Recovery of sulphate from industrial wastewater in the form of strontium sulphate and optimisation using hybrid metaheuristic approach: RSM-GA and RSM-PSO DOI
Navamani Kartic Dhayabaran,

M. Arivazhagan

Indian Chemical Engineer, Год журнала: 2024, Номер unknown, С. 1 - 19

Опубликована: Дек. 22, 2024

Large quantities of inorganic salts from process effluent are inevitable and a threat to the environment. Sulphates were major anions (initial concentration = 70 g/L) in pigment industry effluent. Strontium ions could recover sulphate by precipitation as SrSO4, commercially useful precipitate. The stoichiometric ratio precipitant, mixing, temperature optimised response surface methodology (RSM) precipitant had maximum influence (Sensitivity 99.62%). model created RSM showed notable performance (predicted R2 0.9987). Further enhancement optimisation was done coupling with genetic algorithm (GA) particle swarm (PSO). Both them able determine global optima efficiently when their hyper-parameters optimised. In GA, crossover higher than mutation ratio. PSO converged close 20 iterations, exhibiting better exploration exploitation capacity. values (1.35), (30.7°C), mixing speed (230 rpm) validated experimentally, which gave 99.95% utilisation. reaction followed first-order kinetics (R2 0.9908) majorly dependent on concentration. Preliminary cost estimation Aspen that chemical be an employable option for utilising high levels wastewater.

Язык: Английский

Recovery of sulphate from industrial wastewater in the form of strontium sulphate and optimisation using hybrid metaheuristic approach: RSM-GA and RSM-PSO DOI
Navamani Kartic Dhayabaran,

M. Arivazhagan

Indian Chemical Engineer, Год журнала: 2024, Номер unknown, С. 1 - 19

Опубликована: Дек. 22, 2024

Large quantities of inorganic salts from process effluent are inevitable and a threat to the environment. Sulphates were major anions (initial concentration = 70 g/L) in pigment industry effluent. Strontium ions could recover sulphate by precipitation as SrSO4, commercially useful precipitate. The stoichiometric ratio precipitant, mixing, temperature optimised response surface methodology (RSM) precipitant had maximum influence (Sensitivity 99.62%). model created RSM showed notable performance (predicted R2 0.9987). Further enhancement optimisation was done coupling with genetic algorithm (GA) particle swarm (PSO). Both them able determine global optima efficiently when their hyper-parameters optimised. In GA, crossover higher than mutation ratio. PSO converged close 20 iterations, exhibiting better exploration exploitation capacity. values (1.35), (30.7°C), mixing speed (230 rpm) validated experimentally, which gave 99.95% utilisation. reaction followed first-order kinetics (R2 0.9908) majorly dependent on concentration. Preliminary cost estimation Aspen that chemical be an employable option for utilising high levels wastewater.

Язык: Английский

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