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<p>To address the issue of defect formation during the skew rolling piercing of bimetallic composite pipes, this study proposes a process optimization method integrating numerical simulation and intelligent algorithms. Taking the Incoloy825/P110 bimetallic composite pipe as the research object, a finite element model for skew rolling piercing was established using Simufact Forming simulation software. The simulation results were analyzed and integrated to form a dataset. Based on this dataset, a radial basis function (RBF) neural network prediction model was developed, with six parameters—initial rolling temperature, roll speed, plug advance distance, and others—as inputs, and plug axial force, maximum piercing temperature, and shell elongation as outputs. The model exhibited high prediction accuracy, with coefficient of determination (<i>R</i><sup>2</sup>) values all above 0.92. Furthermore, a multi-objective optimization model was established using the NSGA-II algorithm, aiming to minimize plug axial force and piercing temperature while maximizing shell elongation. The TOPSIS-entropy weight method was applied to select the optimal process parameter combination from the Pareto solution set: roll distance of 178&#xa0;mm, roll speed of 40&#xa0;rpm, plug advance distance of 116&#xa0;mm, pass diameter of 56.5&#xa0;mm, initial rolling temperature of 1142&#xa0;°C, and wall thickness ratio of 0.6. Actual piercing experiments demonstrate that the optimized process parameters effectively suppress defect formation; the resulting tubes exhibit excellent surface finish and a fully bonded interface. Tensile tests yielded an ultimate tensile strength of 940&#xa0;MPa and a yield strength of 582&#xa0;MPa. These mechanical properties satisfy the relevant technical standards and meet the requirements for industrial-scale production.</p>

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Optimization of Skew Rolling Piercing Process for Bimetallic Composite Pipes Based on Numerical Simulation and Intelligent Algorithm Fusion

  • 期刊论文

  • 发表日期：

    2025年9月24日

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  • Jianhua Hu,
  • Jiawang Ma,
  • Yadong Hao,
  • Genyao Zhang,
  • Zhang Zhenqi,
  • Yihang Pei

摘要

To address the issue of defect formation during the skew rolling piercing of bimetallic composite pipes, this study proposes a process optimization method integrating numerical simulation and intelligent algorithms. Taking the Incoloy825/P110 bimetallic composite pipe as the research object, a finite element model for skew rolling piercing was established using Simufact Forming simulation software. The simulation results were analyzed and integrated to form a dataset. Based on this dataset, a radial basis function (RBF) neural network prediction model was developed, with six parameters—initial rolling temperature, roll speed, plug advance distance, and others—as inputs, and plug axial force, maximum piercing temperature, and shell elongation as outputs. The model exhibited high prediction accuracy, with coefficient of determination (R2) values all above 0.92. Furthermore, a multi-objective optimization model was established using the NSGA-II algorithm, aiming to minimize plug axial force and piercing temperature while maximizing shell elongation. The TOPSIS-entropy weight method was applied to select the optimal process parameter combination from the Pareto solution set: roll distance of 178 mm, roll speed of 40 rpm, plug advance distance of 116 mm, pass diameter of 56.5 mm, initial rolling temperature of 1142 °C, and wall thickness ratio of 0.6. Actual piercing experiments demonstrate that the optimized process parameters effectively suppress defect formation; the resulting tubes exhibit excellent surface finish and a fully bonded interface. Tensile tests yielded an ultimate tensile strength of 940 MPa and a yield strength of 582 MPa. These mechanical properties satisfy the relevant technical standards and meet the requirements for industrial-scale production.