Aircraft Air Inlet Design Optimization via Surrogate-Assisted Evolutionary Computation

被引：6
|
作者：
Lombardil, Andre [1 ]
Ferrari, Denise [2 ]
Santos, Luis [3 ]
机构：
[1] Embraer, Sao Paulo, SP, Brazil
[2] Inst Tecnol Aeronaut, Sao Paulo, SP, Brazil
[3] Univ Sao Paulo, Sao Paulo, SP, Brazil
来源：
EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PT II | 2015年 / 9019卷
关键词：
Design optimization; Genetic algorithm; Surrogate modeling; Air inlet; CFD; Aerodynamics;
D O I：
10.1007/978-3-319-15892-1_21
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In aviation, the performance impact of auxiliary air inlets used for system ventilation is significant. The flow phenomena and consequently the numerical model, is highly non-linear, leading to a compromise between pressure recovery and drag for a given mass flow condition. This work follows a step-by-step approach which highlights the important issues related to solving such complex optimization problem, using surrogate methods coupled to evolutionary algorithms. Its conclusions can be used as a guideline to similar industrial applications.
引用
收藏
页码：313 / 327
页数：15
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