Data-driven prediction of the high-dimensional thermal history in directed energy deposition processes via recurrent neural networks-Reference-Cited by-同舟云学术

Data-driven prediction of the high-dimensional thermal history in directed energy deposition processes via recurrent neural networks

Published:2018-10 Issue: Volume:18 Page:35-39
ISSN:2213-8463
Container-title:Manufacturing Letters
language:en
Short-container-title:Manufacturing Letters

Author:

Mozaffar Mojtaba,Paul Arindam,Al-Bahrani Reda^ORCID,Wolff Sarah,Choudhary Alok,Agrawal Ankit,Ehmann Kornel,Cao Jian

Funder

National Institute of Standards and Technology

National Science Foundation

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Mechanics of Materials

Reference26 articles.

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3. Effect of processing parameters on microstructure and tensile properties of austenitic stainless steel 304L made by directed energy deposition additive manufacturing;Wang;Acta Mater,2016

4. Toward determining melt pool quality metrics via coaxial monitoring in laser powder bed fusion;Fisher;Manuf Lett,2018

5. Effect of process parameters on tribological performance of 316L stainless steel parts fabricated by selective laser melting;Li;Manuf Lett,2018

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