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Modelling and optimization of thermophilic anaerobic digestion using biowaste.
Parthiban, A; Sathish, S; Suthan, R; Sathish, T; Rajasimman, M; Vijayan, V; Jayaprabakar, J.
Affiliation
  • Parthiban A; Department of Mechanical Engineering, Vels Institute of Science, Technology & Advanced Studies, Pallavaram, Chennai, India.
  • Sathish S; School of Aeronautical Sciences, Hindustan Institute of Technology and Science, Padur, Chennai, India.
  • Suthan R; Department of Mechanical Engineering, Panimalar Engineering College, Chennai, Tamil Nadu, India.
  • Sathish T; Department of Mechanical Engineering, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India. Electronic address: Sathish.sailer@gmail.com.
  • Rajasimman M; Department of Chemical Engineering, Annamalai University, Annamalai Nagar, 608002, India.
  • Vijayan V; Department of Mechanical Engineering, K.Ramakrishnan College of Technology, Trichy, Tamil Nadu, India.
  • Jayaprabakar J; Department of Mechanical Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India.
Environ Res ; 220: 115075, 2023 03 01.
Article in En | MEDLINE | ID: mdl-36566967
ABSTRACT
Biowaste generation is considerably increasing multiple times recently due to various social and environmental changes like population growth, economic prosperity, globalisation etc. they contain different composition and generated at different stages of their life cycle. Though studies reported for recycle, reproduce and reuse of them, this investigation is unique by focussing to investigate the ideal circumstances for the production of biogas and methane from anaerobic digestion of vegetable waste using response surface methods and artificial neural networks with thermophilic temperature range. Thermophilic temperature of 20.78, organic loading rate of 0.2, pH of 8.81, agitation time of 5.8 and hydro retention time of 3 are the ideal input parameter values for the generation of biogas 3.03 m3 and methane% 186.08 with a desirability of 1. The Response surface model was surpassed by the Artificial Neural Network model.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biofuels / Methane Language: En Journal: Environ Res Year: 2023 Document type: Article Affiliation country: India Publication country: HOLANDA / HOLLAND / NETHERLANDS / NL / PAISES BAJOS / THE NETHERLANDS

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biofuels / Methane Language: En Journal: Environ Res Year: 2023 Document type: Article Affiliation country: India Publication country: HOLANDA / HOLLAND / NETHERLANDS / NL / PAISES BAJOS / THE NETHERLANDS