Physics-Informed Neural Network for monitoring the sulfate ion adsorption process using particle filter.

Journal: Anais da Academia Brasileira de Ciencias
PMID: 39607213

Abstract

Fixed-bed columns are a well-established water purification technology. Several models have been constructed over the decades to scale up and predict the breakthrough curve of an adsorption column varying the flow rate, length, and initial concentration of solute. In this work, we proposed using an emerging computational approach of a physic-informed neural network (PINN) that uses artificial intelligence to solve the partial differential equation model of adsorption. The effectiveness of this approach is compared with finite-volume methods and experimental data. We also couple the PINN with a sampling importance resampling particle filter, a Bayesian technique that allows the filter and estimate states of the process, quantifying uncertainties of experimental measurements. The results shows physic-informed neural network capability in solving the proposed model and its uses as an evolution model for sequential estimation.

Authors

  • Wancley O Pedruzzi
    Universidade Federal do Espírito Santo, Programa de Pós-Graduação em Engenharia Química, Alto Universitário, s/n, Guararema, 29500-000 Alegre, ES, Brazil.
  • Carlos Eduardo R Dalla
    Universidade Federal do Espírito Santo, Programa de Pós-Graduação em Engenharia Mecânica, Av. Fernando Ferrari, 514, Goiabeiras, 29075-910 Vitória, ES, Brazil.
  • Wellington B DA Silva
    Federal University of Espírito Santo/UFES, Department of Rural Engineering, Alto Universitário, s/n, 29500-000 Alegre, ES, Brazil.
  • Damaris Guimarães
    Universidade Federal do Espírito Santo, Departamento de Engenharia Rural, Alto Universitário, s/n, Guararema, 29500-000 Alegre, ES, Brazil.
  • Versiane A Leão
    Universidade Federal de Ouro Preto, Departamento de Engenharia Metalúrgica e de Materiais, Rua Professor Paulo Magalhães Gomes, 122, Bauxita, 35400-000 Ouro Preto, MG, Brazil.
  • Julio Cesar S Dutra
    Universidade Federal do Espírito Santo, Programa de Pós-Graduação em Engenharia Química, Alto Universitário, s/n, Guararema, 29500-000 Alegre, ES, Brazil.

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