Discovery of ultra-high strength aluminum alloys with high damage tolerance via interpretable chain-based machine learning

Discovery of ultra-high strength aluminum alloys with high damage tolerance via interpretable chain-based machine learning

This study proposes an interpretable chain-based machine learning (ICML) strategy for designing ultra-high strength aluminum alloys with high damage tolerance. Firstly, by integrating a gradient boosting regression model linking alloy composition (AC) and solution-aging processes (SAP) to tensile me...

Full description

Saved in:
Bibliographic Details
Main Authors: Lei Jiang, Xinbiao Zhang, Wentao Zhoutai, Zhilin Han, Minghong Mao, Wenli Xue, Jianxin Xie
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Materials & Design
Subjects:
Machine learning
Symbolic regression
Tensile mechanical properties
Fatigue strength
Alloy design
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127525007099
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items