Work

Surrogate-based optimisation of process systems to recover resources from wastewater

Year: 2024

Type: 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.

Source: Computers & Chemical Engineering

DOI: 10.1016/j.compchemeng.2024.108584

Authors: Alex Durkin, Lennart Otte, Miao Guo

Institutions: Imperial College London, King's College London

Language: English

Topic: Process Optimization and Integration

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Responsible consumption and production, Clean water and sanitation

Open Access status: hybrid

Estimated APC paid: $4,230