Indentation plastometry

Capturing of macroscopic (size-independent) properties brings in a requirement[1][2][3][4] to deform a volume of material that is large enough to be representative of the bulk.

The indentation response must be sensitive to the plasticity characteristics of the material over the strain range of interest, which normally extends up to at least several % and commonly up to several tens of %.

Finally, depending on the hardness of the metal, this in turn requires that the facility should have a relatively high load capability – usually of the order of several kN.

As mentioned above, early types of hardness tester focused on this, in the form of (relatively crude) measurement of the “width” of the indent – commonly via simple optical microscopy.

Various empirical correction factors are commonly employed, with neural network “training” procedures sometimes being applied[15][16] to sets of load-displacement data and corresponding stress-strain curves, to help evaluate them.

However, unsurprisingly, universal conversions of this type (applied to samples with unknown stress-strain curves) tend to be unreliable[17][18][19] and it is now widely accepted that the procedure cannot be used with any confidence.

These include easier measurement, greater sensitivity of the experimental outcome to the stress-strain relationship and potential for detection and characterisation of sample anisotropy – see above.

For tractable and user-friendly application, an integrated facility is needed, in which the procedures of indentation, profilometry and convergence on the optimal stress-strain curve are all under automated control