Modelling the removal of volatile pollutants under transient conditions in a two-stage bioreactor using artificial neural networks

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• 作者：M. Estefan&iacute ; a Ló ; pez^a ; Eldon R. Rene^a ; ^b ; Zvi Boger^c ; Mar&iacute ; a C. Veiga^a ; Christian Kennes^a ; ^{Kennes@udc.es}
• 关键词：Artificial neural networks ; Biofilter ; Biotrickling filter ; Two-stage bioreactor ; Transient-state performance
• 刊名：Journal of Hazardous Materials
• 出版年：2017
• 出版时间：15 February 2017
• 年：2017
• 卷：324
• 期：part_PA
• 页码：100-109
• 全文大小：1213 K
• 卷排序：324

文摘

Two-stage bioreactors, i.e., a biotrickling filter (BTF) and a biofilter (BF) were subjected to transient state operations. The removal efficiencies of methanol (REM), hydrogen sulphide (REHS) and α-pinene (REP) were modelled using artificial neural networks (ANN). ANN topologies were: 3-4-2 and 3-3-1 for the BTF and the BF, respectively. REM and REHS in the BTF were affected by the presence of α-pinene. REP in the BF was affected by the inlet concentration of hydrogen sulphide.