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<p>To tackle the excessive nitrogen content in interstitial-free (IF) steel produced via the electric arc furnace (EAF) process through Ruhrstahl-Heraeus (RH) refining, this study develops a coupled mathematical model for decarburization and denitrification during RH treatment. Considering current RH treatments achieve only 20% nitrogen removal due to sluggish nitrogen mass transfer and surface-active element inhibition, and recent modeling for RH denitrification processes have neglected the mutual interaction mechanisms between decarburization and denitrification, while failing to account for mechanistic variations across distinct reaction sites, this model dynamically calculates gas partial pressures, elemental compositions, and effective reaction areas across four reaction sites. The simulation results for different initial carbon, oxygen, and nitrogen contents and varying oxygen flow rates are consistent with industrial test data, thereby confirming the model’s accuracy. The model reveals that the argon bubble surface dominates nitrogen removal (64.1% contribution). Initial carbon content significantly influences denitrification efficiency, reducing endpoint nitrogen by 2.5&#xa0;ppm per 100&#xa0;ppm carbon increment. Conversely, increasing oxygen content (+100&#xa0;ppm) increases residual nitrogen by 0.76&#xa0;ppm due to surface-active effects. Deep denitrification (target: &lt; 30&#xa0;ppm) requires increasing the carbon content to 1000&#xa0;ppm with optimized oxygen blowing, achieving the target nitrogen level within 990&#xa0;s.</p>

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Coupled Mathematical Model of RH Denitrification-Decarburization for IF Steel Produced via the Electric Arc Furnace Process

  • 期刊论文

  • 发表日期：

    2026年1月30日

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  • Yuan Si,
  • Dongfeng He,
  • Xuewen Xiao,
  • Ling Wu

摘要

To tackle the excessive nitrogen content in interstitial-free (IF) steel produced via the electric arc furnace (EAF) process through Ruhrstahl-Heraeus (RH) refining, this study develops a coupled mathematical model for decarburization and denitrification during RH treatment. Considering current RH treatments achieve only 20% nitrogen removal due to sluggish nitrogen mass transfer and surface-active element inhibition, and recent modeling for RH denitrification processes have neglected the mutual interaction mechanisms between decarburization and denitrification, while failing to account for mechanistic variations across distinct reaction sites, this model dynamically calculates gas partial pressures, elemental compositions, and effective reaction areas across four reaction sites. The simulation results for different initial carbon, oxygen, and nitrogen contents and varying oxygen flow rates are consistent with industrial test data, thereby confirming the model’s accuracy. The model reveals that the argon bubble surface dominates nitrogen removal (64.1% contribution). Initial carbon content significantly influences denitrification efficiency, reducing endpoint nitrogen by 2.5 ppm per 100 ppm carbon increment. Conversely, increasing oxygen content (+100 ppm) increases residual nitrogen by 0.76 ppm due to surface-active effects. Deep denitrification (target: < 30 ppm) requires increasing the carbon content to 1000 ppm with optimized oxygen blowing, achieving the target nitrogen level within 990 s.