期刊
RENEWABLE ENERGY
卷 145, 期 -, 页码 1597-1607出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2019.07.074
关键词
Biomass combustion; Computational fluid dynamics; Reduced design cycle time; Advanced burner design; Design optimization
资金
- Wayne and Gayle Laufer Foundation
- Elevated Analytics
Design: of engineered combustion equipment normally involves laborious build and try designs to identify the best possible configuration. The number of design iterations can be reduced with engineering experience of what might work. The expensive cut-and-try approach can be improved using computational aided engineering tools coupled with optimization techniques to find the optimal design. For example, the best air duct configuration with the lowest pressure loss and smallest fan size for an air-fed biomass gasifier may take several weeks using the standard computational fluid dynamics (CFD) cut and try approach. Alternatively, coupling an efficient design optimization algorithm with an existing CFD model can reduce the time to find the best design by more than 50% and can allow the engineer to examine more design options than possible using the cut-and-try approach. Combining an efficient optimization algorithm with an existing CFD model of a biomass gasifier to find the optimal design is the focus of this work. Shape optimization has been performed by combining the optimization tool Sculptor (R) with the commercial CFD code STARCCMthorn. This work illustrates how the linked approach is used to examine design factors to optimize an entrained flow biomass gasifier to improve overall system performance in a methodical comprehensive fashion. (c) 2019 Elsevier Ltd. All rights reserved.
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