Additive manufacturing of nickel-based superalloys: A state-of-the-art review on process-structure-defect-property relationship

A Mostafaei, R Ghiaasiaan, IT Ho, S Strayer… - Progress in Materials …, 2023 - Elsevier
Fusion-based additive manufacturing (AM) has significantly grown to fabricate Nickel-based
superalloys with design freedom across multiple length scales. Several phenomena such as …

Review on field assisted metal additive manufacturing

C Tan, R Li, J Su, D Du, Y Du, B Attard, Y Chew… - International Journal of …, 2023 - Elsevier
Additive manufacturing (AM) offers unprecedented design freedom and manufacturing
flexibility for processing complex components. Despite the numerous advantages of AM over …

Role of porosity defects in metal 3D printing: Formation mechanisms, impacts on properties and mitigation strategies

S Wang, J Ning, L Zhu, Z Yang, W Yan, Y Dun, P Xue… - Materials Today, 2022 - Elsevier
Abstract Metal 3D printing (3DP), a state-of-the-art manufacturing technology that brings the
potential to fabricate complex structures at low cost and reduced energy consumption, has …

Control of grain structure, phases, and defects in additive manufacturing of high-performance metallic components

T Mukherjee, JW Elmer, HL Wei, TJ Lienert… - Progress in Materials …, 2023 - Elsevier
The properties and serviceability of 3D-printed metal parts depend on a variety of attributes.
These include the chemical composition, phases, morphology, spatial distributions of grain …

Towards the next generation of machine learning models in additive manufacturing: A review of process dependent material evolution

M Parsazadeh, S Sharma, N Dahotre - Progress in Materials Science, 2023 - Elsevier
Additive manufacturing facilitates producing of complex parts due to its design freedom in a
wide range of applications. Despite considerable advancements in additive manufacturing …

Machine learning model towards evaluating data gathering methods in manufacturing and mechanical engineering

M Amini, K Sharifani, A Rahmani - International Journal of Applied …, 2023 - papers.ssrn.com
Abstract Supervised Machine Learning (ML) models require extensive training data to
properly approximate the behavior of complex mechanical processes and systems. Real …

A state-of-the-art review on machine learning-based multiscale modeling, simulation, homogenization and design of materials

D Bishara, Y **e, WK Liu, S Li - Archives of computational methods in …, 2023 - Springer
Multiscale simulation and homogenization of materials have become the major
computational technology as well as engineering tools in material modeling and material …

Machine learning process evaluating damage classification of composites

M Amini, A Rahmani - International Journal of Science and …, 2023 - papers.ssrn.com
Composite materials have tremendous and ever-increasing applications in complex
engineering systems; thus, it is important to develop non-destructive and efficient condition …

[HTML][HTML] Holistic computational design within additive manufacturing through topology optimization combined with multiphysics multi-scale materials and process …

M Bayat, O Zinovieva, F Ferrari, C Ayas… - Progress in Materials …, 2023 - Elsevier
Additive manufacturing (AM) processes have proven to be a perfect match for topology
optimization (TO), as they are able to realize sophisticated geometries in a unique layer-by …

Alloy design for laser powder bed fusion additive manufacturing: a critical review

Z Liu, Q Zhou, X Liang, X Wang, G Li… - … Journal of Extreme …, 2024 - iopscience.iop.org
Metal additive manufacturing (AM) has been extensively studied in recent decades. Despite
the significant progress achieved in manufacturing complex shapes and structures …