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At present, the research on supersonic civil aircraft wings mainly focuses on the low sonic boom design and supersonic drag reduction technologies. There are relatively few studies on the wing structural design. Therefore, a multi-level optimization method for the wing structural design in the preliminary design stage of supersonic civil aircrafts was proposed. It included the parametric modeling of the wing structural layout, the automatic generation of the finite element model for the structural size optimization, construction and training of a surrogate model for the deep neural network. And the optimization was solved based on the deep neural network. The analysis results show that the proposed optimization strategy could quickly design the wing structure of the supersonic civil aircraft. The deep neural network model has higher prediction accuracy than the traditional surrogate model. Thus, the proposed approach can improve the efficiency of the preliminary design for wing structure.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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