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19.1 Relaxation Function

The Maxwell Chain model is based on a relaxation function E(t,$ \tau$) . The relation between stresses and strains follows from

$\displaystyle \boldsymbol\sigma$(t) = $\displaystyle \int_{{-\infty}}^{{t}}$E(t,$\displaystyle \tau$)$\displaystyle \bar{{\mathbf{D}}}$$\displaystyle \dot{{\boldsymbol{\varepsilon}}}$ d$\displaystyle \tau$ (19.1)

Here $ \bar{{\mathbf{D}}}$ is a dimensionless matrix that relates the three-dimensional deformation states to the one-dimensional relaxation function by using Poisson's ratio $ \nu$ .

$\displaystyle \bar{{\mathbf{D}}}$ = $\displaystyle {\dfrac{{1}}{{(1+\nu)(1-2\nu)}}}$$\displaystyle \left[\vphantom{ \begin{array}{cccccc} 1-\nu & \nu & \nu & 0 & 0 ...
...\\  [\medskipamount] 0 & 0 & 0 & 0 & 0 & \dfrac{1-2\nu}{2} \end{array} }\right.$$\displaystyle \begin{array}{cccccc} 1-\nu & \nu & \nu & 0 & 0 & 0 \\  [\medskip...
...}{2} & 0 \\  [\medskipamount] 0 & 0 & 0 & 0 & 0 & \dfrac{1-2\nu}{2} \end{array}$$\displaystyle \left.\vphantom{ \begin{array}{cccccc} 1-\nu & \nu & \nu & 0 & 0 ...
...\\  [\medskipamount] 0 & 0 & 0 & 0 & 0 & \dfrac{1-2\nu}{2} \end{array} }\right]$ (19.2)

To get the Maxwell model, the relaxation function is expanded in a truncated Dirichlet series, resulting in the following exponential series.

E(t,$\displaystyle \tau$) = $\displaystyle \sum_{{\alpha=0}}^{{n}}$E$\scriptstyle \alpha$($\displaystyle \tau$)e-$\scriptstyle {\tfrac{{t-\tau}}{{\lambda_{\alpha}}}}$ (19.3)

For a one-dimensional situation this relaxation function can be physically interpreted as a parallel chain of springs and dampers as in Figure 19.1.
Figure 19.1: Maxwell Chain
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In (19.3) E$\scriptstyle \alpha$($ \tau$) indicates that the stiffness of the model can be time dependent, for instance due to temperature or maturity influences. The stiffness of the spring E$\scriptstyle \alpha$ and the viscosity of the damper $ \eta_{{\alpha}}^{}$ in the physical model determine the relaxation time $ \lambda_{{\alpha}}^{}$ .

$\displaystyle \lambda_{{\alpha}}^{}$ = $\displaystyle {\frac{{\eta_{\alpha}}}{{E_{\alpha}}}}$ (19.4)

Often the first element in the Maxwell Chain is represented by one single spring or equivalently with $ \eta_{{0}}^{}$ = $ \infty$ .

If we substitute (19.3) into (19.1) for time t and time t + $ \Delta$t , interchange the order of summation and integration, and assume that nothing has happened from time t = - $ \infty$ until t = 0 , we get

$\displaystyle \boldsymbol\sigma$(t) = $\displaystyle \bar{{\mathbf{D}}}$$\displaystyle \sum_{{\alpha=0}}^{{n}}$$\displaystyle \int_{{0}}^{{t}}$E$\scriptstyle \alpha$($\displaystyle \tau$)e-$\scriptstyle {\tfrac{{t-\tau}}{{\lambda_{\alpha}}}}$$\displaystyle \dot{{\boldsymbol{\varepsilon}}}$ d$\displaystyle \tau$ (19.5)
$\displaystyle \boldsymbol\sigma$(t + $\displaystyle \Delta$t) = $\displaystyle \bar{{\mathbf{D}}}$$\displaystyle \sum_{{\alpha=0}}^{{n}}$$\displaystyle \int_{{0}}^{{t+\Delta t}}$E$\scriptstyle \alpha$($\displaystyle \tau$)e-$\scriptstyle {\tfrac{{t+\Delta t-\tau}}{{\lambda_{\alpha}}}}$$\displaystyle \dot{{\boldsymbol{\varepsilon}}}$ d$\displaystyle \tau$ (19.6)

We can calculate the stress increment by subtracting (19.5) from (19.6) where the integral from 0 to t + $ \Delta$t is split into a part from 0 to t and a part from t to t + $ \Delta$t . The partial stress in every element of the Maxwell Chain is called $ \boldsymbol\sigma$$\scriptstyle \alpha$ .

$\displaystyle \boldsymbol\sigma$$\scriptstyle \alpha$(t) = $\displaystyle \bar{{\mathbf{D}}}$$\displaystyle \int_{{0}}^{{t}}$E$\scriptstyle \alpha$($\displaystyle \tau$)e-$\scriptstyle {\tfrac{{t-\tau}}{{\lambda_{\alpha}}}}$$\displaystyle \dot{{\boldsymbol{\varepsilon}}}$ d$\displaystyle \tau$ (19.7)

If we assume a constant strain rate from t to t + $ \Delta$t the stress increment follows from

$\displaystyle \Delta$$\displaystyle \boldsymbol\sigma$ = $\displaystyle \sum_{{\alpha=0}}^{{n}}$$\displaystyle \left(\vphantom{ 1 - e^{-\tfrac{\Delta t}{\lambda_{\alpha}}} }\right.$1 - e-$\scriptstyle {\tfrac{{\Delta t}}{{\lambda_{\alpha}}}}$$\displaystyle \left.\vphantom{ 1 - e^{-\tfrac{\Delta t}{\lambda_{\alpha}}} }\right)$$\displaystyle \left(\vphantom{ \frac{E_{\alpha}(t^{*})\lambda_{\alpha}}{\Delta ...
...bf{D}} \Delta\boldsymbol{\varepsilon}- \boldsymbol{\sigma}_{\alpha}(t) }\right.$$\displaystyle {\frac{{E_{\alpha}(t^{*})\lambda_{\alpha}}}{{\Delta t}}}$$\displaystyle \bar{{\mathbf{D}}}$$\displaystyle \Delta$$\displaystyle \boldsymbol\varepsilon$ - $\displaystyle \boldsymbol\sigma$$\scriptstyle \alpha$(t)$\displaystyle \left.\vphantom{ \frac{E_{\alpha}(t^{*})\lambda_{\alpha}}{\Delta ...
...bf{D}} \Delta\boldsymbol{\varepsilon}- \boldsymbol{\sigma}_{\alpha}(t) }\right)$ (19.8)

Here t* is a sampling point, usually halfway the time increment. This is only relevant if Young's modulus E changes during the analysis.


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