<p>This study proposes a multiscale slip-line field model for predicting cutting forces in chamfered tool machining of 42CrMo steel. By integrating slip-line field theory with unequal division shear-zone theory, a five-zone model incorporating the Dead Metal Zone (DMZ) effect is established. The Johnson-Cook constitutive model enables multiscale coupling by linking flow stress to shear angle, while the Schulz friction model establishes a velocity-dependent tool-chip friction relationship. The DMZ angle and chamfer friction angle, which are empirical in existing models, are quantitatively determined through DEFORM-2D simulations and embedded into the theoretical framework. These coupled relationships form the foundation for an energy minimization-based solution. Through iterative application of the minimum energy principle, the optimal shear angle is determined, yielding a closed-loop predictive model. Turning experiments on 42CrMo steel demonstrate that the model predicts cutting forces with errors consistently below 10%, achieving a relative improvement of more than 30% in prediction accuracy compared to a purely geometric slip-line model. This work provides an accurate, physics-based tool for chamfered tool design and optimization in 42CrMo steel cutting under fixed parameters.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Multiscale slip-line field modelling for chamfered tool cutting force predictions

  • Zhiming Feng,
  • Huan Long,
  • Donglin Li,
  • Jun Gong,
  • Marian Wiercigroch

摘要

This study proposes a multiscale slip-line field model for predicting cutting forces in chamfered tool machining of 42CrMo steel. By integrating slip-line field theory with unequal division shear-zone theory, a five-zone model incorporating the Dead Metal Zone (DMZ) effect is established. The Johnson-Cook constitutive model enables multiscale coupling by linking flow stress to shear angle, while the Schulz friction model establishes a velocity-dependent tool-chip friction relationship. The DMZ angle and chamfer friction angle, which are empirical in existing models, are quantitatively determined through DEFORM-2D simulations and embedded into the theoretical framework. These coupled relationships form the foundation for an energy minimization-based solution. Through iterative application of the minimum energy principle, the optimal shear angle is determined, yielding a closed-loop predictive model. Turning experiments on 42CrMo steel demonstrate that the model predicts cutting forces with errors consistently below 10%, achieving a relative improvement of more than 30% in prediction accuracy compared to a purely geometric slip-line model. This work provides an accurate, physics-based tool for chamfered tool design and optimization in 42CrMo steel cutting under fixed parameters.