Liquid Metal Embrittlement of Advanced High Strength Steel: Experiments and Damage Modeling

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{prabitz:2021:Materials,

• author = "Konstantin Manuel Prabitz and Mohammad Zhian Asadzadeh and Marlies Pichler and Thomas Antretter and Coline Beal and Holger Schubert and Benjamin Hilpert and Martin Gruber and Robert Sierlinger and Werner Ecker",
• title = "Liquid Metal Embrittlement of Advanced High Strength Steel: Experiments and Damage Modeling",
• journal = "Materials",
• year = "2021",
• volume = "14",
• number = "18",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "1996-1944",
• URL = "https://www.mdpi.com/1996-1944/14/18/5451",
• DOI = "doi:10.3390/ma14185451",
• abstract = "In the automotive industry, corrosion protected galvanized advanced high strength steels with high ductility (AHSS-HD) gain importance due to their good formability and their lightweight potential. Unfortunately, under specific thermomechanical loading conditions such as during resistance spot welding galvanized, AHSS-HD sheets tend to show liquid metal embrittlement (LME). LME is an intergranular decohesion phenomenon leading to a drastic loss of ductility of up to 95percent. The occurrence of LME for a given galvanized material mainly depends on thermal and mechanical loading. These influences are investigated for a dual phase steel with an ultimate tensile strength of 1200 MPa, a fracture strain of 14percent and high ductility (DP1200HD) by means of systematic isothermal hot tensile testing on a Gleeble(R) 3800 thermomechanical simulator. Based on the experimental findings, a machine learning procedure using symbolic regression is applied to calibrate an LME damage model that accounts for the governing quantities of temperature, plastic strain and strain rate. The finite element (FE) implementation of the damage model is validated based on the local damage distribution in the hot tensile tested samples and in an exemplary 2-sheet resistance spot weld. The developed LME damage model predicts the local position and the local intensity of liquid metal induced cracking in both cases very well.",
• notes = "also known as \cite{ma14185451}",

}

Genetic Programming entries for Konstantin Manuel Prabitz Mohammad Zhian Asadzadeh Marlies Pichler Thomas Antretter Coline Beal Holger Schubert Benjamin Hilpert Martin Gruber Robert Sierlinger Werner Ecker

Citations