Damage prediction in single point incremental forming using an extended Gurson model

• Published in: International journal of solids and structures Vol. 151; pp. 45 - 56
• Main Authors: Guzmán, Carlos Felipe, Yuan, Sibo, Duchêne, Laurent, Saavedra Flores, Erick I., Habraken, Anne Marie
• Format: Journal Article Web Resource
• Language: English
• Published: New York Elsevier Ltd 15-10-2018; Elsevier BV; Pergamon Press (part of Elsevier Science)
• Subjects: Coalescing; Computer simulation; Cones; Damage; Ductile fracture; Engineering, computing & technology; Failure analysis; Finite element analysis; Finite element method; Formability; Forming techniques; Gurson model; Ingénierie mécanique; Ingénierie, informatique & technologie; Limarc; Materials science & engineering; Mathematical models; Mechanical engineering; Metal forming; Plastic deformation; Science des matériaux & ingénierie; Single point incremental forming; State-of-the-art reviews; Finite element method; Ductile fracture; 74R99; 74S05; Gurson model; Single point incremental forming
• ISSN: 0020-7683; 1879-2146; 1879-2146
• DOI: 10.1016/j.ijsolstr.2017.04.013

Single point incremental forming (SPIF) has several advantages over traditional forming, such as the high formability attainable by the material. Different hypotheses have been proposed to explain this behavior, but there is still no straightforward relation between the particular stress and strain state induced by SPIF and the material degradation leading to localization and fracture. A systematic review of the state of the art about formability and damage in SPIF is presented and an extended Gurson–Tvergaard–Needleman (GTN) model was applied to predict damage in SPIF through finite element (FE) simulations. The line test was used to validate the simulations by comparing force and shape predictions with experimental results. To analyze the failure prediction, several simulations of SPIF cones at different wall angles were performed. It is concluded that the GTN model underestimates the failure angle on SPIF due to wrong coalescence modeling. A physically-based Thomason coalescence criterion was then used leading to an improvement on the results by delaying the onset of coalescence.