Machine learning-based forward and inverse designs for prediction and optimization of fracture toughness of aluminum alloy-Reference-Cited by-同舟云学术

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Machine learning-based forward and inverse designs for prediction and optimization of fracture toughness of aluminum alloy

Published:2024-09 Issue: Volume:23 Page:102717
ISSN:2590-1230
Container-title:Results in Engineering
language:en
Short-container-title:Results in Engineering

Author:

Fatriansyah Jaka Fajar^ORCID,Satrio Muhammad Riza Raihan,Federico Andreas,Suhariadi Iping,Dhaneswara Donanta,Gascoin Nicolas

Funder

Direktorat Riset and Pengembangan, Universitas Indonesia

Publisher

Elsevier BV

Reference49 articles.

1. Accelerated discovery of high-strength aluminum alloys by machine learning;Li;Communications Materials,2020

2. Recent developments in joining of aluminum alloys;Çam;Int. J. Adv. Des. Manuf. Technol.,2016

3. A review on grain refinement of aluminum alloys: progresses, challenges and prospects;Guan;Acta Metall. Sin.,2017

4. Prediction of mechanical properties of wrought aluminum alloys using feature engineering assisted machine learning approach;Hu;Metall. Mater. Trans.,2021

5. A review on forming techniques for manufacturing lightweight complex—shaped aluminum panel components;Zheng;International Journal of Lightweight Materials and Manufacture,2018

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