In order to find hyperelastic material model constants, data fitting technique is often used. For this task, the data is collected through different laboratory tests, namely, the uniaxial, the biaxial and the pure shear. However, due to the difficulty in getting biaxial data, often only uniaxial data was used for the fitting. Despite frequent use, it was established that this practice creates erroneous results. With a view to improve the data fitting results and at the same time to overcome the difficulty of collecting primary biaxial data, uniaxial data was used to generate a secondary biaxial data set. The data derived through this method was then tested with four common models as to examine the compatibility of the method. Subsequently, real biaxial data was used to compare with the data fitting results obtained through the proposed method. As results indicated combined data fitting for both instances were very much identical with respect to all tested models. Cases where somewhat higher deviation observed between experimental curves and data fitted curves for biaxial data, gave similar results for adjusted data driven data fitting too. However, such deviation could be attributed to mismatch between models with the particular material behaviour rather than the generated data.
Combined data-driven model for the prediction of thermal properties of Ni-based amorphous alloys
