Surrogate drag model of non-spherical fragments based on artificial neural networks

The hazard evaluation of the fragments produced from an explosion requires an accurate prediction of the motion of fragments subjected to gravity and aerodynamic forces. The drag coefficient (Cd) is among the most crucial components of various aerodynamic models. Limited experiments cannot reproduce...

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Veröffentlicht in:	Powder technology 2022-05, Vol.404, p.117412, Article 117412
Hauptverfasser:	Xin, Dajun, Zeng, Junsheng, Xue, Kun
Format:	Artikel
Sprache:	eng
Schlagworte:	Aerodynamic forces Artificial neural networks Ballistics Drag coefficient Drag coefficients Fragments Hazard assessment Icosahedrons Impact analysis Mach number Machine learning Neural networks Non-spherical fragment Terminal ballistics
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