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Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy

With the advancement in computational approaches and experimental, simulation, and modeling tools in recent decades, a trial-and-validation method is attracting more attention in the materials community. The development of powder metallurgy Ni-based superalloys is a vivid example that relies on simu...

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Autores principales: Wang, Jingzhe, Zhang, Siyu, Jiang, Liang, Srivatsa, Shesh, Huang, Zaiwang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10488392/
https://www.ncbi.nlm.nih.gov/pubmed/37687469
http://dx.doi.org/10.3390/ma16175776
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author Wang, Jingzhe
Zhang, Siyu
Jiang, Liang
Srivatsa, Shesh
Huang, Zaiwang
author_facet Wang, Jingzhe
Zhang, Siyu
Jiang, Liang
Srivatsa, Shesh
Huang, Zaiwang
author_sort Wang, Jingzhe
collection PubMed
description With the advancement in computational approaches and experimental, simulation, and modeling tools in recent decades, a trial-and-validation method is attracting more attention in the materials community. The development of powder metallurgy Ni-based superalloys is a vivid example that relies on simulation and experiments to produce desired microstructure and properties in a tightly controlled manner. In this research, we show an integrated approach to predicting the grain size of industrial forgings starting from lab-scale cylindrical compression by employing modeling and experimental validation. (a) Cylindrical compression tests to obtain accurate flow stress data and the hot working processing window; (b) double-cone tests of laboratory scale validation; (c) sub-scale forgings for further validation under production conditions; and (d) application and validation on full-scale industrial forgings. The procedure uses modeling and simulation to predict metal flow, strain, strain rate, temperature, and the resulting grain size as a function of thermo-mechanical processing conditions. The models are calibrated with experimental data until the accuracy of the modeling predictions is at an acceptable level, which is defined as the accuracy at which the results can be used to design and evaluate industrial forgings.
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spelling pubmed-104883922023-09-09 Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy Wang, Jingzhe Zhang, Siyu Jiang, Liang Srivatsa, Shesh Huang, Zaiwang Materials (Basel) Article With the advancement in computational approaches and experimental, simulation, and modeling tools in recent decades, a trial-and-validation method is attracting more attention in the materials community. The development of powder metallurgy Ni-based superalloys is a vivid example that relies on simulation and experiments to produce desired microstructure and properties in a tightly controlled manner. In this research, we show an integrated approach to predicting the grain size of industrial forgings starting from lab-scale cylindrical compression by employing modeling and experimental validation. (a) Cylindrical compression tests to obtain accurate flow stress data and the hot working processing window; (b) double-cone tests of laboratory scale validation; (c) sub-scale forgings for further validation under production conditions; and (d) application and validation on full-scale industrial forgings. The procedure uses modeling and simulation to predict metal flow, strain, strain rate, temperature, and the resulting grain size as a function of thermo-mechanical processing conditions. The models are calibrated with experimental data until the accuracy of the modeling predictions is at an acceptable level, which is defined as the accuracy at which the results can be used to design and evaluate industrial forgings. MDPI 2023-08-23 /pmc/articles/PMC10488392/ /pubmed/37687469 http://dx.doi.org/10.3390/ma16175776 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Jingzhe
Zhang, Siyu
Jiang, Liang
Srivatsa, Shesh
Huang, Zaiwang
Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy
title Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy
title_full Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy
title_fullStr Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy
title_full_unstemmed Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy
title_short Prediction of Grain Size in a High Cobalt Nickel-Based Superalloy
title_sort prediction of grain size in a high cobalt nickel-based superalloy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10488392/
https://www.ncbi.nlm.nih.gov/pubmed/37687469
http://dx.doi.org/10.3390/ma16175776
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