Search Results (5)

The primary focus of this article is to derive a solution to obtain the asymptotic turbulent dispersion parameter provided by the spectral Taylor statistical diffusion model. Unlike previous articles, which employed the Dirac delta function to solve the eddy diffusivity formula, in this study, we used the Dirac delta function properties to obtain directly the asymptotic turbulent dispersion parameter from the particles’ spatial dispersion variance described in terms of the Eulerian turbulence spectrum and of the scale factor defined formally as the ratio between Lagrangian and Eulerian timescales. From the Kolmogorov 1941 theory, a detailed derivation for this scale factor is presented. Furthermore, using high mean wind speed data generated by local topographic features, a magnitude for the Kolmogorov constant for the neutral atmospheric boundary layer is evaluated. Thus, this magnitude when added to other values obtained from the selected studies found in the literature provides an average value for the Kolmogorov constant that agrees with large eddy simulation data results. Therefore, this average value allows to obtain a more reliable description of this scale factor. Finally, employing analytical formulations for the observed neutral turbulent spectra and for the velocity variances as well as turbulent statistical quantities measured in a surface neutral atmospheric boundary layer, a vertical dispersion parameter is derived. This vertical dispersion parameter when utilized in a simple Gaussian diffusion model is able to reproduce well contaminant observed concentrations.The Gaussian simulated concentrations also compare well with those simulated by a Lagrangian stochastic particle dispersion model that uses observed vertical spectral peak frequency values at distinct levels of the neutral surface boundary layer. Therefore, the present study shows that the observational determination of a single vertical spectral peak frequency is sufficient to obtain a realistic vertical dispersion parameter characterizing the dispersive effect in the turbulent environment of the surface neutral atmospheric boundary layer. Full article

A two-way coupled model between polydisperse particle phases with compressible gases and a density-based coupling implicit solution method, combining the third-order MUSCL with QUICK spatial discretization scheme and the second-order temporal discretization scheme, are constructed based on the discrete-phase model (DPM) and the stochastic wander model (DRWM) in the Eulerian–Lagrangian framework in conjunction with a unitary particulate source (PSIC) approach and the SST k-ω turbulence model. The accuracy of the numerical prediction method is verified using previous supersonic nozzle gas-solid two-phase flow experiments. Numerical simulation of a two-phase jet of dry powder extinguishing agent gas with pilot-type supersonic nozzle was performed to analyze the influence of geometrical parameters, such as the length ratio r_L and the area ratio r_A of the main nozzle on the two-phase flow field, as well as on the jet performance indexes, such as the particle mean velocity v_p,a, velocity inhomogeneity Φ_vp, particle dispersion Ψ_p, particle mean acceleration a_p,a, etc. By analyzing the parameters, we indicate the requirements for the combination of jet performance metrics for different flame types such as penetrating, spreading, and dispersing. Full article

Considering the influence of the downslope windstorm called “Vento Norte” (VNOR; Portuguese for “North Wind”) in planetary boundary layer turbulent features, a new set of turbulent parameterizations, which are to be used in atmospheric dispersion models, has been derived. Taylor’s statistical diffusion theory, velocity spectra obtained at four levels (3, 6, 14, and 30 m) in a micrometeorological tower, and the energy-containing eddy scales are used to calculate neutral planetary boundary layer turbulent parameters. Vertical profile formulations of the wind velocity variances and Lagrangian decorrelation time scales are proposed, and to validate this new parameterization, it is applied in a Lagrangian Stochastic Particle Dispersion Model to simulate the Prairie Grass concentration experiments. The simulated concentration results were shown to agree with those observed. Full article

The accumulation of particles in a turbulent flow of incompressible air with mono-dispersed solid particles inside a 90° pipe bend was simulated using ANSYS^® Fluent (CFD), taking into account the effect of gravity, drag force and a bidirectional fluid-particle coupling. An analysis of the geometrical parameters and the structures of the secondary flow generated in a curved pipe (Dean vortices) was developed, thus determining the characteristic time scales of the flow. Four Stokes numbers (Stk) were formulated, whose values are calculated and studied from the numerical simulations performed. Two different particle sizes (d1 = 50 μm y d2 = 150 μm), at two different flow conditions (Re1 = 61,500 y Re2 = 173,972), and for three curvature ratios Rc/R = 1, 4 and 8 were studied. The flow was solved using a Eulerian–Lagrangian approach with a RNG k-ε turbulence model. Once the multiphase flow was solved and validated, the distribution and maximum particle concentration inside the 90° bend were presented. Additionally, the Stk numbers were calculated to estimate the possible particle concentration level for the different system configurations (dp, Re and Rc/R). It is concluded that, if all Stk numbers are less than one, relative concentration levels reach a minimum, while for Stk numbers larger than one, an increase in the maximum concentration inside the pipe bend was noticed. Full article

The multi-phase Rayleigh–Bènard convection has been weakly investigated, even though it plays a leading role in the theoretical and applied physics of the heat transfer enhancement. For the case of moderate turbulent convection, a rather unexpected result is an unusual kind of wind reversal, in the sense that the fluid is found to be strongly influenced by the bubbles, whereas the bubbles themselves appear to be little affected by the fluid, despite the relative smallness of the Stokes numbers. The wind reversal induced by the bubbles dispersed in the fluid is a new and remarkable phenomenon in multi-phase flows that provides further perspectives in understanding the complex physics leading the enhancement of thermal convection. For this reason, the fundamental research proposed in this paper aimed to identify a space of control parameters and the physical mechanisms responsible for the wind reversal induced by dispersed bubbles in a confined convective flow. The strength of the following description lies in an innovative numerical approach, based on the multi-scale physics induced by the coupling of the local thermal and mechanical mechanisms arising between each bubble and the surrounding fluid. The continuous phase has been solved numerically using the direct numerical simulation (DNS) technique and each bubble has been tracked by means of a particle Lagrangian model. Full article