<p>This study examines the effect of friction on flow stress–strain curves from uniaxial compression tests of AZ80-BN magnesium composite. Tests were conducted at temperatures of 300–400&#xa0;°C and strain rates of 0.01–10 s⁻<sup>1</sup>. We developed an analytical friction correction model to adjust the flow stress data, yielding more accurate measurements. The corrected curves revealed that uncorrected data can overestimate the material's behavior by up to 5%, especially at lower strain rates and intermediate temperatures (0.01 s⁻<sup>1</sup> and 350&#xa0;°C). This underscores the necessity of friction correction in hot deformation processes. Our findings provide essential insights into the role of friction, enabling a more reliable analysis of material behavior. These results facilitate the optimization of forming processes for AZ80-BN magnesium composite and have broader implications for improving predictive models and industrial forming techniques in materials science.</p> Graphical abstract <p></p>

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Impact of friction correction on flow stress–strain curves in the upsetting process for AZ80-BN magnesium composite

  • Ayoub Elajjani,
  • Chaoyang Sun,
  • Qian Lingyun,
  • Chunhui Wang

摘要

This study examines the effect of friction on flow stress–strain curves from uniaxial compression tests of AZ80-BN magnesium composite. Tests were conducted at temperatures of 300–400 °C and strain rates of 0.01–10 s⁻1. We developed an analytical friction correction model to adjust the flow stress data, yielding more accurate measurements. The corrected curves revealed that uncorrected data can overestimate the material's behavior by up to 5%, especially at lower strain rates and intermediate temperatures (0.01 s⁻1 and 350 °C). This underscores the necessity of friction correction in hot deformation processes. Our findings provide essential insights into the role of friction, enabling a more reliable analysis of material behavior. These results facilitate the optimization of forming processes for AZ80-BN magnesium composite and have broader implications for improving predictive models and industrial forming techniques in materials science.

Graphical abstract