Optimization of the essential work of fracture method for characterization of the fracture resistance of metallic sheets. (1st June 2022)

• Record Type: Journal Article
• Authors: Hilhorst, A.; Pardoen, T.; Jacques, P.J.
• Is Part Of: Engineering fracture mechanics. Volume 268(2022)
• Publication Date: 2022-06-01
• Subjects: Fracture toughness -- Essential work of fracture -- Ductile thin sheets; Fracture mechanics -- Periodicals; Rupture, Mécanique de la -- Périodiques; Fracture mechanics; Periodicals; 620.112605
• DOI: 10.1016/j.engfracmech.2022.108442
• Languages: English
• ISSNs: 0013-7944

Abstract

Abstract: The essential work of fracture (EWF) method is a powerful approach to characterize the fracture resistance of thin ductile sheets based on a principle of separation of energy contributions. A major drawback of the method is an extensive use of material, requiring a series of double-edge notched tensile (DENT) specimens with several ligament lengths to extract the EWF. This can be a serious limitation when the material is difficult to process and/or expensive. Here, we propose an improved methodology to reduce the amount of material as much as possible while keeping the same statistical level of accuracy for the estimated EWF. We show that the width and height of the DENT specimens can be adapted as a function of the ligament length. A statistical model has been developed to determine the distribution of ligament lengths minimizing the total amount of material. This new approach is validated both numerically with Monte Carlo simulations and experimentally. In the experiments, the strain fields in the ligament were quantified by digital image correlation to ensure that the validity criteria were met for each specimen, as well as to provide an in-depth analysis of the plastic zone development. From these results, guidelines are provided to optimally rationalize EWF experimental data. Highlights: The improved EWF methodology saves up to 70% of the material required. The same level of accuracy is maintained. Digital Image Correlation is useful to ensure that the validity criteria are met.