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Optimisation of a Sequencing Batch Reactor for Production of Polyhydroxybutyrate Using Process Characterisation Method and Neural Network Modelling

Lookup NU author(s): Amin Ganjian, Dr Jie ZhangORCiD


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This paper presents neural network based modelling and optimisation of a sequencing batch reactor (SBR) for the production of polygydroxybutyrate (PHB), a bio-graded plastic with similar physical properties to polyethylene. A process characterisation method is developed for PHB production under mixed microbial culture. Based on the results obtained from the method, two major biological phases are identified and characterised. SBR recipes are designed to impose occurrence of both phases within each cycle of the SBR for sustainable productions. In order to overcome the difficulties of developing complicated mechanistic models and using such models in optimisation, bootstrap aggregated neural network models are developed and used to maximise PHB production. Simulation results show that the proposed method can improve PHB production.

Publication metadata

Author(s): Ganjian A, Zhang J, Oliveira R

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 24th European Symposium on Computer Aided Process Engineering

Year of Conference: 2014

Pages: 733-738

Publisher: Elsevier


DOI: 10.1016/B978-0-444-63456-6.50123-X

Library holdings: Search Newcastle University Library for this item

Series Title: Computer Aided Chemical Engineering

ISBN: 9780444634566