Biomedical Engineering Reference
In-Depth Information
for establishing effective algorithms to extract the intrinsic mechanical
properties of these materials. A comprehensive summary is given below.
350
Identified material from reverse analysis
B u lg e te st
(b)
300
250
200
150
100
(a)
50
0
0.0
0.1
0.2
0. 3
0.4
0. 5
0.6
Strain (%)
Figure 6-9. (a) Stress-strain curve of a Cu film: reverse analysis result (symbols) obtained
from indentation on Cu film deposited on a Si substrate, which agrees well with that
measured from a bulge test (line); (b) The hardness correction factor for indentation on
porous film.
7. Conclusions and Outlook
In all cases of computational modeling of indentation, based on
dimensional analysis, the variables can be grouped into the smallest
possible sets needed to characterize the mechanics of indentation. It is
straightforward to vary materials parameters over a wide range during
the forward analyses, to calibrate the relationships between material
variables ( e.g. constitutive and fracture properties, time-dependent
properties, material structure) and indentation responses ( e.g. shape
factors of the indentation load-displacement curve, stiffness, hardness,
indenter geometry, crack length), sketched in Fig. 6-10. Once indentation
data are obtained from experiments, they are substituted into the
established relationships and the mechanical properties of the specimen
are iterated - the set of material properties that minimizes the total error
with respect to the established functions are the parameters identified
from the nanoindentation experiment. During such reverse analysis
( Fig. 6-10 ), special attentions are given to ensure that the solution is
unique through advanced numerical analyses. In addition, error
sensitivity needs to be carried out to evaluate how sensitive the measured
 
 
 
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