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[HTML][HTML] Optimization of flow behavior models by genetic algorithm: a case study of aluminum alloy
Prediction of the flow stress of materials using a flow constitutive model provides strong
support for engineering practice and promotes the continuous development of aluminum …
support for engineering practice and promotes the continuous development of aluminum …
[HTML][HTML] Enhancing flow stress predictions in CoCrFeNiV high entropy alloy with conventional and machine learning techniques
A machine learning technique leveraging artificial intelligence (AI) has emerged as a
promising tool for expediting the exploration and design of novel high entropy alloys (HEAs) …
promising tool for expediting the exploration and design of novel high entropy alloys (HEAs) …
Leveraging machine learning to minimize experimental trials and predict hot deformation behaviour in dual phase high entropy alloys
In recent time, high entropy alloys (HEAs) are widely used due to their wide design space
and remarkable properties allowing a vast range of property variations with myriads of …
and remarkable properties allowing a vast range of property variations with myriads of …
Predicting the effect of Ta on the mechanical behaviour and experimental validation of novel six component Fe-Co-Ni-Cr-V-Ta eutectic high entropy alloys
Eutectic high entropy alloys (EHEAs) with six components (Fe, Co, Ni, Cr, V and Ta) have
been designed and developed via vacuum arc melting route, following the guidance of the …
been designed and developed via vacuum arc melting route, following the guidance of the …
[HTML][HTML] Data-driven design of high bulk modulus high entropy alloys using machine learning
In the current research, machine learning (ML) models were used as a tool for predicting the
bulk modulus of High Entropy Alloys (HEAs). ML was employed to optimize HEA …
bulk modulus of High Entropy Alloys (HEAs). ML was employed to optimize HEA …
A Comprehensive Review on Hot Deformation Behavior of High-Entropy Alloys for High Temperature Applications
In contrast to conventional alloys, multicomponent high-entropy alloys (HEAs) have
emerged as promising candidates in the field of advanced materials because of their unique …
emerged as promising candidates in the field of advanced materials because of their unique …
[HTML][HTML] Machine learning-driven insights into phase prediction for high entropy alloys
The unique properties of high-entropy alloys (HEAs) have attracted considerable attention,
largely due to their dependence on the choice among three distinct phases: solid solution …
largely due to their dependence on the choice among three distinct phases: solid solution …
Harnessing machine learning for predictive modelling of high entropy alloy phases
The application of classification-based machine-learning techniques offers a faster
approach to designing high entropy alloys (HEAs). In this study, we have established a …
approach to designing high entropy alloys (HEAs). In this study, we have established a …
Machine learning approaches for predicting and validating mechanical properties of Mg rare earth alloys for light weight applications
In this work, we have attempted to predict the mechanical behaviour of light weight Mg
based rare earth alloys fabricated through different mechanical and thermal processes. Our …
based rare earth alloys fabricated through different mechanical and thermal processes. Our …