Non-Newtonian unconfined flow and heat transfer over a heated cylinder using the direct-forcing immersed boundary–thermal lattice Boltzmann method

Delouei, A. Amiri; Nazari, Mohsen; Kayhani, M. H.; Succi, Sauro

doi:10.1103/physreve.89.053312

Cited by 37 publications

(25 citation statements)

References 57 publications

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“…This experimental finding is, therefore, consistent with our result of heat reduction for very large b 2 . There is no systematic experimental study on the effect of the finite extensibility of polymers in the literature, except that an enhancement in heat transport has been reported for shear-thinning fluid over a heated cylinder (Mizushina et al 1978;Khan, Culham & Yovanovich 2006;Delouei et al 2014). Shear-thinning fluid can be described by the FENE-P model, and the larger the shear-thinning effect, the smaller the value of b 2 is.…”

Section: Discussionmentioning

confidence: 95%

Heat transport modification by finitely extensible polymers in laminar boundary layer flow

Benzi

Ching

et al. 2016

J. Fluid Mech.

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We study how heat transport is affected by finitely extensible polymers in a laminar boundary layer flow within the framework of the Prandtl-Blasius-Pohlhausen theory. The polymers are described by the finitely extensible nonlinear elastic-Peterlin model with a parameter b 2 , which is the ratio of the maximum to the equilibrium value of the trace of the polymer conformation tensor. For very large b 2 , heat transport is reduced. When b 2 is small, heat transport is enhanced. We investigate the transition from heat reduction to heat enhancement as a function of the polymer relaxation time and concentration, and show that the transition can be explained in terms of the functional shape of the space-dependent effective viscosity due to the polymers.

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Section: Discussionmentioning

confidence: 95%

Heat transport modification by finitely extensible polymers in laminar boundary layer flow

Benzi

Ching

et al. 2016

J. Fluid Mech.

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“…It is shown in Fig. 7 that the wake length in the polymeric fluid is shorter than that in a Newtonian fluid at the same Re, which is similar to the behavior of a power-law shear-thinning fluid [53,55]. Figure 8 shows the velocity difference ∆ 1 = u − u as well as the stain rate difference ∆ 2 =γ −γ between the flow field of the non-Newtonian polymeric fluid and the Newtonian fluid at Re = 20.…”

Section: Numerical Implementation and Resultsmentioning

confidence: 60%

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

Zhao

Caswell

et al. 2018

Journal of Computational Physics

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We simulate complex fluids by means of an on-the-fly coupling of the bulk rheology to the underlying microstructure dynamics. In particular, a macroscopic continuum model of polymeric fluids is constructed without a pre-specified constitutive relation, but instead it is actively learned from mesoscopic simulations where the dynamics of polymer chains is explicitly computed. To couple the macroscopic rheology of polymeric fluids and the microscale dynamics of polymer chains, the continuum approach (based on the finite volume method) provides the transient flow field as inputs for the (mesoscopic) dissipative particle dynamics (DPD), and in turn DPD returns an effective constitutive relation to close the continuum equations. In this multiscale modeling procedure, we employ an active learning strategy based on Gaussian process regression (GPR) to minimize the number of expensive DPD simulations, where adaptively selected DPD simulations are performed only as necessary. Numerical experiments are carried out for flow past a circular cylinder of a non-Newtonian fluid, modeled at the mesoscopic level by bead-spring chains. The results show that only five DPD simulations are required to achieve an effective closure of the continuum equations at Reynolds number Re = 10. Furthermore, when Re is increased to 100, only one additional DPD simulation is required for constructing an extended GPR-informed model closure. Compared to traditional message-passing multiscale approaches, applying an active learning scheme to multiscale modeling of non-Newtonian fluids can significantly increase the computational efficiency. Although the method demonstrated here obtains only a local viscosity from the mesoscopic model, it can be extended to other multiscale models of complex fluids whose macro-rheology is unknown.

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“…where ω i is the weight associated with e i and c s is the speed of sound, c s = x/ (3) t, and the local fluid density, ρ, and velocity, u, at the lattice node are given by ρ = i f i and ρu = i f i e i +τ * ρg, where g is the strength of an external force [37] and τ * = 0.5+3ν * t/ x 2 . The kinematic viscosity of the non-Newtonian fluid is described as ν * = 2 n−1 |Π D | n−1 2 ξ [34,38], in which ξ is the consistency, Π D is the second invariant of the rate of strain tensor, n is the fluid-type identifier, n < 1, n = 1, and n > 1 correspond to pseudoplastic (shear-thinning), Newtonian, and dilatant (shear-thickening) fluids, respectively. Π D is computed as…”

Section: Lattice-boltzmann Model (Lbm) For Dsps In Non-newtonian Fluimentioning

confidence: 99%

Combined effects of fluid type and particle shape on particles flow in microfluidic platforms

Başağaoğlu

Blount

Succi

et al. 2019

Microfluid Nanofluid

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Recent numerical analyses to optimize the design of microfluidic devices for more effective entrapment or segregation of surrogate circulating tumor cells (CTCs) from healthy cells have been reported in the literature without concurrently accommodating the non-Newtonian nature of the body fluid and the non-uniform geometric shapes of the CTCs. Through a series of two-dimensional proof-of-concept simulations with increased levels of complexity (e.g., number of particles, inline obstacles), we investigated the validity of the assumptions of the Newtonian fluid behavior for pseudoplastic fluids and the circular particle shape for different-shaped particles (DSP) in the context of microfluidics-facilitated shape-based segregation of particles. Simulations with a single DSP revealed that even in the absence of internal geometric complexities of a microfluidics channel, the aforementioned assumptions led to 0.11-0.21W (W is the channel length) errors in lateral displacements of DSPs, up to 3-20% errors in their velocities, and 3-5% errors in their travel times. When these assumptions were applied in simulations involving multiple DSPs in inertial microfluidics with inline obstacles, errors in the lateral displacements of DSPs were as high as 0.78W and in their travel times up to 23%, which led to different (un)symmetric flow and segregation patterns of DSPs. Thus, the fluid type and particle shape should be included in numerical models and experiments to assess the performance of microfluidics for targeted cell (e.g., CTCs) harvesting.

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Non-Newtonian unconfined flow and heat transfer over a heated cylinder using the direct-forcing immersed boundary–thermal lattice Boltzmann method

Cited by 37 publications

References 57 publications

Heat transport modification by finitely extensible polymers in laminar boundary layer flow

Heat transport modification by finitely extensible polymers in laminar boundary layer flow

Active learning of constitutive relation from mesoscopic dynamics for macroscopic modeling of non-Newtonian flows

Combined effects of fluid type and particle shape on particles flow in microfluidic platforms

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