Population Balance Modeling and Multi‐Response Optimization of a Swirling‐Flow Nanobubble Generator

• Published in: Chemical engineering & technology Vol. 45; no. 6; pp. 1058 - 1166
• Main Authors: Syaeful Alam, Hilman, Sutikno, Priyono, Soelaiman, Tubagus Ahmad Fauzi, Sugiarto, Anto Tri
• Format: Journal Article
• Language: English
• Published: Frankfurt Wiley Subscription Services, Inc 01.06.2022
• Subjects: Adequacy; Computational fluid dynamics; Mass transfer; Mathematical models; Nanobubbles; Optimization; Population balance method; Population balance models; Response surface method; Response surface methodology; Size distribution; Swirling; Variance analysis
• ISSN: 0930-7516; 1521-4125
• DOI: 10.1002/ceat.202100360

A novel model is proposed to optimize a swirling‐flow nanobubble generator utilizing a combined model of computational fluid dynamics‐population balance method (CFD‐PBM) coupled model and response surface method (RSM). The CFD‐PBM coupled model was validated by experiments based on the bubble size distribution and mass transfer. The validated model was utilized as an input for optimization using RSM. Optimization involved three factors and four target responses obtained by applying a central composite design (CCD). The adequacy of the models was evaluated by analysis of variance. Based on the optimization results, the proposed model can produce an optimized and feasible solution as a reference in the design of a nanobubble generator and can be applied further on a larger scale. For optimization of a swirling‐flow nanobubble generator, a novel model is proposed using a combination of computational fluid dynamics‐population balance method coupled model and response surface methodology. This model can help producing optimized and feasible solutions as a reference in designing a nanobubble generator. Thus, it can minimize development costs by involving virtual prototypes.