematical formulation of the system of partial differential equations and of respective system stationary equations, describes the numerical approach, and discusses the numerical results obtained in comparison with experimental data.

The application of a conservative numerical method of fluxes is examined for studying the vortex structures in the massive, fast-turned compact astrophysical objects, which are in self-gravity conditions. The simulation is accomplished for the objects with different mass and rotational speed. The pictures of the vortex structure of objects are visualized. In the calculations the gas-dynamic model is used, in which gas is accepted perfected and nonviscous. Numerical procedure is based on the finite-difference approximation of the conservation laws of the additive characteristics of medium for the finite volume. The “upwind” approximations of the densities of distribution of mass, components of momentum and total energy are applied. For the simulation of the objects, which possess fast-spin motion, the control of conservation for the component of moment of momentun is carried out during calculation. Evolutionary calculation is carried out on the basis of the parallel algorithms, realized on the computer complex of cluster architecture. Algorithms are based on the standardized system of message transfer Message Passing Interface (MPI). The blocking procedures of exchange and non-blocking procedures of exchange with control of the completion of operation are used. The parallelization on the space in two or three directions is carried out depending on the size of integration area and parameters of computational grid. For each subarea the parallelization based on the physical factors is carried out also: the calculations of gas dynamics part and gravitational forces are realized on the different processors, that allows to raise the efficiency of algorithms. The real possibility of the direct calculation of gravitational forces by means of the summation of interaction between all finite volumes in the integration area is shown. For the finite volume methods this approach seems to more consecutive than the solution of Poisson’s equation for the gravitational potential. Numerical calculations were carried out on the computer complex of cluster architecture with the peak productivity 523 TFlops. In the calculations up to thousand processors was used.

As part of the paper, a physical and theoretical analysis of the impact processes of various factors of a highaltitude and high-energy nuclear explosion on the asteroid in extra-atmospheric conditions of open space is done. It is shown that, in accordance with the energy and permeability of the plasma of explosion products, X-ray and gamma-neutron radiation, a layered structure with a different energy density depending on angular coordinates is formed on the surface of the asteroid. The temporal patterns of the energy transformation for each layer is clarified and the roles of various photo- and collision processes are determined. The effect of a high-speed plasma flow is erosive in nature, and the plasma pulse is transmitted to the asteroid. The paper presents that in a thin layer of x-ray absorption, the asteroid substance is heated to high temperatures and as a result of its expansion, a recoil impulse is formed, which is not decisive due to the small mass of the expanding high-temperature plasma. Calculations shows that the main impulse received by an asteroid is associated with the entrainment of a heated layer of a substance formed by a neutron flux (7.5 E 10¹⁴ g E cm/s). It is shown that an asteroid with a radius of ~100 m acquires a velocity of . 100 cm/s. The calculations were performed taking into account the explosion energy spent on the destruction of the amorphous structure of the asteroid material (~1 eV/atom = 3.8 E 10¹⁰ erg/g) and ionization in the region of the high-temperature layer. Based on a similar analysis, an approximation is obtained for estimating the average size of fragments in the event of the possible destruction of the asteroid by shock waves generated inside it under the influence of pressure impulses. A physical experiment was conducted in laboratory conditions, simulating the fragmentation of a stone asteroid and confirming the validity of the obtained dependence on the selected values of certain parameters. As a result of numerical studies of the effects of the explosion, carried out at different distances from the surface of the asteroid, it is shown that taking into account the real geometry of the spallation layer gives the optimal height for the formation of the maximum asteroid momentum by a factor of 1.5 greater than similar estimates according to the simplified model. A two-stage concept of the impact of nuclear explosions on an asteroid using radar guidance tools is proposed. The paper analyzes the possible impact of the emerging ionization interference on the radar tracking of the movement of large fragments of the asteroid in the space-time evolution of all elements of the studied dynamic system.

While modeling seismic wave propagation, it is important to take into account nontrivial topography, as this topography causes multiple complex phenomena, such as diffraction at rough surfaces, complex propagation of Rayleigh waves, and side effects caused by wave interference. The primary goal of this research is to construct a method that implements the free surface on topography, utilizing an overset curved grid for characterization, while keeping the main grid structured rectangular. For a combination of the regular and curve-linear grid, the workability of the grid characteristics method using overset grids (also known as the Chimera grid approach) is analyzed. One of the benefits of this approach is computational complexity reduction, caused by the fact that simulation in a regular, homogeneous physical area using a sparse regular rectangle grid is simpler. The simplification of the mesh building mechanism (one grid is regular, and the other can be automatically built using surface data) is a side effect. Despite its simplicity, the method we propose allows us to increase the digitalization of fractured regions and minimize the Courant number. This paper contains various comparisons of modeling results produced by the proposed method-based solver, and results produced by the well-known solver specfem2d, as well as previous modeling results for the same problems. The drawback of the method is that an interpolation error can worsen an overall model accuracy and reduce the computational schema order. Some countermeasures against it are described. For this paper, only two-dimensional models are analyzed. However, the method we propose can be applied to the three-dimensional problems with minimal adaptation required.

In this paper, a time-dependent natural convective heat transfer in a closed square cavity filled with non- Newtonian fluid was considered in the presence of an isothermal energy source located on the lower wall of the region under consideration. The vertical boundaries were kept at constant low temperature, while the horizontal walls were completely insulated. The behavior of a non-Newtonian fluid was described by the Ostwald de Ville power law. The process under study was described by transient partial differential equations using dimensionless non-primitive variables “stream function – vorticity – temperature”. This method allows excluding the pressure field from the number of unknown parameters, while the non-dimensionalization allows generalizing the obtained results to a variety of physical formulations. The considered mathematical model with the corresponding boundary conditions was solved on the basis of the finite difference method. The algebraic equation for the stream function was solved by the method of successive lower relaxation. Discrete analogs of the vorticity equation and energy equation were solved by the Thomas algorithm. The developed numerical algorithm was tested in detail on a class of model problems and good agreement with other authors was achieved. Also during the study, the mesh sensitivity analysis was performed that allows choosing the optimal mesh.

As a result of numerical simulation of unsteady natural convection of a non-Newtonian power-law fluid in a closed square cavity with a local isothermal energy source, the influence of governing parameters was analyzed including the impact of the Rayleigh number in the range 104–106, power-law index $n = 0.6–1.4$, and also the position of the heating element on the flow structure and heat transfer performance inside the cavity. The analysis was carried out on the basis of the obtained distributions of streamlines and isotherms in the cavity, as well as on the basis of the dependences of the average Nusselt number. As a result, it was established that pseudoplastic fluids $(n < 1)$ intensify heat removal from the heater surface. The increase in the Rayleigh number and the central location of the heating element also correspond to the effective cooling of the heat source.

The paper provides the mathematical and numerical models of the interrelated thermo- and hydrodynamic processes in the operational mode of development the unified oil-producing complex during the hydrogel flooding of the non-uniform oil reservoir exploited with a system of arbitrarily located injecting wells and producing wells equipped with submersible multistage electrical centrifugal pumps. A special feature of our approach is the modeling of the special ground-based equipment operation (control stations of submersible pumps, drossel devices on the head of producing wells), designed to regulate the operation modes of both the whole complex and its individual elements.

The complete differential model includes equations governing non-stationary two-phase five-component filtration in the reservoir, quasi-stationary heat and mass transfer in the wells and working channels of pumps. Special non-linear boundary conditions and dependencies simulate, respectively, the influence of the drossel diameter on the flow rate and pressure at the wellhead of each producing well and the frequency electric current on the performance characteristics of the submersible pump unit. Oil field development is also regulated by the change in bottom-hole pressure of each injection well, concentration of the gel-forming components pumping into the reservoir, their total volume and duration of injection. The problem is solved numerically using conservative difference schemes constructed on the base of the finite difference method, and developed iterative algorithms oriented on the parallel computing technologies. Numerical model is implemented in a software package which can be considered as the «Intellectual System of Wells» for the virtual control the oil field development.

This article studies a method of constructing a predictive neural network model of a time series based on determining the composition of input variables, constructing a training sample and training itself using the back propagation method. Traditional methods of constructing predictive models of the time series are: the autoregressive model, the moving average model or the autoregressive model — the moving average allows us to approximate the time series by a linear dependence of the current value of the output variable on a number of its previous values. Such a limitation as linearity of dependence leads to significant errors in forecasting.

Mining Technologies using neural network modeling make it possible to approximate the time series by a nonlinear dependence. Moreover, the process of constructing of a neural network model (determining the composition of input variables, the number of layers and the number of neurons in the layers, choosing the activation functions of neurons, determining the optimal values of the neuron link weights) allows us to obtain a predictive model in the form of an analytical nonlinear dependence.

The determination of the composition of input variables of neural network models is one of the key points in the construction of neural network models in various application areas that affect its adequacy. The composition of the input variables is traditionally selected from some physical considerations or by the selection method. In this work it is proposed to use the behavior of the autocorrelation and private autocorrelation functions for the task of determining the composition of the input variables of the predictive neural network model of the time series.

In this work is proposed a method for determining the composition of input variables of neural network models for stationary and non-stationary time series, based on the construction and analysis of autocorrelation functions. Based on the proposed method in the Python programming environment are developed an algorithm and a program, determining the composition of the input variables of the predictive neural network model — the perceptron, as well as building the model itself. The proposed method was experimentally tested using the example of constructing a predictive neural network model of a time series that reflects energy consumption in different regions of the United States, openly published by PJM Interconnection LLC (PJM) — a regional network organization in the United States. This time series is non-stationary and is characterized by the presence of both a trend and seasonality. Prediction of the next values of the time series based on previous values and the constructed neural network model showed high approximation accuracy, which proves the effectiveness of the proposed method.