Evolution of Corrosion Damage Characteristics of AA7075-T651 Al-alloy Under Mechanical-chemical Interaction Based on Cellular Automata Method

doi:10.11902/1005.4537.2024.111

Journal of Chinese Society for Corrosion and protection

2024, Vol. 44

Issue (6): 1507-1517 DOI: 10.11902/1005.4537.2024.111

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Evolution of Corrosion Damage Characteristics of AA7075-T651 Al-alloy Under Mechanical-chemical Interaction Based on Cellular Automata Method

WENG Shuo¹^,²^,³(

), MENG Chao¹, LUO Linghua⁴, YUAN Yiwen⁵, ZHAO Lihui¹^,²^,³, FENG Jinzhi¹^,²^,³

1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
2. Key Laboratory of Strength and Reliability Evaluation of Auto Mechanical Components for Mechanical Industry, Shanghai 200093, China
3. Shanghai Public Technology Platform for Reliability Evaluation of New Energy Vehicles, Shanghai 200093, China
4. Research Institute of China State Shipbuilding Corporation, Shanghai 201108, China
5. Shanghai Institute of Special Equipment Supervision and Inspection Technology, Shanghai 200062, China

Cite this article:

WENG Shuo, MENG Chao, LUO Linghua, YUAN Yiwen, ZHAO Lihui, FENG Jinzhi. Evolution of Corrosion Damage Characteristics of AA7075-T651 Al-alloy Under Mechanical-chemical Interaction Based on Cellular Automata Method. Journal of Chinese Society for Corrosion and protection, 2024, 44(6): 1507-1517.

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Abstract

The evolution of corrosion damage characteristics of AA7075-T651 Al-alloy under combined force-chemical interaction was clarified via a combination of cellular automaton method and mechanical numerical simulation software, aiming to simulate the evolution process of corrosion damage of Al-alloy under different load levels, and to revealing the effect of mechanical stress on the variation of corrosion growth rate and morphological characteristics evolution of the Al-alloy as well. The results show that compared with the corrosion of Al-alloy without external load, the number of cells lost due to the corrosion and the maximum corrosion depth or width under the action of force-chemical coupling are significantly increased, while the maximum ratio of corrosion depth to width of the corrosion damage characteristics are significantly increased. It can be seen that the ratio of depth to width gradually increases with the increase of load level. It can be seen that the tensile stress causes the corrosion pit to show a faster growth trend in the longitudinal direction, which in turn causes the stress concentration coefficient to increase, causing the bottom of the corrosion damage characteristic to change from elastic deformation to plastic deformation, ultimately accelerating the corrosion process of the Al-alloy.

Key words: cellular automata finite element analysis AA7075-T651 Al-alloy corrosion damage

Received: 02 April 2024 32134.14.1005.4537.2024.111

ZTFLH:

TG156

Fund: National Natural Science Foundation of China(52005336);State Administration for Market Regulation Innovative Talent Program(QNBJ202318)

Corresponding Authors: WENG Shuo，E-mail: wengshuo@usst.edu.cn

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https://www.jcscp.org/EN/10.11902/1005.4537.2024.111 OR https://www.jcscp.org/EN/Y2024/V44/I6/1507

Fig.1 Schematic diagram of pitting of AA7075-T651 aluminum alloy

Fig.2 The Von Neumann model of cellular automata

Table 1 Types of all cells in cellular automata model

Fig.3 Spatial model diagram of cellular automata

Fig.4 Schematic diagram of corrosion evolution of cellular automata

Table 2 Parameter probabilities of cellular automata model

Fig.5 Structure diagram of finite element model of cellular automata

Fig.6 Schematic diagrams of the cross sections of corrosion pits^[20]

Fig.7 Simulated cross sections of various corrosion pits in CA model: (a) wide and shallow type, (b) horizontal type, (c) groove type

Fig.8 Morphology evolution of corrosion pit in CA model under the simulation time steps of 100 (a), 200 (b), 300 (c), 400 (d), 500 (e) and 600 (f)

Fig.9 Cross-sectional morphologies of corrosion pits of 2024 (a, c, e, g) and 7B04 (b, d, f, h) aluminum alloys after corrosion for 24 h (a, b), 48 h (c, d), 96 h (e, f) and 192 h (g, h) ^[23]

Fig.10 Comparison of the numbers of corrosion cells under different corrosion probabilities

Fig.11 Comparison of the number changes of corrosion cells under different precipitation coefficients

Fig.12 Comparison of morphologies of corrosion pits in different simulation time steps under the stresses of 0 (a), 100 MPa (b), 200 MPa (c), 300 MPa (d), 500 MPa (e) and 550 MPa (f)

Fig.13 Comparison of morphologies of corrosion pits at different stress levels under the simulation time steps of 100 (a), 200 (b), 300 (c), 400 (d) and 500 (e)

Fig.14 Influences of stress variation on the number (a), depth (b), width (c) and depth-width ratio (d) of corrosion cells in CA model

Fig.15 Stress (a, b) and strain (c, d) diagrams of corrosion pits under the conditions of 200 simulated time steps and the stresses of 200 MPa (a, c) and 500 MPa (b, d)

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