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A large number of methods have been developed to solve the Navier – Stokes equations in the case of incompressible flows, the most popular of which are methods with velocity correction by the SIMPLE algorithm and its analogue — the method of splitting by physical variables. These methods, developed more than 40 years ago, were used to solve rather simple problems — simulating both stationary flows and non-stationary flows, in which the boundaries of the calculation domain were stationary. At present, the problems of computational fluid dynamics have become significantly more complicated. CFD problems are involving the motion of bodies in the computational domain, the motion of contact boundaries, cavitation and tasks with dynamic local adaptation of the computational mesh. In this case the computational mesh changes resulting in violation of the velocity divergence condition on it. Since divergent velocities are used not only for Navier – Stokes equations, but also for all other equations of the mathematical model of fluid motion — turbulence, mass transfer and energy conservation models, violation of this condition leads to numerical errors and, often, to undivergence of the computational algorithm.

This article presents an implicit method of splitting by physical variables that uses divergent velocities from a given time step to solve the incompressible Navier – Stokes equations. The method is developed to simulate flows in the case of movable and contact boundaries treated in the Euler paradigm. The method allows to perform computations with the integration step exceeding the explicit time step by orders of magnitude (Courant – Friedrichs – Levy number $CFL\gg1$). This article presents a variant of the method for incompressible flows. A variant of the method that allows to calculate the motion of liquid and gas at any Mach numbers will be published shortly. The method for fully compressible flows is implemented in the software package FlowVision.

Numerical simulating classical fluid flow around circular cylinder at low Reynolds numbers ($50 < Re < 140$), when laminar flow is unsteady and the Karman vortex street is formed, are presented in the article. Good agreement of calculations with the experimental data published in the classical works of Van Dyke and Taneda is demonstrated.

The spatiotemporal dynamics of a three-component model for food web is considered. The model describes the interactions among resource, prey and predator that consumes both species. In a previous work, the author analyzed the model without taking into account spatial heterogeneity. This study continues the model study of the community considering the diffusion of individuals, as well as directed movements of the predator. It is assumed that the predator responds to the spatial change in the resource and prey density by occupying areas where species density is higher or avoiding them. Directed predator movement is described by the advection term, where velocity is proportional to the gradient of resource and prey density. The system is considered on a one-dimensional domain with zero-flux conditions as boundary ones. The spatiotemporal dynamics produced by model is determined by the system stability in the vicinity of stationary homogeneous state with respect to small inhomogeneous perturbations. The paper analyzes the possibility of wave instability leading to the emergence of autowaves and Turing instability, as a result of which stationary patterns are formed. Sufficient conditions for the existence of both types of instability are obtained. The influence of local kinetic parameters on the spatial structure formation was analyzed. It was shown that only Turing instability is possible when taxis on the resource is positive, but with a negative taxis, both types of instability are possible. The numerical solution of the system was found by using method of lines (MOL) with the numerical integration of ODE system by means of splitting techniques. The spatiotemporal dynamics of the system is presented in several variants, realizing one of the instability types. In the case of a positive taxis on the prey, both autowave and stationary structures are formed in smaller regions, with an increase in the region size, Turing structures are not formed. For negative taxis on the prey, stationary patterns is observed in both regions, while periodic structures appear only in larger areas.

This paper is dedicated to the analysis of medical and biological data obtained through locomotor training and testing of astronauts conducted both on Earth and during spaceflight. These experiments can be described as the astronaut’s movement on a treadmill according to a predefined regimen in various speed modes. During these modes, not only the speed is recorded but also a range of parameters, including heart rate, ground reaction force, and others, are collected. In order to analyze the dynamics of the astronaut’s condition over an extended period, it is necessary to perform a qualitative segmentation of their movement modes to independently assess the target metrics. This task becomes particularly relevant in the development of an autonomous life support system for astronauts that operates without direct supervision from Earth. The segmentation of target data is complicated by the presence of various anomalies, such as deviations from the predefined regimen, arbitrary and varying duration of mode transitions, hardware failures, and other factors. The paper includes a detailed review of several contemporary retrospective (offline) nonparametric methods for detecting multiple changepoints, which refer to sudden changes in the properties of the observed time series occurring at unknown moments. Special attention is given to algorithms and statistical measures that determine the homogeneity of the data and methods for detecting change points. The paper considers approaches based on dynamic programming and sliding window methods. The second part of the paper focuses on the numerical modeling of these methods using characteristic examples of experimental data, including both “simple” and “complex” speed profiles of movement. The analysis conducted allowed us to identify the preferred methods, which will be further evaluated on the complete dataset. Preference is given to methods that ensure the closeness of the markup to a reference one, potentially allow the detection of both boundaries of transient processes, as well as are robust relative to internal parameters.

In the development of the previously obtained result on modeling the dynamics of vegetation cover, due to variations in the temperature background, a new scheme for the interval analysis of the dynamics of floristic images of formations is presented in the case when the parameter of the response rate of the model of the dynamics of each counting plant species is set by the interval of scatter of its possible values. The detailed description of the functional parameters of macromodels of biodiversity, desired in fundamental research, taking into account the essential reasons for the observed evolutionary processes, may turn out to be a problematic task. The use of more reliable interval estimates of the variability of functional parameters “bypasses” the problem of uncertainty in the primary assessment of the evolution of the phyto-resource potential of the developed controlled territories. The solutions obtained preserve not only a qualitative picture of the dynamics of species diversity, but also give a rigorous, within the framework of the initial assumptions, a quantitative assessment of the degree of presence of each plant species. The practical significance of two-sided estimation schemes based on the construction of equations for the upper and lower boundaries of the trajectories of the scatter of solutions depends on the conditions and measure of proportional correspondence of the intervals of scatter of the initial parameters with the intervals of scatter of solutions. For dynamic systems, the desired proportionality is not always ensured. The given examples demonstrate the acceptable accuracy of interval estimation of evolutionary processes. It is important to note that the constructions of the estimating equations generate vanishing intervals of scatter of solutions for quasi-constant temperature perturbations of the system. In other words, the trajectories of stationary temperature states of the vegetation cover are not roughened by the proposed interval estimation scheme. The rigor of the result of interval estimation of the species composition of the vegetation cover of formations can become a determining factor when choosing a method in the problems of analyzing the dynamics of species diversity and the plant potential of territorial systems of resource-ecological monitoring. The possibilities of the proposed approach are illustrated by geoinformation images of the computational analysis of the dynamics of the vegetation cover of the Yamal Peninsula and by the graphs of the retro-perspective analysis of the floristic variability of the formations of the landscapelithological group “Upper” based on the data of the summer temperature background of the Salehard weather station from 2010 to 1935. The developed indicators of floristic variability and the given graphs characterize the dynamics of species diversity, both on average and individually in the form of intervals of possible states for each species of plant.

Most biomechanical tasks of interest to clinicians can be solved only using personalized mathematical models. Such models allow to formalize and relate key pathophysiological processes, basing on clinically available data evaluate non-measurable parameters that are important for the diagnosis of diseases, predict the result of a therapeutic or surgical intervention. The use of models in clinical practice imposes additional restrictions: clinicians require model validation on clinical cases, the speed and automation of the entire calculated technological chain, from processing input data to obtaining a result. Limitations on the simulation time, determined by the time of making a medical decision (of the order of several minutes), imply the use of reduction methods that correctly describe the processes under study within the framework of reduced models or machine learning tools.

Personalization of models requires patient-oriented parameters, personalized geometry of a computational domain and generation of a computational mesh. Model parameters are estimated by direct measurements, or methods of solving inverse problems, or methods of machine learning. The requirement of personalization imposes severe restrictions on the number of fitted parameters that can be measured under standard clinical conditions. In addition to parameters, the model operates with boundary conditions that must take into account the patient’s characteristics. Methods for setting personalized boundary conditions significantly depend on the clinical setting of the problem and clinical data. Building a personalized computational domain through segmentation of medical images and generation of the computational grid, as a rule, takes a lot of time and effort due to manual or semi-automatic operations. Development of automated methods for setting personalized boundary conditions and segmentation of medical images with the subsequent construction of a computational grid is the key to the widespread use of mathematical modeling in clinical practice.

The aim of this work is to review our solutions for personalization of mathematical models within the framework of three tasks of clinical cardiology: virtual assessment of hemodynamic significance of coronary artery stenosis, calculation of global blood flow after hemodynamic correction of complex heart defects, calculating characteristics of coaptation of reconstructed aortic valve.

Laminar-turbulent transition is the subject of an active research related to improvement of economic efficiency of air vehicles, because in the turbulent boundary layer drag increases, which leads to higher fuel consumption. One of the directions of such research is the search for efficient methods, that can be used to find the position of the transition in space. Using this information about laminar-turbulent transition location when designing an aircraft, engineers can predict its performance and profitability at the initial stages of the project. Traditionally, $e^N$ method is applied to find the coordinates of a laminar-turbulent transition. It is a well known approach in industry. However, despite its widespread use, this method has a number of significant drawbacks, since it relies on parallel flow assumption, which limits the scenarios for its application, and also requires computationally expensive calculations in a wide range of frequencies and wave numbers. Alternatively, flow analysis can be done by using Dynamic Mode Decomposition, which allows one to analyze flow disturbances using flow data directly. Since Dynamic Mode Decomposition is a dimensionality reduction method, the number of computations can be dramatically reduced. Furthermore, usage of Dynamic Mode Decomposition expands the applicability of the whole method, due to the absence of assumptions about the parallel flow in its derivation.

The presented study proposes an approach to finding the location of a laminar-turbulent transition using the Dynamic Mode Decomposition method. The essence of this approach is to divide the boundary layer region into sets of subregions, for each of which the transition point is independently calculated, using Dynamic Mode Decomposition for flow analysis, after which the results are averaged to produce the final result. This approach is validated by laminar-turbulent transition predictions of subsonic and supersonic flows over a 2D flat plate with zero pressure gradient. The results demonstrate the fundamental applicability and high accuracy of the described method in a wide range of conditions. The study focuses on comparison with the $e^N$ method and proves the advantages of the proposed approach. It is shown that usage of Dynamic Mode Decomposition leads to significantly faster execution due to less intensive computations, while the accuracy is comparable to the such of the solution obtained with the $e^N$ method. This indicates the prospects for using the described approach in a real world applications.

Object of research: The creation of algorithm for mass computations of options‘ price for formation of a riskless portfolio. The method is based on the generalization of the Black–Scholes method. The task is the modeling of behavior of all options and tools for their insurance. This task is characterized by large volume of realtime complex computations that should be executed concurrently The problem of the research: depending on conditions approaches to the solution should be various. There are three methods which can be used with different conditions: the finite difference method, the path-integral approach and methods which work in conditions of trade stop. Distributed computating in these three cases is organized differently and it is necessary to involve various approaches. In addition to complexity the mathematical formulation of the problem in literature is not quite correct. There is no complete description of boundary and initial conditions and also several hypotheses of the model do not correspond to real market. It is necessary to give mathematically correct formulation of the task, and to neutralize a difference between hypotheses of the model and their prototypes in the market. For this purpose it is necessary to expand standard formulation by additional methods and develop methods of realization for each of solution branches.