Predictive study of Inconel718 mechanical properties at sub-zero temperatures

ABSTRACT

Inconel has applications in nuclear, chemical industry, aircraft and gas turbines due to their excellent mechanical properties in static and dynamic conditions. This study characterised Inconel 718 and predicted mechanical properties at sub-zero temperature. Experiments are conducted on the tensile specimens at different process parameters like temperature ranging from room temperature to −70°C, strain rate of 0.01/s and orientations in Rolling, 45° and transverse direction, and studied the fracture surface of the specimens to understand the mechanical behaviour of materials using a Scanning Electron Microscope. This study mainly focuses on calculation of the properties from tensile stress–strain graph at different temperatures. Using these properties trained an Artificial Neural Network (ANN) model to predict mechanical properties of the material at different temperatures, and validated the ANN output data with experimental data. Predicted values have very good correlation with actual values.

KEYWORDS:

• Inconel 718
• tensile testing
• fracture study
• artificial neural network

Acknowledgments

The authors would like to thank JNTU-Hyderabad for financial support of this research work (through TEQIP-III) JNTUH/TEQIP-III/CRC/2019/MECH/03.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Jawaharlal Nehru Technological University Hyderabad [JNTUH/TEQIP-III/CRC/2019/MECH/03].