State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, Shanghai, 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Tongji University, Shanghai, 200092, China.
State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, Shanghai, 200092, China; Shanghai Institute of Pollution Control and Ecological Security, Tongji University, Shanghai, 200092, China.
Water Res. 2020 Sep 1;182:115972. doi: 10.1016/j.watres.2020.115972. Epub 2020 Jun 5.
Vibration membrane filtration has been confirmed as an effective method to improve algae separation from water. However, the fouling evolution process and the antifouling mechanism are not well understood. In this study, a novel hybrid method based on a dynamics model was proposed, a comprehensive evaluation was conducted, and the critical vibration frequency for accurate analysis and prediction of membrane fouling was developed. The dynamics model was studied with an improved collision-attachment model by considering all the concurrent and synergistic effects of the hydrodynamic interactions acting on algae. From the perspective of potential energy, the improved model systematically elucidated the reason why the antifouling performance was enhanced when the vibration frequency varied from 1 Hz to 5 Hz. In addition, the Technique for Order Preference by Similarity to Ideal Solution-grey relational analysis (TOPSIS-GRA) method with combined weights was incorporated for the first time to provide direct comprehensive evaluation evidence to determine the effect of the vibration frequency on membrane fouling. It was found that increasing the vibration frequency could not alleviate membrane fouling caused by extracellular organic matter. Moreover, the concept of a critical vibration frequency was proposed using genetic algorithm optimized back propagation neural network, and the energy consumption was analyzed. This combination could provide an effective means to choose the most appropriate vibration frequency, thereby improving the efficiency of the vibration membrane system in the algae separation process.
振动膜过滤已被证实是一种从水中提高藻类分离的有效方法。然而，其污垢演变过程和抗污染机制还没有被很好地理解。在这项研究中，提出了一种基于动力学模型的新型混合方法，进行了综合评估，并开发了用于准确分析和预测膜污染的临界振动频率。动力学模型通过考虑作用在藻类上的所有水力相互作用的并发和协同效应，研究了一个改进的碰撞附着模型。从势能的角度出发，改进后的模型系统地阐明了振动频率从 1 Hz 增加到 5 Hz 时抗污染性能增强的原因。此外，首次结合权重使用理想解法-灰色关联分析（TOPSIS-GRA）方法进行技术排序偏好，为确定振动频率对膜污染的影响提供了直接的综合评估证据。结果表明，增加振动频率并不能缓解由细胞外有机物引起的膜污染。此外，利用遗传算法优化的反向传播神经网络提出了临界振动频率的概念，并对能耗进行了分析。这种组合可以提供一种有效的方法来选择最合适的振动频率，从而提高藻类分离过程中振动膜系统的效率。
