Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design

A Sharma, T Mukhopadhyay, SM Rangappa… - … Methods in Engineering, 2022‏ - Springer
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …

Data-driven modeling of process, structure and property in additive manufacturing: A review and future directions

Z Wang, W Yang, Q Liu, Y Zhao, P Liu, D Wu… - Journal of Manufacturing …, 2022‏ - Elsevier
A thorough understanding of complex process-structure-property (PSP) relationships in
additive manufacturing (AM) has long been pursued due to its paramount importance in …

[HTML][HTML] Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems

CE Okafor, S Iweriolor, OI Ani, S Ahmad, S Mehfuz… - Hybrid Advances, 2023‏ - Elsevier
Reinforced composite is a preferred choice of material for the design of industrial lightweight
structures. As of late, composite materials analysis and development utilizing machine …

A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management

Y Zhang, M Safdar, J **e, J Li, M Sage… - Journal of Intelligent …, 2023‏ - Springer
Additive manufacturing (AM) techniques are maturing and penetrating every aspect of the
industry. With more and more design, process, structure, and property data collected …

Effect of infill density, build direction and heat treatment on the tensile mechanical properties of 3D-printed carbon-fiber nylon composites

Z Ali, Y Yan, H Mei, L Cheng, L Zhang - Composite Structures, 2023‏ - Elsevier
This work investigates the effect of infill density with various fill patterns and build direction
with composite type on the tensile mechanical properties of carbon fiber reinforced 3D …

[HTML][HTML] Predicting stress–strain curves using transfer learning: Knowledge transfer across polymer composites

Z Zhang, Q Liu, D Wu - Materials & Design, 2022‏ - Elsevier
The engineering stress–strain curve of a material allows one to determine mechanical
properties such as elastic modulus, strength, and toughness. While machine learning has …

Development of ensemble machine learning approaches for designing fiber-reinforced polymer composite strain prediction model

A Milad, SH Hussein, AR Khekan, M Rashid… - Engineering with …, 2022‏ - Springer
Over the past few decades, it has been observed a remarkable progression in the
development of computer aid models in the field of civil engineering. Machine learning …

The use of machine learning in process–structure–property modeling for material extrusion additive manufacturing: a state-of-the-art review

Z Abdelhamid, H Mohamed, S Kelouwani - Journal of the Brazilian Society …, 2024‏ - Springer
Since its first appearance in the 1980s, additive manufacturing has become increasingly
popular. Complex parts can be produced with high quality, minimal waste, and a variety of …

Effect of build orientation and raster pattern on the fracture behavior of carbon fiber reinforced polymer composites fabricated by additive manufacturing

Z Zhang, D Yavas, Q Liu, D Wu - Additive Manufacturing, 2021‏ - Elsevier
Additive manufacturing (AM) process parameters highly affect the mechanical and fracture
properties of additively manufactured carbon fiber reinforced polymer (CFRP) composites. In …

[HTML][HTML] Investigation of 3D printed lightweight hybrid composites via theoretical modeling and machine learning

S Ferdousi, R Advincula, AP Sokolov, W Choi… - Composites Part B …, 2023‏ - Elsevier
Hybrid composites combine two or more different fillers to achieve multifunctional or
advanced material properties, such as lightweight and enhanced mechanical properties …