Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1563124 | Computational Materials Science | 2009 | 7 Pages |
Abstract
Failure behavior of Zn coated Fe is simulated through molecular dynamics (MD) and the energy absorbed at the onset of failure along with the corresponding strain of the Zn lattice are computed for different levels of applied shear rate, temperature and thickness. Data-driven models are constructed by feeding the MD results to an evolutionary neural network. The outputs of these neural networks are utilized to carry out a multi-objective optimization through genetic algorithms, where the best possible tradeoffs between two conflicting requirements, minimum deformation and maximum energy absorption at the onset of failure, are determined by constructing a Pareto frontier.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Baidurya Bhattacharya, G.R. Dinesh Kumar, Akash Agarwal, Şakir Erkoç, Arunima Singh, Nirupam Chakraborti,