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Prediction of Yoshida Uemori model parameters by The Bees Algorithm and Genetic Algorithm for 5xxx series aluminium alloys

Yıl 2021, Cilt: 10 Sayı: 2, 815 - 823, 27.07.2021
https://doi.org/10.28948/ngumuh.895920

Öz

In sheet metal forming processes, springback is a very important issue in the view of the excellent quality design. Several mathematical models have been developed to estimate the springback more accurately, including various material parameters. In this study, the model parameters of Yoshida-Uemori two surface plasticity model, which can well predict the springback for different loading conditions, have been determined using The Bees Algorithm and Genetic Algorithm which are frequently used recently for optimization of nonlinear problems. In addition, the performances of the algorithms have been determined for the different frequency of experimental data, dense-sparse, sparse-dense, dense-dense and sparse-sparse for elastic and plastic regions. According to the results, although the determined material parameters have different values, the fitting performances are found similar for both The Bees Algorithm and Genetic Algorithm. However, in the view of the data frequency, the more appropriate results are obtained from the dense-dense data set (Case 3).

Kaynakça

  • Y. K. Chen, X. X. Li, and L. H. Lang, Various elastic moduli of AA6016 and their application on accurate prediction of springback. Journal of the Chinese Institute of Engineers, 42, 319-326, May 19 2019. https://doi.org/10.1080/02533839.2019.1584765
  • B. Chongthairungruang, V. Uthaisangsuk, S. Suranuntchai, and S. Jirathearanat, Springback prediction in sheet metal forming of high strength steels. Materials & Design, 50, 253-266, Sep 2013. https://doi.org/10.1016/j.matdes.2013.02.060
  • X. Xue, J. Liao, G. Vincze, A. B. Pereira, and F. Barlat, Experimental assessment of nonlinear elastic behaviour of dual-phase steels and application to springback prediction. International Journal of Mechanical Sciences, 117, 1-15, Oct 2016. https://doi.org/10.1016/ j.ijmecsci.2016.08.003
  • S. Chatti and N. Hermi, The effect of non-linear recovery on springback prediction. Computers & Structures, 89, 1367-1377, Jul 2011. https://doi.org/ 10.1016/j.compstruc.2011.03.010
  • W. Prager, A new method of analyzing stresses and strains in work hardening plastic solids. ASME J. App. Mech 23, 493-496, 1956.
  • T. Uemori, T. Okada, and F. Yoshida, Simulation of springback in V-bending process by elasto-plastic finite element method with consideration of Bauschinger effect. Metals and Materials-Korea, 4, 311-314, 1998. https://doi.org/10.1007/BF03187783
  • T. Uemori, T. Okada, and F. Yoshida, FE analysis of springback in hat-bending with consideration of initial anisotropy and the Bauschinger effect. Advances in Engineering Plasticity, Pts 1-2, 177-1, 497-502, 2000. https://doi.org/10.4028/www.scientific.net/KEM.177-180.497
  • F. Yoshida and T. Uemori, A model of large-strain cyclic plasticity describing the Bauschinger effect and workhardening stagnation. International Journal of Plasticity, 18, 661-686, 2002. https://doi.org/ 10.1016/S0749-6419(01)00050-X
  • R. K. Boger, R. H. Wagoner, F. Barlat, M. G. Lee, and K. Chung, Continuous, large strain, tension/compression testing of sheet material. International Journal of Plasticity, 21, 2319-2343, 2005. https://doi.org/10.1016/j.ijplas.2004.12.002
  • J. H. Kim, D. Kim, Y. S. Lee, M. G. Lee, K. Chung, H. Y. Kim, et al., A temperature-dependent elasto-plastic constitutive model for magnesium alloy AZ31 sheets. International Journal of Plasticity, 50, 66-93, Nov 2013. https://doi.org/10.1016/j.ijplas.2013.04.001
  • M. G. Lee, D. Kim, C. M. Kim, M. L. Wenner, R. H. Wagoner, and K. Chung, Spring-back evaluation of automotive sheets based on isotropic-kinematic hardening laws and non-quadratic anisotropic yield functions - Part II: characterization of material properties. International Journal of Plasticity, 21, 883-914, 2005. https://doi.org/10.1016/j.ijplas.2004.05.015
  • F. Yoshida, T. Uemori, and K. Fujiwara, Elastic–plastic behavior of steel sheets under in-plane cyclic tension–compression at large strain. International Journal of Plasticity, 18, 633-659, 2002. https://doi.org/10.1016/ S0749-6419(01)00049-3
  • C. Y. Chang, M. H. Ho, and P. C. Shen, Yoshida-Uemori material models in cyclic tension-compression tests and shear tests. Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture, 228, 245-254, Feb 2014. https://doi.org/10.1177/0954405413499011
  • P. A. Eggertsen and K. Mattiasson, An efficient inverse approach for material hardening parameter identification from a three-point bending test. Engineering with Computers, 26, 159-170, Apr 2010. https://doi.org/10.1007/s00366-009-0149-y.
  • P. A. Eggertsen and K. Mattiasson, On the identification of kinematic hardening material parameters for accurate springback predictions. International Journal of Material Forming, 4, 103-120, Jun 2011. https://doi.org/10.1007/s12289-010-1014-7
  • S. Toros, Parameters determination of Yoshida Uemori model through optimization process of cyclic tension-compression test and V-bending springback. Latin American Journal of Solids and Structures, 13, 1893-1911, 2016. https://doi.org/10.1590/1679-78252916
  • A. H. Mahmoudi, S. M. Pezeshki-Najafabadi, and H. Badnava, Parameter determination of Chaboche kinematic hardening model using a multi objective Genetic Algorithm. Computational Materials Science, 50, 1114-1122, Jan 2011. https://doi.org/10.1016/ j.commatsci.2010.11.010
  • J. H. Yongfeng Li, Bin Gu, Shuhui Li, Identification of advanced constitutive model parameters through global optimization approach for DP780 steel sheet. Procedia Engineering, 207, 125-130, 2017. https://doi.org/ 10.1016/j.proeng.2017.10.749
  • D. T. Pham and M. Castellani, Benchmarking and comparison of nature-inspired population-based continuous optimisation algorithms. Soft Computing, 18, 871-903, May 2014. https://doi.org/10.1007/ s00500-013-1104-9
  • D. T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, and M. Zaidi, The Bees Algorithm technical note. Manufacturing Engineering Centre, 1-57, 2005.
  • D. T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, and M. Zaidi, The Bees Algorithm - A novel tool for complex optimisation problems. Manufacturing Engineering Centre, 454-458, 2006. https://doi.org/10.1016/B978-008045157-2/50081-X
  • A. A. Fahmy, M. Kalyoncu, and M. Castellani, Automatic design of control systems for robot manipulators using the bees algorithm. Proceedings of the Institution of Mechanical Engineers Part I-Journal of Systems and Control Engineering, 226, 497-508, Apr 2012.
  • D. T. Pham, E. Koç, M. Kalyoncu, and M. Tınkır, Hierarchical PID controller design for a flexible link robot manipulator using The Bees Algorithm. Proceedings of Proceedings of 6th International Symposium on Intelligent Manufacturing Systems, Sakarya, Turkey, 2008.
  • D. T. Pham and M. Kalyoncu, Optimisation of a Fuzzy Logic Controller for a flexible single-link robot arm using The Bees Algorithm. Proceedings of 7th IEEE International Conference on Industrial Informatics, Cardiff, UK, 2009.
  • M. A. Sen, V. Bakırcıoğlu, and M. Kalyoncu, Performances comparison of The Bees Algorithm and Genetic Algorithm for PID controller tuning. Proceedings of 5th International Mechatronics and Control Engineering, Venice, Italy, 2016.
  • O. Öztürk, M. Kalyoncu, and A. Ünüvar, Multi objective optimization of cutting parameters in a single pass turning operation using The Bees Algorithm. Proceedings of 1st International Conference on Advances in Mechanical and Mechatronics Engineering, Ankara/TURKEY, 2018.
  • O. Acar, M. Kalyoncu, and A. Hassan, The design optimization of a gripper mechanism using The Bees’ Algorithm. Proceedings of International Conference on Engineering Technologies (ICENTE'18), Konya/TURKEY, 2018.
  • O. Acar, M. Kalyoncu, and A. Hassan, Proposal of a harmonic Bees Algorithm for design optimization of a gripper mechanism, Cham, 2019, 2829-2839. https://doi.org/10.1007/978-3-030-20131-9_280
  • Anonymous. (2019). MATLAB global optimization toolbox sser's guide. Available: https://www. mathworks.com/help/gads/index.html. (Accessed March 12nd, 2021)
  • P. C. B. Abdulaziz Alghtani, D.C. Barton, V.V. Toropov, Springback analysis and optimization in sheet metal forming. Proceedings of 9th European LS-DYNA Conference, Manchester, 2013.
  • D. E. G. Ali Aryanpour, Evaluation of LS-DYNA material models for the analysis of sidewall curl in advanced high strength steels. Proceedings of 12th International LS-DYNA Conference, Detroit, 2012.
  • S. Tamura, S. Sumikawa, T. Uemori, H. Hamasaki, and F. Yoshida, Experimental observation of elasto-plasticity behavior of type 5000 and 6000 aluminum alloy sheets, Materials Transactions, 52, 868-875, May 2011. https://doi.org/10.2320/matertrans.L-MZ201101

5xxx serisi alüminyum alaşımları için Yoshida Uemori model parametrelerinin Arı Algoritması ve Genetik Algoritma ile tahmini

Yıl 2021, Cilt: 10 Sayı: 2, 815 - 823, 27.07.2021
https://doi.org/10.28948/ngumuh.895920

Öz

Sac metal şekillendirme işlemlerinde tasarım kalitesinin mükemmelliği açısından geri esneme çok önemli bir yer teşkil etmektedir. Geri esnemelerin tahmini için birçok matematiksel model geliştirilmiş olup bu matematiksel model parametrelerinin belirlenmesi için birçok yöntem kullanılmaktadır. Bu çalışmada farklı yükleme koşulları için geri esnemeyi çok iyi tahmin edebilen Yoshida-Uemori iki yüzeyli plastisite malzeme model parametreleri, son zamanlarda doğrusal olmayan problemlerin optimizasyonu için sıkça kullanılan “Arı Algoritması” ve “Genetik Algoritma” kullanılarak belirlenmiştir. Aynı zamanda deneysel veriler elastik ve plastik bölgede sırasıyla; sık-seyrek, seyrek-sık, sık-sık ve seyrek-seyrek olacak şekilde ayarlanarak veri yoğunluğunun parametre sonuçlarına etkisinin incelenmiştir. Elde edilen sonuçlara göre belirlenen malzeme parametreleri farklı değerlere sahip olmasına rağmen Arı Algoritması ve Genetik Algoritma için uyum performansı yaklaşık olarak benzer çıkmıştır. Ancak sonuçlar data sıklığı açısından incelendiğinde sık-sık (Durum 3) veri kümesi daha iyi sonuçlar vermiştir.

Kaynakça

  • Y. K. Chen, X. X. Li, and L. H. Lang, Various elastic moduli of AA6016 and their application on accurate prediction of springback. Journal of the Chinese Institute of Engineers, 42, 319-326, May 19 2019. https://doi.org/10.1080/02533839.2019.1584765
  • B. Chongthairungruang, V. Uthaisangsuk, S. Suranuntchai, and S. Jirathearanat, Springback prediction in sheet metal forming of high strength steels. Materials & Design, 50, 253-266, Sep 2013. https://doi.org/10.1016/j.matdes.2013.02.060
  • X. Xue, J. Liao, G. Vincze, A. B. Pereira, and F. Barlat, Experimental assessment of nonlinear elastic behaviour of dual-phase steels and application to springback prediction. International Journal of Mechanical Sciences, 117, 1-15, Oct 2016. https://doi.org/10.1016/ j.ijmecsci.2016.08.003
  • S. Chatti and N. Hermi, The effect of non-linear recovery on springback prediction. Computers & Structures, 89, 1367-1377, Jul 2011. https://doi.org/ 10.1016/j.compstruc.2011.03.010
  • W. Prager, A new method of analyzing stresses and strains in work hardening plastic solids. ASME J. App. Mech 23, 493-496, 1956.
  • T. Uemori, T. Okada, and F. Yoshida, Simulation of springback in V-bending process by elasto-plastic finite element method with consideration of Bauschinger effect. Metals and Materials-Korea, 4, 311-314, 1998. https://doi.org/10.1007/BF03187783
  • T. Uemori, T. Okada, and F. Yoshida, FE analysis of springback in hat-bending with consideration of initial anisotropy and the Bauschinger effect. Advances in Engineering Plasticity, Pts 1-2, 177-1, 497-502, 2000. https://doi.org/10.4028/www.scientific.net/KEM.177-180.497
  • F. Yoshida and T. Uemori, A model of large-strain cyclic plasticity describing the Bauschinger effect and workhardening stagnation. International Journal of Plasticity, 18, 661-686, 2002. https://doi.org/ 10.1016/S0749-6419(01)00050-X
  • R. K. Boger, R. H. Wagoner, F. Barlat, M. G. Lee, and K. Chung, Continuous, large strain, tension/compression testing of sheet material. International Journal of Plasticity, 21, 2319-2343, 2005. https://doi.org/10.1016/j.ijplas.2004.12.002
  • J. H. Kim, D. Kim, Y. S. Lee, M. G. Lee, K. Chung, H. Y. Kim, et al., A temperature-dependent elasto-plastic constitutive model for magnesium alloy AZ31 sheets. International Journal of Plasticity, 50, 66-93, Nov 2013. https://doi.org/10.1016/j.ijplas.2013.04.001
  • M. G. Lee, D. Kim, C. M. Kim, M. L. Wenner, R. H. Wagoner, and K. Chung, Spring-back evaluation of automotive sheets based on isotropic-kinematic hardening laws and non-quadratic anisotropic yield functions - Part II: characterization of material properties. International Journal of Plasticity, 21, 883-914, 2005. https://doi.org/10.1016/j.ijplas.2004.05.015
  • F. Yoshida, T. Uemori, and K. Fujiwara, Elastic–plastic behavior of steel sheets under in-plane cyclic tension–compression at large strain. International Journal of Plasticity, 18, 633-659, 2002. https://doi.org/10.1016/ S0749-6419(01)00049-3
  • C. Y. Chang, M. H. Ho, and P. C. Shen, Yoshida-Uemori material models in cyclic tension-compression tests and shear tests. Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture, 228, 245-254, Feb 2014. https://doi.org/10.1177/0954405413499011
  • P. A. Eggertsen and K. Mattiasson, An efficient inverse approach for material hardening parameter identification from a three-point bending test. Engineering with Computers, 26, 159-170, Apr 2010. https://doi.org/10.1007/s00366-009-0149-y.
  • P. A. Eggertsen and K. Mattiasson, On the identification of kinematic hardening material parameters for accurate springback predictions. International Journal of Material Forming, 4, 103-120, Jun 2011. https://doi.org/10.1007/s12289-010-1014-7
  • S. Toros, Parameters determination of Yoshida Uemori model through optimization process of cyclic tension-compression test and V-bending springback. Latin American Journal of Solids and Structures, 13, 1893-1911, 2016. https://doi.org/10.1590/1679-78252916
  • A. H. Mahmoudi, S. M. Pezeshki-Najafabadi, and H. Badnava, Parameter determination of Chaboche kinematic hardening model using a multi objective Genetic Algorithm. Computational Materials Science, 50, 1114-1122, Jan 2011. https://doi.org/10.1016/ j.commatsci.2010.11.010
  • J. H. Yongfeng Li, Bin Gu, Shuhui Li, Identification of advanced constitutive model parameters through global optimization approach for DP780 steel sheet. Procedia Engineering, 207, 125-130, 2017. https://doi.org/ 10.1016/j.proeng.2017.10.749
  • D. T. Pham and M. Castellani, Benchmarking and comparison of nature-inspired population-based continuous optimisation algorithms. Soft Computing, 18, 871-903, May 2014. https://doi.org/10.1007/ s00500-013-1104-9
  • D. T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, and M. Zaidi, The Bees Algorithm technical note. Manufacturing Engineering Centre, 1-57, 2005.
  • D. T. Pham, A. Ghanbarzadeh, E. Koç, S. Otri, S. Rahim, and M. Zaidi, The Bees Algorithm - A novel tool for complex optimisation problems. Manufacturing Engineering Centre, 454-458, 2006. https://doi.org/10.1016/B978-008045157-2/50081-X
  • A. A. Fahmy, M. Kalyoncu, and M. Castellani, Automatic design of control systems for robot manipulators using the bees algorithm. Proceedings of the Institution of Mechanical Engineers Part I-Journal of Systems and Control Engineering, 226, 497-508, Apr 2012.
  • D. T. Pham, E. Koç, M. Kalyoncu, and M. Tınkır, Hierarchical PID controller design for a flexible link robot manipulator using The Bees Algorithm. Proceedings of Proceedings of 6th International Symposium on Intelligent Manufacturing Systems, Sakarya, Turkey, 2008.
  • D. T. Pham and M. Kalyoncu, Optimisation of a Fuzzy Logic Controller for a flexible single-link robot arm using The Bees Algorithm. Proceedings of 7th IEEE International Conference on Industrial Informatics, Cardiff, UK, 2009.
  • M. A. Sen, V. Bakırcıoğlu, and M. Kalyoncu, Performances comparison of The Bees Algorithm and Genetic Algorithm for PID controller tuning. Proceedings of 5th International Mechatronics and Control Engineering, Venice, Italy, 2016.
  • O. Öztürk, M. Kalyoncu, and A. Ünüvar, Multi objective optimization of cutting parameters in a single pass turning operation using The Bees Algorithm. Proceedings of 1st International Conference on Advances in Mechanical and Mechatronics Engineering, Ankara/TURKEY, 2018.
  • O. Acar, M. Kalyoncu, and A. Hassan, The design optimization of a gripper mechanism using The Bees’ Algorithm. Proceedings of International Conference on Engineering Technologies (ICENTE'18), Konya/TURKEY, 2018.
  • O. Acar, M. Kalyoncu, and A. Hassan, Proposal of a harmonic Bees Algorithm for design optimization of a gripper mechanism, Cham, 2019, 2829-2839. https://doi.org/10.1007/978-3-030-20131-9_280
  • Anonymous. (2019). MATLAB global optimization toolbox sser's guide. Available: https://www. mathworks.com/help/gads/index.html. (Accessed March 12nd, 2021)
  • P. C. B. Abdulaziz Alghtani, D.C. Barton, V.V. Toropov, Springback analysis and optimization in sheet metal forming. Proceedings of 9th European LS-DYNA Conference, Manchester, 2013.
  • D. E. G. Ali Aryanpour, Evaluation of LS-DYNA material models for the analysis of sidewall curl in advanced high strength steels. Proceedings of 12th International LS-DYNA Conference, Detroit, 2012.
  • S. Tamura, S. Sumikawa, T. Uemori, H. Hamasaki, and F. Yoshida, Experimental observation of elasto-plasticity behavior of type 5000 and 6000 aluminum alloy sheets, Materials Transactions, 52, 868-875, May 2011. https://doi.org/10.2320/matertrans.L-MZ201101
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Mühendisliği
Bölüm Makine Mühendisliği
Yazarlar

Habip Gökay Korkmaz 0000-0003-2670-7912

Serkan Toros 0000-0003-0438-2862

Mete Kalyoncu 0000-0002-2214-7631

Yayımlanma Tarihi 27 Temmuz 2021
Gönderilme Tarihi 17 Mart 2021
Kabul Tarihi 5 Mayıs 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 10 Sayı: 2

Kaynak Göster

APA Korkmaz, H. G., Toros, S., & Kalyoncu, M. (2021). Prediction of Yoshida Uemori model parameters by The Bees Algorithm and Genetic Algorithm for 5xxx series aluminium alloys. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 10(2), 815-823. https://doi.org/10.28948/ngumuh.895920
AMA Korkmaz HG, Toros S, Kalyoncu M. Prediction of Yoshida Uemori model parameters by The Bees Algorithm and Genetic Algorithm for 5xxx series aluminium alloys. NÖHÜ Müh. Bilim. Derg. Temmuz 2021;10(2):815-823. doi:10.28948/ngumuh.895920
Chicago Korkmaz, Habip Gökay, Serkan Toros, ve Mete Kalyoncu. “Prediction of Yoshida Uemori Model Parameters by The Bees Algorithm and Genetic Algorithm for 5xxx Series Aluminium Alloys”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 10, sy. 2 (Temmuz 2021): 815-23. https://doi.org/10.28948/ngumuh.895920.
EndNote Korkmaz HG, Toros S, Kalyoncu M (01 Temmuz 2021) Prediction of Yoshida Uemori model parameters by The Bees Algorithm and Genetic Algorithm for 5xxx series aluminium alloys. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 10 2 815–823.
IEEE H. G. Korkmaz, S. Toros, ve M. Kalyoncu, “Prediction of Yoshida Uemori model parameters by The Bees Algorithm and Genetic Algorithm for 5xxx series aluminium alloys”, NÖHÜ Müh. Bilim. Derg., c. 10, sy. 2, ss. 815–823, 2021, doi: 10.28948/ngumuh.895920.
ISNAD Korkmaz, Habip Gökay vd. “Prediction of Yoshida Uemori Model Parameters by The Bees Algorithm and Genetic Algorithm for 5xxx Series Aluminium Alloys”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 10/2 (Temmuz 2021), 815-823. https://doi.org/10.28948/ngumuh.895920.
JAMA Korkmaz HG, Toros S, Kalyoncu M. Prediction of Yoshida Uemori model parameters by The Bees Algorithm and Genetic Algorithm for 5xxx series aluminium alloys. NÖHÜ Müh. Bilim. Derg. 2021;10:815–823.
MLA Korkmaz, Habip Gökay vd. “Prediction of Yoshida Uemori Model Parameters by The Bees Algorithm and Genetic Algorithm for 5xxx Series Aluminium Alloys”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, c. 10, sy. 2, 2021, ss. 815-23, doi:10.28948/ngumuh.895920.
Vancouver Korkmaz HG, Toros S, Kalyoncu M. Prediction of Yoshida Uemori model parameters by The Bees Algorithm and Genetic Algorithm for 5xxx series aluminium alloys. NÖHÜ Müh. Bilim. Derg. 2021;10(2):815-23.

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