Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)

The Rt of Analysis Model under the Adiabatic Shear Mechanism

Authors
Yucai Dong, Jianjun Wang
Corresponding Author
Yucai Dong
Available Online August 2018.
DOI
10.2991/caai-18.2018.56How to use a DOI?
Keywords
A-T model; penetration; adiabatic shear; failure mechanism
Abstract

A-T model of the modified hydrodynamics, is widely used in metal projectile and target materials, good prediction accuracy for penetration depth in penetration process. But the Rt (target defense force) is determined relatively difficult, lack of real physical meaning to widely accepted the Rt of calculation model. Based on the role of the existence of adiabatic shear failure mechanism between projectile and target, the Rt is endowed with real physical meaning, It can be better reflected the failure mechanism of target plate for influence of the thermal effect and strain rate in penetration. Theoretical model calculation is carried out under the Rt of new mechanism, The results are in good agreement with the experimental and simulation results.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
August 2018
ISBN
10.2991/caai-18.2018.56
ISSN
2589-4919
DOI
10.2991/caai-18.2018.56How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yucai Dong
AU  - Jianjun Wang
PY  - 2018/08
DA  - 2018/08
TI  - The Rt of Analysis Model under the Adiabatic Shear Mechanism
BT  - Proceedings of the 2018 3rd International Conference on Control, Automation and Artificial Intelligence (CAAI 2018)
PB  - Atlantis Press
SP  - 238
EP  - 241
SN  - 2589-4919
UR  - https://doi.org/10.2991/caai-18.2018.56
DO  - 10.2991/caai-18.2018.56
ID  - Dong2018/08
ER  -