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Polymer Solutions

From Atoms to Flows

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Understanding Viscoelasticity

Part of the book series: Graduate Texts in Physics ((GTP))

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Abstract

In the microstructure approach to the quest for a relevant constitutive equation for the complex-structure fluid, a relevant model for the microstructure is postulated, and the consequences of the micromechanics are then explored at the macrostructural level, with appropriate averages being taken to smear out the details of the microstructure.

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Notes

  1. 1.

    A stochastic process is a family of random variables X(t), where t is the time, X is a random variable, and X(t) is the value observed at time t. The totality of \(\left\{ X\left( t\right) ,\;t\in \mathbb {R}\right\} \) is said to be a random function or a stochastic process.

  2. 2.

    W. Kuhn (1899–1963) was a Professor at the Technische Hochschule in Karlruhe, and later on, in Basel, Switzerland. He is most famous for the f-summation theorem in quantum mechanics.

  3. 3.

    P. Langevin (1872–1940) introduced the stochastic DE (7.20) in 1908, and showed that the particle obeys the same diffusion equation as described by Einstein (1905).

  4. 4.

    The random zig-zag motion of small particles (less than about \(10\,\upmu \)m) is named after R. Brown (1773–1858), an English botanist, who mistook this as a sign of life. He travelled with Matthew Flinders to Australia in 1801 on the ship Investigator as a naturalist. The correct explanation of the phenomenon was given by Perrin (Fig. 7.3). Brownian particles are those undergoing a random walk, or Brownian motion.

  5. 5.

    This approximation is called white noise, i.e., Gaussian noise of all possible frequencies uniformly distributed. Sometimes it is called “rain-on-the-roof” approximation: two (or more) rain drops do not fall on the same spot on the roof.

  6. 6.

    A.D. Fokker derived the diffusion equation for a Brownian particle in velocity space in 1914. The general case was considered by M. Planck (1858–1947) in 1917.

  7. 7.

    The general solution to the random walk problem in one dimension was obtained by M. von Smoluchowski in 1906.

  8. 8.

    Dilute solutions of polymers in highly viscous solvents [9].

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Correspondence to Nhan Phan-Thien .

Problems

Problems

Problem 7.1

Use the solution (7.24) in (7.27) to show that

$$ \mathbf {D}=kT\varvec{\zeta }^{-1}. $$

This is the Stokes–Einstein relation, relating the diffusivity to the mobility of a Brownian particle.

Problem 7.2

Starting from the Langevin equation in configuration space, in the limit \( \mathbf {m}\rightarrow \mathbf {0},\)

$$\begin{aligned} {\dot{\mathbf x}}=-\varvec{\zeta }^{-1}\cdot \mathbf {Kx}+\varvec{\zeta }^{-1}\mathbf {F }^{(b)}\left( t\right) , \end{aligned}$$
(7.87)

show that

$$\begin{aligned} \varDelta \mathbf {x}\left( t\right) =-\varvec{\zeta }^{-1}\cdot \mathbf {Kx} \varDelta t+\int _{t}^{t+\varDelta t}{\varvec{\zeta }^{-1}\mathbf {F}^{(b)}\left( { t^{\prime }}\right) dt^{\prime }}. \end{aligned}$$
(7.88)

From this, show that

$$\begin{aligned} \left\langle {\varDelta \mathbf {x}}\right\rangle =-\varvec{\zeta }^{-1}\cdot \mathbf {Kx},\;\;\;\left\langle {\varDelta \mathbf {x}\left( t\right) \varDelta \mathbf {x}\left( t\right) }\right\rangle =2kT\varvec{\zeta }^{-1}\varDelta t \end{aligned}$$
(7.89)

and conclude that the Fokker–Planck equation is

$$ \frac{{\partial \phi }}{{\partial t}}=\frac{\partial }{{\partial \mathbf {x}}} \cdot \left[ {kT\varvec{\zeta }^{-1}\frac{{\partial \phi }}{{\partial \mathbf {x}}}+\varvec{\zeta }^{-1}\cdot \mathbf {Kx}\phi }\right] . $$

Problem 7.3

Investigate the migration problem in a plane Poiseuille flow.

Problem 7.4

Show that the solution to (7.56) is

$$\begin{aligned} \left\langle {\mathbf {R}\left( t \right) } \right\rangle = e^{ - t/2\lambda } e^{\mathbf {L}t} \mathbf {R}_{0} . \end{aligned}$$
(7.90)

Thus conclude that the flow is strong if

$$ \text {eigen }\left( \mathbf {L} \right) \ge 1/2\lambda , $$

where eigen (\(\mathbf {L}\)) is the maximum eigenvalue of \(\mathbf {L}\).

Problem 7.5

Using the result (7.70), show that the following solves the Maxwell equation (7.62):

$$ \mathbf {S}^{(p)}\left( t\right) =\frac{G}{\lambda }\int _{-\infty }^{t}{ e^{(s-t)/\lambda }\mathbf {C}_{t}\left( s\right) ^{-1}ds}=G\mathbf {I}+\varvec{ \tau }^{(p)}. $$

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Phan-Thien, N., Mai-Duy, N. (2017). Polymer Solutions. In: Understanding Viscoelasticity. Graduate Texts in Physics. Springer, Cham. https://doi.org/10.1007/978-3-319-62000-8_7

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