A review of the application of machine learning and data mining approaches in continuum materials mechanics
Machine learning tools represent key enablers for empowering material scientists and
engineers to accelerate the development of novel materials, processes and techniques. One …
engineers to accelerate the development of novel materials, processes and techniques. One …
Perspective: Materials informatics and big data: Realization of the “fourth paradigm” of science in materials science
A Agrawal, A Choudhary - Apl Materials, 2016 - pubs.aip.org
Our ability to collect “big data” has greatly surpassed our capability to analyze it,
underscoring the emergence of the fourth paradigm of science, which is datadriven …
underscoring the emergence of the fourth paradigm of science, which is datadriven …
Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters
This paper describes the use of data analytics tools for predicting the fatigue strength of
steels. Several physics-based as well as data-driven approaches have been used to arrive …
steels. Several physics-based as well as data-driven approaches have been used to arrive …
Pore-affected fatigue life scattering and prediction of additively manufactured Inconel 718: An investigation based on miniature specimen testing and machine learning …
Fatigue life scattering and prediction of Inconel 718 fabricated by selective laser melting
were investigated using miniature specimen tests combined with statistical method and …
were investigated using miniature specimen tests combined with statistical method and …
On the use of transfer modeling to design new steels with excellent rotating bending fatigue resistance even in the case of very small calibration datasets
X Wei, S van der Zwaag, Z Jia, C Wang, W Xu - Acta Materialia, 2022 - Elsevier
In this research a machine learning model for predicting the rotating bending fatigue
strength and the high-throughput design of fatigue resistant steels is proposed. In this …
strength and the high-throughput design of fatigue resistant steels is proposed. In this …
An online tool for predicting fatigue strength of steel alloys based on ensemble data mining
A Agrawal, A Choudhary - International Journal of Fatigue, 2018 - Elsevier
Fatigue strength is one of the most important mechanical properties of steel. Here we
describe the development and deployment of data-driven ensemble predictive models for …
describe the development and deployment of data-driven ensemble predictive models for …
Prediction of the evolution of the stress field of polycrystals undergoing elastic-plastic deformation with a hybrid neural network model
A Frankel, K Tachida, R Jones - Machine Learning: Science and …, 2020 - iopscience.iop.org
Crystal plasticity theory is often employed to predict the mesoscopic states of polycrystalline
metals, and is well-known to be costly to simulate. Using a neural network with convolutional …
metals, and is well-known to be costly to simulate. Using a neural network with convolutional …
Microstructure optimization with constrained design objectives using machine learning-based feedback-aware data-generation
Microstructure sensitive design has a critical impact on the performance of engineering
materials. The safety and performance requirements of critical components, as well as the …
materials. The safety and performance requirements of critical components, as well as the …
Machine learning algorithms for the prediction of non-metallic inclusions in steel wires for tire reinforcement
M Cuartas, E Ruiz, D Ferreño, J Setién… - Journal of Intelligent …, 2021 - Springer
Non-metallic inclusions are unavoidably produced during steel casting resulting in lower
mechanical strength and other detrimental effects. This study was aimed at developing a …
mechanical strength and other detrimental effects. This study was aimed at developing a …
Context aware machine learning approaches for modeling elastic localization in three-dimensional composite microstructures
The response of a composite material is the result of a complex interplay between the
prevailing mechanics and the heterogenous structure at disparate spatial and temporal …
prevailing mechanics and the heterogenous structure at disparate spatial and temporal …