@inproceedings{262bba322ffb45b3b10420d99a664753,
title = "Monte Carlo-based simulation study on the firing performance of mortar projectiles trigger mechanism",
abstract = "The mortar projectiles often land on the back of the hillside when fighting in mountainous areas. The projectile hits the target with a small landing angle, and there will be a phenomenon of rubbing the ground, resulting in a low hit rate. In this paper, a multi-rigid-body dynamics virtual prototype model is established for different targets struck by a different falling angle of the mortar projectile, the displacement and velocity data of the firing-pin and detonator as well as the incomplete firing results are obtained through simulation, the firing probability is evaluated by applying the Monte Carlo method, the contribution of the variables affecting the target value is obtained by applying the design of experiment(DOE), and the relevant parameters are optimized to realize fully fire when the parameters are in their new value range.",
keywords = "Monte Carlo, firing probability, mortar projectiles, performance optimization",
author = "Mengjie Shi and Rongchang Song and Haibin Cui and Hongshe Li and Guanglin He and Yanan Du",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; 2022 International Symposium on Robotics, Artificial Intelligence, and Information Engineering, RAIIE 2022 ; Conference date: 15-07-2022 Through 17-07-2022",
year = "2022",
doi = "10.1117/12.2658704",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Johan Debayle",
booktitle = "International Symposium on Robotics, Artificial Intelligence, and Information Engineering, RAIIE 2022",
address = "United States",
}
