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Currently, a significant development has been observed in the direction of distributed computing theory, where computational tasks are solved collectively by resource-constrained devices. In practice, this scenario is implemented when processing data in Internet of Things systems, with the aim of reducing system latency and network infrastructure load, as data is processed on edge network computing devices. However, the rapid growth and widespread adoption of IoT systems raise questions about the need to develop methods for reducing the resource intensity of computations. The resource constraints of computing devices pose the following issues regarding the distribution of computational resources: firstly, the necessity to account for the transit cost between different devices solving various tasks; secondly, the necessity to consider the resource cost associated directly with the process of distributing computational resources, which is particularly relevant for groups of autonomous devices such as drones or robots. An analysis of modern publications available in open access demonstrated the absence of proposed models or methods for distributing computational resources that would simultaneously take into account all these factors, making the creation of a new mathematical model for organizing distributed computing in IoT systems and its solution methods topical. This article proposes a novel mathematical model for distributing computational resources along with heuristic optimization methods, providing an integrated approach to implementing distributed computing in IoT systems. A scenario is considered where there exists a leader device within a group that makes decisions concerning the allocation of computational resources, including its own, for distributed task resolution involving information exchanges. It is also assumed that no prior knowledge exists regarding which device will assume the role of leader or the migration paths of computational tasks across devices. Experimental results have shown the effectiveness of using the proposed models and heuristics: achieving up to a 52% reduction in resource costs for solving computational problems while accounting for data transit costs, saving up to 73% of resources through supplementary criteria optimizing task distribution based on minimizing fragment migrations and distances, and decreasing the resource cost of resolving the computational resource distribution problem by up to 28 times with reductions in distribution quality up to 10%.

The given work is devoted aerodynamic properties of system of the bodies which are flowed round by a supersonic stream. The question on reduction of mutual influence with increase in the size characterising scattering of elements of system is considered. The method of construction of a grid is applied to current modeling from a set of grids. One of grids, regular with rectangular cells, is responsible for an interference between bodies
and serves for the description of an external nonviscous current. Other grids are  connected with surfaces of streamline bodies and allow to describe viscous layers about streamline bodies. These grids are imposed on the first, without combination of any knots. Boundary conditions are realized through interpolation of functions on borders from one grid on another.

Molecular dynamics simulation using the embedded-atom method is applied to study the structural evolution of the particle diameter of 40 Å during the quenching process. Was carried comparative analysis of the structural reconstruction for the particle and the bulk models. Was a reduction in temperature of the beginning and end of the transformation of the particle. In formation of a percolation cluster from interpenetrating and contacting icosahedrons, for model of the particle, it is involved for 10 percent of atoms more, than for model of a bulk.

Carpooling has gained considerable importance as an effective solution for reducing pollution, mitigation of traffic and congestion on the roads, reduced demand for parking facilities, lesser energy and fuel consumption and most importantly, reduction in carbon emission, thus improving the quality of life in cities. This work presents a hybrid GA-A* algorithm to obtain optimal routes for the carpooling problem in the domain of multiobjective optimization having multiple conflicting objectives. Though the Genetic Algorithm provides optimal solutions, the A* algorithm because of its efficiency in providing the shortest route between any two points based on heuristics, enhances the optimal routes obtained using the Genetic algorithm. The refined routes obtained using the GA-A* algorithm, are further subjected to dominance test to obtain non-dominating solutions based on Pareto-Optimality. The routes obtained maximize the profit of the service provider by minimizing the travel and detour distance as well as pick-up/drop costs while maximizing the utilization of the car. The proposed algorithm has been implemented over the Salt Lake area of Kolkata. Route distance and detour distance for the optimal routes obtained using the proposed algorithm are consistently lesser for the same number of passengers when compared to the corresponding results obtained from an existing algorithm. Various statistical analysis like boxplots have also confirmed that the proposed algorithm regularly performed better than the existing algorithm using only Genetic Algorithm.

The development of a high-temperature gas-cooled reactor (HTGR) constituting a part of nuclear power-and-process station and intended for large-scale hydrogen production is now in progress in the Russian Federation. One of the key objectives in development of the high-temperature gas-cooled reactor is the computational justification of the accepted design.

The article gives the procedure for the computational analysis of thermal and physical characteristics of the high-temperature gas-cooled reactor. The procedure is based on the use of the state-of-the-art codes for personal computer (PC).

The objective of thermal and physical analysis of the reactor as a whole and of the core in particular was achieved in three stages. The idea of the first stage is to justify the neutron physical characteristics of the block-type core during burn-up with the use of the MCU-HTR code based on the Monte Carlo method. The second and the third stages are intended to study the coolant flow and the temperature condition of the reactor and the core in 3D with the required degree of detailing using the FlowVision and the ANSYS codes.

For the purpose of carrying out the analytical studies the computational models of the reactor flow path and the fuel assembly column were developed.

As per the results of the computational modeling the design of the support columns and the neutron physical characteristics of the fuel assembly were optimized. This results in the reduction of the total hydraulic resistance of the reactor and decrease of the maximum temperature of the fuel elements.

The dependency of the maximum fuel temperature on the value of the power peaking factors determined by the arrangement of the absorber rods and of the compacts of burnable absorber in the fuel assembly is demonstrated.

The article is devoted to the effect of thermal feedback, which occurs during the operation of integrated circuits and electronic systems with their use. Thermal feedback is due to the fact that the power consumed by the functioning of the microchip heats it and, due to the significant dependence of its electrical parameters on temperature, interactive interaction arises between its electrical and thermal processes. The effect of thermal feedback leads to a change in both electrical parameters and temperature levels in microcircuits. Positive thermal feedback is an undesirable phenomenon, because it causes the output of the electrical parameters of the microcircuits beyond the permissible values, the reduction in reliability and, in some cases, burn out. Negative thermal feedback is manifested in stabilizing the electrical and thermal regimes at lower temperature levels. Therefore, when designing microcircuits and electronic systems with their application, it is necessary to achieve the implementation of negative feedback. In this paper, we propose a method for modeling of thermal modes in electronic systems, taking into account the effect of thermal feedback. The method is based on introducing into the thermal model of the electronic system new model circuit elements that are nonlinearly dependent on temperature, the number of which is equal to the number of microcircuits in the electronic system. This approach makes it possible to apply matrix-topological equations of thermal processes to the thermal model with new circuit elements introduced into it and incorporate them into existing thermal design software packages. An example of modeling a thermal process in a real electronic system is presented, taking into account the effect of thermal feedback on the example of a microcircuit installed on a printed circuit board. It is shown that in order to adequately model the electrical and thermal processes of microcircuits and electronic systems, it is necessary to take into account the effects of thermal feedback in order to avoid design errors and create competitive electronic systems.

The development of a viral infection in the organism is a complex process which depends on the competition race between virus replication in the host cells and the immune response. To study different regimes of infection progression, we analyze the general mathematical model of immune response to viral infection. The model consists of two ODEs for virus and immune cells non-dimensionalized concentrations. The proliferation rate of immune cells in the model is represented by a bell-shaped function of the virus concentration. This function increases for small virus concentrations describing the antigen-stimulated clonal expansion of immune cells, and decreases for sufficiently high virus concentrations describing down-regulation of immune cells proliferation by the infection. Depending on the virus virulence, strength of the immune response, and the initial viral load, the model predicts several scenarios: (a) infection can be completely eliminated, (b) it can remain at a low level while the concentration of immune cells is high; (c) immune cells can be essentially exhausted, or (d) completely exhausted, which is accompanied (c, d) by high virus concentration. The analysis of the model shows that virus concentration can oscillate as it gradually converges to its equilibrium value. We show that the considered model can be obtained by the reduction of a more general model with an additional equation for the total viral load provided that this equation is fast. In the case of slow kinetics of the total viral load, this more general model should be used.

As the population of cities grows, the need to plan for the development of transport infrastructure becomes more acute. For this purpose, transport modeling packages are created. These packages usually contain a set of convex optimization problems, the iterative solution of which leads to the desired equilibrium distribution of flows along the paths. One of the directions for the development of transport modeling is the construction of more accurate generalized models that take into account different types of passengers, their travel purposes, as well as the specifics of personal and public modes of transport that agents can use. Another important direction of transport models development is to improve the efficiency of the calculations performed. Since, due to the large dimension of modern transport networks, the search for a numerical solution to the problem of equilibrium distribution of flows along the paths is quite expensive. The iterative nature of the entire solution process only makes this worse. One of the approaches leading to a reduction in the number of calculations performed is the construction of consistent models that allow to combine the blocks of a 4-stage model into a single optimization problem. This makes it possible to eliminate the iterative running of blocks, moving from solving a separate optimization problem at each stage to some general problem. Early work has proven that such approaches provide equivalent solutions. However, it is worth considering the validity and interpretability of these methods. The purpose of this article is to substantiate a single problem, that combines both the calculation of the trip matrix and the modal choice, for the generalized case when there are different layers of demand, types of agents and classes of vehicles in the transport network. The article provides possible interpretations for the gauge parameters used in the problem, as well as for the dual factors associated with the balance constraints. The authors of the article also show the possibility of combining the considered problem with a block for determining network load into a single optimization problem.

Modeling of channel processes in the study of coastal channel deformations requires the calculation of hydrodynamic flow parameters that take into account the existence of secondary transverse currents formed at channel curvature. Three-dimensional modeling of such processes is currently possible only for small model channels; for real river flows, reduced-dimensional models are needed. At the same time, the reduction of the problem from a three-dimensional model of the river flow movement to a two-dimensional flow model in the cross-section assumes that the hydrodynamic flow under consideration is quasi-stationary and the hypotheses about the asymptotic behavior of the flow along the flow coordinate of the cross-section are fulfilled for it. Taking into account these restrictions, a mathematical model of the problem of the a stationary turbulent calm river flow movement in a channel cross-section is formulated. The problem is formulated in a mixed formulation of velocity — “vortex – stream function”. As additional conditions for problem reducing, it is necessary to specify boundary conditions on the flow free surface for the velocity field, determined in the normal and tangential direction to the cross-section axis. It is assumed that the values of these velocities should be determined from the solution of auxiliary problems or obtained from field or experimental measurement data.

To solve the formulated problem, the finite element method in the Petrov – Galerkin formulation is used. Discrete analogue of the problem is obtained and an algorithm for solving it is proposed. Numerical studies have shown that, in general, the results obtained are in good agreement with known experimental data. The authors associate the obtained errors with the need to more accurately determine the circulation velocities field at crosssection of the flow by selecting and calibrating a more appropriate model for calculating turbulent viscosity and boundary conditions at the free boundary of the cross-section.

The dynamics of coupled elements’ ensembles are investigated in the context of description of spatio-temporal processes in the myocardium. Basic element is map-based model constructed by simplification and reduction of Luo-Rudy model. In particular, capabilities of the model in replication of different regimes of cardiac activity are shown, including excitable and oscillatory regimes. The dynamics of 1D and 2D lattices of coupled oscillatory elements with a random distribution of individual frequencies are considered. Effects of cluster synchronization and transition to global synchronization by increasing of coupling strength are discussed. Impulse propagation in the chain of excitable cells has been observed. Analysis of 2D lattice of excitable elements with target and spiral waves have been made. The characteristics of the spiral wave has been analyzed in depending on the individual parameters of the map and coupling strength between elements of the lattice. A study of mixed ensembles consisting of excitable and oscillatory elements with a gradient changing of the properties have been made, including the task for description of normal and pathological activity of the sinoatrial node.