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Project

Towards a practical engineering tool for inverse calibration of plastic behavior of sheet metals

Sheet metal forming is widely used in diverse industries, including automotive and aerospace. The modern mechanical design of sheet metal products and structures is driven by increasingly stringent performance requirements aimed at reducing energy and resource consumption. Design optimization and failure prediction for thin-walled metallic products now heavily rely on numerical simulations. A crucial element for accurate simulations is the precise reproduction of physical material behavior using advanced plasticity models.

Traditional approaches to calibrating such material models, relying on standard material tests, often involve complex, slow, expensive, and resource-intensive experimental campaigns. The integration of full-field optical measurements, inverse identification techniques, and heterogeneous mechanical tests for material model calibration has given rise to the concept of Material Testing 2.0 (MT2.0), which holds the potential to alleviate the increased calibration effort.

This thesis focuses on investigating the feasibility of using the MT2.0 concept to determine the plastic behavior of sheet metals. The starting point of the thesis is the design of a complex tensile test through shape optimization to maximize strain heterogeneity. A positive correlation between the strain heterogeneity indicator and identifiability was found for relatively simple anisotropic yield functions. However, for more advanced anisotropic yield functions, such as the Yld2000-2d yield function, it is demonstrated that two non-conventional tests (uniaxial and biaxial) and a weight-based FEMU (Finite Element Model Updating) method are required to inversely identify the anisotropy parameters. The results indicate that combining the two MT2.0 tests yields identification results comparable to the traditional calibration, which involved 17 linear stress path experiments.

Finally, a user-friendly inverse identification software is developed, integrating several key components of the MT2.0 concept. The latter is considered essential for the widespread adoption of the MT2.0 concept in the industry.

Date:16 Oct 2018 →  15 Dec 2023
Keywords:deforming process , fatigue assessment and mechanisms of fatigue, Digital image correlation
Disciplines:Ceramic and glass materials, Materials science and engineering, Semiconductor materials, Other materials engineering
Project type:PhD project