Optimization of ozone generator sizing and performance using response surface modeling and metaheuristic algorithms: a comparative study of HLOA and LCA

• Published in: Journal of the Korean Physical Society Vol. 86; no. 9; pp. 856 - 874
• Main Authors: Khelifi, Elmabrouk, Brahami, Mohammed Nadjib, Bousmaha, Imen Souhila, Brahami, Mostefa, Nemmich, Said, Bechekir, Seyf Eddine, Jbilou, Mokhtaria, Belabed, Meriem
• Format: Journal Article
• Language: English
• Published: Seoul The Korean Physical Society 01.05.2025; Springer Nature B.V; 한국물리학회
• Subjects: Air purification; Algorithms; Business metrics; Chemical oxygen demand; Chemical synthesis; Comparative studies; Design; Dielectric barrier discharge; Electrodes; Energy consumption; Energy efficiency; Heuristic methods; Investigations; Liver cancer; Mathematical and Computational Physics; Modelling; Optimization; Optimization algorithms; Optimization techniques; Ozone; Parameter identification; Particle and Nuclear Physics; Performance measurement; Physics; Physics and Astronomy; Plasma; Plasmas and Phenomenology; Research - Fluids; Response surface methodology; Theoretical; Waste management; Wastewater treatment; Water purification; Water treatment; 물리학; Energy efficiency (EE); Ozone concentration (OC); Horned lizard optimization algorithm (HLOA); Response surface modeling (RSM); Liver cancer algorithm (LCA); Cylindrical ozone generator
• ISSN: 0374-4884; 1976-8524
• DOI: 10.1007/s40042-025-01302-z

This study investigates the optimization of a dielectric barrier discharge (DBD) cylindrical-shaped ozone generator, crucial for air purification and water treatment. The research focuses on the effects of voltage, electrode length, and discharge gap on ozone concentration, ozone generation rate, and energy efficiency, aiming to enhance performance while minimizing energy consumption. Systematic experiments were conducted by varying generator parameters at the APELEC Laboratory, Djillali Liabes University of Sidi-Bel-Abbes, Algeria, yielding a peak ozone concentration of 53.32 mg/L and an energy efficiency of 5.82 g/Wh. To enhance understanding and performance, response surface modeling (RSM) was employed to develop a mathematical model that elucidates the relationships between performance metrics and generator parameters. This model facilitated the identification of optimal parameter combinations to maximize ozone concentration and efficiency. In a novel approach, two advanced metaheuristic algorithms the liver cancer algorithm (LCA) and the horned lizard optimization algorithm (HLOA) were utilized. The HLOA achieved an improved ozone concentration of 57.35 mg/L and an energy efficiency of 5.88 g/Wh, surpassing the LCA’s results of 56.9 mg/L and 5.76 g/Wh. The results provide valuable insights for enhancing ozone generators, demonstrating the effectiveness of combining RSM with metaheuristic approaches. This hybrid method not only clarifies parameter relationships but also establishes a new benchmark for future research in ozone generator optimization.