nsCouette – A high-performance code for direct numerical simulations of turbulent Taylor–Couette flow

Lopez, José M.; Feldmann, Daniel; Rampp, Markus; Vela-Martín, Alberto; Shi, Liang; Avila, Marc

doi:10.1016/j.softx.2019.100395

Cited by 14 publications

(15 citation statements)

References 20 publications

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“…In order to study the departure from the laminar Sexl–Womersley flow and the dynamics of intermittent localised turbulence, we perform direct numerical simulations (DNS) using our open-source pseudo-spectral simulation code [ 22 ]. In , the governing Equation ( 2 ) are treated in cylindrical coordinates

and discretised using a Fourier–Galerkin ansatz in

and z and high-order finite differences in r .…”

Section: Numerical Methodologymentioning

confidence: 99%

“…The discretised NSEs are integrated forward in time using a second-order predictor–corrector method with variable time-step size; details are given in López et al. [ 22 ] and the references therein. We have modified to account for a time-dependent driving force that maintains a pulsating flow rate according to Equation ( 1 ) and an additional volume force

to perturb the flow locally.…”

Section: Numerical Methodologymentioning

confidence: 99%

“…In nsPipe, the governing Equation (2) are treated in cylindrical coordinates (r, θ, z) and discretised using a Fourier-Galerkin ansatz in θ and z and high-order finite differences in r. No-slip boundary conditions are imposed at the solid pipe wall and periodic boundary conditions in θ and z. The discretised NSEs are integrated forward in time using a second-order predictorcorrector method with variable time-step size; details are given in López et al [22] and the references therein. We have modified nsPipe to account for a time-dependent driving force that maintains a pulsating flow rate according to Equation (1) and an additional volume force F p to perturb the flow locally.…”

Section: Direct Numerical Simulationmentioning

confidence: 99%

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Spatiotemporal Intermittency in Pulsatile Pipe Flow

Feldmann¹,

Morón²,

Avila³

2020

Entropy

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Despite its importance in cardiovascular diseases and engineering applications, turbulence in pulsatile pipe flow remains little comprehended. Important advances have been made in the recent years in understanding the transition to turbulence in such flows, but the question remains of how turbulence behaves once triggered. In this paper, we explore the spatiotemporal intermittency of turbulence in pulsatile pipe flows at fixed Reynolds and Womersley numbers (Re=2400, Wo=8) and different pulsation amplitudes. Direct numerical simulations (DNS) were performed according to two strategies. First, we performed DNS starting from a statistically steady pipe flow. Second, we performed DNS starting from the laminar Sexl–Womersley flow and disturbed with the optimal helical perturbation according to a non-modal stability analysis. Our results show that the optimal perturbation is unable to sustain turbulence after the first pulsation period. Spatiotemporally intermittent turbulence only survives for multiple periods if puffs are triggered. We find that puffs in pulsatile pipe flow do not only take advantage of the self-sustaining lift-up mechanism, but also of the intermittent stability of the mean velocity profile.

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and discretised using a Fourier–Galerkin ansatz in

and z and high-order finite differences in r .…”

Section: Numerical Methodologymentioning

confidence: 99%

to perturb the flow locally.…”

Section: Numerical Methodologymentioning

confidence: 99%

Section: Direct Numerical Simulationmentioning

confidence: 99%

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Spatiotemporal Intermittency in Pulsatile Pipe Flow

Feldmann¹,

Morón²,

Avila³

2020

Entropy

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“…Our data base is available at Pangaea [22] and consists of 351 full velocity snapshots taken from a DNS we performed with our publicly available pseudo-spectral simulation code nsPipe [35]. The size of the computational domain is Ω = (R × 2π × 42R) in wall-normal (r), azimuthal (θ) and streamwise (z) direction, respectively, and therefore four times longer than the one used by Härtel et al [33].…”

Section: Methodology a Dns Data Basementioning

confidence: 99%

How does filtering change the perspective on the scale-energetics of the near-wall cycle?

Feldmann,

Umair,

Avila

et al. 2020

Preprint

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We investigate the flux of kinetic energy across length scales in a turbulent pipe flow. We apply explicit spatial filtering of DNS data and assess the effect of different filter kernels (Fourier, Gauss, box) on the local structure of the inter-scale energy flux (Π) and its statistics. Qualitatively, the mean energy flux at each wall-normal distance is robust with respect to the filter kernel, whereas there are significant differences in the estimated intensity and distribution of localised Π events. We find conflicting correlations between typical flow structures in the buffer layer (streaks, vortices and different Q events) and regions of forward/backward transfer in the instantaneous Π field. In particular, cross-correlations are highly upstream-downstream symmetric for the Fourier kernel, but asymmetric for the Gauss and box kernel. We show that for the Gauss and box kernel, Π events preferably sit on the inclined meander at the borders of streaks where strong shear layers occur, whereas they appear centred on top of the streaks for the Fourier kernel. Moreover, using the Fourier kernel we reveal a direct coincidence of backward scatter and fluid transport away from the wall (Q 1 ), which is absent for the Gauss and the box kernel. However, all kernels equally predict backward scatter directly downstream of Q 1 events. Our findings expand the common understanding of the wall cycle and might impact modelling and control strategies. Altogether, our results suggest that interpretations of the inter-scale energy flux relying on Fourier filters should be taken with caution, because Fourier filters act globally in physical space, whereas Π events are strongly spatially localised. Our python post-processing tool eFlux for scale separation and flux computations in pipe flows is freely available and can be easily adapted to other flow geometries.

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“…We perform axisymmetric DNS of Taylor-Couette flow with periodic BC in z for moderate shear Reynolds numbers (Re s ≤ 3 × 10 4 ), allowing for both, large computational domains (Γ ≤ 48) and long integration times (t ≤ 170 d 2 /ν). The simulations are based on integrating the incompressible Navier-Stokes equations forward in time (t) using our pseudo-spectral DNS code nsCouette [20]. In nsCouette, the equations are formulated in cylindrical coordinates (r, θ, z) and rendered dimensionless using d, ν /d and d 2 /ν, as unit length, speed and time, respectively.…”

mentioning

confidence: 99%