Creep deformation of materials in light water reactors (LWRs) - Materials' Ageing and Degradation in Light Water Reactors - page 49

the power-law creep regime, have been proposed following microstructural
studies on the crept specimens. For instance observation of subgrains in the
crept microstructure is considered evidence for creep controlled by climb
of edge dislocations. Similarly observation of jogged screw dislocations is
believed to indicate deformation controlled by the Barrett-Nix model or its
recent modifi cation proposed by Mills and co-workers.
In most cases the deformation microstructures are investigated through
TEM studies. Hence the sample studied, due to its very small volume, may
not be a real representation of the condition of the material. Thus there is
some uncertainty associated with the rate controlling mechanism. While the
physically based mechanisms discussed in the previous sections are impor-
tant for understanding and predicting deformation rates, an equally large
number of studies has been carried out to predict creep life using math-
ematical models and empirical correlations. The Larson-Miller parameter
(LMP), Monkman-Grant constant, -projection concept and a host of other

graphical and mathematical methods have been utilized to predict the creep
life of various engineering materials.
Generally engineering components are designed for a stress level below
which there is no danger of rupture or excess deformation during the ser-
vice life of the component. The stress level is decided by one of the follow-
ing two criteria: (a) stress level at which rupture/failure would be caused in
100 000 or 200 000 h, whichever period is appropriate and (b) stress level
which produces a nominal strain of 0.1%, 0.2% or 0.5% in a certain period,
say 100 000 h. 82 However there are not many tests carried out till 100 000 h
even for established materials and hence it is necessary to extrapolate data
from much shorter tests, say 10 3 -10 4 h. This is especially important for new
materials where it is necessary to understand their long term behavior
within a short span of time. Hence the extrapolation techniques become
important and in this section we discuss some of the existing extrapolation
techniques for predicting long term creep behaviors. Penny and Marriott 82
provide an excellent review of the various extrapolation methods and also
the advantages and disadvantages associated with each method. They divide
the extrapolation techniques into three main groups:

θ

￿ ￿ ￿ ￿ ￿ ￿

1 Parametric methods

2 Graphical methods

3 Algebraic methods.

Equations correlating time-temperature or stress-time fall under the para-
metric method. Functional relationships between time, temperature and
stress are established and it is believed that when stress is plotted against
a function of time and temperature, a single master curve will be obtained.
This master curve can be constructed by performing short term tests at