Prediction of ductile damage and fracture in the single- and multi-stage incremental hole-flanging processes using a new damage accumulation law

Seyyedi, Seyyed Emad; Gorji, Hamid; Mirnia, Mohammad Javad; Bakhshi-Jooybari, Mohammad

doi:10.1007/s00170-021-08638-3

Cited by 9 publications

(1 citation statement)

References 46 publications

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“…They showed that increasing the redundant shearing in the softer layer is the main reason for this delay in local strain instability. Experimental and numerical analysis of the effective parameters on the forming of Al/St doublelayered sheets was conducted by Seyyedi et al [19]. They showed that the Al sheet's formability can be improved by laminating with the steel sheet.…”

Section: Introductionmentioning

confidence: 99%

Investigation on formability of three-layer joined Al/Cu/Al sheets annealed at different temperature

Roostaei

Darabi

2020

Materials Science and Technology

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Today, the use of multi-layer sheets has expanded widely in various industries. The determination of the forming limit curve for sheets is essential. In this project, three-layer aluminium1100-copper10100-aluminium1100 sheet was produced using an explosive welding method and cold rolling up to 85% strain. Then to eliminate the rolling microstructure and create the isotropic properties and to investigate the effect of annealing temperature on formability, three-layer sheets were annealed at 350°C, 400°C, and 450°C for one hour. Afterward, the numerical and experimental forming limits for these sheets are obtained at room temperature. ABAQUS finite element software and Freudenthal, Cockcroft, and Brozzo ductile fracture criteria were used in numerical method, and punch stretching test was used in the experimental method.

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Section: Introductionmentioning

confidence: 99%

Investigation on formability of three-layer joined Al/Cu/Al sheets annealed at different temperature

Roostaei

Darabi

2020

Materials Science and Technology

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Enhancement of incremental forming process formability by using improved clamping and multi-stage deformation strategies

Kumar,

Lingam,

Agrawal

2023

Int J Adv Manuf Technol

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Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification

Gerlach,

Schulte,

Schowtjak

et al. 2024

Arch Appl Mech

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The open-source parameter identification tool ADAPT (A diversely applicable parameter identification Tool) is integrated with a machine learning-based approach for start value prediction in order to calibrate a Gurson–Tvergaard–Needleman (GTN) and a Lemaitre damage model. As representative example case-hardened steel 16MnCrS5 is elaborated. An artificial neural network (ANN) is initially trained by using load–displacement curves derived from simulations of a boundary value problem—instead of using data generated for homogeneous states of deformation at material point or one-element level—with varying material parameter combinations. The ANN is then employed so as to predict sets of material parameters that already provide close solutions to the experiment. These predicted parameter sets serve as starting values for a subsequent multi-objective parameter identification by using ADAPT. ADAPT allows for the consideration of input data from multiple scales, including integral data such as load–displacement curves, full-field data such as displacement and strain fields, and high-resolution experimental void data at the micro-scale. The influence of each data set on prediction quality is analyzed. Using various types of input data introduces additional information, enhancing prediction accuracy. The validation is carried out with respect to experimental void measurements of forward rod extruded parts. The results demonstrate, by incorporating void measurements in the optimization process, that it is possible to improve the quantitative prediction of ductile damage in the sense of void area fractions by factor 28 in forward rod extrusion.

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Prediction of ductile damage and fracture in the single- and multi-stage incremental hole-flanging processes using a new damage accumulation law

Cited by 9 publications

References 46 publications

Investigation on formability of three-layer joined Al/Cu/Al sheets annealed at different temperature

Investigation on formability of three-layer joined Al/Cu/Al sheets annealed at different temperature

Enhancement of incremental forming process formability by using improved clamping and multi-stage deformation strategies

Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification

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