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AIP Conference ProceedingsVolume 2293, 24 November 2020, Article number 140019International Conference on Numerical Analysis and Applied Mathematics 2019, ICNAAM 2019; Sheraton Rhodes ResortRhodes; Greece; 23 September 2019 through 28 September 2019; Code 165330

Approximating heat resistance of nickel-based superalloys by a sigmoid(Conference Paper)(Open Access)

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  • Ural Federal University, Mira str., 19, Ekaterinburg, 620002, Russian Federation

Abstract

The nickel-based superalloys are unique materials with complex doping applied to manufacturing the gas turbine engine parts. The alloys show resistance to mechanical and chemical degradation under high pressure, high temperature, and long-term isothermal exposures. One of the main alloys' service properties is the heat resistance. Numerically, it is expressed in the tensile strength values (MPa). Simulation of the heat resistance behavior is an important engineering task, which would significantly simplify the analysis of existing and designing the new alloys. In this paper, we use results of the heat resistance simulation by an artificial neural network, as well as, experimental data for approximating the changes in the heat resistance vs isothermal exposures expressed in the complex Larson-Miller parameter by a sigmoidal function. © 2020 American Institute of Physics Inc.. All rights reserved.

Author keywords

Larson-Miller parameterNickel-based superalloysSigmoidSimulationTensile strength
  • ISSN: 0094243X
  • ISBN: 978-073544025-8
  • Source Type: Conference Proceeding
  • Original language: English
  • DOI: 10.1063/5.0026744
  • Document Type: Conference Paper
  • Volume Editors: Simos T.E.,Simos T.E.,Simos T.E.,Simos T.E.,Simos T.E.,Tsitouras C.
  • Publisher: American Institute of Physics Inc.

  Tarasov, D.A.; Ural Federal University, Mira str., 19, Ekaterinburg, Russian Federation;
© Copyright 2020 Elsevier B.V., All rights reserved.

Cited by 1 document

Liu, Y. , Xu, B. , Huangfu, W.
Nickel-based polycrystalline superalloy composition design framework based on non-dominated sorting genetic algorithm II
(2023) Computational Materials Science
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