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Abstract <p>The hydromechanical pressing of bimetallic composite material workpieces is optimized. Neural network modeling is used to determine the optimum values of key technological parameters (reduction ratio, die cone angle, contact friction conditions) to achieve a complex minimum (quality criterion) of deformation heterogeneity, fiber (filament) damage, and pressing stress.</p>

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Optimization of Hydromechanical Pressing of (Nb–Ti) + Cu Metal Matrix Composite Workpieces Using Neural Network Modeling

  • 期刊论文

  • 发表日期：

    2025年5月1日

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  • D. A. Dvoinikov,
  • A. G. Zalazinskii,
  • V. G. Titov,
  • V. P. Shveikin

摘要

Abstract

The hydromechanical pressing of bimetallic composite material workpieces is optimized. Neural network modeling is used to determine the optimum values of key technological parameters (reduction ratio, die cone angle, contact friction conditions) to achieve a complex minimum (quality criterion) of deformation heterogeneity, fiber (filament) damage, and pressing stress.