摘要
采用响应曲面法的中心组合设计原理,建立浸出温度、硫酸浓度及液固比及三者之间交互作用对选择性浸出率与矿浆过滤速率的多元二次回归方程,并使用自适应权重粒子群算法对铜冶炼渣氧压硫酸选择性浸出工艺进行多目标优化。结果表明:浸出温度、硫酸浓度和液固比均是影响浸出率和过滤速率的主要因素,各响应因素间存在交互效应,且选择性浸出率与矿浆过滤速率在最佳条件上存在差异。优化后的选择性浸出率和矿浆过滤速率最佳的工艺条件为:温度为204.1℃、硫酸浓度为0.46mol/L、液固比为6.9mL/g,此条件下选择性浸出率为96.95%,过滤速率为399.42L/(m2∙h),与验证实验中平均选择性浸出率、平均过滤速率分别为96.57%,398L/(m2∙h)相比,偏差较小,预测值与验证实际值吻合好,表明模型选择准确,优化方案可信。
Based on the central combination design principle of response surface methodology,the multiple quadratic regression equation relating leaching temperature,sulfuric acid concentration,liquidsolid ratio and interaction between them on selective leaching rate and slurry filtration rate was established,and the multi-objective optimization of the oxygen pressure sulfuric acid selective leaching process for copper smelting slag was performed using the adaptive weighted particle swarm method.The results show that the leaching temperature and sulfuric acid concentration and liquid-solid ratio are the main factors affecting the leaching rate and filtration rate.There are interaction effects among the response factors affecting the leaching rate and filtration rate,and each of the optimal conditions for the selective leaching rate and the pulp filtration rate are different.The optimum conditions for the simultaneous optimization of selective leaching rate and slurry filtration rate are as follows:temperature of 204.1℃,sulfuric acid concentration of 0.46mol/L,and liquid-solid ratio of 6.9mL/g.Under the optimum conditions,the selective leaching rate is 96.95%,the filtration rate is 399.42L/(m^2∙h).Compared the average selective leaching rate and average filtration rate with that of 96.57%and 398L/(m^2∙h)respectively in verification experiment,the deviation between them is small.The value predicted by the equation is in good agreement with the verified actual value,indicating that the model obtained is accurate and the optimization scheme is credible.
作者
史公初
廖亚龙
苏博文
张宇
郗家俊
SHI Gongchu;LIAO Yalong;SU Bowen;ZHANG Yu;XI Jiajun(Faculty of Metallurgical and Energy Engineering of Kunming University of Science and Technology,Kunming 650093,Yunnan,China)
出处
《化工进展》
EI
CAS
CSCD
北大核心
2020年第S01期270-280,共11页
Chemical Industry and Engineering Progress
基金
国家自然科学基金(21978122,21566017)。
关键词
铜冶炼渣
选择性浸出
矿浆过滤性能
响应曲面法
自适应权重粒子群算法
多目标优化
copper metallurgical slag
selective leaching
slurry filtration property
response surface methodology
adaptive weight particle swarm optimization
multi-objective optimization