Estimation of wavy honeycombs’ compression performance via a machine learning algorithm

In this study, the wavy honeycomb's initial peak crushing force (IPCF) and energy absorption (EA) were estimated using decision tree algorithm. First, experimental results, Ls-Dyna models of honeycombs verified. way, stress-strain curves shapes compatible. Secondly, effect parameters was examined. Waves contribute significantly to values. particular, for with same geometric properties, when wavenumber is 3, IPCF specific (SEA) values increase by 121.59% 75.08%, respectively. addition, wave amplitude 0.15mm, SEA 60.89% 71.3%, Afterward, full factorial, a data set various parameter prepared. The (inputs) (outputs) in used train verify algorithm Python. Finally, new introduced into algorithm, estimated. Errors ranged from 0.17% 14.65% between results. These findings show that machine learning suitable honeycombs.