Statistical treatment of grid indentation considering the effect of the interface and the microstructural length scale

Abstract

Statistical evaluation of grid indentation data is a well-known method used for determination of mechanical properties of multiphase materials. The statistical distribution of these type of data can be significantly influenced by the presence of an interface between adjacent phases. Consequently, the bias in mechanical properties (e.g. Young´s modulus, hardness), more pronounced for higher penetration depths, is usually observed. Using standard multimodal Gaussian distribution leads to underestimation of mechanical properties of harder/stiffer phases and vice versa. To eliminate this effect, statistical distribution taking into account the conditional probability of the indentation near the interface was developed and used in this case study on tungsten–copper composite. Using this approach, intrinsic material properties (Young´s modulus and hardness) of the individual phases were determined. Moreover, the contribution from the presence of the neighboring phase was separated and thus, so-called indentation size effect was successfully identified in individual phases of tungsten–copper composite.