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Stacked Auto-Encoder Network to Predict Tensile Deformation Behavior of a Typical Nickel-Based Superalloy Considering Portevin–Le Chatelier Effects

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Abstract

The intermediate-temperature (473–973 K) deformation behavior of a nickel-based superalloy is researched by uniaxial tensile experiments. It is observed that the flow characteristics and the Portevin–Le Chatelier (PLC) effects are significantly affected by the thermo-mechanical parameters. The serrated flow features are obvious under the testing conditions. A stacked auto-encoders (SAEs) network model is proposed for predicting the flow behaviors of the researched superalloy. The architecture of the established SAEs model is optimized layer by layer. The best number of hidden layer is 3, and the nodes per hidden layer are 15, 20 and 50, respectively. The excellent prediction ability suggests that the developed SAEs model can well reconstruct the intermediate-temperature flow behavior involving the PLC effects of the researched superalloy.

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Acknowledgements

This work was supported by the National Natural Science Foundation Council of China (Grant No. 51775564).

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Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, Central South University, Changsha, 410083, China

    Y. C. Lin, Hui Yang, Dong-Dong Chen & Dao-Guang He

  2. State Key Laboratory of High Performance Complex Manufacturing, Changsha, 410083, China

    Y. C. Lin, Hui Yang, Dong-Dong Chen & Dao-Guang He

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Lin, Y.C., Yang, H., Chen, DD. et al. Stacked Auto-Encoder Network to Predict Tensile Deformation Behavior of a Typical Nickel-Based Superalloy Considering Portevin–Le Chatelier Effects. Met. Mater. Int. 27, 254–261 (2021). https://doi.org/10.1007/s12540-019-00435-8

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