Surrogate-based optimisation of process systems to recover resources from wastewater
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Published version
Author(s)
Durkin, Alex
Otte, Lennart
Guo, Miao
Type
Journal Article
Abstract
Wastewater systems are transitioning towards integrative process systems to recover multiple resources whilst simultaneously satisfying regulations on final effluent quality. This work contributes to the literature by bringing a systems-thinking approach to resource recovery from wastewater, harnessing surrogate modelling and mathematical optimisation techniques to highlight holistic process systems. A surrogate-based process synthesis methodology was presented to harness high-fidelity data from black box process simulations, embedding first principles models, within a superstructure optimisation framework. Modelling tools were developed to facilitate tailored derivative-free optimisation solutions widely applicable to black box optimisation problems. The optimisation of a process system to recover energy and nutrients from a brewery wastewater reveals significant scope to reduce the environmental impacts of food and beverage production systems. Additionally, the application demonstrates the capabilities of the modelling methodology to highlight optimal processes to recover carbon, nitrogen, and phosphorous resources whilst also accounting for uncertainties inherent to wastewater systems.
Date Issued
2024-03
Date Acceptance
2024-01-02
Citation
Computers and Chemical Engineering, 2024, 182
ISSN
0098-1354
Publisher
Elsevier
Journal / Book Title
Computers and Chemical Engineering
Volume
182
Copyright Statement
© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
http://dx.doi.org/10.1016/j.compchemeng.2024.108584
Publication Status
Published
Article Number
108584
Date Publish Online
2024-01-09