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AI-Enhanced Metal/Alloy Forming

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Materials Science and Engineering".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 348

Special Issue Editors

School of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
Interests: metal forming; design and manufacturing of metal plastic-forming equipment; AI-driven reliable prediction of product performance; multi-performance simulation analysis and optimization design; digital-twin

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Guest Editor
Institute of Metal Research, Chinese Academy of Sciences, Shenyang 110016, China
Interests: metal-forming technologies; data-driven computational plasticity, including machine learning; near-net shape manufacturing; flexible forming technologies; integrated multi-scale modeling based on microstructure evolution and crystal plasticity finite-element method
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Special Issue Information

Dear Colleagues,

Metal/alloy components play a crucial role in modern industry. They are widely used in fields such as construction, mechanical manufacturing, automotive, aerospace, electronics, and medical devices due to their high strength, good conductivity, and heat resistance. Metal/alloy components not only provide structural stability and durability but can also be designed into various complex shapes due to their plasticity, meeting diverse functional requirements. With the development of AI technology, more and more industrial fields have received its support, including the field of metal/alloy forming.

This Special Issue aims to collect recent advancements in the application of AI-enhanced metal/alloy forming. Metal/alloy rolling, forging, extrusion, drawing, stamping, hydroforming, and other processes utilize new-generation AI methods, including deep learning, optimization, and decision algorithms, digital-twin technology, and large language models, needing further in-depth research.

Dr. Zili Wang
Prof. Dr. Yong Xu
Guest Editors

Manuscript Submission Information

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Keywords

  • metal/alloy forming
  • deep learning algorithms
  • optimization algorithms
  • digital twin technology
  • large language models
  • rolling
  • forging
  • extrusion
  • drawing
  • stamping
  • hydroforming

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Published Papers (1 paper)

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Research

10 pages, 3178 KiB  
Article
The Influence of Minor Additions of La and Ce on the Microstructural Components and Forming Properties of Al-1.4Fe Alloys
by Maja Vončina, Jožef Medved, David Bombač and Klavdija Ozimič
Appl. Sci. 2024, 14(18), 8194; https://doi.org/10.3390/app14188194 - 12 Sep 2024
Viewed by 254
Abstract
This study investigated the microstructural constituents and forming properties of alloy Al-1.4 wt.% Fe with different additions of Ce and/or La. The addition of rare earth (RE) elements to aluminum alloys improves their microstructures in their as-cast and heat-treated states. RE additions and [...] Read more.
This study investigated the microstructural constituents and forming properties of alloy Al-1.4 wt.% Fe with different additions of Ce and/or La. The addition of rare earth (RE) elements to aluminum alloys improves their microstructures in their as-cast and heat-treated states. RE additions and appropriate heat treatment also improve their mechanical properties. The influence of the homogenization process on the microstructure and forming properties of Al-1.4 wt.% Fe alloy with various additions of Ce and/or La was investigated. When homogenizing the Al-1.4 wt.% Fe alloy at 580 °C, the majority of the homogenization process is completed after 6 h; at 600 °C, after about 5 h; and at 620 °C, after about 4 h. In the micro-alloyed Al-1.4 wt.%–Fe alloy, α-Al, stable Al13Fe4 phases in an agglomerated form, La-containing phases in a spherical form, and Ce-containing phases in a rod-shaped form are present after homogenization. The addition of La was shown to be advantageous as a micro-addition to Al–Fe alloys. Its forming properties show that the combination of Ce and La is the most favorable addition, whereby the homogenization process is fully optimized. Full article
(This article belongs to the Special Issue AI-Enhanced Metal/Alloy Forming)
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