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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.

Under increasing loading and at a constant temperature shape memory solids become deformed in an ideal elastic plastic way as other metals, and the maximum elastic strains are much less than the ultimate plastic ones. The shape is restored at the elevated temperature and low stress level. Phenomenologically, the «reverse» deformation is equivalent to the change in shape under active loading up to sign. Plastic deformation plays a leading role in a non-elastic process; thus, the mechanical behavior should be analyzed within the ideal rigid-plastic model with two loading surfaces. In this model two physical states of the material correspond to the loading surfaces: plastic flow under high stresses and melting at a relatively low temperature. The second section poses a problem of deformation of rigid-plastic bodies at the constant temperature in two forms: as a principle of virtual velocities with the von Mises yield condition and as a requirement of the minimum dissipative functionаl. The equivalence of the accepted definitions and the existence of the generalized solutions is proved for both principles. The third section studies the rigid-plastic model of the solid at the variable temperature with two loading surfaces. For the assumed model two optimal principles are defined that link the external loads and the displacement velocities of the solid points both under active loading and in the process of shape restoration under heating. The existence of generalized velocities is proved for the wide variety of 3D domains. The connection between the variational principles and the variable temperature is ensured by inclusion of the first and second principles of thermodynamics in the calculation model. It is essential that only the phenomenological description of the phenomenon is used in the proving process. The austenite-tomartensite transformations of alloys, which are often the key elements in explanations of the mechanical behavior of shape memory materials, are not used here. The fourth section includes the definition of the shape memory materials as solids with two loading surfaces and proves the existence of solutions within the accepted restrictions. The adequacy of the model and the experiments on deformation of shape memory materials is demonstrated. In the conclusion mathematical problems that could be interesting for future research are defined.

The article presented the computational algorithm developed to study chemical processes in the internal flows of a multicomponent gas under the influence of laser radiation. The mathematical model is the gas dynamics’ equations with chemical reactions at low Mach numbers. It takes into account dissipative terms that describe the dynamics of a viscous heat-conducting medium with diffusion, chemical reactions and energy supply by laser radiation. This mathematical model is characterized by the presence of several very different time and spatial scales. The computational algorithm is based on a splitting scheme by physical processes. Each time integration step is divided into the following blocks: solving the equations of chemical kinetics, solving the equation for the radiation intensity, solving the convection-diffusion equations, calculating the dynamic component of pressure and calculating the correction of the velocity vector. The solution of a stiff system of chemical kinetics equations is carried out using a specialized explicit second-order accuracy scheme or a plug-in RADAU5 module. Numerical Rusanov flows and a WENO scheme of an increased order of approximation are used to find convective terms in the equations. The code based on the obtained algorithm has been developed using MPI parallel computing technology. The developed code is used to calculate the pyrolysis of ethane with radical reactions. The superequilibrium concentrations’ formation of radicals in the reactor volume is studied in detail. Numerical simulation of the reaction gas flow in a flat tube with laser radiation supply is carried out, which is in demand for the interpretation of experimental results. It is shown that laser radiation significantly increases the conversion of ethane and yields of target products at short lengths closer to the entrance to the reaction zone. Reducing the effective length of the reaction zone allows us to offer new solutions in the design of ethane conversion reactors into valuable hydrocarbons. The developed algorithm and program will find their application in the creation of new technologies of laser thermochemistry.

The paper investigates a potential solution to the problem of Self-Interference Cancellation (SIC) encountered in the design of In-Band Full-Duplex (IBFD) communication systems. The suppression of selfinterference is implemented in the digital domain using multilayer nonlinear models adapted via the gradient descent method. The presence of local optima and saddle points in the adaptation of multilayer models prevents the use of second-order methods due to the indefinite nature of the Hessian matrix.

This work proposes the use of the Mixed Newton Method (MNM), which incorporates information about the second-order mixed partial derivatives of the loss function, thereby enabling a faster convergence rate compared to traditional first-order methods. By constructing the Hessian matrix solely with mixed second-order partial derivatives, this approach mitigates the issue of “getting stuck” at saddle points when applying the Mixed Newton Method for adapting multilayer nonlinear self-interference compensators in full-duplex system design.

The Hammerstein model with complex parameters has been selected to represent nonlinear selfinterference. This choice is motivated by the model’s ability to accurately describe the underlying physical properties of self-interference formation. Due to the holomorphic property of the model output, the Mixed Newton Method provides a “repulsion” effect from saddle points in the loss landscape.

The paper presents convergence curves for the adaptation of the Hammerstein model using both the Mixed Newton Method and conventional gradient descent-based approaches. Additionally, it provides a derivation of the proposed method along with an assessment of its computational complexity.

The mathematical model for aeroelastic oscillations of a narrow channel wall with a nonlinear-elastic suspension and interacting with a pulsating viscous gas layer is proposed. Within the framework of this model, the aeroelastic response of the channel wall and its phase response were determined and investigated. The authors simultaneously studied the influence of the nonlinear stiffness elastic suspension of the wall, compressibility and dissipative properties of gas, as well as the inertia of its motion on the wall oscillations. The model was elaborated based on the formulation and solution of the initial boundary-value plane problem of mathematical physics. The problem governing equations include the equations of dynamics for barotropic viscous gas, equation of dynamics for the rigid wall as the spring-mass nonlinear oscillator. Using the perturbation method, the asymptotic analysis of the problem was carried out. The solution of the equations of dynamics for the thin layer of viscous gas was obtained by the iteration method. As a result, the law of gas pressure distribution in the channel was determined and the initial problem of aeroelasticity was reduced to the study of the generalized Duffing equation. Its solution was realized by the harmonic balance method, which allowed us to determine the aeroelastic and phase responses of the channel wall in the form of implicit functions. The numerical study of these responses was carried out to evaluate the influence for inertia of gas motion and its compressibility, as well as a comparison of the results obtained with the special cases of creeping motion of viscous gas and incompressible viscous fluid. The results of this study have shown the importance of simultaneous consideration of compressibility and inertia of viscous gas motion when modeling aeroelastic oscillations of the considered channel wall.

Mathematical simulation on unsteady natural convection in a closed porous cylindrical cavity having finite thickness heat-conducting solid walls in conditions of convective heat exchange with an environment has been carried out. A boundary-value problem of mathematical physics formulated in dimensionless variables such as stream function and temperature on the basis of Darcy–Boussinesq model has been solved by finite difference method. Effect of a porous medium permeability 10^–5≤Da<∞, ratio between a solid wall thickness and the inner radius of a cylinder 0.1≤h/L≤0.3, a thermal conductivity ratio 1≤λ_1,2≤20 and a dimensionless time on both local distributions of isolines and isotherms and integral complexes reflecting an intensity of convective flow and heat transfer has been analyzed in detail.

Modification of the invariant imbedding method to describe the interaction of 3D electromagnetic field with “woodpile” photonic crystal of finite thickness is considered in this paper. This modification allows solving a problem of evanescent modes resonant amplification during numerical calculations for the first layer of photonic crystal. The mathematical model created in this work gives good agreement with physical experiment results.