Neural network for fractal dimension evolution

Autor(es)

Oliveira, Alessandra da Silva ^[1] ; Lopes, Veronica dos Santos ^[1] ; Coutinho Filho, Ubirajara ^[2] ; Moruzzi, Rodrigo Braga ^[3] ; de Oliveira, Andre Luiz ^[1]

Afiliação do(s) autor(es)

^[1] Univ Fed Uberlandia, Fac Engn Civil, Uberlandia, MG - Brazil

^[2] Univ Fed Uberlandia, Fac Engn Quim, Uberlandia, MG - Brazil

^[3] Univ Estadual Paulista UNESP, Inst Geociencias & Ciencias Exatas, Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: WATER SCIENCE AND TECHNOLOGY; v. 78, n. 4, p. 795-802, AUG 2018.
• Citações Web of Science: 0

Resumo

The coagulation/flocculation process is an essential step in drinking water treatment. The process of formation, growth, breakage and rearrangement of the formed aggregates is key to enhancing the understanding of the flocculation process. Artificial neural networks (ANNs) are a powerful technique, which can be used to model complex problems in several areas, such as water treatment. This work evaluated the evolution of the fractal dimension of aggregates obtained through ANN modeling in the coagulation/flocculation process conducted in high apparent color water (100 +/- 5 PtCo), using alum as coagulant in dosages varying from 1 to 12 mg Al3+ L-1, and shear rates from 20 to 60 s(-1) for flocculation times from 1 to 60 minutes. Based on raw data, the ANN model resulted in optimized condition of 9.5 mg Al3+ L-1 and pH 6.1, for color removal of 90.5%. For fractal dimension evolution, the ANN was able to represent from 95% to 99% of the results. (AU)

• Processo FAPESP: 17/19195-7 - Dinâmica numérica e morfológica de agregados de fractal formados durante a floculação e seus efeitos na separação sólido-líquido
• Beneficiário: Rodrigo Braga Moruzzi
• Modalidade de apoio: Bolsas no Exterior - Pesquisa