Solve the rigid-short-fibers rheology constitutive models by two approaches numerically:
- Spherical Harmonics approach;
- Object Tensor approach.
Spherical Harmonic method capable of obtaining the 3D orientation distribution
Author: Dr. Benke Li (李本科)
Author's ORCID: https://orcid.org/0000-0002-8830-0563
Author's ResearchGate: https://www.researchgate.net/profile/Benke-Li
Please cite theis paper if you use this package:
Benke Li, Ying Guo, Paul Steeman, Markus Bulters, Wei Yu. "Wall effect on the rheology of short-fiber suspensions under shear." Journal of Rheology 2021, 65 (6), 1169–1185.
numpy, scipy, pandas, jupyter, matplotlib, pyshtools
- Make sure that Python3 and the dependencies have been installed. The dependencies could be installed by this command:
If there are any problems with system environment configurations, users could run this package in my Docker container:
python3 -m pip3 install numpy scipy pandas jupyter matplotlib pyshtools
docker run -it -p8888:8888 libenke/base
- Download this package directly or run the command in the terminal to download this package:
git clone https://github.com/libenke/FiberRheoModels
- Run command in your terminal:
Then open the
jupyter-notebook
.ipynb
files in the jupyter workspace, enjoy it. Usage of jupyter could be found in https://jupyter.org/. - The models were solved by: (a) object tensor approach (see examples in
.ipynb
files with the prefix ofDemo_Tensor Method_
), and (b) spherical harmonics approach (see examples in.ipynb
files with prefix ofDemo_SH Method_
). - Background of models and spherical harmonic methods is shown in the following sections.
Readers are highly recommended to read our published paper (Benke Li et. al. "Wall effect on the rheology of short-fiber suspensions under shear." Journal of Rheology 2021, 65, 1169-1185.), all the detail background and references could be found in the introduction section of this paper.
For rigid-short-fibers filled suspensions, their microsopic transient behaviors were mosted interested in two aspects:
-
Evolution of orientation distributions during flow, denoted as
$\dot{\psi}(\mathbf{p})$ or$\frac{\mathrm{d}\psi(\mathbf{p})}{\mathrm{d}t}$ . With the definition of the second moment as$\mathbf{A}=\oint\psi(\mathbf{p})\mathbf{pp}\mathrm{d}\mathbf{p}$ , the evolution of tensor is denoted as$\mathbf{\dot{A}}$ or$\frac{\mathrm{d}\mathbf{A}}{\mathrm{d}t}$ . -
Rotation of single fiber during flow, denoted as
$\mathbf{\dot{p}}$ or$\frac{\mathrm{d}\mathbf{p}}{\mathrm{d}t}$ .
The evolution of the
Here
$\mathbf{\nabla}_s$ is the surface gradient operator (Ref: Bird, R. B. et. al. "Dynamics of Polymeric Liquids. Vol. 1: Fluid Mechanics." Wiley, New York, 1987.). It could be written in the following form:$$\qquad\mathbf{\nabla}_s=\mathbf{\nabla}-\mathbf{p}(\mathbf{p}\cdot\mathbf{\nabla})=(\mathbf{I}-\mathbf{pp})\cdot\mathbf{\nabla}$$
$\mathbf{\nabla}_s$ can also be written as:$$\qquad\begin{aligned} \mathbf{\nabla}_s&=\frac{\partial}{\partial\theta}\mathbf{e}_\theta+\frac{1}{\sin\theta}\frac{\partial}{\partial\phi}\mathbf{e}_\phi\\\ \mathbf{e}_\theta&=(\cos\theta\cos\phi)\mathbf\delta_x+(\cos\theta\sin\phi)\mathbf\delta_y-\sin\theta\,\mathbf\delta_z\\\ \mathbf{e}_\phi&=-\sin\phi\mathbf\delta_x+\cos\phi\mathbf\delta_y \end{aligned}$$
These terms are summarized as following:
- HD term (hydro dynamic term), also known as Jefferey term. (Ref: Jeffery, G. B., “The motion of ellipsoidal particles immersed in a viscous fluid.” Proc. R. Soc. London A 1922, 102, 161–179.) Written as:
- IRD term (isotropic diffusion term), also known as FT term. (Ref: Folgar, F., and C. L. Tucker, “Orientation behavior of fibers in concentrated suspensions.” J. Reinf. Plast. Compos. 1984, 3, 98–119.) Written as:
- ARD or iARD term (anisotropic diffusion term), introduced for slender fibers with a large aspect ratio. (Refs: Phelps, J. H. et. al. “An anisotropic rotary diffusion model for fiber orientation in short- and long-fiber thermoplastics.” J. Non-Newtonian Fluid Mech. 2009, 156, 165–176. Tseng, H.-C. et. al. “An objective tensor to predict anisotropic fiber orientation in concentrated suspensions.” J. Rheol. 2016, 60, 215–224.) Written as:
- RSC term (reduced strain closure term), introduced to slow down the evolution of fiber orientation. (Ref: Wang, J. et. al. “An objective model for slow orientation kinetics in concentrated fiber suspensions: Theory and rheological evidence.” J. Rheol. 2008, 52, 1179–1200.) Written as:
- Brownian term. The rotational diffusion coefficient of short-rigid-fiber
$D_{r0}$ can be estimated by shish-kebab model, described in the (Eq. 8.16) of the book: Doi, M. and Edwards, S. F. "The theory of polymer dynamics." Oxford University Press 1988. Application of this term could see section IX in the supporting information of our previous publication: Benke Li et. al. "Revealing the Shear Effect on the Interfacial Layer in Polymer Nanocomposites through Nanofiber Reorientation." Macromolecules 2023, 56, 3050-3063.
- Confined Term (Proposed in our on-going studies. Here
$\mathbf{D}^*$ is the confinement induced virtual compression flow, while$\epsilon$ and$\alpha$ is the tunning parameter.
Ref: Montgomery-Smith, S.et. al. “A systematic approach to obtaining numerical solutions of Jeffery’s type equations using spherical harmonics.” Compos. Part A 2010, 41, 827–835.
- Expand the orientation distribution function
$\psi(t)$ as spherical harmonics series:
- Expand the above equation (2-2) by Math Operators of special function
$Y_l^m$
These operators were defined in the source file:models/sph_harm_operator.py
- Obtain orientation tensor
$\mathbf{A}(t)$ from the spherical harmonic expansion coeficients$c_{l,m}(t)$ :
Sph_Harm_Operators.nb
, we got:
- Fiber orientation distribution
$\psi(\mathbf{p},t)$ , with the$Y_l^m$ expansion degree choosing 100.
- Evolution of orientation tensor
$\mathbf{A}(t)$ . Comparison with the paper's results. The$Y_l^m$ expansion degree here is 100.
- Orientation distribution in the gradient-flow plane, i.e.
$\psi(\phi)$ . The$\theta$ axis were elimited by numeric integration:
- Fiber tumbling trajectory
$\mathbf{p}(t)$ , with parameter of$C_I=0.01,C_M=0,\kappa=1,\xi=1$ , and$Y_l^m$ expansion degree is 100.
- Influence of
$Y_l^m$ expansion degree to the tumbling period. It seems that expansion degree of 50 could provide enough calculation precision.