Machine learning for design, phase transformation and mechanical properties of alloys

JF Durodola - Progress in Materials Science, 2022 - Elsevier
Abstract Machine learning is now applied in virtually every sphere of life for data analysis
and interpretation. The main strengths of the method lie in the relative ease of the …

Discovery and prediction capabilities in metal-based nanomaterials: An overview of the application of machine learning techniques and some recent advances

EA Bamidele, AO Ijaola, M Bodunrin, O Ajiteru… - Advanced Engineering …, 2022 - Elsevier
The application of machine learning (ML) techniques to metal-based nanomaterials has
contributed greatly to understanding the interaction of nanoparticles, properties prediction …

[HTML][HTML] Evaluation of tool wear, energy consumption, and surface roughness during turning of inconel 718 using sustainable machining technique

N Khanna, C Agrawal, M Dogra, CI Pruncu - Journal of materials research …, 2020 - Elsevier
Heat resistant alloys such as Inconel 718 present challenges to manufacturing industries
during its machining. Machinability of such alloys can be improved using smart cutting …

Machine learning for material characterization with an application for predicting mechanical properties

A Stoll, P Benner - GAMM‐Mitteilungen, 2021 - Wiley Online Library
Currently, the growth of material data from experiments and simulations is expanding
beyond processable amounts. This makes the development of new data‐driven methods for …

[HTML][HTML] Performances of regression model and artificial neural network in monitoring welding quality based on power signal

D Zhao, Y Wang, D Liang, M Ivanov - Journal of materials research and …, 2020 - Elsevier
In this study, a systematic research was conducted to compare the performances of the
regression model and artificial neural network in predicting the nugget diameter of spot …

[HTML][HTML] Manipulation of mechanical properties of 7xxx aluminum alloy via a hybrid approach of machine learning and key experiments

B Li, Y Du, ZS Zheng, XC Ye, D Fang, XD Si… - Journal of Materials …, 2022 - Elsevier
Considering the complex relationship among mechanical properties of 7xxx aluminum alloy,
it is very crucial to optimize two or more target properties simultaneously in developing new …

Forming and fracture limits of IN718 alloy at elevated temperatures: experimental and theoretical investigation

G Mahalle, A Morchhale, N Kotkunde, AK Gupta… - Journal of Manufacturing …, 2020 - Elsevier
Forming and fracture forming limit diagrams are significant performance indexes for
evaluating the formability of a material. In the present study, experimental and theoretical …

PVD AlTiN coating effects on tool-chip heat partition coefficient and cutting temperature rise in orthogonal cutting Inconel 718

J Zhao, Z Liu, B Wang, J Hu - International Journal of Heat and Mass …, 2020 - Elsevier
Significant cutting temperature rise is induced in dry machining Inconel 718 with high cutting
speed due to its low thermal conductivity and high hot hardness. PVD AlTiN coating can …

[HTML][HTML] Effect of temperature on the plastic flow and strain hardening of direct-quenched ultra-high strength steel S960MC

M Ghafouri, S Afkhami, AP Pokka, V Javaheri… - Thin-Walled …, 2024 - Elsevier
This study investigates the plastic deformation and hardening behavior of the direct-
quenched ultra-high strength steel S960MC at various temperatures ranging from room …

[HTML][HTML] Influences of stress-aging on the precipitation behavior of δ phase (Ni3Nb) in a nickel-based superalloy

H Cheng, YC Lin, DG He, YL Qiu, JC Zhu, MS Chen - Materials & Design, 2021 - Elsevier
The precipitation behaviors of δ phases (Ni 3 Nb) in a nickel-based superalloy are
investigated by stress-free and stress aging tests. The effects of aging parameters on the …