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A novel model for electrocoagulation reactors: process-based approach to address the design and scale-up issues

Dissanayaka Mudiyanselage, C (2022) A novel model for electrocoagulation reactors: process-based approach to address the design and scale-up issues. Doctoral thesis, Liverpool John Moores University.

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Abstract

The wider application of electrocoagulation (EC) as a water and industrial wastewater treatment technology has been hindered due to knowledge gaps in the design and operational optimization process. The conventional EC reactor design follows a black-box design approach, while white-box modelling is widely applied in other water treatment systems. This is due to the complex nature of the electrochemical effect on the pollutant abatement process. Hence, this study aimed to address this knowledge gap by developing a novel numeric computing platform model for defluoridation established on pollutant abatement mechanisms to address the design and modelling issues such as scale-up and process optimisation of EC reactors. Dissolved fluoride was selected as the pollutant, considering the vast body of knowledge available on defluoridation using electrocoagulation. A critical evaluation of the scientific and mechanistic approaches developed over the years for EC was carried out to develop a process-based conceptual model (PBCM) for batch and continuous EC reactors for defluoridation. Here, the EC process was conceptualized as a conventional water treatment process. This engineering approach of identification of the pollutant abatement and floc aggregation mechanisms resulted in the discretisation of the defluoridation process in EC reactors. Next, the model equations were numerically transformed into a scheme of integrated continuous-time models by applying the principle of conservation of mass to the system. Finally, the PBCM was implemented in two computer platforms namely, Microsoft® Excel® ver. 2016 and MATLAB® ver. R2021a which were then validated using primary and secondary data. Ten physical and chemical calibration parameters were identified from the process-based models from which the integrated effects were evaluated at the model calibration stage. Primary data for the model calibration and validation were collected through experiments that were conducted at the laboratory level for both batch and continuous reactors at two geometric scales. The extrapolation of the PBCM for batch and continuous EC for varied operating conditions, pollutant types and scales were evaluated. Also, the optimization of retention time and the relationship of hydrodynamic parameters (pressure, flow velocity) and reactor geometry were analysed using the novel model. Evaluation of model prediction accuracy was conducted using Mean Squared Error (MSE), Root Mean Square Error (RMSE). It could be noted that there is a good agreement between the experimental fluoride concentrations and model simulations of fluoride concentrations where R2 is 0.994, thus proving the higher precision of the model predictions. The optimization process consisted of a local sensitivity test which was carried out in MATLAB® ver. R2021a using a programme written to analyse each calibration parameter range within the selected domain. The dj; colloid size which participates in the adsorption and flocculation process was found to be the most sensitive parameter for the PBCM. The extended use of the model could be well evaluated using both calibration and experimental parameters in terms of application to scale-up/down, longer operation time, different pollutants, etc. A novel numeric computing platform model for EC to simultaneously address the prediction of pollution removal, settling/flotation, scale-up and techno-economic optimization was established from this study, thus aiding wider applicability of EC reactors.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: Electrocoagulation; process-based conceptual model; pollutant abatement; water treatment modelling; defluoridation
Subjects: T Technology > TD Environmental technology. Sanitary engineering
Divisions: Civil Engineering & Built Environment
Date Deposited: 20 Apr 2022 07:06
Last Modified: 20 Apr 2022 07:07
DOI or Identification number: 10.24377/LJMU.t.00016548
Supervisors: Carnacina, I, Harris, C and Hashim, K
URI: https://researchonline.ljmu.ac.uk/id/eprint/16548

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