A new high-order method for the simulation of incompressible wall-bounded turbulent flows

Lenaers, Peter; Schlatter, Philipp; Brethouwer, Geert; Johansson, A.

doi:10.1016/j.jcp.2014.04.034

Cited by 3 publications

(9 citation statements)

References 24 publications

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“…Examples provided are under assumptions that the transducer's sensing ball (diameter of 3 mm) is placed in fluid flow, which is fully impacted by the measured flow. According to the Bernoulli Equation of fluid mechanics, the applying forces are set at a range from 0.05N to 0.5N, corresponding to the flow velocity from 0.5m/s to 3 m/s [24]. The forces (  .…”

Section: Validation Of Forces' Decomposition and Synthesismentioning

confidence: 99%

A Measuring Method for Three-Dimensional Turbulent Velocities Based on Vector Decomposition and Synthesis

Zheng¹,

Zhang²,

Zhuan³

et al. 2015

IJHT

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In this paper, an approach is proposed for measuring three-dimensional (3D) turbulence velocities by the vector characteristics of flow velocity. Based on the principle of vector decomposition and synthesis, a special multi-vector three components (3C) tripod structure, which can sense flow velocities with little disturbance to the measured flow, is studied. At the front most of the 3C structure, the sensing ball exposed to the flow creates strains on each of the three silicon piezoresistance beams, and the corresponding deformation of the beams is converted into electrical output signals by the Wheatstone bridge. The desired 3D turbulent velocities could be obtained by the vectors output signals of the three piezoresistive sensing microcircuits with an embedded microprocessor. The reasonability and feasibility of the 3D structure design can be verified by simulation experiments. The 3D velocities data can be collected in a certain period of time in a transparent water experiment. Furthermore, this method as a complex way will be used for measuring 3D turbulence velocity in fluid flow with hyper-sediment content up to 350kg/m3, where the Laser Doppler Velocimeter (LDV) and other types of flow meter cannot be used.

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Section: Validation Of Forces' Decomposition and Synthesismentioning

confidence: 99%

A Measuring Method for Three-Dimensional Turbulent Velocities Based on Vector Decomposition and Synthesis

Zheng¹,

Zhang²,

Zhuan³

et al. 2015

IJHT

View full text Add to dashboard Cite

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“…As will be described in the following, the equations are formulated in primitive-variable form, and the arising pressure-poisson equation is solved with consistent boundary conditions derived using an influence-matrix method [3]. The method is an adaptation of the recent scheme by Lenaers et al [4], and further details about the present method can be found in the corresponding thesis [5].…”

Section: Introduction and Problem Formulationmentioning

confidence: 99%

“…The governing equations thus contain three velocities (u, v, w) and the pressure p. No-slip conditions at the walls at r = R are imposed, however, the method can also deal with other conditions [4]. Using a Fourier ansatz and high-order compact finite differences, a semi-discretisation can be obtained, which is further discretised in time using an explicit Runge-Kutta scheme.…”

Section: Introduction and Problem Formulationmentioning

confidence: 99%

“…Special care has to be taken of terms multiplied by 1/r and 1/r 2 as described in Ref. [5]. Alleviating the strict time-step limitations was achieved by reducing gradually the number of azimuthal Fourier modes as the centre is approached.…”

Section: Introduction and Problem Formulationmentioning

confidence: 99%

“…[3,4]. A pressure-Poisson equation is derived, which replaces the continuity equation in the interiour of the domain.…”

Section: Introduction and Problem Formulationmentioning

confidence: 99%

See 2 more Smart Citations

A New High-Order Method for Simulating Turbulent Pipe Flow

Lenaers¹,

Schlatter²,

Brethouwer³

et al. 2016

Springer Proceedings in Physics

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The minimal-span channel for rough-wall turbulent flows

et al. 2017

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Roughness predominantly alters the near-wall region of turbulent flow while the outer layer remains similar with respect to the wall shear stress. This makes it a prime candidate for the minimal-span channel, which only captures the near-wall flow by restricting the spanwise channel width to be of the order of a few hundred viscous units. Recently, Chung et al. (J. Fluid Mech., vol. 773, 2015, pp. 418-431) showed that a minimal-span channel can accurately characterise the hydraulic behaviour of roughness. Following this, we aim to investigate the fundamental dynamics of the minimal-span channel framework with an eye towards further improving performance. The streamwise domain length of the channel is investigated with the minimum length found to be three times the spanwise width or 1000 viscous units, whichever is longer. The outer layer of the minimal channel is inherently unphysical and as such alterations to it can be performed so long as the near-wall flow, which is the same as in a full-span channel, remains unchanged. Firstly, a half-height (open) channel with slip wall is shown to reproduce the near-wall behaviour seen in a standard channel, but with half the number of grid points. Next, a forcing model is introduced into the outer layer of a half-height channel. This reduces the high streamwise velocity associated with the minimal channel and allows for a larger computational time step. Finally, an investigation is conducted to see if varying the roughness Reynolds number with time is a feasible method for obtaining the full hydraulic behaviour of a rough surface. Currently, multiple steady simulations at fixed roughness Reynolds numbers are needed to obtain this behaviour. The results indicate that the non-dimensional pressure gradient parameter must be kept below 0.03-0.07 to ensure that pressure gradient effects do not lead to an inaccurate roughness function. An empirical costing argument is developed to determine the cost in terms of CPU hours of minimal-span channel simulations a priori. This argument involves counting the number of eddy lifespans in the channel, which is then related to the statistical uncertainty of the streamwise velocity. For a given statistical uncertainty in the roughness function, this can then be used to determine the simulation run time. Following this, a finite-volume code with a body-fitted grid is used to determine the roughness function for square-based pyramids using the above insights. Comparisons to experimental studies for the same roughness geometry are made and good agreement is observed.

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A new high-order method for the simulation of incompressible wall-bounded turbulent flows

Cited by 3 publications

References 24 publications

A Measuring Method for Three-Dimensional Turbulent Velocities Based on Vector Decomposition and Synthesis

A Measuring Method for Three-Dimensional Turbulent Velocities Based on Vector Decomposition and Synthesis

A New High-Order Method for Simulating Turbulent Pipe Flow

The minimal-span channel for rough-wall turbulent flows

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