Odriozola Magela, van Lier Jules B, Spanjers Henri
Department of Water Management, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands.
Membranes (Basel). 2022 Jan 26;12(2):151. doi: 10.3390/membranes12020151.
Flux enhancers (FEs) have been successfully applied for fouling mitigation in membrane bioreactors. However, more research is needed to compare and optimise different dosing strategies to improve the filtration performance, while minimising the use of FEs and preventing overdosing. Therefore, the goal of this research is to develop an optimised control strategy for FE dosing into an AnMBR by developing a comprehensive integrated mathematical model. The integrated model includes filtration, flocculation, and biochemical processes to predict the effect of FE dosing on sludge filterability and membrane fouling rate in an AnMBR. The biochemical model was based on an ADM1, modified to include FEs and colloidal material. We developed an empirical model for the FE-induced flocculation of colloidal material. Various alternate filtration models from the literature and our own empirical models were implemented, calibrated, and validated; the best alternatives were selected based on model accuracy and capacity of the model to predict the effect of varying sludge characteristics on the corresponding output, that is fouling rate or sludge filterability. The results showed that fouling rate and sludge filterability were satisfactorily predicted by the selected filtration models. The best integrated model was successfully applied in the simulation environment to compare three feedback and two feedforward control tools to manipulate FE dosing to an AnMBR. The modelling results revealed that the most appropriate control tool was a feedback sludge filterability controller that dosed FEs continuously, referred to as ∆R20_10. Compared to the other control tools, application of the ∆R20_10 controller resulted in a more stable sludge filterability and steady fouling rate, when the AnMBR was subject to specific disturbances. The simulation environment developed in this research was shown to be a useful tool to test strategies for dosing flux enhancer into AnMBRs.
通量增强剂（FEs）已成功应用于膜生物反应器中的污垢缓解。然而，需要更多研究来比较和优化不同的投加策略，以提高过滤性能，同时尽量减少通量增强剂的使用并防止过量投加。因此，本研究的目标是通过开发一个综合的集成数学模型，为厌氧膜生物反应器（AnMBR）中通量增强剂的投加制定优化控制策略。该集成模型包括过滤、絮凝和生化过程，以预测通量增强剂投加对AnMBR中污泥过滤性能和膜污染速率的影响。生化模型基于ADM1，并进行了修改以纳入通量增强剂和胶体物质。我们开发了一个通量增强剂诱导胶体物质絮凝的经验模型。实施、校准并验证了文献中的各种替代过滤模型以及我们自己的经验模型；根据模型准确性以及模型预测不同污泥特性对相应输出（即污染速率或污泥过滤性能）影响的能力，选择了最佳替代方案。结果表明，所选过滤模型能够令人满意地预测污染速率和污泥过滤性能。最佳集成模型已成功应用于模拟环境，以比较三种反馈控制工具和两种前馈控制工具，用于控制向AnMBR投加通量增强剂。建模结果表明，最合适的控制工具是一种反馈污泥过滤性能控制器，它持续投加通量增强剂，称为∆R20_10。与其他控制工具相比，当AnMBR受到特定干扰时，应用∆R20_10控制器可使污泥过滤性能更稳定，污染速率更稳定。本研究开发的模拟环境被证明是测试向AnMBR投加通量增强剂策略的有用工具。
