Damage prediction of rear plate in Whipple shields based on machine learning method

Damage prediction of rear plate in Whipple shields based on machine learning method

A typical Whipple shield consists of double-layered plates with a certain gap. The space debris impacts the outer plate and is broken into a debris cloud (shattered, molten, vaporized) with dispersed energy and momentum, which reduces the risk of penetrating the bulkhead. In the realm of hyperveloci...

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Bibliographic Details
Main Authors: Chenyang Wu, Xiangbiao Liao, Lvtan Chen, Xiaowei Chen
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2025-08-01
Series:Defence Technology
Subjects:
Damage prediction of rear plate
Cumulative effect of debris cloud
Whipple shield
Machine learning
Random forest
Online Access:http://www.sciencedirect.com/science/article/pii/S2214914725001060
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