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An overview is given for identification criteria of tip vortices, trailing from lifting surfaces of aircraft. $Q$-distribution is used as the main vortex identification method in this work. According to the definition of Q-criterion, the vortex core is bounded by a surface on which the norm of the vorticity tensor is equal to the norm of the strain-rate tensor. Moreover, following conditions are satisfied inside of the vortex core: (i) net (non-zero) vorticity tensor; (ii) the geometry of the identified vortex core should be Galilean invariant. Based on the existing analytical vortex models, a vortex center of a twodimensional vortex is defined as a point, where the $Q$-distribution reaches a maximum value and it is much greater than the norm of the strain-rate tensor (for an axisymmetric 2D vortex, the norm of the vorticity tensor tends to zero at the vortex center). Since the existence of the vortex axis is discussed by various authors and it seems to be a fairly natural requirement in the analysis of vortices, the above-mentioned conditions (i), (ii) can be supplemented with a third condition (iii): the vortex core in a three-dimensional flow must contain a vortex axis. Flows, having axisymmetric or non-axisymmetric (in particular, elliptic) vortex cores in 2D cross-sections, are analyzed. It is shown that in such cases $Q$-distribution can be used to obtain not only the boundary of the vortex core, but also to determine the axis of the vortex. These concepts are illustrated using the numerical simulation results for a finite span wing flow-field, obtained using the Reynolds-Averaged Navier – Stokes (RANS) equations with $k-\omega$ turbulence model.

Reduction of the fire hazard of polymeric materials is one of the important scientific and technical problems. Since complexity of experimental procedures associated with flame spread, establishing reacting flows theoretical basics turned out to be crucial field of modern fundamental science. In order to determine parameters of flame spread over solid combustible materials numerical modelling methods have to be improved. Large amount of physical and chemical processes taking place needed to be resolved not just separately one by one but in connection with each other in gas and solid phases.

Upward flame spread over vertical solid combustible material is followed by unsteady eddy structures of gas flow in the vicinity of flame zone caused by thermal instability and natural convection forces accelerating hot combustion products. At every moment different amount of heat energy is transferred from hot gas-phase flame to solid material because of eddy flow structures. Therefore, satisfactory heat flux and eddy flow modelling are important to estimate flame spread rate.

In the current study we evaluated parameters of numerical method for flame spread over solid combustible material problem taking into account coupled nature of complex interaction between gas phase, solid material and eddy flow resulted from natural convection. We studied aspects of different approximation schemes used in differential equations integration process over space and time, of fields relaxation during iterations procedure carried out inside time step, of different time step values.

Mathematical model formulated allows to simulate flame spread over solid combustible material. Fluid dynamics is modeled by Navier – Stokes system of equations, eddy flow is described by combined turbulent model RANS–LES (DDES), turbulent combustion is resolved by modified turbulent combustion model Eddy Break-Up taking into account kinetic effects, radiation transfer is modeled by spherical harmonics method of first order approximation (P1). The equations presented are solved in OpenFOAM software.

The article presents the results of a numerical study of the flow structure in a two-dimensional flat diffuser. A feature of diffusers is that they have a complex anisotropic turbulent flow, which occurs due to recirculation flows. The turbulent RANS models, which are based on the Boussinesq hypothesis, are not able to describe the flow in diffusers with sufficient accuracy. Because the Boussinesq hypothesis is based on isotropic turbulence. Therefore, to calculate anisotropic turbulent flows, models are used that do not use this hypothesis. One of such directions in turbulence modeling is the methods of Reynolds stresses. These methods are complex and require rather large computational resources. In this work, a relatively recently developed two-fluid turbulence model was used to study the flow in a flat diffuser. This model is developed on the basis of a two-fluid approach to the problem of turbulence. In contrast to the Reynolds approach, the two-fluid approach allows one to obtain a closed system of turbulence equations using the dynamics of two fluids. Consequently, if empirical equations are used in RANS models for closure, then in the two-fluid model the equations used are exact equations of dynamics. One of the main advantages of the two-fluid model is that it is capable of describing complex anisotropic turbulent flows. In this work, the obtained numerical results for the profiles of the longitudinal velocity, turbulent stresses in various sections of the channel, as well as the friction coefficient are compared with the known experimental data. To demonstrate the advantages of the used turbulence model, the numerical results of the Reynolds stress method EARSM are also presented. For the numerical implementation of the systems of equations of the two-fluid model, a non-stationary system of equations was used, the solution of which asymptotically approached the stationary solution. For this purpose, a finite-difference scheme was used, where the viscosity terms were approximated by the central difference implicitly, and for the convective terms, an explicit scheme against the flow of the second order of accuracy was used. The results are obtained for the Reynolds number Re = 20 000. It is shown that the two-fluid model, despite the use of a uniform computational grid without thickening near the walls, is capable of giving a more accurate solution than the rather complex Reynolds stress method with a high resolution of computational grids.

Modern approach to modernization of the experimental techniques involves design of mathematical models of the wind-tunnel, which are also referred to as Electronic of Digital Wind-Tunnels. They are meant to supplement experimental data with computational analysis. Using Electronic Wind-Tunnels is supposed to provide accurate information on aerodynamic performance of an aircraft basing on a set of experimental data, to obtain agreement between data from different test facilities and perform comparison between computational results for flight conditions and data with the presence of support system and test section.

Completing this task requires some preliminary research, which involves extensive wind-tunnel testing as well as RANS-based computational research with the use of supercomputer technologies. At different stages of computational investigation one may have to model not only the aircraft itself but also the wind-tunnel test section and the model support system. Modelling such complex geometries will inevitably result in quite complex vertical and separated flows one will have to simulate. Another problem is that boundary layer transition is often present in wind-tunnel testing due to quite small model scales and therefore low Reynolds numbers.

In the current article the first stage of the Electronic Wind-Tunnel design program is covered. This stage involves computational investigation of aerodynamic characteristics of the generic flying-wing UAV model previously tested in TsAGI T-102 wind-tunnel. Since this stage is preliminary the model was simulated without taking test-section and support system geometry into account. The boundary layer was considered to be fully turbulent.

For the current research FlowVision computational code was used because of its automatic grid generation feature and stability of the solver when simulating complex flows. A two-equation k–ε turbulence model was used with special wall functions designed to properly capture flow separation. Computed lift force and drag force coefficients for different angles-of-attack were compared to the experimental data.

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).

Numerical modeling of turbulent flows requires finding the balance between accuracy and computational efficiency. For example, DNS and LES models allow to obtain more accurate results, comparing to RANS models, but are more computationally expensive. Because of this, modern applied simulations are mostly performed with RANS models. But even RANS models can be computationally expensive for complex geometries or series simulations due to the necessity of resolving the boundary layer. Some methods, such as wall functions and near-wall domain decomposition, allow to significantly improve the speed of RANS simulations. However, they inevitably lose precision due to using a simplified model in the near-wall domain. To obtain a model that is both accurate and computationally efficient, it is possible to construct a surrogate model based on previously made simulations using the precise model.

In this paper, an operator is constructed that allows reconstruction of the flow field obtained by an accurate model based on the flow field obtained by the simplified model. Spalart–Allmaras model with approximate nearwall domain decomposition and Spalart–Allmaras model resolving the near-wall region are taken as the simplified and the base models respectively. The operator is constructed using a local approach, i. e. to reconstruct a point in the flow field, only features (flow variables and their derivatives) at this point in the field are used. The operator is constructed using the Random Forest algorithm. The efficiency and accuracy of the obtained surrogate model are demonstrated on the supersonic flow over a compression corner with different values for angle $\alpha$ and Reynolds number. The investigation has been conducted into interpolation and extrapolation both by $Re$ and $\alpha$.