Autonomous water quality management in an electrochemical desalination process

IF 11.4 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Water Research Pub Date : 2025-03-20 DOI:10.1016/j.watres.2025.123521

Zahid Ullah, Nakyeong Yun, Ruggero Rossi, Moon Son

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引用次数: 0

Abstract

This research explores advanced control strategies to enhance water quality in membrane capacitive deionization (MCDI) systems, employing a validated modified Donnan model. Three types of artificial neural network (ANN) controllers were developed and evaluated, namely, ANN-proportional-integral-derivative, ANN-Integral, and Multiple Parallel ANN-Integral (MPAI) Controllers. Among these, the MPAI Controller demonstrated the best performance and was selected for further optimization. It was then compared with an offline reinforcement learning controller using the Conservative Q-Learning (CQL) algorithm. To optimize the CQL Controller, various reward functions were tested, including quadratic penalty, exponential penalty, and a Gaussian reward function, with the Gaussian function ultimately selected for its effectiveness, achieving a reward at approximately one. Both control strategies maintained the effluent concentration at approximately 17 mM, despite variations in inlet concentration and fouling dynamics, with absolute errors under 0.4 mM. Notably, the MPAI Controller showed the highest precision, with an error margin approaching nearly zero compared to the CQL Controller. This study underscores the potential of AI-driven controllers in enhancing the efficiency and reliability of MCDI systems, contributing to advancements in water treatment technologies.

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来源期刊

Water Research 环境科学-工程：环境

CiteScore

20.80

自引率

9.40%

发文量

1307

审稿时长

38 days

期刊介绍： Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.