Current Results and Proposed Activities in Microgravity Fluid Dynamics

The Institute for Problems in Mechanics' Laboratory work in mathematical and physical modelling of fluid mechanics develops models, methods, and software for analysis of fluid flow, instability analysis, direct numerical modelling and semi-empirical models of turbulence, as well as experimental research and verification of these models and their applications in technological fluid dynamics, microgravity fluid mechanics, geophysics, and a number of engineering problems. This paper presents an overview of the results in microgravity fluid dynamics research during the last two years. Nonlinear problems of weakly compressible and compressible fluid flows are discussed

Enhanced evaporation from an oscillating liquid in a capillary tube

Enhanced evaporation inside a capillary tube into which the liquid/gas meniscus oscillates is experimentally studied. It is found that the meniscus oscillation can markedly level-off the evaporation rate, while keeping an apparent diffusive behaviour. The apparent diffusive coefficient can reach a tenfold increase in the explored range of parameters. The dependence of the effect is studied by varying the capillary tube diameter, the frequency and the amplitude of the liquid oscillations. The parametric dependence of the apparent diffusive coefficient is well captured by the associated dimensionless Péclet number. A nice collapse of the experimental measurements consistent with a quadratic scaling with Péclet number is found. Such scaling is suggested by previous theoretical and experimental analysis associated with a Taylor dispersion transport mechanism. Nevertheless the prefactor of those theory is found to under-predict the observed effect by a factor three. This deviation from Taylor’s dispersion driven transport predictions is discussed

Selected methods of hydrogen obtaining and mineral resources for their implementation

Institute of Geochemistry, Mineralogy and Mineral ResourcesÚstav geochemie, mineralogie a nerostných zdrojůPřírodovědecká fakultaFaculty of Scienc

Forming the Architecture of a Multi-Layered Model of Physical Data Storage for Complex Telemedicine Systems

The relevance of this research is determined by the need to study the issues of improving data storage technologies for complex telemedicine systems. The objective is to create a multi-layered data storage model for complex telemedicine systems to ensure the most complete use of their capacity and the timely expansion of existing storage. The research is conducted on the basis of an analysis of existing opportunities and problems in the field of data storage technologies. An analysis of the main features of the development of data storage technologies revealed that the existing models have no detailed description of the recording and physical storage of data bits, which is necessary for describing the storage process. Different architectures are reviewed, and their strengths and weaknesses are discussed. Within the framework of a demonstration experiment using the Kohonen neural network apparatus as a tool for solving the problem of placing objects in accordance with the required parameters, it is shown that the proposed storage system resource management model is operable and allows solving the problem of rational use of physical resources. As a result, a multilevel model of data storage is proposed, which combines the levels of storage process organization and technology. The distinguishing feature of this method is the comparison of storage organization levels, data media, and characteristics of physical storage and stored files. Doi: 10.28991/HIJ-2023-04-04-09 Full Text: PD

Thermal gravity-driven convection of near-critical helium in enclosures

The results of numerical simulation of Rayleigh-Benard convection in ³He near the thermodynamic critical point are presented. The mathematical model including the full Navier-Stokes equations with two-scale splitting of the pressure and the van der Waals equation of state is applied. The known experimental data on ³He are used in simulations. On the basis of the calibration laws the "real" Rayleigh and Prandtl numbers are estimated. It is shown that one should agree these "real" criteria of similarity in the model and physical media to approach results of simulations to experiments. The Rayleigh number characterising the convection onset is defined from obtained numerical data. This number is shown to be in a good agreement with known experimental and theoretical values

Machine Learning Approaches to Choose Heroes in Dota 2

The winning in the multiplayer online game Dota 2 for teams is a sum of many factors. One of the most significant of them is the right choice of heroes for the team. It is possible to predict a match result based on the chosen heroes for both teams. This paper considers different approaches to predicting results of a match using machine learning methods to solve the classification problem. The experimental comparison of predictive classification models was done, including the optimization of their hyperparameters. It showed that the best classification models are linear regression, linear support vector machine, as well as neural network with Softplus and Sigmoid activation functions. The fastest of them is the linear regression model, so it is best suited for practical implementation