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The presence of a contact boundary between water and transformer oil greatly reduces the electrical strength of the oil phase. The presence of an electric field leads to varying degrees of polarization at the interface and the appearance of a force acting on a liquid with a higher dielectric constant (water) in the direction of a liquid with a lower dielectric constant (oil). This leads to the contact surface instability development. Instability as a result of its development leads to a stream of water being drawn into oil volume and a violation of the insulating gap. In this work, we experimentally and numerically study electrohydrodynamic instability at the phase boundary between electrically weakly conductive water and transformer oil in a highly inhomogeneous electric field directed perpendicular to the contact boundary. The results of a full-scale and numerical experiment of studying of the electrohydrodynamic instability development in a strong electric field at the interface between water and transformer oil are presented. The system consists of a spherical electrode with a radius of 3.5 mm, placed in water with a conductivity of 5 $\mu S/cm$, and a thin blade electrode 0.1 mm thick, placed in transformer oil of the GK brand. The contact boundary passes at the same distance from the nearest points of the electrodes, equal to 3 mm. The work shows that at a certain electric field strength, the cone-shaped structure of water grows towards the electrode immersed in transformer oil. A numerical correspondence was obtained for both the shape of the resulting water structure (cone) during the entire growth time and the size measured from its top to the level of the initial contact boundary of phase separation. The dynamics of this structure growth has been studied. Both in numerical calculations and in experiment, it was found that the size of the resulting cone along the electrode connection line depends linearly on time.

A review of the problems of preparing accurate geometric models of steel ropes based on mathematical models without significant simplifications, taking into account the intended purpose of the model, is carried out. Possible approaches to the generation of precise geometric models of steel ropes that have no fundamental limitations on their integration in computational domains and the subsequent construction of finite element models based on them are shown. A generalized parameterized geometric model of single and double twist ropes and its algorithmic implementation using the OpenCASCADE Core Technology geometric modeling kernel in the Gmsh environment (open source software) is considered. The problems of using generic tabular data from steel rope assortment standards as initial data for constructing geometric models are considered. Methods of preliminary verification of collisions of a geometric model based on the initial data of a geometric model are given. Post-verification methods based on Boolean operations over rope wire bodies are given to identify incorrect results of generating models of wire bodies with curvilinear side surfaces based on the algorithm of sequential hierarchical construction of individual wires of single strand and sequential copying of it. Various methods of the process of constructing geometric models of rope wires by extrusion are shown: through a sequence of generatrix with the formation of a body limited by curvilinear surfaces, through a sequence of generatrix with the formation of a body limited by linearly approximated surfaces, and extrusion of one generatrix along a single guideline. The computational complexity of the geometric model generation and the required volume of RAM for the two most universal methods of creating a body of wire are investigated. A method for estimating the value of the step of the arrangement of the generatrix of a single wire is shown, and the influence of its value on the computational complexity of the procedure of wire construction is investigated. Recommendations are given for choosing the value of the radial gap between the layers of wires. An algorithmic implementation of the method for searching for collisions of a geometric model of a steel rope in a non-interactive mode is shown. Approaches to the formation of procedures for processing collisions are proposed. Approaches presented in the article can be implemented in the form of software modules for execution in the Gmsh environment, as well as for another environment using the OpenCascade Core Technology geometric modeling kernel. Such modules allow automation of the construction of accurate geometric models of steel ropes in any configuration without fundamental restrictions on subsequent use, both stand-alone and in the form of objects (primitives) suitable for integration in a third-party model.

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.

In this paper, we consider the interaction of a kink of the $\varphi^4$ equation with two identical extended impurities. An extended impurity is described using a rectangular function. The case of an attractive impurity is analyzed. Using analytical methods, we consider the case of small amplitudes of localized waves, when it is possible to linearize the equations of motion. For the numerical solution, the method of lines for partial differential equations was used. To find the oscillation frequencies of waves localized on impurities, the discrete Fourier transform is used. The kink was launched in the direction of the impurities with different initial velocities. The distance between the two impurities was also varied. It is shown that when a kink interacts with impurities, long-lived localized breather-type waves are excited on them. Their structure and coupled dynamics are investigated. It is determined how, by changing the parameters of the impurities and the distance between them, it is possible to control the type and dynamic parameters of the coupled oscillations of the waves localized on the impurities. Possible solutions in the form of in-phase, antiphase oscillations, in the form of beats are found. The oscillations of localized waves occur with the emission of small-amplitude waves. The spectrum of these emissions consists of two frequencies. The first is approximately equal to $\sqrt{2}$, which corresponds to the frequency value for the wobbling breather tail of the $\varphi^4$ equation. The second is approximately equal to the doubled frequency of impurity mode oscillations. The presence of two possible frequencies for coupled localized oscillations is found both analytically and numerically. It is shown that the frequencies strongly depend on the distance between impurities. With increasing distance between impurities, the frequencies merge into one — frequency obtained for the case of a single impurity. The dependences of the frequencies on the distance between impurities found numerically and analytically coincide well for large distances, when the interaction between impurities is weak, and begin to differ noticeably at small distances, when the interaction between impurities is strong. The analytical value of the obtained frequencies is always greater than the numerical ones. It is shown that the dependence of the amplitude of localized waves on the initial kink velocity has several minima and maxima.

This study develops a previously proposed Method of Computer Analogy (MCA) based on formalization of digital computer operations. The paper discusses the position of the proposed approach among other well-known methods. It is emphasized that the primary objective is to derive analytical solutions, although in some cases they have to resort to semianalytical approximations. The paper focuses on constructing solutions for systems which, for certain parameter values, demonstrate the deterministic chaos behavior, namely Lorenz, Marioka – Shimitsu and R¨ossler systems. The paper also considers obtaining solution for Van der Pol equation (reduced to a nonlinear system). The aim of the study is to construct semi-analytical solutions represented as a segment of a power series in a step size of approximating difference scheme. To prevent overflow, authors formalize rank transfer operation. The authors apply a convergent difference scheme, referred to as the “guiding” scheme, to advance to the next step of the independent variable. The resulting approximation by a sum with only a few terms provides an approximation to the solution with any accuracy in accordance with the accuracy of the governing difference scheme. The senior digits in the resulting approximation exhibit probabilistic properties that can be modeled by known distributions, thereby enabling the derivation of analytical and semi-analytical approximations. The paper presents linear approximations that are the base for a complete approximations of solutions and provide important qualitative as well as some quantitative properties of solutions of considered systems. This work describes approximations of various orders, including those that do not guarantee convergence to the exact solution, but simplify the analysis of certain properties of nonlinear equations and systems. In particular, for the Van der Pol equation, authors demonstrate that its corresponding system has a cyclic solution and provide an estimate of its scale. A modification of the MCA that has features of the Monte Carlo method makes it possible to remove recurrent sequences and construct complete solutions in simple situations. The authors mention a promising approach for representing the solution using branched continued fractions.

The currently performed mathematical and computer modeling of thermal processes in technical systems is based on an assumption that all the parameters determining thermal processes are fully and unambiguously known and identified (i.e., determined). Meanwhile, experience has shown that parameters determining the thermal processes are of undefined interval-stochastic character, which in turn is responsible for the intervalstochastic nature of thermal processes in the electronic system. This means that the actual temperature values of each element in an technical system will be randomly distributed within their variation intervals. Therefore, the determinative approach to modeling of thermal processes that yields specific values of element temperatures does not allow one to adequately calculate temperature distribution in electronic systems. The interval-stochastic nature of the parameters determining the thermal processes depends on three groups of factors: (a) statistical technological variation of parameters of the elements when manufacturing and assembling the system; (b) the random nature of the factors caused by functioning of an technical system (fluctuations in current and voltage; power, temperatures, and flow rates of the cooling fluid and the medium inside the system); and (c) the randomness of ambient parameters (temperature, pressure, and flow rate). The interval-stochastic indeterminacy of the determinative factors in technical systems is irremediable; neglecting it causes errors when designing electronic systems. A method that allows modeling of unsteady interval-stochastic thermal processes in technical systems (including those upon interval indeterminacy of the determinative parameters) is developed in this paper. The method is based on obtaining and further solving equations for the unsteady statistical measures (mathematical expectations, variances and covariances) of the temperature distribution in an technical system at given variation intervals and the statistical measures of the determinative parameters. Application of the elaborated method to modeling of the interval-stochastic thermal process in a particular electronic system is considered.

Solution of Dynamic Light Scattering problem makes it possible to determine particle size distribution (PSD) from the spectrum of the intensity of scattered light. As a result of experiment, an intensity curve is obtained. The experimentally obtained spectrum of intensity is compared with the theoretically expected spectrum, which is the Lorentzian line. The main task is to determine on the basis of these data the relative concentrations of particles of each class presented in the solution. The article presents a method for constructing and using a neural network trained on synthetic data to determine PSD in a solution in the range of 1–500 nm. The neural network has a fully connected layer of 60 neurons with the RELU activation function at the output, a layer of 45 neurons and the same activation function, a dropout layer and 2 layers with 15 and 1 neurons (network output). The article describes how the network has been trained and tested on synthetic and experimental data. On the synthetic data, the standard deviation metric (rmse) gave a value of 1.3157 nm. Experimental data were obtained for particle sizes of 200 nm, 400 nm and a solution with representatives of both sizes. The results of the neural network and the classical linear methods are compared. The disadvantages of the classical methods are that it is difficult to determine the degree of regularization: too much regularization leads to the particle size distribution curves are much smoothed out, and weak regularization gives oscillating curves and low reliability of the results. The paper shows that the neural network gives a good prediction for particles with a large size. For small sizes, the prediction is worse, but the error quickly decreases as the particle size increases.

One of the destroying natural processes is the initiation of the regional seismic activity. It leads to a large number of human deaths. Much effort has been made to develop precise and robust methods for the estimation of the seismic stability of buildings. One of the most common approaches is the natural frequency method. The obvious drawback of this approach is a low precision due to the model oversimplification. The other method is a detailed simulation of dynamic processes using the finite-element method. Unfortunately, the quality of simulations is not enough due to the difficulty of setting the correct free boundary condition. That is why the development of new numerical methods for seismic stability problems is a high priority nowadays.

The present work is devoted to the study of spatial dynamic processes occurring in geological medium during an earthquake. We describe a method for simulating seismic wave propagation from the hypocenter to the day surface. To describe physical processes, we use a system of partial differential equations for a linearly elastic body of the second order, which is solved numerically by a grid-characteristic method on parallelepiped meshes. The widely used geological hypocenter model, called the “double-couple” model, was incorporated into this numerical algorithm. In this case, any heterogeneities, such as geological layers with curvilinear boundaries, gas and fluid-filled cracks, fault planes, etc., may be explicitly taken into account.

In this paper, seismic waves emitted during the earthquake initiation process are numerically simulated. Two different models are used: the homogeneous half-space and the multilayered geological massif with the day surface. All of their parameters are set based on previously published scientific articles. The adequate coincidence of the simulation results is obtained. And discrepancies may be explained by differences in numerical methods used. The numerical approach described can be extended to more complex physical models of geological media.

The Arctic region contains large hydrocarbon deposits. The presence of different ice formations, such as icebergs, ice hummocks, ice fields, complicates the process of carrying out seismic works on the territory. The last of them, ice fields, bring multiple reflections, spreading all over the surface of ice, into seismogramms. These multiple reflections are necessary to be taken into account while analyzing the seismograms, and geologists should be able to exclude them in order to obtain the reflected waves from the lower geological layers, including hydrocarbon layers.

In this work, we solve the problem of the seismic waves spread in the heterogeneous medium. The systems of equations for the linear elastic medium and for the acoustic medium describe the geological layers. We present the detailed description of the numerical solution of these systems of equations with the help of the grid-characteristic method. The final 1D transfer equations are solved with the use of the Rusanov scheme of the third order of accuracy. In the work, we examine the way of multiple waves decrease in ice by establishing the source of impulse deep into the ice field on border with water. We present the results of computer modelling of the seismic waves spread in geological layers, where the seismic source of impulse is situated on the contact border between ice and water, and also with the seismic source of impulse on the surface of ice for the 3D case. The results of the numerical modelling are presented by wave fields, graphs of the velocity x-components and seismogramms for the two problem formulations. We carry out the analysis of influence of establishing the source of impulse on the border between ice and water on the decrease of the x-components of seismic wave velocities, on seismogramms and on wave fields. As a result, the model, where the seismic source of impulse is situated on the contact border between ice and water, makes worse the final result. The model with the source of impulse on the surface of ice demonstrates a decrease of the x-components of seismic wave velocities.

Inverse geophysical problems are difficult to solve due to their mathematically incorrect formulation and large computational complexity. Geophysical exploration in frontier areas is even more complicated due to the lack of reliable geological information. In this case, inversion methods that allow interpretation of several types of geophysical data together are recognized to be of major importance. This paper is dedicated to one of such inversion methods, which is based on minimization of the determinant of the Gram matrix for a set of model vectors. Within the framework of this approach, we minimize a nonlinear functional, which consists of squared norms of data residual of different types, the sum of stabilizing functionals and a term that measures the structural similarity between different model vectors. We apply this approach to seismic and electromagnetic synthetic data set. Specifically, we study joint inversion of acoustic pressure response together with controlled-source electrical field imposing structural constraints on resulting electrical conductivity and P-wave velocity distributions.

We start off this note with the problem formulation and present the numerical method for inverse problem. We implemented the conjugate-gradient algorithm for non-linear optimization. The efficiency of our approach is demonstrated in numerical experiments, in which the true 3D electrical conductivity model was assumed to be known, but the velocity model was constructed during inversion of seismic data. The true velocity model was based on a simplified geology structure of a marine prospect. Synthetic seismic data was used as an input for our minimization algorithm. The resulting velocity model not only fit to the data but also has structural similarity with the given conductivity model. Our tests have shown that optimally chosen weight of the Gramian term may improve resolution of the final models considerably.