A physics-informed machine learning method for predicting grain structure characteristics in directed energy deposition

Machine-learning assisted laser powder bed fusion process optimization for AlSi10Mg: New microstructure description indices and fracture mechanisms

(2020) Qian Liu et al.   ACTA MATERIALIA

Investigation on evolution mechanisms of site-specific grain structures during metal additive manufacturing

(2018) P.W. Liu et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

Modeling of thermal behavior and mass transport in multi-layer laser additive manufacturing of Ni-based alloy on cast iron

(2017) Zhengtao Gan et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Laser powder-bed fusion additive manufacturing: Physics of complex melt flow and formation mechanisms of pores, spatter, and denudation zones

(2016) Saad A. Khairallah et al.   ACTA MATERIALIA

Influence of metal powder characteristics on product quality with directed energy deposition of Inconel 625

(2016) Yasuhiro Kakinuma et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Anisotropic tensile behavior of Ti–6Al–4V components fabricated with directed energy deposition additive manufacturing

(2015) Beth E. Carroll et al.   ACTA MATERIALIA

Microstructural and texture development in direct laser fabricated IN718

(2014) Lakshmi L. Parimi et al.   MATERIALS CHARACTERIZATION

60 Years of Hall-Petch: Past to Present Nano-Scale Connections

(2013) Ronald W. Armstrong   MATERIALS TRANSACTIONS

Using a neural network for predicting the average grain size in friction stir welding processes

(2009) Livan Fratini et al.   COMPUTERS & STRUCTURES