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Soft sensor for substrate characterization through the reverse application of the ADM1 model for anaerobic digestion plant operations.

Fernando ZorrillaMa Constanza Sadino-RiquelmeFelipe HansenAndrés Donoso-Bravo
Published in: Water science and technology : a journal of the International Association on Water Pollution Research (2024)
Accurately characterizing the substrate used in anaerobic digestion is crucial for predicting the biogas plant's performance. This issue makes particularly challenging the application of modeling in codigestion plants. In this work, a novel methodology called substrate prediction module (SPM) has been developed and tested, using virtual codigestion data. The SPM aims to estimate the inlet properties of the substrate based on the reverse application of the anaerobic digestion model n1 (ADM1). The results show that, while the SPM can estimate some properties of the substrate based on certain output parameters, there are limitations in accurately determining all required variables.
Keyphrases
  • anaerobic digestion
  • sewage sludge
  • antibiotic resistance genes
  • municipal solid waste
  • structural basis
  • amino acid
  • machine learning
  • microbial community
  • big data
  • artificial intelligence
  • data analysis