Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural Network
2A12 aluminum alloy is a high-strength aerospace alloy. During its extrusion process, the extrusion process parameters have a great impact on the microstructure evolution of the extruded products. There are three extrusion process parameters controlled in the actual project, which are the initial te...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-03-01
|
| Series: | Metals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4701/13/4/664 |
| _version_ | 1827744445962911744 |
|---|---|
| author | Haishun Jiang Rendong Wu Chaolong Yuan Wei Jiao Lingling Chen Xingyou Zhou |
| author_facet | Haishun Jiang Rendong Wu Chaolong Yuan Wei Jiao Lingling Chen Xingyou Zhou |
| author_sort | Haishun Jiang |
| collection | DOAJ |
| description | 2A12 aluminum alloy is a high-strength aerospace alloy. During its extrusion process, the extrusion process parameters have a great impact on the microstructure evolution of the extruded products. There are three extrusion process parameters controlled in the actual project, which are the initial temperature of billet, the initial temperature of die and the extrusion speed. Combined with a back propagation (BP) neural network and finite element method (FEM) simulation, based on the constitutive equation and recrystallization evolution process of 2A12 aluminum alloy, this paper establishes a prediction model for the grain size of extruded pipe by these three extrusion process parameters. This paper used a 35MN extruding machine for a production verification of 2A12 pipe. The results show that the predicted grain size is 3% smaller than the actual size. |
| first_indexed | 2024-03-11T04:44:56Z |
| format | Article |
| id | doaj.art-aee654940a2e4c65bb30505d0ee3c803 |
| institution | Directory Open Access Journal |
| issn | 2075-4701 |
| language | English |
| last_indexed | 2024-03-11T04:44:56Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Metals |
| spelling | doaj.art-aee654940a2e4c65bb30505d0ee3c8032023-11-17T20:25:54ZengMDPI AGMetals2075-47012023-03-0113466410.3390/met13040664Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural NetworkHaishun Jiang0Rendong Wu1Chaolong Yuan2Wei Jiao3Lingling Chen4Xingyou Zhou5Key Laboratory for Advanced Materials Processing Technology, Ministry of Education of China, Beijing 100084, ChinaKey Laboratory for Advanced Materials Processing Technology, Ministry of Education of China, Beijing 100084, ChinaKey Laboratory for Advanced Materials Processing Technology, Ministry of Education of China, Beijing 100084, ChinaKey Laboratory for Advanced Materials Processing Technology, Ministry of Education of China, Beijing 100084, ChinaKey Laboratory for Advanced Materials Processing Technology, Ministry of Education of China, Beijing 100084, ChinaKey Laboratory for Advanced Materials Processing Technology, Ministry of Education of China, Beijing 100084, China2A12 aluminum alloy is a high-strength aerospace alloy. During its extrusion process, the extrusion process parameters have a great impact on the microstructure evolution of the extruded products. There are three extrusion process parameters controlled in the actual project, which are the initial temperature of billet, the initial temperature of die and the extrusion speed. Combined with a back propagation (BP) neural network and finite element method (FEM) simulation, based on the constitutive equation and recrystallization evolution process of 2A12 aluminum alloy, this paper establishes a prediction model for the grain size of extruded pipe by these three extrusion process parameters. This paper used a 35MN extruding machine for a production verification of 2A12 pipe. The results show that the predicted grain size is 3% smaller than the actual size.https://www.mdpi.com/2075-4701/13/4/6642A12 aluminum alloyhot extrusionBP neural networkrecrystallization structurepipe |
| spellingShingle | Haishun Jiang Rendong Wu Chaolong Yuan Wei Jiao Lingling Chen Xingyou Zhou Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural Network Metals 2A12 aluminum alloy hot extrusion BP neural network recrystallization structure pipe |
| title | Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural Network |
| title_full | Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural Network |
| title_fullStr | Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural Network |
| title_full_unstemmed | Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural Network |
| title_short | Prediction of Recrystallization Structure of 2A12 Aluminum Alloy Pipe Extrusion Process Based on BP Neural Network |
| title_sort | prediction of recrystallization structure of 2a12 aluminum alloy pipe extrusion process based on bp neural network |
| topic | 2A12 aluminum alloy hot extrusion BP neural network recrystallization structure pipe |
| url | https://www.mdpi.com/2075-4701/13/4/664 |
| work_keys_str_mv | AT haishunjiang predictionofrecrystallizationstructureof2a12aluminumalloypipeextrusionprocessbasedonbpneuralnetwork AT rendongwu predictionofrecrystallizationstructureof2a12aluminumalloypipeextrusionprocessbasedonbpneuralnetwork AT chaolongyuan predictionofrecrystallizationstructureof2a12aluminumalloypipeextrusionprocessbasedonbpneuralnetwork AT weijiao predictionofrecrystallizationstructureof2a12aluminumalloypipeextrusionprocessbasedonbpneuralnetwork AT linglingchen predictionofrecrystallizationstructureof2a12aluminumalloypipeextrusionprocessbasedonbpneuralnetwork AT xingyouzhou predictionofrecrystallizationstructureof2a12aluminumalloypipeextrusionprocessbasedonbpneuralnetwork |