Development of Composition and Heat Treatment Process of 2000 MPa Grade Spring Steels Assisted by Machine Learning
Received date: 2022-02-14
Revised date: 2022-04-28
Online published: 2022-10-31
Supported by
National Natural Science Foundation of China(52101118);Young Elite Scientists Sponsorship Program by China Association for Science and Technology(2022QNRC001)
The rapid development of rail transit has led to the proposition of higher requirements for the mechanical properties of springs and spring steels. Thus, bogies have been identified as the key components for trains to achieve high speed since they are connected with train bodies and wheel sets through springs. Alternatively, since the properties of spring steel materials have an important effect on the safety and comfort of high-speed trains, the development of spring steels with ultra-high strength and good plasticity has attracted the attention of researchers and industrial circles. However, simultaneously improving strength and plasticity has remained an important challenge for the research and development of high-end steels. Notwithstanding, machine learning has recently made substantial progress in designing and predicting various materials, and is expected to become a powerful tool for clarifying the relationship between the composition, process, and properties of complex alloys like steels. Based on the above background, this study reports the realization of rapid chemical composition and heat treatment process-design parameters for new spring steels, using a performance-oriented machine learning design system with high strength and good plasticity (tensile strength (2050 ± 50) MPa, elongation 10.5% ± 1.5%) after collecting literature data on spring steels and other typical quenched + tempered steels. Experimental studies were also carried out to obtain a further optimized heat treatment process (heating at 950oC for 30 min and oil quenching + tempering at 380oC for 90 min and water cooling). Investigations revealed that the tensile strengths of the two new spring steel materials developed were 2183.5 and 2193.0 MPa, their yield strengths were 1923.0 and 2024.5 MPa, their elongations after fracture were 10.5% and 9.7%, and the area reductions were 42.4% and 41.5%, respectively, with grain boundary strengthening and dislocation strengthening being the main strengthening mechanisms of the new spring steels. It was also observed that the fine grain size and appropriate amounts of austenite made the spring steels maintain good plasticity and have ultra-high strength. Moreover, compared with the existing ultra-high strength steels at the same strength grade, the new spring steels had significant technological and cost advantages. Hence, based on the above research, a new method and theory are provided to design chemical composition and heat treatment processes for quenched and tempered steels.
Key words: spring steel; ultra-high strength; heat treatment; machine learning
YANG Lei , ZHAO Fan , JIANG Lei , XIE Jianxin . Development of Composition and Heat Treatment Process of 2000 MPa Grade Spring Steels Assisted by Machine Learning[J]. Acta Metall Sin, 2023 , 59(11) : 1499 -1512 . DOI: 10.11900/0412.1961.2022.00047
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