Multi-objective Bayesian optimization of chemical reactor design using computational fluid dynamics

Title
Multi-objective Bayesian optimization of chemical reactor design using computational fluid dynamics
Authors
나종걸김민준이종민박성언
Issue Date
2018-11
Publisher
Computers & chemical engineering
Citation
VOL 119-37
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.
URI
http://pubs.kist.re.kr/handle/201004/68183
ISSN
0098-1354
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KIST Publication > Article
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