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Optimization Model for Roasting Parameters of High-Copper Low-Sulfur Concentrate Based on Response Surface Methodology
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Xing LUO1, 2, Fucheng ZHAO1, 2, Kangle JIA1, 2, Haibao FAN1, 2, Jun PU1, 2
Mining and Metallurgical Engineering | 2026, 46(4) : 210 - 214
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Mining and Metallurgical Engineering | 2026, 46(4): 210-214
• METALLURGY •
Optimization Model for Roasting Parameters of High-Copper Low-Sulfur Concentrate Based on Response Surface Methodology
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Xing LUO1, 2, Fucheng ZHAO1, 2, Kangle JIA1, 2, Haibao FAN1, 2, Jun PU1, 2
Affiliations
  • 1.Huagang Mining Co., Ltd., Beijing 100039, China
  • 2.China Railway Resources Group Co., Ltd., Beijing 100039, China
doi: 10.3969/j.issn.0253-6099.2026.04.032
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By adopting central composite design (CCD) of response surface methodology (RSM), a binary quadratic regression prediction model was established, with roasting temperature and oxygen concentration as influencing factors and copper leaching rate of calcine as the response value. It is shown that the prediction model presents a P value of 0.018 2, adjusted determination coefficient of 0.810 1, and signal-to-noise ratio of 7.323 6, exhibiting favorable reliability and prediction accuracy. Roasting temperature has an extremely significant effect on copper leaching rate, while oxygen concentration brings insignificant effect, and their interaction is weak. The parameters were optimized via Design-Expert software, and the optimal roasting process parameters are obtained as follows:roasting temperature of 750 ℃ and oxygen concentration of 30%. Under such optimized parameters, the predicted copper leaching rate of calcine is 97.47%, while the copper leaching rate of calcine in industrial applications reaches 98.17%.

high-copper low-sulfur concentrate  /  copper sulfide ore  /  roasting  /  response surface methodology  /  parameter optimization  /  leaching rate  /  prediction model
罗星, 赵富城, 贾康乐, 范海宝, 蒲俊. 基于响应曲面法的高铜低硫精矿焙烧参数优化模型. 矿冶工程杂志, 2026 , 46 (4) : 210 -214 . DOI: 10.3969/j.issn.0253-6099.2026.04.032
Xing LUO, Fucheng ZHAO, Kangle JIA, Haibao FAN, Jun PU. Optimization Model for Roasting Parameters of High-Copper Low-Sulfur Concentrate Based on Response Surface Methodology[J]. Mining and Metallurgical Engineering, 2026 , 46 (4) : 210 -214 . DOI: 10.3969/j.issn.0253-6099.2026.04.032
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Year 2026 volume 46 Issue 4
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doi: 10.3969/j.issn.0253-6099.2026.04.032
  • Receive Date：2026-02-02
  • Online Date：2026-10-08
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  • Received：2026-02-02
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Affiliations
    1.Huagang Mining Co., Ltd., Beijing 100039, China
    2.China Railway Resources Group Co., Ltd., Beijing 100039, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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