Machine learning methods for predicting the outcome of hypervelocity impact events
Authors:
- Shannon RyanSRShannon Ryan
- Stephen ThalerSTStephen Thaler
- Sevvandi KandanaarachchiSKSevvandi Kandanaarachchi
- 1 March 2016
- journal article
- Published by Elsevier in Expert Systems with Applications
- Vol. 45, 23-39
Abstract
No abstract availableThis publication has 13 references indexed in Scilit:
- Determination of penetration depth at high velocity impact using finite element method and artificial neural network toolsDefence Technology, 2015
- Analytic Ballistic Performance Model of Whipple ShieldsProcedia Engineering, 2015
- A ballistic limit analysis programme for shielding against micrometeoroids and orbital debrisActa Astronautica, 2011
- Whipple shield performance in the shatter regimeInternational Journal of Impact Engineering, 2011
- Performance of Whipple shields at impact velocities above 9km/sInternational Journal of Impact Engineering, 2011
- Modified Cour-Palais/Christiansen damage equations for double-wall structuresInternational Journal of Impact Engineering, 2006
- Fragmentation-Initiation Threshold for Spheres Impacting at HypervelocityInternational Journal of Impact Engineering, 2003
- Whipple shields characterized by a nondimensional geometry parameterJournal of Spacecraft and Rockets, 1995
- Design and performance equations for advanced meteoroid and debris shieldsInternational Journal of Impact Engineering, 1993
- Material Phase Transformation Effects upon Performance of Spaced Bumper SystemsJournal of Spacecraft and Rockets, 1972