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1) Explain what will happen in the strain vs. time graph when a polymer is heated...

Question:

1) Explain what will happen in the strain vs. time graph when a polymer is heated while under constant loading.


Answers

Polymer-based adhesives that have been especially designed to feature a high degree of toughness, flexibility, or, even deliberately, viscoelastic properties exhibit a pronounced time-dependent stress–strain behavior with under static mechanical load conditions and heating. Therefore, a suitable mechanical approach to describe and experimentally access phenomena related to creep (strain vs time curve) in polymers and adhesives needs to consider elastic as well as viscous material properties. Creep occurs at load levels below the yield strength, and particularly, creep of viscoelastic materials by definition is assigned to reversible deformation being able to recover after unloading. In technical practice, the term creep is often being used to describe arbitrary time-dependent strain including viscous and elastic-viscous behavior. The concept of generating mechanical substitute models consisting of a combination of spring (elastic) and dashpot (viscous) elements dates back to the late eighteenth century with the Maxwell model, for example, representing a serial connection of both.

Other viscoelastic models are discussed in terms of their creep (retardation) strain- and relaxation stress-response to a corresponding stress or strain input in the generalized form of a step-unit function. The resulting constitutive laws for stress–strain–time relationship under static stress or strain conditions can be applied in the limits of linear elasticity where the Boltzmann superposition principle and the correspondence principle are valid. The options for experimentally accessing creep and relaxation phenomena range from standardized procedures to advanced test methods, which are discussed in the context of experimental data. Applying the theoretical background of the standard models for viscoelasticity to the experimental results can improve the reliability of predictive methods intending to extrapolate results from short-term experiments to a long-term timescale.

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