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Multi-objective Bayesian optimization of chemical reactor design using computational fluid dynamics
- Source :
- Computers & Chemical Engineering. 119:25-37
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- This study presents a computational fluid dynamics (CFD) based optimal design tool for chemical reactors, in which multi-objective Bayesian optimization (MBO) is utilized to reduce the number of required CFD runs. Detailed methods used to automate the process by connecting CFD with MBO are also proposed. The developed optimizer was applied to minimize the power consumption and maximize the gas holdup in a gas-sparged stirred tank reactor, which has six design variables: the aspect ratio of the tank, the diameter and clearance of each of the two impellers, and the gas sparger. The saturated Pareto front is obtained after 100 iterations. The resulting Pareto front consists of many near-optimal designs with significantly enhanced performances compared to conventional reactors reported in the literature. We anticipate that this design approach can be applied to any process unit design problems that require a large number of CFD simulation runs.
- Subjects :
- Optimal design
business.industry
Computer science
General Chemical Engineering
Bayesian optimization
Continuous stirred-tank reactor
02 engineering and technology
Chemical reactor
Computational fluid dynamics
021001 nanoscience & nanotechnology
Multi-objective optimization
Computer Science Applications
Impeller
020401 chemical engineering
0204 chemical engineering
0210 nano-technology
business
Process engineering
Sparging
Subjects
Details
- ISSN :
- 00981354
- Volume :
- 119
- Database :
- OpenAIRE
- Journal :
- Computers & Chemical Engineering
- Accession number :
- edsair.doi...........da74826ad32375c8ab0bbf1bf69def58