Williams–Landel–Ferry equation

The Williams–Landel–Ferry Equation (or WLF Equation) is an empirical equation associated with time–temperature superposition. The WLF equation has the form log ⁡ ( a T ) = − C 1 ( T − T r ) C 2 + ( T − T r ) {\displaystyle \log(a_{T})={\frac {-C_{1}(T-T_{\mathrm {r} })}{C_{2}+(T-T_{\mathrm {r} })}}} where log ⁡ ( a T ) {\displaystyle \log(a_{T})} is the decadic logarithm of the WLF shift factor, T is the temperature, Tr is a reference temperature chosen to construct the compliance master curve and C1, C2 are empirical constants adjusted to fit the values of the superposition parameter aT. The equation can be used to fit (regress) discrete values of the shift factor aT vs.

Source: Wikipedia — Williams–Landel–Ferry equation (CC BY-SA 4.0)

Williams–Landel–Ferry equation

The Williams–Landel–Ferry Equation (or WLF Equation) is an empirical equation associated with time–temperature superposition. The WLF equation has the form log ⁡ ( a T ) = − C 1 ( T − T r ) C 2 + ( T − T r ) {\displaystyle \log(a_{T})={\frac {-C_{1}(T-T_{\mathrm {r} })}{C_{2}+(T-T_{\mathrm {r} })}}} where log ⁡ ( a T ) {\displaystyle \log(a_{T})} is the decadic logarithm of the WLF shift factor, T is the temperature, Tr is a reference temperature chosen to construct the compliance master curve and C1, C2 are empirical constants adjusted to fit the values of the superposition parameter aT. The equation can be used to fit (regress) discrete values of the shift factor aT vs.

This neuron ends here.

Source: Wikipedia "Williams–Landel–Ferry equation" · CC BY-SA 4.0

Share this article: X · Bluesky
Privacy Policy