Abstract
In the present work, creep tests on Zr–2.5Nb alloy at different stresses and temperatures in the two-phase region were carried out. The three creep regions were very distinct at low stresses and temperatures, whereas the secondary creep regions narrowed down considerably at higher temperatures and stresses. Data obtained from these creep tests were used to simulate the creep curves by multiple linear regression (MLR) and artificial neural network (ANN) modeling. The MLR model was able to predict the primary creep region accurately; however, it over-predicted the secondary creep region. ANN model could simulate all the three creep regions with very high accuracy, where 98% of the creep strain could be predicted within a deviation of ± 5%. Two different creep experiments were conducted to verify the predictability of the proposed models. The results indicate that the ANN technique can be used to predict the creep curves of two-phase alloys.
Graphical Abstract
Similar content being viewed by others
References
X. Wu, S. Williams, D. Gong, J. Mater. Eng. Perform. 21, 2255 (2012)
M. Kumar, I.V. Singh, B.K. Mishra, S. Ahmad, A. Venugopal Rao, V. Kumar, J. Mater. Eng. Perform. 25, 3985 (2016)
S. Bagui, B.P. Sahu, K. Laha, S. Tarafder, R. Mitra, Metall. Mater. Trans. A 52, 94 (2021)
C.-L. Dong, H.-C. Yu, Z.-H. Jiao, Rare Metals 35, 106 (2016)
T. Izaki, T. Kobayashi, J. Kusumoto, A. Kanaya, Int. J. Pres. Ves. Pip. 86, 637 (2009)
M. Taheri, S.F. Kashani-Bozorg, Metallogr. Microstruct. Anal. 10, 199 (2021)
K. Sawada, M. Tabuchi, K. Kimura, Mater. Sci. Eng. A 510–511, 190 (2009)
S. Manson, A. Haferd, Technical Note 2890, National Advisory Committee for Aeronautics (National Advisory Committee for Aeronautics, Washington, 1953)
O.D. Sherby, R.L. Orr, J.E. Dorn, Jom 6, 71 (1954)
F.R. Larson, J. Miller, Trans. ASME 74, 765 (1952)
A. Ghatak, P.S. Robi, Trans. Indian Inst. Met. 69, 579 (2016)
F.C. Monkman, N.J. Grant, in Proceedings of ASTM (ASTM International, West Conshohocken, 1956), pp. 593–620
F. Dobeš, K. Milička, Met. Sci. 10, 382 (1976)
T.A. Hayes, M.E. Kassner, Metall. Mater. Trans. A 37, 2389 (2006)
R.N. Singh, S. Mukherjee, R. Kishore, B.P. Kashyap, J. Nucl. Mater. 345, 146 (2005)
R.N. Singh, R. Kishore, A.K. Singh, T.K. Sinha, B.P. Kashyap, Metall. Mater. Trans. A 32, 2827 (2001)
S. Dutta, P.S. Robi, J. Mech. Sci. Technol. 35, 3369 (2021)
G. Nandan, P. Majumdar, P.K. Sahoo, R. Kumar, B. Chatterjee, D. Mukhopadhyay, H.G. Lele, Nucl. Eng. Des. 243, 301 (2012)
A. Sarkar, S.K. Sinha, J.K. Chakravartty, R.K. Sinha, Ann. Nucl. Energy 69, 246 (2014)
R.S.W. Shewfelt, L.W. Lyall, J. Nucl. Mater. 132, 41 (1985)
N. Christodoulou, P.A. Turner, C.N. Tomé, C.K. Chow, R.J. Klassen, Metall. Mater. Trans. A 33, 1103 (2002)
Y.S. Kim, K.S. Im, Y.M. Cheong, S.B. Ahn, J. Nucl. Mater. 346, 120 (2005)
R.A. Holt, J. Nucl. Mater. 372, 182 (2008)
B.N. Rath, H.N. Singh, J.L. Singh, N. Kumawat, P.M. Ouseph, D.N. Sah, Trans. Indian Inst. Met. 63, 671 (2010)
K. Guguloth, M. Ghosh, J. Swaminathan, R. Mitra, Mater. Sci. Eng. A 791, 139681 (2020)
A.F. Schon, N.A. Castro, A. dos Santos Barros, J.E. Spinelli, A. Garcia, N. Cheung, B.L. Silva, Mater. Lett. 304 , 130587 (2021)
M. Kusano, S. Miyazaki, M. Watanabe, S. Kishimoto, D.S. Bulgarevich, Y. Ono, A. Yumoto, Mater. Sci. Eng. A 787, 139549 (2020)
D. Yang, Z. Liu, Int. J. Refract. Met. Hard Mater. 51, 192 (2015)
S. Milhomme, J. Lartigau, C. Brugger, C. Froustey, Int. J. Adv. Manuf. Technol. 117, 607 (2021)
Y. Lazo, L. Suárez, M. Fernández, L. Fernández, Superlattice. Microst. 45, 117 (2009)
P.S. Robi, U.S. Dixit, J. Mater. Process. Tech. 142, 289 (2003)
M. Kamrunnahar, M. Urquidi-Macdonald, Corros. Sci. 52, 669 (2010)
A.F. Yetim, M.Y. Codur, M. Yazici, Mater. Lett. 158, 170 (2015)
L. Ping, X. Kemin, L. Yan, T. Jianrong, J. Mater. Process. Tech. 148, 235 (2004)
N.S. Reddy, Y.H. Lee, C.H. Park, C.S. Lee, Mater. Sci. Eng. A 492, 276 (2008)
S. Banerjee, P.S. Robi, A. Srinivasan, Metall. Mater. Trans. A 43, 3834 (2012)
A. Asgharzadeh, H. Asgharzadeh, A. Simchi, Met. Mater. Int. 27, 5212 (2021)
R. Kapoor, D. Pal, J.K. Chakravartty, J. Mater. Process. Tech. 169, 199 (2005)
H. R. Rezaei Ashtiani, A. A. Shayanpoor, Met. Mater. Int. 27, 5017 (2021).
S.K. Singh, K. Mahesh, A.K. Gupta, Mater. Design 31, 2288 (2010)
T.-W. Hong, S.-I. Lee, J.-H. Shim, M.-G. Lee, J. Lee, B. Hwang, Met. Mater. Int. 27, 3935 (2021)
Y.V. Deshpande, A.B. Andhare, P.M. Padole, SN Appl, Sci. 1, 104 (2019)
E. Maleki, O. Unal, M. Guagliano, S. Bagherifard, Met. Mater. Int. 28, 112 (2022)
E. Maleki, O. Unal, Met. Mater. Int. 27, 262 (2021)
E. Maleki, O. Unal, Met. Mater. Int. 27, 3173 (2021)
N. Wang, S.-T. Tu, F.-Z. Xuan, Eng. Fail. Anal. 31, 302 (2013)
T. Liang, X. Liu, P. Fan, L. Zhu, Y. Bi, Y. Zhang, Int. J. Pres. Ves. Pip. 179, 104014 (2020)
J. Zhong, C. Yang, W. Ma, Z. Zhang, Polym. Test. 93, 106893 (2021)
Y.I. Kwon, B.S. Lim, Met. Mater. Int. 7, 311 (2001)
A. Ghatak, P.S. Robi, Neural Comput. Appl. 30, 2953 (2018)
D. Srivastava, G.K. Dey, S. Banerjee, Metall. Mater. Trans. A 26, 2707 (1995)
B.S. Rodchenkov, A.N. Semenov, Nucl. Eng. Des. 235, 2009 (2005)
A. Ghatak, Creep correlation of micro-alloyed HP40Nb reformerer steel, Ph.D. thesis, Indian Institute of Technology Guwahati (2015)
G.E. Dieter, Mechanical Metallurgy SI Metric Edn. (McGraw-Hill, New York, 1988)
G.D. Garson, AI Expert 6, 46 (1991)
K. Guguloth, R. Mitra, S.G. Chowdhury, J. Swaminathan, Mater. Sci. Eng. A 721, 286 (2018)
S.V. Shukla, C. Chandrashekharayya, R.N. Singh, R. Fotedar, R. Kishore, T.K. Sinha, B.P. Kashyap, J. Nucl. Mater. 273, 130 (1999)
A. J. Lockley, R. E. Mayville, Microsc. Microanal. 8, 1308 (2002)
B. Kombaiah, K.L. Murty, Metall. Mater. Trans. A 46, 4646 (2015)
Acknowledgements
The authors are grateful to BARC, India, for providing the Zr–2.5Nb tubes necessary for the study. The authors express their sincere thanks to the staff of the central workshop, IIT Guwahati, for the help extended in the preparation of test samples and carrying out the experiments.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors have no competing interests to declare that are relevant to the content of this article.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Appendix
See Table 5.
Rights and permissions
About this article
Cite this article
Dutta, S., Robi, P.S. Experimental Investigation and Modeling of Creep Curve of Zr–2.5Nb Alloy by Machine Learning Techniques. Met. Mater. Int. 28, 2884–2897 (2022). https://doi.org/10.1007/s12540-022-01182-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12540-022-01182-z