Time and Temperature Behavior of Polymers

One of the most important functions of engineering design is to be able to predict the performance of a structure over its design lifetime. Necessarily the mechanical behavior of materials used in a structure must also be known over the intended life of the structure. For engineering design based upon linear elasticity, it is assumed that no intrinsic change in mechanical properties occurs over time1. However, the molecular structure of polymers gives rise to mechanical properties that do change over time. As engineering structures are often designed to last as long as 20 to 50 years, there is a compelling reason to develop experimental and analytical approaches for polymer based materials that will allow the prediction of long term properties from relatively short term test data. The motivation is even higher when one considers that part of the design process is often that of developing and/or comparing candidate polymeric material systems. Long term testing on the order of years to determine fundamental polymer properties such as the relaxation modulus, E(t), or creep compliance, D(t), are quite impractical. Fortunately, the relationship between property changes of a polymer with time and property changes of a polymer with temperature can be utilized to develop accelerated test methods. The methods discussed in this chapter can assist the design engineer in the difficult task of estimating long-term properties of polymer-based materials from short-term tests. The procedure by which such estimates can be made is known as the time- temperature-superposition principle (TTSP) and is introduced in the following sections.


Free Volume Master Curve Physical Aging Shift Factor Relaxation Modulus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2008

Personalised recommendations