Co-incineration of multiple inorganic solid wastes towards clean disposal: Heat and mass transfer modeling, pollutant generation, and machine learning based proportioning

Guanyi Chen , Guandong Chen , Jingwei Li , Queyi Pan , Daolun Liang , Jie Qiu , Xiqiang Zhao , Xiaojia Wang , Zhongshan Li , Xiangping Li , Xiaoling Ma , Shuang Wu , Yunan Sun
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Abstract

The co-disposal of solid waste by industrial kilns is presently attracting increasing attention. In this study, we investigate the co-disposal of solid waste, i.e. converter ash (CA), sintered ash (SA), blast furnace bag ash (BA), and municipal solid waste incineration fly ash (MSWIFA), under simulated blast furnace ironmaking conditions. The results show that it is feasible to use blast furnace to treat MSWIFA, but the stability of temperature field should be controlled in the process of co-disposal. With the increase of temperature, the conversion rate of NO decreased to 16.4%, and ZnFe2O4 became the main mineral composition, accounting for 75.53%. Corresponding to the flue gas corrosion condition of solid waste treatment, it is found that the corrosion resistance of the furnace material TH347H is better than 20G. Finally, based on the experimental data, the nested optimization algorithm of machine learning model is established to achieve the reverse output of optimal conditions. Overall, the study provides theoretical support and methodology guidance for the co-disposal of solid waste in blast furnaces in providing support for the further development of co-disposal of solid waste in industrial kilns.

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多种无机固体废物的共焚化清洁处置:传热和传质建模、污染物生成以及基于机器学习的配比
目前,工业窑炉对固体废物的协同处置正引起越来越多的关注。本研究探讨了在模拟高炉炼铁条件下转炉灰(CA)、烧结灰(SA)、高炉布袋灰(BA)和城市固体废弃物焚烧飞灰(MSWIFA)等固体废弃物的协同处置。结果表明,利用高炉处理 MSWIFA 是可行的,但在协同处置过程中应控制温度场的稳定性。随着温度的升高,NO 的转化率降至 16.4%,ZnFe2O4 成为主要矿物成分,占 75.53%。与固废处理的烟气腐蚀条件相对应,发现炉料 TH347H 的耐腐蚀性优于 20G。最后,基于实验数据,建立机器学习模型的嵌套优化算法,实现最优条件的反向输出。总之,该研究为高炉固废协同处置提供了理论支持和方法指导,为工业窑炉固废协同处置的进一步发展提供了支持。
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