A machine-learning-based method for automatizing lattice-Boltzmann simulations of respiratory flows

Many simulation workflows require to prepare the data for the simulation manually. This is time consuming and leads to a massive bottleneck when a large number of numerical simulations is requested. This bottleneck can be overcome by an automated data processing pipeline. Such a novel pipeline is developed for a medical use case from rhinology, where computer tomography recordings are used as input and flow simulation data define the results. Convolutional neural networks are applied to segment the upper airways and to detect and prepare the in- and outflow regions for accurate boundary condition prescription in the simulation. The automated process is tested on three cases which have not been used to train the networks. The accuracy of the pipeline is evaluated by comparing the network-generated output surfaces to those obtained from a semi-automated procedure performed by a medical professional. Except for minor deviations at interfaces between ethmoidal sinuses, the network-generated surface is sufficiently accurate. To further analyze the accuracy of the automated pipeline, flow simulations are conducted with a thermal lattice-Boltzmann method for both cases on a high-performace computing system. The comparison of the results of the respiratory flow simulations yield averaged errors of less than 1% for the pressure loss between the in- and outlets, and for the outlet temperature. Thus, the pipeline is shown to work accurately and the geometrical deviations at the ethmoidal sinuses to be negligible.

Adaptive Mesh Refinement Strategies for a Novel Modelof Immiscible Fluid Flow in Fractures

In this paper, we consider two Adaptive Mesh Refinement (AMR) methods to simulate flow through fractures using a novel multiphase model. The approach represents the fluid using a two-dimensional parallel-plate model that employs techniques adapted from lattice-Boltzmann simulations to track the fluid interface. Here, we discuss different mesh refinement strategies for the model and compare their performance to that of a uniform grid. Results from the simulations are demonstrated showing excellent agreement between the model and analytical solutions for both unrefined and refined meshes. We also present results from the study that illustrate the behavior of the AMR front-tracking method. The AMR model is able to accurately track the interfacial properties in cases where uniform fine meshes would significantly increase the simulation cost.The ability of the model to dynamically refine the domain is demonstrated by presenting the results from an example with evolving interfaces.

Numerical Simulations of Flows in a Cerebral Aneurysm Using the Lattice Boltzmann Method with the Half-Way and Interpolated Bounce-Back Schemes

Lattice Boltzmann simulations and a velocity measurement of flows in a cerebral aneurysm reconstructed from MRA (magnetic resonance angiography) images of an actual aneurysm were carried out and the numerical results obtained using the bounce-back schemes were compared with the experimental data to discuss the effects of the numerical treatment of the no-slip boundary condition of the complex boundary shape of the aneurysm on the predictions. The conclusions obtained are as follows: (1) measured data of the velocity in the aneurysm model useful for validation of numerical methods were obtained, (2) the numerical stability of the quadratic interpolated bounce-back scheme (QBB) in the flow simulation of the cerebral aneurysm is lower than those of the half-way bounce-back (HBB) and the linearly interpolated bounce-back (LBB) schemes, (3) the flow structures predicted using HBB and LBB are comparable and agree well with the experimental data, and (4) the fluctuations of the wall shear stress (WSS), i.e., the oscillatory shear index (OSI), can be well predicted even with the jaggy wall representation of HBB, whereas the magnitude of WSS predicted with HBB tends to be smaller than that with LBB.

Lattice Boltzmann simulations of drying suspensions of soft particles

The ordering of particles in the drying process of a colloidal suspension is crucial in determining the properties of the resulting film. For example, microscopic inhomogeneities can lead to the formation of cracks and defects that can deteriorate the quality of the film considerably. This type of problem is inherently multiscale and here we study it numerically, using our recently developed method for the simulation of soft polymeric capsules in multicomponent fluids. We focus on the effect of the particle softness on the film microstructure during the drying phase and how it relates to the formation of defects. We quantify the order of the particles by measuring both the Voronoi entropy and the isotropic order parameter. Surprisingly, both observables exhibit a non-monotonic behaviour when the softness of the particles is increased. We further investigate the correlation between the interparticle interaction and the change in the microstructure during the evaporation phase. We observe that the rigid particles form chain-like structures that tend to scatter into small clusters when the particle softness is increased. This article is part of the theme issue ‘Progress in mesoscale methods for fluid dynamics simulation’.

Lattice Boltzmann simulations on the tumbling to tank-treading transition: effects of membrane viscosity

The tumbling to tank-treading (TB-TT) transition for red blood cells (RBCs) has been widely investigated, with a main focus on the effects of the viscosity ratio λ (i.e., the ratio between the viscosities of the fluids inside and outside the membrane) and the shear rate γ ˙ applied to the RBC. However, the membrane viscosity μ m plays a major role in a realistic description of RBC dynamics, and only a few works have systematically focused on its effects on the TB-TT transition. In this work, we provide a parametric investigation on the effect of membrane viscosity μ m on the TB-TT transition for a single RBC. It is found that, at fixed viscosity ratios λ , larger values of μ m lead to an increased range of values of capillary number at which the TB-TT transition occurs; moreover, we found that increasing λ or increasing μ m results in a qualitatively but not quantitatively similar behaviour. All results are obtained by means of mesoscale numerical simulations based on the lattice Boltzmann models. This article is part of the theme issue ‘Progress in mesoscale methods for fluid dynamics simulation’.

Unsteady lattice Boltzmann simulations of corner separation in a compressor cascade

Lattice-Boltzmann simulations of corner separation flow in a compressor cascade are presented. The lattice Boltzmann approach is rather new in the context of turbomachinery and the configuration is known to be particularly challenging for turbulence modelling. The present methodology is characterized by a quasi-autonomous meshing strategy and a limited computational cost (a net ratio of 5 compared to a previous finite-volume compressible Navier-Stokes simulation). The simulation of the reference case (4° incidence) shows a good agreement with the experimental data concerning the wall pressure distribution or the distribution of losses. A good description is also obtained when incidence angle is increased to 7°, with a span-wise development of the separation. Subsequently, the methodology is used to investigate the sensitivity of the flow to the end-wall boundary-layer thickness. A thinner boundary-layer results in a smaller corner separation, but not a complete elimination. Finally, the ingredients of the wall modelling are analysed in details. On the one hand, the curvature correction term promotes transition to turbulence on the blade suction side and avoids a spurious separation. On the other hand, the addition of the pressure-gradient correction term allows a wider and more realistic corner separation.