@inproceedings{a77931d3b340480e85ca83ee0f77c8b5,
title = "Optimization of small caliber projectile based on neural network",
abstract = "When small caliber projectile is moving at high speed underwater, the water around the projectile will cavitate. The geometric shape of the warhead with the best drag coefficient corresponds to the supercavitating state where the projectile is completely enveloped by cavitation. In this paper, aiming at a small-caliber projectile, the three-section cone is selected as the basic projectile, and the shape of the projectile is optimized with the drag coefficient as the optimization objective. The neural network and sequential quadratic programming (SQP) algorithm are combined to reduce the calculation amount in the optimization process and improve the optimization efficiency. The drag coefficient of the optimized projectile is reduced by about 40\% compared with the projectile before optimization, and it can form a supercavitation that envelops the entire projectile.",
keywords = "dragcoefficient, neural network, projectile optimization, sqp algorithm",
author = "Wenxuan Ma and Yong Yu and Jun Hu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2021 ; Conference date: 18-06-2021 Through 20-06-2021",
year = "2021",
month = jun,
day = "18",
doi = "10.1109/IMCEC51613.2021.9482069",
language = "English",
series = "IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2060--2064",
editor = "Bing Xu",
booktitle = "IMCEC 2021 - IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference",
address = "United States",
}