In sheet metal stamping, the occurrence of strain localization in a deformed sheet is considered a failure. As so, sheet metal's formability is conventionally evaluated using the Forming Limit Diagram (FLD), which separates the principal strain space into safety and unsafety regions by a Forming Limit Curve (FLC). This study presents an evaluation method for detecting strain localization based on Digital Image Correlation (DIC) during the experiment. The commercial DIC software ARAMIS is adopted to monitor the strain-field distribution on the deformed specimen's surface. A detailed analysis of the proposed method is presented considering Nakajima tests conducted for two automotive sheet metals: AA6016 and DP800. The identified FLC based on the proposed method is compared with that of well-established methods such as ISO 12004:2-2008 and time-dependent methods. For both investigated materials, the proposed method presents a lower FLC than the others.

With the increased demand for application of sustainable materials and lightweight structures, the sheet metal forming industry is forced to push existing materials to the limits. One area where this is particular difficult is when it comes to assessing the formability limit for sheet edges. For decades, the ISO-16630 Hole Expansion Test (HET) has been the industry standard for expressing the edge formability of sheet metals through the Hole Expansion Ratio (HER). However, in recent years, this test has been criticized for its high scatter in results for repeated experiments. This scatter has been suspected to be caused by the operator-reliant post-processing of the test, or variations in the cutting conditions for the different test specimens. This study investigates the impact of shifting the evaluation point of the test from the through-thickness crack to the onset of surface failure on the reported scatter, as well as performs inverse modeling of the Hole Expansion Test to obtain an edge limit strain value.

This study presents a new criterion (MMFC2) for predicting the forming limit curve (FLC) of sheet metal. The strain path evolution of a critical element examined in a uniaxial tensile test is elaborated by incorporating the results of experimental measurement, finite element simulation, and theoretical prediction via the Modified Maximum Force Criterion (MMFC). A scaling factor is introduced to mimic the theoretical evaluation with the simulated one. It is believed that the rotation of the principal axes of the theoretically considering material point, which is initially co-axial with the external load coordinate, implicates the macro track of the strain path change. Furthermore, an optimal event of the second derivative of the axial rotations is proposed to indicate the strain localization and formulate the FLC. The performance of the proposed criterion is compared with that of the original MMFC in predicting the FLC of three automotive sheet metals, of which all related data were published in the Benchmark of Numisheet 2014 conference. The use of three different hardening laws and three yield functions is examined in the analogy. The comparison reveals that the results of MMFC2 are more sensitive to the employed constitutive model than that of MMFC. Furthermore, the proposed MMFC2 presents concordant results with the experimental data. Nakajima tests are conducted for CR4 mild steel sheets to validate the capacity of the proposed criterion. Well agreement between the experimentally measured data and theoretical prediction based on the Yld2k yield function verifies its usefulness in practice. © 2023 The Author(s)

This study presents a modeling approach for predicting strain localization during sheet metal stamping processes focused on automotive engineering applications. The so-called stretching-to-bending ratio, ρ, is proposed to characterize the loading conditions acting on an element during stamping processes. Then, localized strain or necking strain is suggested to be a function of ρ. Different stretch–bending tests with different tool radii, i.e., R3, R6, R10, and R50 are conducted for two automotive sheet metals, DP800 and AA6010, to identify their forming limits under combined stretch–bend loads. The calibrated necking limit curve of the AA6016 sheet is then employed in AutoForm R10 software to predict the necking and failure of a stamped panel. Agreement with the experimental observation of failure positions of the panel validates the usefulness of the proposed modeling approach in practice. © 2023 The Author(s)

A theoretical model for predicting the forming limit diagram of sheet metal, namedMMFC2, was recently proposed by the authors based on the modified maximum force criterion(MMFC). This study examines the application of MMFC2 for two automotive sheets, DP800 andAA6016, which are widely used in making car body parts. Uniaxial tensile and bulge tests areconducted to calibrate constitutive equations for modeling the tested materials. The developedmaterial models are employed into different frameworks such as MMFC, MMFC2, and Marciniak-Kuczynski (MK) models to forecast the forming limit curve (FLC) of the tested materials. Theirpredictions are validated by comparing with an experimental one obtained from a series ofNakajima tests. It is found that the derived results of MMFC2 are comparable to that of MK modeland agreed reasonably with experimental data. Less computational time is the major advantage ofMMFC2 against the MK model. (PDF) Prediction of forming limit diagram of automotive sheet metals using a new necking criterion.

With the increased focus on reducing carbon emissions in the automotive industry, more advanced materials are introduced to reduce the vehicle weight, and more complex component geometries are designed to both satisfy customer demands and to optimize the vehicle aerodynamically. With the increase in component complexity, the strain paths produced during the forming operation of car body components often display a highly non-linear behavior which makes the task of failure prediction during the manufacturing feasibility studies more difficult. Therefore, CAE engineers need better capabilities to predict failure induced by strain path nonlinearity. This study proposes a new tool designed for creating bi-linear strain paths, by performing a pre-strain of a sheet large enough to cut out Nakajima specimens to perform the post-straining in any direction. From five pre-straining tests the tool present a stable pre-straining operation with a uniform strain field in a radius of 100 [mm] from the centre, corresponding to the region of interest of a Nakajima specimen. From the five pre-strained samples, different Nakajima specimens are cut transverse and longitudinal to the rolling direction and a failure prediction approach in an alternative, path independent evaluation space was used to predict the onset of necking with promising results.

The commercial-pure titanium (CP-Ti) sheet has attracted a great interest from biomedical and aerospace industries because of its strong mechanical advantages such as lightweight, high strength, good formability, and corrosion-resistance. However, strong anisotropic features, such as evolutionary yield surface and strength difference in tension and compression, of the CP-Ti require advanced constitutive modeling compared to standard advanced high strength steel sheets. This study took into account the differential hardening behavior and the changing R-value of CP-Ti sheet observed during the uniaxial tensile and bulge tests in developing a material model. The observed behaviors are modeled by Hill48 quadratic function based on non-associated flow rule with equivalent plastic work dependent evolutionary parameters. The developed material model was then implemented into a user material subroutine (VUMAT) for ABAQUS/EXPLICIT and used to simulate a circular deep drawing to verify the developed model. Simulation results are compared with those of a material model coupling Yld2000–2d yield function with associated flow rule. The comparison shows that the developed material model provides not only a good agreement with the experiment for yield and potential surfaces but also accurate predictions in forming simulations.