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The paper contains numerical simulation of nonisothermal nonlinear flow in a porous medium. Twodimensional unsteady problem of heavy oil, water and steam flow is considered. Oil phase consists of two pseudocomponents: light and heavy fractions, which like the water component, can vaporize. Oil exhibits viscoplastic rheology, its filtration does not obey Darcy's classical linear law. Simulation considers not only the dependence of fluids density and viscosity on temperature, but also improvement of oil rheological properties with temperature increasing.

To solve this problem numerically we use streamline method with splitting by physical processes, which consists in separating the convective heat transfer directed along filtration from thermal conductivity and gravitation. The article proposes a new approach to streamline methods application, which allows correctly simulate nonlinear flow problems with temperature-dependent rheology. The core of this algorithm is to consider the integration process as a set of quasi-equilibrium states that are results of solving system on a global grid. Between these states system solved on a streamline grid. Usage of the streamline method allows not only to accelerate calculations, but also to obtain a physically reliable solution, since integration takes place on a grid that coincides with the fluid flow direction.

In addition to the streamline method, the paper presents an algorithm for nonsmooth coefficients accounting, which arise during simulation of viscoplastic oil flow. Applying this algorithm allows keeping sufficiently large time steps and does not change the physical structure of the solution.

Obtained results are compared with known analytical solutions, as well as with the results of commercial package simulation. The analysis of convergence tests on the number of streamlines, as well as on different streamlines grids, justifies the applicability of the proposed algorithm. In addition, the reduction of calculation time in comparison with traditional methods demonstrates practical significance of the approach.

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.

This article solves the problem of constructing a neuro-fuzzy model of fuzzy rules formation and using them for objects state evaluation in conditions of uncertainty. Traditional mathematical statistics or simulation modeling methods do not allow building adequate models of objects in the specified conditions. Therefore, at present, the solution of many problems is based on the use of intelligent modeling technologies applying fuzzy logic methods. The traditional approach of fuzzy systems construction is associated with an expert attraction need to formulate fuzzy rules and specify the membership functions used in them. To eliminate this drawback, the automation of fuzzy rules formation, based on the machine learning methods and algorithms, is relevant. One of the approaches to solve this problem is to build a fuzzy neural network and train it on the data characterizing the object under study. This approach implementation required fuzzy rules type choice, taking into account the processed data specificity. In addition, it required logical inference algorithm development on the rules of the selected type. The algorithm steps determine the number and functionality of layers in the fuzzy neural network structure. The fuzzy neural network training algorithm developed. After network training the formation fuzzyproduction rules system is carried out. Based on developed mathematical tool, a software package has been implemented. On its basis, studies to assess the classifying ability of the fuzzy rules being formed have been conducted using the data analysis example from the UCI Machine Learning Repository. The research results showed that the formed fuzzy rules classifying ability is not inferior in accuracy to other classification methods. In addition, the logic inference algorithm on fuzzy rules allows successful classification in the absence of a part of the initial data. In order to test, to solve the problem of assessing oil industry water lines state fuzzy rules were generated. Based on the 303 water lines initial data, the base of 342 fuzzy rules was formed. Their practical approbation has shown high efficiency in solving the problem.

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.

Rugose spiraling whitefly (RSW) is one of the major pests which affects the coconut trees. It feeds on the tree by sucking up the water content as well as the essential nutrients from leaves. It also forms sooty mold in leaves due to which the process of photosynthesis is inhibited. Biocontrol of pest is harmless for trees and crops. The experimental results in literature reveal that Pseudomallada astur is a potential predator for this pest. We investigate the dynamics of predator, Pseudomallada astur’s interaction with rugose spiralling whitefly, Aleurodicus rugioperculatus in coconut trees using a mathematical model. In this system of ordinary differential equation, the pest-predator interaction is modeled using Holling type III functional response. The parametric values are calculated from the experimental results and are tabulated. An approximate analytical solution for the system has been derived. The homotopy analysis method proves to be a suitable method for creating solutions that are valid even for moderate to large parameter values, hence we employ the same to solve this nonlinear model. The $\hbar$-curves, which give the admissible region of $\hbar$, are provided to validate the region of convergence. We have derived the approximate solution at fifth order and stopped at this order since we obtain a more approximate solution in this iteration. Numerical simulation is obtained through MATLAB. The analytical results are compared with numerical simulation and are found to be in good agreement. The biological interpretation of figures implies that the use of a predator reduces the whitefly’s growth to a greater extent.

Technical carbon (soot) is a product obtained by thermal decomposition (pyrolysis) of hydrocarbons (usually oil) in a stream of heat carrier gas. Technical carbon is widely used as a reinforcing component in the production of rubber and plastic masses. Tire production uses 70% of all carbon produced. In furnace carbon production, the liquid hydrocarbon feedstock is injected into the natural gas combustion product stream through nozzles. The raw material is atomized and vaporized with further pyrolysis. It is important for the raw material to be completely evaporated before the pyrolysis process starts, otherwise coke, that contaminates the product, will be produced. It is impossible to operate without mathematical modeling of the process itself in order to improve the carbon production technology, in particular, to provide the complete evaporation of the raw material prior to the pyrolysis process. Mathematical modelling is the most important way to obtain the most complete and detailed information about the peculiarities of reactor operation.

A three-dimensional mathematical model and calculation method for raw material atomization and evaporation in the thermal gas flow are being developed in the FlowVision software package PC. Water is selected as a raw material to work out the modeling technique. The working substances in the reactor chamber are the combustion products of natural gas. The motion of raw material droplets and evaporation in the gas stream are modeled in the framework of the Eulerian approach of interaction between dispersed and continuous media. The simulation results of raw materials atomization and evaporation in a real reactor for technical carbon production are presented. Numerical method allows to determine an important atomization characteristic: average Sauter diameter. That parameter could be defined from distribution of droplets of raw material at each time of spray forming.

Approbation of calculation of borders of water quality classes for the purpose of ecological diagnosis and standardization by data of the Rybinsk reservoir is carried out. For bioindication indicators of phytoplankton fluorescence and the contents of pigments of phytoplankton are used. Chesnokov's importance coefficient proved to be the most preferred measure of connection for analyzing the effects of environmental factors on indicators. The factors important for environmental condition are identified. Comparison of borders between quality classes “valid” and “invalid” of factors values and boundaries of the classifications of water quality.

A vertically distributed three-component model of marine ecosystem is considered. State of the plankton community with nutrients is analyzed under the active movement of zooplankton in a vertical column of water. The necessary conditions of the Turing instability in the vicinity of the spatially homogeneous equilibrium are obtained. Stability of the spatially homogeneous equilibrium, the Turing instability and the oscillatory instability are examined depending on the biological characteristics of zooplankton and spatial movement of plankton. It is shown that at low values of zooplankton grazing rate and intratrophic interaction rate the system is Turing instable when the taxis rate is low. Stabilization occurs either through increased decline of zooplankton either by increasing the phytoplankton diffusion. With the increasing rate of consumption of phytoplankton range of parameters that determine the stability is reduced. A type of instability depends on the phytoplankton diffusion. For large values of diffusion oscillatory instability is observed, with a decrease in the phytoplankton diffusion zone of Turing instability is increases. In general, if zooplankton grazing rate is faster than phytoplankton growth rate the spatially homogeneous equilibrium is Turing instable or oscillatory instable. Stability is observed only at high speeds of zooplankton departure or its active movements. With the increase in zooplankton search activity spatial distribution of populations becomes more uniform, increasing the rate of diffusion leads to non-uniform spatial distribution. However, under diffusion the total number of the population is stabilized when the zooplankton grazing rate above the rate of phytoplankton growth. In general, at low rate of phytoplankton consumption the spatial structures formation is possible at low rates of zooplankton decline and diffusion of all the plankton community. With the increase in phytoplankton predation rate the phytoplankton diffusion and zooplankton spatial movement has essential effect on the spatial instability.

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.

The biohydrochemical portrait of the White Sea is constructed on the CNPSi-model calculations based on long-term mean annual observations (average monthly hydrometeorological, hydrochemical and hydrobiological parameters of the marine environment) as well as on updated information on the nutrient input to the sea with the runoff of the main river tributaries (Niva, Onega, Northern Dvina, Mezen, Kem, Keret). Parameters of the marine environment are temperature, light, transparency, and biogenic load. Ecological characteristics of the sea “portrait” were calculated for nine marine areas (Kandalaksha, Onega, Dvinsky, Mezensky Bays, Solovetsky Islands, Basin, Gorlot, Voronka, Chupa Bay), these are: the concentration changes of organic and mineral compounds of biogenic elements (C, N, P, Si), the biomass of organisms of the lower trophic level (heterotrophic bacteria, diatomic phytoplankton, herbivorous and predatory zooplankton) and other ones (rates of substance concentration and organism biomass changes, internal and external substance flows, balances of individual substances and nutrients as a whole). Parameters of the marine environment state (water temperature, ratio of mineral fractions N < P) and dominant diatom phytoplankton in the sea (abundance, production, biomass, chlorophyll content a) were calculated and compared with the results of individual surveys (for 1972–1991 and 2007–2012) of the White Sea water areas. The methods for estimating the values of these parameters from observations and calculations differ, however, the calculated values of the phytoplankton state are comparable with the measurements and are similar to the data given in the literature. Therefore, according to the literature data, the annual production of diatoms in the White Sea is estimated at 1.5–3 million tons C (at a vegetation period of 180 days), and according to calculations it is ~2 and 3.5 million tons C for vegetation period of 150 and 180 days respectively.