Numerical modeling of fibre suspensions in grid-generated turbulent flow

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National Library of Canada , Ottawa
SeriesCanadian theses = -- Thèses canadiennes
The Physical Object
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ID Numbers
Open LibraryOL20306256M
ISBN 100612503615

Numerical Modeling of Fibre Suspensions In Grid-Generated Turbulent Flow Master of Applied Science Atanasis Plilcas Graduate Department of Chemical Engineering and Applied Chemistry University of Toronto Abstract Cellulose fibre floc formation and destruction by hydrodynarnic forces in a grid- generated turbulent flow, such as that occUmng Author: Atanasis Plikas.

Round turbulent jet of fiber suspension is shown in Fig. 2.A finite volume method is used to solve Eqs.,,, to get the mean fluid velocity, turbulent kinetic energy and turbulent dissipation rate of fluid. Equations, and, are solved by using the Runge–Kutta 4th order method.

The computation grid is comprised of 50 × 40 × 80 =(axial × circumferential × radial Cited by:   The simulation matrix consists of four different fibre Stokes numbers (St = 1, 5, 25, and ) and five different fibre aspect ratios (λ =3, 10, 30, and 50), with results considered at four distances from a channel wall (in the viscous sub-layer, buffer, and fully turbulent regions), which are taken as a measure of the flow velocity Cited by: COMSOL Multiphysics Software, for the turbulent flow regime, agree very well with the experimental results obtained in a pilot rig.

Additionally, the use of the k −ε Turbulence Model for the simulation of pulp fibre suspensions flow, associated with the rheological data acquired experimentally, revealed to be a prompt and accurate strategy.

A new model for turbulent fibre suspension flow is proposed by introducing a model for the fibre orientation distribution function (ODF).

The coupling between suspended fibres and the fluid momentum is then introduced through the second and fourth order fibre orientation tensors, respectively. From the modelled ODF, a method to construct explicit expressions for the components of the Author: Vijay Shankar, Anton Lundberg, Taraka Pamidi, Lars-Olof Landström, Örjan Johansson.

turbulent channel flow Currently, fully resolved simulations based on IBM and LBM are computationally expensive approaches which are not designed to handle suspensions of millions of small finite sized parti-cles, as often met in engineering systems, and as required to obtain reliable particle statistics in a turbulent flow environment.

JianZhong Lin, SuHua Shen, A theoretical model of turbulent fiber suspension and its application to the channel flow, Science China Physics, Mechanics and Astronomy, /s, 53, 9, (), ().

A.R. Mansour, Simple and explicit equations for the friction factor in turbulent fiber suspension flow, Journal of Non-Newtonian Fluid Mechanics, /(85), 17, 2, (), (). turbulent flow is the infinite number of scales so that a full numerical resolution of the flow requires the construction of a grid with a number of nodes that is proportional to Re.

9/4. The governing equations for a Newtonian fluid are Conservation of Mass i. 0 i. u tx ∂ ρ ∂ρ + = ∂∂ (1). A computational model based on the micro-scale discretization is called Direct Numerical Simulation (DNS).

It involves complete resolution of the flow field by a direct solution of unsteady Navier-Stokes Equations resolving all active scales of motion in the flow. The current numerical model is validated against different experimental studies, including deflection of fiber in uniform flow, fibers in isotropic turbulent flow, and concentrated fiber suspension in channel flow.

The numerical model was able to reproduce the damping/enhancement phenomena of turbulence in a channel flow as a consequence of the. A numerical model of fiber suspensions in a grid generated turbulent flow.

Article. Jan ; A numerical model of the fiber flow was developed using an Eulerian multiphase flow model in where. Plikas A, Kuhn DCS, Sullivan PE: A numerical model of fibre suspensions in a grid generated turbulent flow. Proceedings of ASME FEDSM’00– Google Scholar. In laminar fiber suspensions, Peclet numbers show the effect of Brownian motion on the orientation distribution of fibers: the less the Peclet numbers are, the more intensive the effect of Brownian motion is.

So, Peclet numbers are criterion for studying the effect of Brownian motion. Simulation of turbulent pipe flow.

Description Numerical modeling of fibre suspensions in grid-generated turbulent flow PDF

A theoretical model of turbulent fiber suspension is developed by deriving the equations of Reynolds averaged Navier-Stokes, turbulence kinetic energy and turbulence dissipation rate with the additional term of fibers. In order to close the above equations, the equation of probability distribution function for mean fiber orientation is also derived.

The dynamics of individual flexible fibers in a turbulent flow field have been analyzed, varying their initial position, density and length. A particle-level fiber model has been integrated into a.

In this course, we will present and discuss the numerical models/ methods currently available for the accurate simulation of turbulent multiphase flows. In particular, we will consider: Lagrangian methods for particle dispersion in turbulence (with and without finite-size effects), boundary-fitted methods for deformable gas and liquid layers.

We present a study of the drag reduction induced by rigid fibres in a turbulent channel flow using direct numerical simulation.

Details Numerical modeling of fibre suspensions in grid-generated turbulent flow PDF

The extra stresses due to the fibres are calculated with the well-known constitutive equation involving the moments of the orientation vector.

The v2-f model is based on the argument that k/ε is the correct turbulent time scale in the flow (close to the wall and in the outer region) but k is not the appropriate turbulent velocity scale An additional equation for the 2correct velocity scale v (independent from k) has to be solved.

Moreover, the damping effect produced from the. Application of the energy dissipation model of turbulence to the calculation of flow near a spinning disc. Letters in Heat and Mass Transfer 1 (2), – (). Lee S, Lee C. The motion of flocculated fibres in a streaming suspension is governed by the balance of the network strength and hydrodynamic forces.

With increasing flow rate through a channel, (1) the network initially occupying all space, (2) is then compressed to the centre, and (3) ultimately dispersed. This classical view neglects fibres-fines: we find that the distribution of these small particles.

The numerical modeling and experiment observation indicates that the turbulent momentum κ and effective energy consumption ε can be used as an indicator of flocculation efficiency. The rectangular shaped flocculation tank can dampen the flow effectively, but in the four corners there is a lack of mixing, which can be solved by installing.

The model, discussed here, has been verified and validated by comparison of the numerical results with the experimental data by Hussainov et al. () for the turbulent downward vertical channel flow grid-generated by gas-solid particles.

MATERIALS AND METHODS Model description The sketch of the computational flow domain is shown in Fig. Rheological Behavior of Fiber Suspensions in a Turbulent Channel Flow,” Gao, Z.

Y., Zhou, K., and. Chan, T. L.,“ Mathematical Modeling of Turbulent Fiber Suspension and Successive Iteration Solution in the Channel Flow Thien, N., and. Yeo, K. S.,“ Numerical Simulation of Fibre Suspension Flowthrough an Axisymmetric.

The model was then further validated with experimental data from a turbulent fibre suspension channel flow. Simulations were also carried out using a Bingham viscoplastic fluid model for comparison. The ODF model and the Bingham model performed reasonably well for the turbulent flow areas, and the latter model showed to be slightly better given.

experimental and numerical methods in the area of flow monitoring of pulp fibre suspensions are increasingly important. Aiming to gain more knowledge concerning flow of pulp suspensions, the applicability of Computational Fluid Dynamics (CFD) strategies to predict pulp’s flow was the main motivation for this work.

An Introduction to Turbulent Flow Transition to Turbulent Flow Statistical Concepts for Turbulent Flow Analysis Turbulent Length and Time Scales Vorticity and Strain Tensors Classification of Turbulence Models References flow will be discussed based on direct computational simulation of fiber suspension in shear flow.

References Wu, J. and Aidun, C.K., “A numerical study of the effect of fiber stiffness on the rheology of sheared flexible fiber suspensions, J. Fluid Mech., vol.pp. –, Aidun, C.K., and Parsheh, M., “Counter-rotating core.

A numerical study of the effects of superhydrophobic surface on skin-friction drag in turbulent channel flow Phys. Flu (); / Ideal stochastic forcing for the motion of particles in large-eddy simulation extracted from direct numerical simulation of turbulent channel flow.

Fibre Motion in Turbulent Flow: A Mathematical study of fibre suspensions in turbulent flow. Lambert Academic Publishing Limited, Germany, ISBN: Book Chapters. Energy equation for dusty fluid turbulent flow has been derived in terms of correlation tensors of second order.

In presence of dust particles, mathematical modeling of turbulent energy is discussed including the correlation between the pressure fluctuations and velocity fluctuations at two points of the flow field, where the correlation tensors are the functions of space coordinates, distance.

In this paper we present a chain of mathematical models that enables the numerical simulation of the airlay process and the investigation of the resulting nonwoven material by means of virtual tensile strength tests.

Download Numerical modeling of fibre suspensions in grid-generated turbulent flow FB2

The models range from a highly turbulent dilute fiber suspension flow to stochastic surrogates for fiber lay-down and web formation and further to Cosserat networks with .efficiency in the pulp and paper industry a model for turbulent fibre suspension flow was needed.

The model was also desired to be suitable for applications alongside additional multiphase flow models to study cavitation in fibre suspension flows. Two models with different levels of complexity were studied. A relatively simple model was the Bingham.