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Flexible woven composites are classified as high-tech innovative materials. Due to the combination of various components of the filler and reinforcement elements, such materials are used in construction, in the defense industry, in shipbuilding and aircraft construction, etc. In the domestic literature, insufficient attention is paid to woven composites that change their geometric structure of the reinforcing layer during deformation. This paper presents an analysis of the previously proposed complex approach to modeling the behavior of flexible woven composites under static uniaxial tension for further generalization of the approach to biaxial tension. The work is aimed at qualitative and quantitative description of mechanical deformation processes occurring in the structure of the studied materials under tension, which include straightening the strands of the reinforcing layer and increasing the value of mutual pressure of the cross-lying reinforcement strands. At the beginning of the deformation process, the straightening of the threads and the increase in mutual pressure of the threads are most intense. With the increase in the level of load, the change of these parameters slows down. For example, the bending of the reinforcement strands goes into the Central tension, and the value of the load from the mutual pressure is no longer increased (tends to constant). To simulate the described processes, the basic geometrical and mechanical parameters of the material affecting the process of forming are introduced, the necessary terminology and description of the characteristics are given. Due to the high geometric nonlinearity of the all processes described in the increments, as in the initial load values there is a significant deformation of the reinforcing layer. For the quantitative and qualitative description of mechanical deformation processes occurring in the reinforcing layer, analytical dependences are derived to determine the increment of the angle of straightening of reinforcement filaments and the load caused by the mutual pressure of the cross-lying filaments at each step of the load increment. For testing of obtained dependencies shows an example of their application for flexible woven composites brands VP4126, VP6131 and VP6545. The simulation results confirmed the assumptions about the processes of straightening the threads and slowing the increase in mutual pressure of the threads. The results and dependences presented in this paper are directly related to the further generalization of the previously proposed analytical models for biaxial tension, since stretching in two directions will significantly reduce the straightening of the threads and increase the amount of mutual pressure under similar loads.

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 gradual incorporation of automated vehicles into the global transport networks leads to the need to develop tools to assess the impact of this process on various aspects of traffic. This implies a more organized movement of automated vehicles which can form uniformly moving platoons. The influence of the formation and movement of these platoons on the dynamics of traffic flow is of great interest. The currently most developed traffic flow models are based on the cellular automaton approach. They are mainly developed in the direction of increasing accuracy. This inevitably leads to the complication of models, which in their modern form have significantly moved away from the original philosophy of cellular automata, which implies simplicity and schematicity of models at the level of evolution rules, leading, however, to a complex organized behavior of the system. In the present paper, a simulation model of connected automated vehicles platoon dynamics in a heterogeneous transport system is proposed, consisting of two types of agents (vehicles): human-driven and automated. The description of the temporal evolution of the system is based on modified rules 184 and 240 for elementary cellular automata. Human-driven vehicles move according to rule 184 with the addition of accidental braking, the probability of which depends on the distance to the vehicle in front. For automated vehicles, a combination of rules is used depending on the type of nearest neighbors, regardless of the distance to them, which brings non-local interaction to the model. At the same time, it is considered that a group of sequentially moving connected automated vehicles can form an organized platoon. The influence of the ratio of types of vehicles in the system on the characteristics of the traffic flow during free movement on a circular one-lane and two-lane roads, as well as in the presence of a traffic light, is studied. The simulation results show that the effect of platoon formation is significant for a freeway traffic flow; the presence of a traffic light reduces the positive effect by about half. The movement of platoons of connected automated vehicles on two-lane roads with the possibility of lane changing was also studied. It is shown that considering the types of neighboring vehicles (automated or human-driven) when changing lanes for automated vehicles has a positive effect on the characteristics of the traffic flow.

Excitation waves are a prototype of self-organized dynamic patterns in non-equilibrium systems. They develop their own intrinsic dynamics resulting in travelling waves of various forms and shapes. Prominent examples are rotating spirals and scroll waves. It is an interesting and challenging task to find ways to control their behavior by applying external signals, upon which these propagating waves react. We apply external electric fields to such waves in the excitable Belousov–Zhabotinsky (BZ) reaction. Remarkable effects include the change of wave speed, reversal of propagation direction, annihilation of counter-rotating spiral waves and reorientation of scroll wave filaments. These effects can be explained in numerical simulations, where the negatively charged inhibitor bromide plays an essential role. Electric field effects have also been investigated in biological excitable media such as the social amoebae Dictyostelium discoideum. Quite recently we have started to investigate electric field effect in the BZ reaction dissolved in an Aerosol OT water-in-oil microemulsion. A drift of complex patterns can be observed, and also the viscosity and electric conductivity change. We discuss the assumption that this system can act as a model for long range communication between neurons.

The article contains the description of developed mathematical models of fractures which can be used for numerical solution of exploration seismology problems with use of grid-characteristic method on unstructured triangular and tetrahedral meshes. The base of developed models is the concept of infinitely thin fracture. This fracture is represented by contact boundary. Such approach significantly reduces the consumption of computer resources by the absence of the mesh definition inside of fracture necessity. By the other side it lets state the fracture discretely in integration domain, therefore one can observe qualitative new effects which are not available to observe by use of effective models of fractures, actively used in computational seismic.

The main target in the development of models have been getting the most accurate result. Developed models thet can receive the response close to the actual response of the existing fracture in geological environment. We considered fluid-filled fractures, glued and partially glued fractures, and also fractures with dynamical friction force. Fracture behavior determinated by the nature of condition on the border.

Empty fracture was represented as free boundary condition. This condition give us opportunity for total reflection of wave fronts from fracture. Fluid-filling provided the condition for sliding on the border. Under this condition, there was a passage of longitudinal and total reflection of converted waves. For the real fractures, which has unequal distance between the borders has been proposed the model of partially glued fracture. At different points of the fracture's boundary were sat different conditions. Almost the same effect is achieved by using a fracture model of dynamic friction condition. But its disadvantage is the inabillity to specify the proportion of fracture's glued area due to the friction factor can take values from zero to infinity. The model of partially glued fracture is devoid of this disadvantage.

In the paper the statistical relationships between the size and production characteristics of phytoplankton and zooplankton of the Vistula and Curonian lagoons, the Baltic Sea, were investigated. Research phytoplankton and zooplankton within the Russian part of the area of the Vistula and the Curonian lagoon was carried out on the monthly basis (from April to November) within the framework of long-term monitoring program on evaluating of ecological status of the lagoons. The size structure of plankton is the basis for understanding of the development of production processes, mechanisms of formation of the plankton species diversity and functioning of the lagoon ecosystems. As results of the work it was found that the maximum rate of photosynthesis and the integral value of the primary production with a change in cell volume of phytoplankton are changed according to a power law. The result shows that the smaller the size of algal cells in phytoplankton communities the more actively occur metabolism and the more effective they assimilate the solar energy. It is shown that the formation of plankton species diversity in ecosystems of lagoons is closely linked with the size structure of plankton communities and with features of development of the production processes. It is proposed the structure of a spatially homogenous mathematical model of the plankton food chain for the lagoon ecosystems taking into account the size spectrum and the characteristics of phytoplankton and zooplankton. The model parameters are the sizedependent indicators allometrically linked with average volumes of cells and organisms in different ranges of their sizes. In the model the algorithm for changes over time the coefficients of food preferences in the diet of zooplankton was proposed. Developed the size-dependent mathematical model of aquatic ecosystems allows to consider the impact of turbulent exchange on the size structure and temporal dynamics of the plankton food chain of the Vistula and Curonian lagoons. The model can be used to study the different regimes of dynamic behavior of plankton systems depending on the changes in the values of its parameters and external influences, as well as to quantify the redistribution of matter flows in ecosystems of the lagoons.

We present results of a study aimed at identification of a controlled object’s channels based on postprocessing of measurements with development of a model of a multiple-input controlled object and subsequent active modelling experiment. The controlled object model is developed using approximation of its behavior by a neural network model using trends obtained during a passive experiment in the mode of normal operation. Recurrent neural network containing feedback elements allows to simulate behavior of dynamic objects; input and feedback time delays allow to simulate behavior of inertial objects with pure delay. The model was taught using examples of the object’s operation with a control system and is presented by a dynamic neural network and a model of a regulator with a known regulation function. The neural network model simulates the system’s behavior and is used to conduct active computing experiments. Neural network model allows to obtain the controlled object’s response to an exploratory stimulus, including a periodic one. The obtained complex frequency response is used to evaluate parameters of the object’s transfer system using the least squares method. We present an example of identification of a channel of the simulated control system. The simulated object has two input ports and one output port and varying transport delays in transfer channels. One of the input ports serves as a controlling stimulus, the second is a controlled perturbation. The controlled output value changes as a result of control stimulus produced by the regulator operating according to the proportional-integral regulation law based on deviation of the controlled value from the task. The obtained parameters of the object’s channels’ transfer functions are close to the parameters of the input simulated object. The obtained normalized error of the reaction for a single step-wise stimulus of the control system model developed based on identification of the simulated control system doesn’t exceed 0.08. The considered objects pertain to the class of technological processes with continuous production. Such objects are characteristic of chemical, metallurgic, mine-mill, pulp and paper, and other industries.

In various areas of science, technology, environment protection, construction, it is very important to study processes of porous materials interaction with different substances in different aggregation states. From the point of view of ecology and environmental protection it is particularly actual to investigate processes of porous materials interaction with water in liquid and gaseous phases. Since one mole of water contains 6.022140857 · 10²³ molecules of H₂O, macroscopic approaches considering the water vapor as continuum media in the framework of classical aerodynamics are mainly used to describe properties, for example properties of water vapor in the pore. In this paper we construct and use for simulation the macroscopic two-dimensional diffusion model [Bitsadze, Kalinichenko, 1980] describing the behavior of water vapor inside the isolated pore. Together with the macroscopic model it is proposed microscopic model of the behavior of water vapor inside the isolated pores. This microscopic model is built within the molecular dynamics approach [Gould et al., 2005]. In the microscopic model a description of each water molecule motion is based on Newton classical mechanics considering interactions with other molecules and pore walls. Time evolution of “water vapor – pore” system is explored. Depending on the external to the pore conditions the system evolves to various states of equilibrium, characterized by different values of the macroscopic characteristics such as temperature, density, pressure. Comparisons of results of molecular dynamic simulations with the results of calculations based on the macroscopic diffusion model and experimental data allow to conclude that the combination of macroscopic and microscopic approach could produce more adequate and more accurate description of processes of water vapor interaction with porous materials.

The paper presents the physical and mathematical formulation of the problems of internal ballistics of an artillery shot for a charge consisting of a set of powder tubes and their stress-strain state. Combustion and movement of a bundle of powder tubes along the barrel channel is modeled by an equivalent tubular charge of all-round combustion. It is assumed that the equivalent tube moves along the axis of the bore. The speed of movement of an equivalent tubular charge and its current position are determined from Newton’s second law. When calculating the flow parameters, two-dimensional axisymmetric equations of gas dynamics were used, for the solution of which an axisymmetric orthogonalized difference grid is constructed, which adapts to the flow conditions. The control volume method is used to numerically solve the system of gas-dynamic equations. The gas parameters at the boundaries of the control volumes are determined using a self-similar solution to the Godunov’s problem of the decay of an arbitrary discontinuity. The stress-strain state is modeled for a separate burning powder tube located in the field of gas-dynamic parameters. The calculation of the gas-dynamic parameters of the shot is carried out without taking into account the deformed state of the powder elements. The behavior of powder elements during firing is considered under these conditions. The finite element method with the division of the calculation area into triangular elements is used to solve the problem of elasticity. In the process of powder tube burnout, the computational grid on each time layer of the dynamic problem is completely updated due to a change in the boundaries of the powder element due to combustion. The paper shows the time dependences of the parameters of the internal ballistics process and the stress-strain state of powder elements, as well as the distribution of the main parameters of the flow of combustion products at different points in time. It has been established that the tubular powder elements during the shot experience significant deformations, which must be taken into account when solving the basic problem of internal ballistics. The data obtained give an idea of the level of equivalent stresses acting at various points of the powder element. The results obtained indicate the relevance of the conjugate formulation of the problem of gas dynamics and the stress-strain state for charges consisting of tubular powders, since this allows a new approach to the design of tubular charges and opens up the possibility of determining the parameters on which the physics of the combustion process of gunpowder significantly depends, therefore, and the dynamics of the shot process.