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

被引:1
作者
Durkin, Alex [1 ]
Otte, Lennart [2 ]
Guo, Miao [1 ,2 ]
机构
[1] Imperial Coll London, Dept Chem Engn, London SW7 2AZ, England
[2] Kings Coll London, Dept Engn, London WC2R 2LS, England
基金
英国工程与自然科学研究理事会;
关键词
Surrogate modelling; Derivative-free optimisation; Resource recovery from wastewater; DERIVATIVE-FREE OPTIMIZATION; SUPERSTRUCTURE OPTIMIZATION; ANAEROBIC-DIGESTION; DESIGN; MODELS; ALGORITHM; FRAMEWORK; ENERGY; BIOREFINERIES; KNOWLEDGE;
D O I
10.1016/j.compchemeng.2024.108584
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页数:28
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