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Langevin Dynamics, Monte Carlo, and all-atom Molecular Dynamics simulations in implicit solvent require a reliable source of pseudorandom numbers generated at each step of calculation. We present the two main approaches for implementation of pseudorandom number generators on a GPU. In the first approach, inherent in CPU-based calculations, one PRNG produces a stream of pseudorandom numbers in each thread of execution, whereas the second approach builds on the ability of different threads to communicate, thus, sharing random seeds across the entire device. We exemplify the use of these approaches through the development of Ran2, Hybrid Taus, and Lagged Fibonacci algorithms. As an application-based test of randomness, we carry out LD simulations of N independent harmonic oscillators coupled to a stochastic thermostat. This model allows us to assess statistical quality of pseudorandom numbers. We also profile performance of these generators in terms of the computational time, memory usage, and the speedup factor (CPU/GPU time).

А new cloud center of parallel computing is to be created in the Laboratory of Information Technologies (LIT) of the Joint Institute for Nuclear Research JINR) what is expected to improve significantly the efficiency of numerical calculations and expedite the receipt of new physically meaningful results due to the more rational use of computing resources. To optimize a scheme of parallel computations at a cloud environment it is necessary to test this scheme for various combinations of equipment parameters (processor speed and numbers, throughput оf а communication network etc). As a test problem, the parallel MPI algorithm for calculations of the long Josephson junctions (LDJ) is chosen. Problems of evaluating the impact of abovementioned factors of computing mean on the computing speed of the test problem are solved by simulation with the simulation program SyMSim developed in LIT.

The simulation of the LDJ calculations in the cloud environment enable users without a series of test to find the optimal number of CPUs with a certain type of network run the calculations in a real computer environment. This can save significant computational time in countable resources. The main parameters of the model were obtained from the results of the computational experiment conducted on a special cloud-based testbed. Computational experiments showed that the pure computation time decreases in inverse proportion to the number of processors, but depends significantly on network bandwidth. Comparison of results obtained empirically with the results of simulation showed that the simulation model correctly simulates the parallel calculations performed using the MPI-technology. Besides it confirms our recommendation: for fast calculations of this type it is needed to increase both, — the number of CPUs and the network throughput at the same time. The simulation results allow also to invent an empirical analytical formula expressing the dependence of calculation time by the number of processors for a fixed system configuration. The obtained formula can be applied to other similar studies, but requires additional tests to determine the values of variables.

The paper investigates the features of group dynamics of individuals-agents in the computer model of the animal population interacting with each other and with a renewable resource. This type of dynamics was previously found in [Belotelov, Konovalenko, 2016]. The model population consists of a set of individuals. Each individual is characterized by its mass, which is identified with energy. It describes in detail the dynamics of the energy balance of the individual. The habitat of the simulated population is a rectangular area where the resource grows evenly (grass).

Various computer experiments carried out with the model under different parameter values and initial conditions are described. The main purpose of these computational experiments was to study the group (herd) dynamics of individuals. It was found that in a fairly wide range of parameter values and with the introduction of spatial inhomogeneities of the area, the group type of behavior is preserved. The values of the model population parameters under which the regime of spatial oscillations of the population occurs were found numerically. Namely, in the model population periodically group (herd) behavior of animals is replaced by a uniform distribution over space, which after a certain number of bars again becomes a group. Numerical experiments on the preliminary analysis of the factors influencing the period of these solutions are carried out. It turned out that the leading parameters affecting the frequency and amplitude, as well as the number of groups are the mobility of individuals and the rate of recovery of the resource. Numerical experiments are carried out to study the influence of parameters determining the nonlocal interaction between individuals of the population on the group behavior. It was found that the modes of group behavior persist for a long time with the exclusion of fertility factors of individuals. It is confirmed that the nonlocality of interaction between individuals is leading in the formation of group behavior.

The review is based on some of the authors ’early works of particular scientific, methodological and practical interest and the greatest attention is paid to recent works, where quite detailed numerical studies of not only single, but also double and multiple explosions in a wide range of heights and environmental conditions have been performed . Since the shock wave of a powerful explosion is one of the main damaging factors in the lower atmosphere, the review focuses on both the physical analysis of their propagation and their interaction. Using the three-dimensional algorithms developed by the authors, the effects of interference and diffraction of several shock waves, which are interesting from a physical point of view, in the absence and presence of an underlying surface of various structures are considered. Quantitative characteristics are determined in the region of their maximum values, which is of known practical interest. For explosions in a dense atmosphere, some new analytical solutions based on the small perturbation method have been found that are convenient for approximate calculations. For a number of conditions, the possibility of using the self-similar properties of equations of the first and second kind to solve problems on the development of an explosion has been shown.

Based on numerical analysis, a fundamental change in the structure of the development of the perturbed region with a change in the height of the explosion in the range of 100–120 km is shown. At altitudes of more than 120 km, the geomagnetic field begins to influence the development of the explosion; therefore, even for a single explosion, the picture of the plasma flow after a few seconds becomes substantially three-dimensional. For the calculation of explosions at altitudes of 120–1000 km under the guidance of academician A. Kholodov. A special three-dimensional numerical algorithm based on the MHD approximation was developed. Numerous calculations were performed and for the first time a quite detailed picture of the three-dimensional flow of the explosion plasma was obtained with the formation of an upward jet in 5–10 s directed in the meridional plane approximately along the geomagnetic field. After some modification, this algorithm was used to calculate double explosions in the ionosphere, spaced a certain distance. The interaction between them was carried out both by plasma flows and through a geomagnetic field. Some results are given in this review and are described in detail in the original articles.

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.

The course and outcome of the battle is largely dependent on the morale of the troops, characterized by the percentage of loss in killed and wounded, in which the troops still continue to fight. Every fight is a psychological act of ending his rejection of one of the parties. Typically, models of battle psychological factor taken into account in the decision of Lanchester equations (the condition of equality of forces, when the number of one of the parties becomes zero). It is emphasized that the model Lanchester type satisfactorily describe the dynamics of the battle only in the initial stages. To resolve this contradiction is proposed to use a modification of Lanchester's equations, taking into account the fact that at any moment of the battle on the enemy firing not affected and did not abandon the battle fighters. The obtained differential equations are solved by numerical method and allow the dynamics to take into account the influence of psychological factor and evaluate the completion time of the conflict. Computational experiments confirm the known military theory is the fact that the fight usually ends in refusal of soldiers of one of the parties from its continuation (avoidance of combat in various forms). Along with models of temporal and spatial dynamics proposed to use a modification of the technology features of the conflict of S. Skaperdas, based on the principles of combat. To estimate the probability of victory of one side in the battle takes into account the interest of the maturing sides of the bloody casualties and increased military superiority.

The method of balanced identification was used to describe the response of Net Ecosystem Exchange of CO₂ (NEE) to change of environmental factors, and to fill the gaps in continuous CO₂ flux measurements in a sphagnum peat bog in the Tver region. The measurements were provided in the peat bog by the eddy covariance method from August to November of 2017. Due to rainy weather conditions and recurrent periods with low atmospheric turbulence the gap proportion in measured CO₂ fluxes at our experimental site during the entire period of measurements exceeded 40%. The model developed for the gap filling in long-term experimental data considers the NEE as a difference between Ecosystem Respiration (RE) and Gross Primary Production (GPP), i.e. key processes of ecosystem functioning, and their dependence on incoming solar radiation (Q), soil temperature (T), water vapor pressure deficit (VPD) and ground water level (WL). Applied for this purpose the balanced identification method is based on the search for the optimal ratio between the model simplicity and the data fitting accuracy — the ratio providing the minimum of the modeling error estimated by the cross validation method. The obtained numerical solutions are characterized by minimum necessary nonlinearity (curvature) that provides sufficient interpolation and extrapolation characteristics of the developed models. It is particularly important to fill the missing values in NEE measurements. Reviewing the temporary variability of NEE and key environmental factors allowed to reveal a statistically significant dependence of GPP on Q, T, and VPD, and RE — on T and WL, respectively. At the same time, the inaccuracy of applied method for simulation of the mean daily NEE, was less than 10%, and the error in NEE estimates by the method was higher than by the REddyProc model considering the influence on NEE of fewer number of environmental parameters. Analyzing the gap-filled time series of NEE allowed to derive the diurnal and inter-daily variability of NEE and to obtain cumulative CO₂ fluxs in the peat bog for selected summer-autumn period. It was shown, that the rate of CO₂ fixation by peat bog vegetation in August was significantly higher than the rate of ecosystem respiration, while since September due to strong decrease of GPP the peat bog was turned into a consistent source of CO₂ for the atmosphere.

The article reports the findings of an investigation into pollution migration processes at the municipal solid waste (MSW) landfill located in the water protection zone of Lake Seliger (Tver Region). The distribution of pollutants is investigated and migration parameters are determined in field and laboratory conditions at the landfill site. A mathematical model describing physical and chemical processes of substance migration in soil strata is constructed. Pollutant migration is found to be due to a variety of factors. The major ones, having a significant impact on the migration of MSW ingredients and taken into account mathematically, include convective transport, diffusion and sorption processes. A modified mathematical model differs from its conventional counterparts by considering a number of parameters reflecting the decrease in the concentration of ammonium and nitrate nitrogen ions in ground water (transpiration by plant roots, dilution with infiltration waters, etc.). An analytical solution to assess the pollutant spread from the landfill is presented. The mathematical model provides a set of simulation models helping to obtain a computational solution of specific problems, vertical and horizontal migration of substances in the underground flow. Numerical experiments, analytical solutions, as well as field and laboratory data was studied the dynamics of pollutant distribution in the object under study up to the lake. A long-term forecast for the spread of landfill pollution is made. Simulation experiments showed that some zones of clean groundwater interact with those of contaminated groundwater during the pollution migration from the landfill, each characterized by a different pollutant content. The data of a computational experiments and analytical calculations are consistent with the findings of field and laboratory investigations of the object and give grounds to recommend the proposed models for predicting pollution migration from a landfill. The analysis of the pollution migration simulation allows to substantiate the numerical estimates of the increase in $NH_4^+$ and $NO_3^-$ ion concentration with the landfill operation time. It is found that, after 100 years following the landfill opening, toxic filtrate components will fill the entire pore space from the landfill to the lake resulting in a significant deterioration of the ecosystem of Lake Seliger.

Migration has a significant impact on the shaping of the demographic structure of the territories population, the state of regional and local labour markets. As a rule, rapid change in the working-age population of any territory due to migration processes results in an imbalance in supply and demand on labour markets and a change in the demographic structure of the population. Migration is also to a large extent a reflection of socio-economic processes taking place in the society. Hence, the issues related to the study of migration factors, the direction, intensity and structure of migration flows, and the prediction of their magnitude are becoming topical issues these days.

Mathematical tools are often used to analyze, predict migration processes and assess their consequences, allowing for essentially accurate modelling of migration processes for different territories on the basis of the available statistical data. In recent years, quite a number of scientific papers on modelling internal and external migration flows using mathematical methods have appeared both in Russia and in foreign countries in recent years. Consequently, there has been a need to systematize the currently most commonly used methods and tools applied in migration modelling to form a coherent picture of the main trends and research directions in this field.

The presented review considers the main approaches to migration modelling and the main components of migration modelling methodology, i. e. stages, methods, models and model classification. Their comparative analysis was also conducted and general recommendations on the choice of mathematical tools for modelling were developed. The review contains two sections: migration modelling methods and migration models. The first section describes the main methods used in the model development process — econometric, cellular automata, system-dynamic, probabilistic, balance, optimization and cluster analysis. Based on the analysis of modern domestic and foreign publications on migration, the most common classes of models — regression, agent-based, simulation, optimization, probabilistic, balance, dynamic and combined — were identified and described. The features, advantages and disadvantages of different types of migration process models were considered.

Base long-term modern scenarios of hydrochemical and temperature regimes of the Sea of Azov were considered. New schemes of modeling mechanisms of algal adaptation to changes in the hydrochemical regime and temperature were proposed. In comparison to the traditional ecological-evolutionary schemes, these models have a relatively small dimension, high speed and allow carrying out various calculations on long-term perspective (evolutionally significant times). Based on the ecology-evolutionary model of the lower trophic levels the impact of these environmental factors on the dynamics and microevolution of algae in the Sea of Azov was estimated. In each scenario, the calculations were made for 100 years, with the final values of the variables and parameters not depending on the choice of the initial values. In the process of such asymptotic computer analysis, it was found that as a result of climate warming and temperature adaptation of organisms, the average annual biomass of thermophilic algae (Pyrrophyta and Cyanophyta) naturally increases. However, for a number of diatom algae (Bacillariophyta), even with their temperature adaptation, the average annual biomass may unexpectedly decrease. Probably, this phenomenon is associated with a toughening of competition between species with close temperature parameters of existence. The influence of the variation in the chemical composition of the Don River’s flow on the dynamics of nutrients and algae of the Sea of Azov was also investigated. It turned out that the ratio of organic forms of nitrogen and phosphorus in sea waters varies little. This stabilization phenomenon will take place for all high-productive reservoirs with low flow, due to autochthonous origin of larger part of organic matter in water bodies of this type.