Fuzzy optimization for the removal of uranium from mine water using batch electrocoagulation: A case study

This research presents a case study on the remediation of a radioactive waste (uranium: U) utilizing a multi-objective fuzzy optimization in an electrocoagulation process for the iron-stainless steel and aluminum-stainless steel anode/cathode systems. The incorporation of the cumulative uncertainty of result, operational cost and energy consumption are essential key elements in determining the feasibility of the developed model equations in satisfying specific maximum contaminant level (MCL) required by stringent environmental regulations worldwide. Pareto-optimal solutions showed that the iron system (0 mg/L U: 492 USD/g-U) outperformed the aluminum system (96 mu g/L U: 747 USD/g-U) in terms of the retained uranium concentration and energy consumption. Thus, the iron system was further carried out in a multi-objective analysis due to its feasibility in satisfying various uranium standard regulatory limits. Based on the 30 mu g/L MCL, the decision-making process via fuzzy logic showed an overall satisfaction of 6.1% at a treatment time and current density of 101.6 min and 59.9 mA/cm(2), respectively. The fuzzy optimal solution reveals the following: uranium concentration - 5 mu g/L, cumulative uncertainty - 25 mu g/L, energy consumption - 461.7 kWh/g-U and operational cost based on electricity cost in the United States - 60.0 USD/g-U, South Korea - 55.4 USD/g-U and Finland - 78.5 USD/g-U. (C) 2020 Korean Nuclear Society, Published by Elsevier Korea LLC.