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Plastic flow is an essential component of a material model describing material behaviors under external loads. Conventionally, a standard uniaxial tensile test is performed to determine the flow curve of sheet metals. This study implements two advanced methods: data-driven and inverse FE methods to identify the plastic flow of a VDA239-100 CR4 sheet using a notch-tensile sample. In the former method, a simulated database is generated to train a neural network, which is able to predict the plastic flow of a sheet metal using the experimental data. The latter adopts an optimization algorithm to minimize the difference between the strain distribution observed during experiment and that of simulations. The derived results are compared with the results obtained from a standard uniaxial tensile test. The benefits of each calibration method are discussed based on the comparisons.

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Identification of the Plastic Flow of VDA239-100 CR4 Sheets Using Advanced Methods

  • 会议论文

  • 发表日期：

    2025年

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  • Quoc Tuan Pham,
  • Md Shafiqul Islam,
  • Oliver Nillsson,
  • Jan Lim,
  • Anton Haller,
  • Nicke Fridström,
  • Johan Pilthammar,
  • Mats Sigvant

摘要

Plastic flow is an essential component of a material model describing material behaviors under external loads. Conventionally, a standard uniaxial tensile test is performed to determine the flow curve of sheet metals. This study implements two advanced methods: data-driven and inverse FE methods to identify the plastic flow of a VDA239-100 CR4 sheet using a notch-tensile sample. In the former method, a simulated database is generated to train a neural network, which is able to predict the plastic flow of a sheet metal using the experimental data. The latter adopts an optimization algorithm to minimize the difference between the strain distribution observed during experiment and that of simulations. The derived results are compared with the results obtained from a standard uniaxial tensile test. The benefits of each calibration method are discussed based on the comparisons.