Key performance indicators for heterogeneous mechanical tests

Abstract

Characterizing sheet metal behavior is crucial for accurately simulating sheet metal forming processes. Typically, material parameters are obtained through quasi-homogeneous mechanical tests, which makes the mechanical testing task expensive and time-consuming. However, newly proposed mechanical testing approaches, known as heterogeneous tests, are outperforming quasi-homogeneous mechanical tests. Full-field measurement techniques, such as Digital Image Correlation, are used to extract this information. Despite several proposed test designs, selecting the best one to characterize a specific complex material behavior remains challenging. This work aims to apply Key Performance Indicators (KPIs) in a robust and straightforward way to rank mechanical tests, based on their potential to improve the material behavior characterization procedure. Scalar indicators are suggested to quantitatively evaluate important features of each test, from the diversity of strain states to the test’s sensitivity to the material model parameters. Additionally, measurement errors associated with Digital Image Correlation are taken into account via a numerical procedure. For validation purposes, five recently developed advanced mechanical tests are chosen to be analyzed. The performance of each test is evaluated numerically, leading to an overall ranking of these heterogeneous mechanical tests.