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Register a new userAirflow in a Multiscale Subject-Specific Breathing Human Lung Model
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The airflow in a subject-specific breathing human lung is simulated with a multiscale computational fluid dynamics (CFD) lung model. The three-dimensional (3D) airway geometry beginning from the mouth to about 7 generations of airways is reconstructed from the multi-detector row computed tomography (MDCT) image at the total lung capacity (TLC). Along with the segmented lobe surfaces, we can build an anatomically-consistent one-dimensional (1D) airway tree spanning over more than 20 generations down to the terminal bronchioles, which is specific to the CT resolved airways and lobes (J Biomech 43(11): 2159-2163, 2010). We then register two lung images at TLC and the functional residual capacity (FRC) to specify subject-specific CFD flow boundary conditions and deform the airway surface mesh for a breathing lung simulation (J Comput Phys 244:168-192, 2013). The 1D airway tree bridges the 3D CT-resolved airways and the registration-derived regional ventilation in the lung parenchyma, thus a multiscale model. Large eddy simulation (LES) is applied to simulate airflow in a breathing lung (Phys Fluids 21:101901, 2009). In this fluid dynamics video, we present the distributions of velocity, pressure, vortical structure, and wall shear stress in a breathing lung model of a normal human subject with a tidal volume of 500 ml and a period of 4.8 s. On exhalation, air streams from child branches merge in the parent branch, inducing oscillatory jets and elongated vortical tubes. On inhalation, the glottal constriction induces turbulent laryngeal jet. The sites where high wall shear stress tends to occur on the airway surface are identified for future investigation of mechanotransduction.
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This work is devoted to the study of the decay of multiscale deterministic solutions of the unforced Burgers equation in the limit of vanishing viscosity. A deterministic model of turbulence-like evolution is considered. We con- struct the initial perturbation as a piecewise linear analog of the Weierstrass function. The wavenumbers of this function form a Weierstrass spectrum, which accumulates at the origin in geometric progression.Reverse sawtooth functions with negative initial slope are used in this series as basic functions, while their amplitudes are chosen by the condition that the distribution of energy over exponential intervals of wavenumbers is the same as for the continuous spectrum in Burgers turbulence. Combining these two ideas allows us to obtain an exact analytical solution for the velocity field. We also notice that such multiscale waves may be constructed for multidimensional Burgers equation. This solution has scaling exponent h=-(1+n)/2 and its evolution in time is self-similar with logarithmic periodicity and with the same average law L(t) as for Burgers turbulence. Shocklines form self-similar regular tree-like struc- tures. This model also describes important properties of the Burgers turbulence such as the self-preservation of the evolution of large scale structures in the presence of small scales perturbations.
A series of benchmarks based on the physical situation of phase inversion between two immiscible liquids is presented. These benchmarks aim at progressing toward the direct numerical simulation of two-phase flows. Several CFD codes developed in French laboratories and using either Volume-of-Fluid or Level-Set interface tracking methods are used to provide physical solutions of the benchmarks, convergence studies and code comparisons. Two typical configurations are retained, with integral scale Reynolds numbers of 13.700 and 433.000, respectively. The physics of the problem are probed through macroscopic quantities such as potential and kinetic energies, or enstrophy. In addition, scaling laws for the temporal decay of the kinetic energy are derived to check the physical relevance of the simulations. Finally the droplet size distribution is probed. Additional test problems are also reported to estimate the influence of viscous effects in the vicinity of the interface.
In a seminal article, citet[J. Fluid Mech., 174:441-465]{maxey87} presented a theoretical analysis showing that enhanced particle settling speeds in turbulence occur through the preferential sweeping mechanism, which depends on the preferential sampling of the fluid velocity gradient field by the inertial particles. However, recent Direct Numerical Simulation (DNS) results in citet[J. Fluid Mech., 796:659--711]{ireland16b} show that even in a portion of the parameter space where this preferential sampling is absent, the particles nevertheless exhibit enhanced settling velocities. Further, there are several outstanding questions concerning the role of different turbulent flow scales on the enhanced settling, and the role of the Taylor Reynolds number $R_lambda$. The analysis of Maxey does not explain these issues, partly since it was restricted to particle Stokes numbers $Stll1$. To address these issues, we have developed a new theoretical result, valid for arbitrary $St$, that reveals the multiscale nature of the mechanism generating the enhanced settling speeds. In particular, it shows how the range of scales at which the preferential sweeping mechanism operates depends on $St$. This analysis is complemented by results from DNS where we examine the role of different flow scales on the particle settling speeds by coarse-graining the underlying flow. The results show how the flow scales that contribute to the enhanced settling depend on $St$, and that contrary to previous claims, there can be no single turbulent velocity scale that characterizes the enhanced settling speed. The results explain the dependence of the particle settling speeds on $R_lambda$, and show how the saturation of this dependence at sufficiently large $R_lambda$ depends upon $St$. The results also show ...
The angle between subsequent particle displacement increments is evaluated as a function of the timelag in isotropic turbulence. It is shown that the evolution of this angle contains two well-defined power-laws, reflecting the multi-scale dynamics of high-Reynolds number turbulence. The proba-bility density function of the directional change is shown to be self-similar and well approximated by an analytically derived model assuming Gaussianity and independence of the velocity and the Lagrangian acceleration.
We use direct numerical simulations to investigate the interaction between the temperature field of a fluid and the temperature of small particles suspended in the flow, employing both one and two-way thermal coupling, in a statistically stationary, isotropic turbulent flow. Using statistical analysis, we investigate this variegated interaction at the different scales of the flow. We find that the variance of the fluid temperature gradients decreases as the thermal response time of the suspended particles is increased. The probability density function (PDF) of the fluid temperature gradients scales with its variance, while the PDF of the rate of change of the particle temperature, whose variance is associated with the thermal dissipation due to the particles, does not scale in such a self-similar way. The modification of the fluid temperature field due to the particles is examined by computing the particle concentration and particle heat fluxes conditioned on the magnitude of the local fluid temperature gradient. These statistics highlight that the particles cluster on the fluid temperature fronts, and the important role played by the alignments of the particle velocity and the local fluid temperature gradient. The temperature structure functions, which characterize the temperature fluctuations across the scales of the flow, clearly show that the fluctuations of the fluid temperature increments are monotonically suppressed in the two-way coupled regime as the particle thermal response time is increased. Thermal caustics dominate the particle temperature increments at small scales, that is, particles that come into contact are likely to have very large differences in their temperature. This is caused by the nonlocal thermal dynamics of the particles...
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