Результаты поиска по 'permeability':
Найдено статей: 13
  1. Zaika Y.V., Rodchenkova N.I., Sidorov N.I.
    Modeling of H2-permeability of alloys for gas separation membranes
    Computer Research and Modeling, 2016, v. 8, no. 1, pp. 121-135

    High-purity hydrogen is required for clean energy and a variety of chemical technology processes. A considerable part of hydrogen is to be obtained by methane conversion. Different alloys, which may be wellsuited for use in gas-separation plants, were investigated by measuring specific hydrogen permeability. One had to estimate the parameters of diffusion and sorption to numerically model the different scenarios and experimental conditions of the material usage (including extreme ones), and identify the limiting factors. This paper presents a nonlinear model of hydrogen permeability in accordance with the specifics of the experiment, the numerical method for solving the boundary-value problem, and the results of parametric identification for the alloy V85Ni15.

    Keywords: hydrogen interaction with solids, surface processes, boundary-value problems, numerical simulation.
    Views (last year): 1. Citations: 7 (RSCI).
  2. Umavovskiy A.V.
    Data-driven simulation of a two-phase flow in heterogenous porous media
    Computer Research and Modeling, 2021, v. 13, no. 4, pp. 779-792

    The numerical methods used to simulate the evolution of hydrodynamic systems require the considerable use of computational resources thus limiting the number of possible simulations. The data-driven simulation technique is one promising approach to the development of heuristic models, which may speed up the study of such models. In this approach, machine learning methods are used to tune the weights of an artificial neural network that predicts the state of a physical system at a given point in time based on initial conditions. This article describes an original neural network architecture and a novel multi-stage training procedure which create a heuristic model of a two-phase flow in a heterogeneous porous medium. The neural network-based model predicts the states of the grid cells at an arbitrary timestep (within the known constraints), taking in only the initial conditions: the properties of the heterogeneous permeability of the medium and the location of sources and sinks. The proposed model requires orders of magnitude less processor time in comparison with the classical numerical method, which served as a criterion for evaluating the effectiveness of the trained model. The proposed architecture includes a number of subnets trained in various combinations on several datasets. The techniques of adversarial training and weight transfer are utilized.

    Keywords: data-driven simulation, physics informed neural networks, proxy modelling, hydrodynamics, porous media, convolutional neural networks, GAN.
  3. Rukhlenko A.S., Zlobina K.E., Guria G.T.
    Hydrodynamical activation of blood coagulation in stenosed vessels. Theoretical analysis
    Computer Research and Modeling, 2012, v. 4, no. 1, pp. 155-183

    The mechanisms of hydrodynamical activation of blood coagulation system are investigated in stenosed vessels for a wide range of Reynolds number values (from 10 up to 500). It is assumed that the vessel wall permeability for procoagulant factors rapidly increases when wall shear stress exceeds specific threshold value. A number of patterns of blood coagulation processes development are described. The influence of blood flow topology changes on activation of blood coagulation is explored. It is established that not only blood flow decrease, but also its increase may promote activation of blood coagulation. It was found that dependence of thrombogenic danger of stenosis on vessel lumen blockage ratio is non-monotonic. The relevance of obtained theoretical results for clinical practice is discussed.

    Keywords: mathematical modeling, blood coagulation, vessel stenosis, pattern formation.
    Views (last year): 2. Citations: 5 (RSCI).
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