|
| Aerodynamic Shape Optimization Design of Guided Bullet Based on Surrogate Model |
| Received:July 13, 2023 Revised:October 25, 2023 |
| View Full Text View/Add Comment Download reader |
| DOI：10.7643/issn.1672-9242.2023.12.013 |
| KeyWord:guided bullet surrogate model drag coefficient optimization for design aerodynamic shape CFD |
| Author | Institution |
| ZHANG Meng-yang |
a. Key Laboratory of Transient Physics, b. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing , China |
| CHEN Zhi-hua |
a. Key Laboratory of Transient Physics, b. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing , China |
| ZHENG Chun |
a. Key Laboratory of Transient Physics, b. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing , China |
| HUANG Zhen-gui |
a. Key Laboratory of Transient Physics, b. School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing , China |
|
| Hits: |
| Download times: |
| Abstract: |
| Aiming at the problem that the traditional aerodynamic shape optimization design relies on high-precision simulation and takes a long time, the work aims to propose an aerodynamic shape optimization method based on a surrogate modelin order to effectively improve the efficiency of aerodynamic optimization design. The 12.7 mm guided bullet was taken as the research object. Through the CFD simulation of the guided bullet, the effect of the length of the tail contraction section, the radius of the bullet base, and the radius of the junction of the tail contraction expansion section on the drag coefficient of the guided bullet during flight were analyzed. Based on the surrogate model technology, the surrogate model of aerodynamic shape optimization design of guided bulletwas constructed by experimental design, parametric modeling, CFD technology, and a fourth-order response surface model. The minimum drag coefficient during the flight of the guided bullet was taken as the optimization objective, and the genetic algorithm was used to optimize the shape parameters of the guided bullet. The prediction accuracy of the surrogate model established by the fourth-order polynomial response surface and the Kriging model was compared. Compared with the calculation results of the CFD simulation of the test sample points, the average error of the predicted value of the drag coefficient of the fourth-order response surface surrogate model was 0.386%, which indicated that the fourth-order response surface surrogate model could effectively replace the CFD simulation to predict the drag coefficient of guided projectile under different shape parameters. Compared with the initial shape of the guided bullet, the drag coefficient of the guided bullet is reduced by 14.59%, which effectively reduces the energy loss of the bullet during the flight and shortens the optimization time. This method reduces the design cycle of the guided bullet under the premise of ensuring accuracy and provides a certain reference for related engineering applications and research. |
| Close |
|
|
|