Recent publications of the Research Unit

2021

    M. Wouters, O. Aouane, M. Sega, and J. Harting
    Lattice Boltzmann simulations of drying suspensions of soft particles
    Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. , 2021, 379, 20200399
    DOI: 10.1098/rsta.2020.0399

Snapshot of a simulation of 4806 particles. The boundary elements of the particles are coloured according to their height. For clarity, the fluid-fluid interface is not shown.
Snapshot of a simulation of 4806 particles.

    Evgeny S. Asmolov, Tatiana V. Nizkaya1, Jens Harting, and Olga I. Vinogradova
    Instability of particle inertial migration in shear flow
    Phys. Fluids , 2021, 33, 092008
    DOI: 10.1063/5.0063566

(a) Sketch of the particle motion in a shear flow. A particle translating across the streamlines experiences a transverse drag and a lift force. (b) Particle velocity in a neutral equilibrium.
Sketch of the particle motion in a shear flow.

    Daniel Feldmann, Daniel Morón, and Marc Avila
    Spatiotemporal Intermittency in Pulsatile Pipe Flow
    Entropy, 2021, 23, 46
    DOI: 10.3390/e23010046

Instantaneous representation of localised turbulent structures in a pulsatile pipe flow DNS at (Re=2400, Wo=8, A=1.4). The DNS was initialised at t/T=0.25 using the corresponding SW profile and by introducing a local bump like body force. Grey surfaces represent low-speed streaks and blue/red surfaces represent positive/negative axial vorticity. (a–d) Local bump. (e–h) Tilted bump. The direction of the mean bulk flow is always from left to right.
Instantaneous representation of localised turbulent structures in a pulsatile pipe flow.

    Steffen M. Recktenwald, Christian Wagner, and Thomas John
    Optimizing pressure-driven pulsatile flows in microfluidic devices
    Lab Chip, 2021, 14, 4680-4687
    DOI: 10.1039/D0LC01297A

(a) Schematic representation of the microfluidic setup. The feedback control system consists of the pressure controller and sensor, the tubing, the sample containers, and the microfluidic chip. The effect of the optimization approach is schematically shown in (b). While the non-optimized device output pressure deviates from the desired waveform (top), the optimization approach enhances the time-dependent pressure output and hence the flow velocity in the microfluidic chip (bottom).
Schematic representation of the microfluidic setup and the effect of the optimization approach.

  • Pascal Corso, Jonas Walheim, Hannes Dillinger, George Giannakopoulos, Utku Gülan, Christos Emmanouil Frouzakis, Sebastian Kozerke, and Markus Holzner
    Toward an accurate estimation of wall shear stress from 4D flow magnetic resonance downstream of a severe stenosis
    Magn Reson Med., 2021, 00, 1– 13
    DOI: 10.1002/mrm.28795

Magnitude of wall shear stress from the posterior view obtained A, from DNS complemented with the arrow representation of the WSS vector at the aorta wall; B, from MRI data using the direct and formal definition of WSS; C, using the first model M1 for the evaluation from MRI measurements; D, using the second model M2 for the MRI-based assessment.
Magnitude of wall shear stress from the posterior view.

  • Othmane Aouane, Andrea Scagliarini, and Jens Harting
    Structure and rheology of suspensions of spherical strain-hardening capsules
    J. Fluid Mech., 2021, 911, A11
    DOI: 10.1017/jfm.2020.1040

Relative viscosity as a function of the effective volume fraction. The dashed and dotted lines corresponds to fits of the numerical data.
Relative viscosity as a function of the effective volume fraction. The dashed and dotted lines corresponds to fits of the numerical data.

  • François Yaya, Johannes Römer, Achim Guckenberger, Thomas John, Stephan Gekle, Thomas Podgorski, and Christian Wagner
    Vortical Flow Structures Induced by Red Blood Cells in Capillaries
    Microcirculation, 2021, e12693
    DOI: 10.1111/micc.12693

3D view showing the provenance (blue arrow) of the tracers and their trajectories for a cell velocity of 2.2 mm/s.
3D view showing the provenance (blue arrow) of the tracers and their trajectories for a cell velocity of 2.2 mm/.

  • Alexander Kihm, Stephan Quint, Matthias W. Laschke, Michael D. Menger, Thomas John, Lars Kaestner, and Christian Wagner
    Lingering Dynamics in Microvascular Blood Flow
    Biophysj, 2021, 4, 1-8
    DOI: 10.1016/j.bpj.2020.12.012

Probability density functions of scaled void durations for all branches if only lingering events are taken into account. The inset graph shows both the probability densities in the case of lingering and nonlingering, respectively to represent extreme cases of the median shift.
Probability density functions of scaled void durations for all branches if only lingering events are taken into account. The inset graph shows both the probability densities in the case of lingering and nonlingering, respectively to represent extreme cases of the median shift.

  • Duo Xu, Baofang Song, and Marc Avila
    Non-modal transient growth of disturbances in pulsatile and oscillatory pipe flows
    J. Fluid Mech., 2021, 907, R5
    DOI: 10.1017/jfm.2020.940

Contours of stream-wise vorticity (on an r-θ cross-section) of the helical disturbance at t<sub>0</sub>/T = 0.5.
Contours of stream-wise vorticity (on an r-θ cross-section) of the helical disturbance at t0/T = 0.5.

2020

  • Maarten Wouters, Othmane Aouane, Marcello Sega, and Jens Harting
    Capillary interactions between soft capsules protruding through thin fluid films
    Soft Matter, 2020, 16, 10910–10920
    DOI: 10.1039/d0sm01385d

Time evolution of the gap between two soft particles: (solid line) β = 10, (dashed line) β = 25, (dot-dashed line) β = 50. The grey area indicates the repulsive region. Inset: Final state of two particles with β = 50 (solid lines) at the interface (dashed line).
Time evolution of the gap between two soft particles: (solid line) β = 10, (dashed line) β = 25, (dot-dashed line) β = 50. The grey area indicates the repulsive region.

  • Moritz Lehmann, Sebastian Johannes Müller, and Stephan Gekle
    Efficient viscosity contrast calculation for blood flow simulations using the lattice Boltzmann method
    Int. J. Numer. Methods Fluids, 2020, 92, 1463–1477
    DOI: 10.1002/fld.4835

The center of mass radial displacement averaged over the last 0.2 seconds for different values of 𝜆. Lattice Boltzmann method with our inside/outside tracking and local viscosity change reproduces the 𝜆-phase-transition from boundary-integral simulations quite accurately.
The center of mass radial displacement averaged over the last 0.2 seconds for different values of 𝜆.

  • Duo Xu, Matthias Heil, Thomas Seeböck, and Marc Avila
    Resonances in Pulsatile Channel Flow with an Elastic Wall
    Phys. Rev. Lett., 2020, 125, 254501
    DOI: 10.1103/PhysRevLett.125.254501

(a),(b) Sketch of the model. (c) Oscillation amplitude, where the solid and the dashed lines denote the viscous and the inviscid prediction, and black and blue correspond to β = 0.25 and β = 0. The black symbols show the results from the simulations. The dotted lines mark the corresponding eigenfrequencies.
(a),(b) Sketch of the model. (c) Oscillation amplitude, where the solid and the dashed lines denote the viscous and the inviscid prediction, and black and blue correspond to β = 0.25 and β = 0. The black symbols show the results from the simulations. The dotted lines mark the corresponding eigenfrequencies.

  • Tatiana V. Nizkaya, Evgeny S. Asmolov, Jens Harting, and Olga I. Vinogradova
    Inertial migration of neutrally buoyant particles in superhydrophobic channels
    Phys. Rev. Fluids, 2020, 5, 014201
    DOI: 10.1103/PhysRevFluids.5.014201

Sketch of the system: side (a) and top (b) views, with a schematic of vertical and transverse migration.
Sketch of the system: side (a) and top (b) views, with a schematic of vertical and transverse migration.

  • Tatiana V. Nizkaya1, Anna S. Gekova, Jens Harting, Evgeny S. Asmolov, and Olga I. Vinogradova
    Inertial migration of oblate spheroids in a plane channel
    Phys. Fluids, 2020, 32, 112017
    DOI: 10.1063/5.0028353

An oblate spheroid orienting in a pressure-driven flow to perform a stable log-rolling state.
An oblate spheroid orienting in a pressure-driven flow to perform a stable log-rolling state.

  • Duo Xu, Atul Varshney, Xingyu Ma, Baofang Song, Michael Riedl, Marc Avila, and Björn Hof
    Nonlinear hydrodynamic instability and turbulence in pulsatile flow
    PNAS, 2020, 117, 21, 11233–11239
    DOI: 10.1073/pnas.1913716117

Visualization of the numerical simulation of a turbulent blood stream.
Visualization of the numerical simulation of a turbulent blood stream.

  • Asena Abay, Steffen M. Recktenwald, Thomas John, Lars Kaestner, and Christian Wagner
    Cross-sectional focusing of red blood cells in a constricted microfluidic channel
    Soft Matter, 2020,16, 534-543
    DOI: 10.1039/C9SM01740B

Schematic representation of red blood cells (RBCs)
	flowing through a contraction–expansion microfluidic device. Passing the contraction, RBCs are 
	mainly focused in two lines near the shorter faces in the channel center plane (z = 0 and y/W ≈ ±0.4)
	and at the top and bottom of the channel near the walls (z/H ≈ ±0.3 and −0.4 ≤ y/W ≤ 0.4).
Schematic representation of red blood cells flowing through a contraction–expansion microfluidic device.



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