TAExplorer: visualizing key factors in titanium alloy performance

HE Yilei; NING Zhen; WU Die; ZHANG Yu; DUAN Qingchao; PU Jiansu; ZHU Yanlin

doi:10.7513/j.issn.1004-7638.2025.05.013

Volume 46 Issue 5

Oct. 2025

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HE Yilei, NING Zhen, WU Die, ZHANG Yu, DUAN Qingchao, PU Jiansu, ZHU Yanlin. TAExplorer: visualizing key factors in titanium alloy performance[J]. IRON STEEL VANADIUM TITANIUM, 2025, 46(5): 123-132. doi: 10.7513/j.issn.1004-7638.2025.05.013

Citation:

HE Yilei, NING Zhen, WU Die, ZHANG Yu, DUAN Qingchao, PU Jiansu, ZHU Yanlin. TAExplorer: visualizing key factors in titanium alloy performance[J]. IRON STEEL VANADIUM TITANIUM, 2025, 46(5): 123-132. doi: 10.7513/j.issn.1004-7638.2025.05.013

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TAExplorer: visualizing key factors in titanium alloy performance

doi: 10.7513/j.issn.1004-7638.2025.05.013

HE Yilei^1
,,
NING Zhen^{2, 3, 4},
WU Die^{2, 3, 4},
ZHANG Yu¹,
DUAN Qingchao¹,
PU Jiansu¹,
ZHU Yanlin^{2, 3, 4
,
,}

1.
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2.
Chengdu Advanced Metal Materials Industry Technology Research Institute Co., Ltd., Chengdu 610300, Sichuan, China
3.
State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization,Panzhihua 617000, Sichuan, China
4.
Pangang Group Research Institute Co., Ltd., Chengdu 610031, Sichuan, China

More Information

Received Date: 2025-03-20
Accepted Date: 2025-07-30
Rev Recd Date: 2025-07-30
Publish Date: 2025-10-30

Abstract

Abstract

Titanium alloys have the characteristics of high strength, excellent corrosion resistance and heat resistance, so they are widely used in aerospace, chemical and medical fields. Since the properties of titanium alloys depend on their structural characteristics and the requirements for titanium alloy properties vary from application to application, researchers have been working on designing and obtaining new materials with the targeted properties through experimental trial-and-error methods, as well as searching for process factors affecting the properties of titanium alloys. However, the production process of titanium alloy is complex, time-consuming, and it is very difficult to find the appropriate material by traditional methods. Machine learning based methods have currently being introduced and used for material prediction, but there are few learning tools designed for researchers that are capable of intuitively comparing and analyzing the performance of machine learning models. Herein, we propose TAExplorer, an interactive visualization and analysis system based on titanium alloys that can provide experts with multifaceted references. Our system employs a multifaceted visualization scheme that aims to analyze from various perspectives, such as feature distribution, data similarity, model performance, and result presentation. Experts have conducted case studies through practical laboratory experiments, and the final results confirm the effectiveness and practicality of our system.
- titanium alloy,
- materials data,
- data visualization,
- machine learning

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References(31)

References

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