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ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI

Yıl 2021, Cilt: 26 Sayı: 3, 937 - 954, 31.12.2021

Murat Hiçyılmaz

https://doi.org/10.17482/uumfd.917271

Öz

Metasezgisel optimizasyon yöntemleri 1990'lı yıllardan beri mühendislik problemlerini çözmek için kullanılmaktadır. Sadece bir fazı olan ve probleme özgü bir kontrol parametresi gerektirmeyen Jaya algoritması, çelik yapıların tasarımında oldukça etkili bir metasezgisel yöntemdir. Bu çalışmanın amacı, eksenel kuvvet ve eğilme momenti altındaki çok parçalı basınç çubuklarının ağırlık bakımından optimum tasarımında Jaya algoritmasının kullanılabilirliğini değerlendirmektir. Bununla birlikte, farklı tür ve ebatlardaki profil ve ara bağlantı tiplerinin optimum tasarım üzerindeki etkileri de incelenmiştir. Bu amaçla, kafes örgü elemanı ya da bağ levhaları ile birbirine bağlanan dört farklı tipte çok parçalı basınç çubuğu modeli oluşturulmuştur. Kolon elemanları olarak geniş başlıklı H profiller ve U profiller, kafes örgü elemanı olarak ise eşit kollu korniyerler kullanılmıştır. Kullanılan bu elemanlar sıcak haddelenmiş Avrupa enkesitleri arasından seçilmiştir. Kolon enkesiti ve ara mesafesi, kafes örgü elemanı ve bağ levhalarının enkesit özellikleri ve yerleşimleri ana tasarım değişkenleri olarak kullanılmıştır. Elde edilen nümerik sonuçlar değerlendirildiğinde, Jaya algoritmasının çok parçalı basınç çubuklarının optimum ağırlık tasarımında kullanılabilir olduğu sonucuna ulaşılmıştır.

Anahtar Kelimeler

Optimizasyon Metasezgisel arama Jaya algoritması Çok parçalı basınç çubukları Eurocode 3

Kaynakça

  • 1. Abhishek, K., Kumar, V.R., Datta, S. ve Mahapatra, S.S. (2016) Application of jaya algorithm for the optimization of machining performance characteristics during the turning of cfrp (epoxy) composites: comparison with tlbo, ga, and ica, Engineering with Computers doi:10.1007/s00366-016-0484-8
  • 2. Aslani, F. ve Goel, S.C. (1991) Stitch spacing and local buckling in seismicresistant double-angle braces, J Struct Eng ASCE 117 2442–63.
  • 3. Beyer, H.G. ve Schwefel, H.P. (2002) Evolution strategies a comprehensive introduction, Nat Comput, 1 3–52.
  • 4. Bleich, F. (1952) Buckling strength of metal structures, 2nd ed. New York: McGraw-Hill Book Company.
  • 5. Bredenkamp, P.J., Berg, G.J. ve Johannesburg, P.M. (1998) The behaviour of hot-rolled and built-up stainless steel structural members, J. Construct. Steel Res. 46.
  • 6. Dede, T. (2018) Jaya algorithm to solve single objective size optimization problem for steel grillage structures, Steel and Composite Structures, 26, 163-170.
  • 7. Değertekin, S.O., Lamberti, L. ve Uğur, I.B. (2018) Sizing, layout and topology design optimization of truss structures using the Jaya algorithm, Applied Soft Computing, 70 903– 928. doi: 10.1016/j.asoc.2017.10.001
  • 8. Değertekin, S.O., Lamberti, L. ve Uğur, İ.B. (2018) Discrete and continuous design optimization of tower structures using the jaya algorithm, Technological Applied Sciences (NWSATAS), 13(2) 134-144.
  • 9. Dorigo, M., Birattari, M. ve Stutzle, T. (2006) Ant colony optimization—artificial ants as a computational intelligence technique, IEEE Comput Intell Mag, 28–39.
  • 10. Du, D.C., Vinh, H.H., Trung, V.D., Quyen, N.T. ve Trung, N.T. (2018) Efficiency of Jaya algorithm for solving the optimization-based structural damage identification problem based on a hybrid objective function, Engineering Optimization, 50:81233-1251. doi: 10.1080/0305215X.2017.1367392
  • 11. Duan, L., Reno, M. ve Uang, C.M. (2002) Effect of compound buckling on compression, Strength of Built-up Members Engineering Journal, 39, 30-37.
  • 12. Erol, O.K. ve Eksin, I. (2006) A new optimization method: Big bang– big crunch, Adv. Eng. Soft, 37106–111.
  • 13. Eurocode 3: (2002) Design of steel structures. Part 1.1: general structural rules. CEN-European Committee for Standardisation, Brussels, EN1993-1-1.
  • 14. Gandomi, A.H., Yang, X.S. ve Alavi, A.H. (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems, Engineering with Computers, 29 17–35.
  • 15. Grzywiński, M., Dede, T. ve Özdemir, Y.I. (2019) Optimization of the braced dome structures by using Jaya algorithm with frequency constraints, Steel and Composite Structures, 3047–55. doi: 10.12989/scs.2019.30.1.047
  • 16. Hatamlou, A. (2013) Black hole: A new heuristic optimization approach for data clustering, Inf. Sci. 222, 175–184.
  • 17. Holland, J.H. (1975) Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor.
  • 18. Kalochairetis, K.E., Gantes, C.J. ve Lignos, X.A. (2014) Experimental and numerical investigation of eccentrically loaded laced built-up steel columns, Journal of Constructional Steel Research, 101 66-81. doi.org/10.1016/j.jcsr.2014.04.032
  • 19. Karaboğa, D. Ve Basturk, B. (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, J Glob Optim. 39-3, 459–471.
  • 20. Kaveh, A. ve Khayatazad, M. (2012) A new meta-heuristic method: Ray optimization, Comput.Struct., 112, 283–294.
  • 21. Kennedy, J. ve Eberhart, R.C. (1995) Particle swarm optimization, Proceedings of IEEE international conference on neural networks, 1942–1948.
  • 22. Kirkpatrick, S., Gelatt, C.D. ve Vecchi, M.P. (1983) Optimization by simulated annealing, Science, 220 671–680.
  • 23. Konstantinos, E., Kalochairetis, C. ve Gantes, J. (2011) Numerical and analytical investigation of collapse loads of laced built-up columns, Computers & Structures, 891166-1176.
  • 24. Koza, J.R. (1992) Genetic programming II, automatic discovery of reusable subprograms, MIT Press, Cambridge.
  • 25. Liu, J.L., Lue, D.M. ve Lin, C.H. (2009) Investigation on slenderness ratios of built-up compression members, Journal of Constructional Steel Research, 65-1237-248 doi.org/10.1016/j.jcsr.2008.02.012
  • 26. MatLab Release (2016) The MathWorks Inc., Natick, MA, USA
  • 27. Orbán, F. ve Farkas, J. (2013) Optimum design of steel built-up compression members, Design, Fabrication and Economy of Metal Structures International Conference Proceedings
  • 28. Qing, (2009) A. Differential evolution, Fundamentals and applications in electrical engineering, Wiley.
  • 29. Rao, R.V. (2016) Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems, Int. J. Ind. Eng. Comput.,719–34.
  • 30. Rao, R.V. ve More, K.C. (2017) Design optimization and analysis of selected thermal devices using self-adaptive jaya algorithm, Energy Conversion and Management 14024–35. doi:10.1016/j.enconman.2017.02.068
  • 31. Rao, R.V., Rai, D.P., Ramkumar, J. ve Balic, J. (2016) A new multi-objective jaya algorithm for optimization of modern machining processes, Advances in Production Engineering & Management, 11 (4) 271–286. doi:10.14743/apem2016.4.226.
  • 32. Šapalas, V., Daniūnas, A. ve Urbonasc, K. (2013) Built-up axial loaded column fe modelling and design according to STR and EC3, Procedia Engineering, 57, 1131 – 1137.
  • 33. Shu, T.G. ve Fan, C.S. (1989) An interactive buckling theory for built-up beam-columns and its application to centrally compressed built-up members, Journal of Constructional Steel Research, 14221-241. doi.org/10.1016/0143-974X(89)90074-6
  • 34. Storn, R., ve Price, K. (1995) Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces, Technical Report TR-ICSI, 95-012.
  • 35. Timoshenko, S.P. ve Gere, J.M. (1961)Theory of elastic stability, Second Edition McGraw-Hill Book Company New York.
  • 36. Waheed, A., Vafaei, M., Alih, S.C. ve Ullah, R. (2020) Experimental and numerical investigations on the seismic response of built-up battened columns, Journal of Constructional Steel Research, 174 https://doi.org/10.1016/j.jcsr.2020.106296
  • 37. Yang, X.S. (2010) Nature-inspired metaheuristic algorithms, Second Edition Luniver Press
  • 38. Yildiz, A.R., Abderazek, H. ve Mirjalili, S. (2020) A comparative study of recent non-traditional methods for mechanical design, Optimization Archives of Computational Methods in Engineering, 27, 1031–1048.

Optimum Weight Design of Built-Up Steel Columns Using The Jaya Algorithm

Yıl 2021, Cilt: 26 Sayı: 3, 937 - 954, 31.12.2021

Murat Hiçyılmaz

https://doi.org/10.17482/uumfd.917271

Öz

Metaheuristic optimization methods have been used to solve engineering problems since 1990’s. The Jaya algorithm which has only one phase and doesn’t require any specific control parameters is a very effective metaheuristic method for designing steel structures. The objective of this study is to evaluate the usability of the Jaya in optimum weight design of hot rolled built-up steel columns under compressive axial force and bending moment. However, the effects of different profile and interconnection types on optimum design were also examined. For this purpose, four structural types of built-up columns with two different ways of interconnecting as lacing and battening are used. In a wide range of dimensions, European standard wide flange and channel types of hot-rolled steel sections are used as chords and equal angels as laces. Dimension of chords and the distance between them, dimension and placement of the lacings and battenings are used as the main design variables. The numerical results show that Jaya is a very effective and useful algorithm to obtain the optimum weight of built-up steel columns.

Anahtar Kelimeler

Optimization Metaheuristic search Jaya algorithm Built-up columns Eurocode 3

Kaynakça

  • 1. Abhishek, K., Kumar, V.R., Datta, S. ve Mahapatra, S.S. (2016) Application of jaya algorithm for the optimization of machining performance characteristics during the turning of cfrp (epoxy) composites: comparison with tlbo, ga, and ica, Engineering with Computers doi:10.1007/s00366-016-0484-8
  • 2. Aslani, F. ve Goel, S.C. (1991) Stitch spacing and local buckling in seismicresistant double-angle braces, J Struct Eng ASCE 117 2442–63.
  • 3. Beyer, H.G. ve Schwefel, H.P. (2002) Evolution strategies a comprehensive introduction, Nat Comput, 1 3–52.
  • 4. Bleich, F. (1952) Buckling strength of metal structures, 2nd ed. New York: McGraw-Hill Book Company.
  • 5. Bredenkamp, P.J., Berg, G.J. ve Johannesburg, P.M. (1998) The behaviour of hot-rolled and built-up stainless steel structural members, J. Construct. Steel Res. 46.
  • 6. Dede, T. (2018) Jaya algorithm to solve single objective size optimization problem for steel grillage structures, Steel and Composite Structures, 26, 163-170.
  • 7. Değertekin, S.O., Lamberti, L. ve Uğur, I.B. (2018) Sizing, layout and topology design optimization of truss structures using the Jaya algorithm, Applied Soft Computing, 70 903– 928. doi: 10.1016/j.asoc.2017.10.001
  • 8. Değertekin, S.O., Lamberti, L. ve Uğur, İ.B. (2018) Discrete and continuous design optimization of tower structures using the jaya algorithm, Technological Applied Sciences (NWSATAS), 13(2) 134-144.
  • 9. Dorigo, M., Birattari, M. ve Stutzle, T. (2006) Ant colony optimization—artificial ants as a computational intelligence technique, IEEE Comput Intell Mag, 28–39.
  • 10. Du, D.C., Vinh, H.H., Trung, V.D., Quyen, N.T. ve Trung, N.T. (2018) Efficiency of Jaya algorithm for solving the optimization-based structural damage identification problem based on a hybrid objective function, Engineering Optimization, 50:81233-1251. doi: 10.1080/0305215X.2017.1367392
  • 11. Duan, L., Reno, M. ve Uang, C.M. (2002) Effect of compound buckling on compression, Strength of Built-up Members Engineering Journal, 39, 30-37.
  • 12. Erol, O.K. ve Eksin, I. (2006) A new optimization method: Big bang– big crunch, Adv. Eng. Soft, 37106–111.
  • 13. Eurocode 3: (2002) Design of steel structures. Part 1.1: general structural rules. CEN-European Committee for Standardisation, Brussels, EN1993-1-1.
  • 14. Gandomi, A.H., Yang, X.S. ve Alavi, A.H. (2013) Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems, Engineering with Computers, 29 17–35.
  • 15. Grzywiński, M., Dede, T. ve Özdemir, Y.I. (2019) Optimization of the braced dome structures by using Jaya algorithm with frequency constraints, Steel and Composite Structures, 3047–55. doi: 10.12989/scs.2019.30.1.047
  • 16. Hatamlou, A. (2013) Black hole: A new heuristic optimization approach for data clustering, Inf. Sci. 222, 175–184.
  • 17. Holland, J.H. (1975) Adaptation in natural and artificial systems, University of Michigan Press, Ann Arbor.
  • 18. Kalochairetis, K.E., Gantes, C.J. ve Lignos, X.A. (2014) Experimental and numerical investigation of eccentrically loaded laced built-up steel columns, Journal of Constructional Steel Research, 101 66-81. doi.org/10.1016/j.jcsr.2014.04.032
  • 19. Karaboğa, D. Ve Basturk, B. (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, J Glob Optim. 39-3, 459–471.
  • 20. Kaveh, A. ve Khayatazad, M. (2012) A new meta-heuristic method: Ray optimization, Comput.Struct., 112, 283–294.
  • 21. Kennedy, J. ve Eberhart, R.C. (1995) Particle swarm optimization, Proceedings of IEEE international conference on neural networks, 1942–1948.
  • 22. Kirkpatrick, S., Gelatt, C.D. ve Vecchi, M.P. (1983) Optimization by simulated annealing, Science, 220 671–680.
  • 23. Konstantinos, E., Kalochairetis, C. ve Gantes, J. (2011) Numerical and analytical investigation of collapse loads of laced built-up columns, Computers & Structures, 891166-1176.
  • 24. Koza, J.R. (1992) Genetic programming II, automatic discovery of reusable subprograms, MIT Press, Cambridge.
  • 25. Liu, J.L., Lue, D.M. ve Lin, C.H. (2009) Investigation on slenderness ratios of built-up compression members, Journal of Constructional Steel Research, 65-1237-248 doi.org/10.1016/j.jcsr.2008.02.012
  • 26. MatLab Release (2016) The MathWorks Inc., Natick, MA, USA
  • 27. Orbán, F. ve Farkas, J. (2013) Optimum design of steel built-up compression members, Design, Fabrication and Economy of Metal Structures International Conference Proceedings
  • 28. Qing, (2009) A. Differential evolution, Fundamentals and applications in electrical engineering, Wiley.
  • 29. Rao, R.V. (2016) Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems, Int. J. Ind. Eng. Comput.,719–34.
  • 30. Rao, R.V. ve More, K.C. (2017) Design optimization and analysis of selected thermal devices using self-adaptive jaya algorithm, Energy Conversion and Management 14024–35. doi:10.1016/j.enconman.2017.02.068
  • 31. Rao, R.V., Rai, D.P., Ramkumar, J. ve Balic, J. (2016) A new multi-objective jaya algorithm for optimization of modern machining processes, Advances in Production Engineering & Management, 11 (4) 271–286. doi:10.14743/apem2016.4.226.
  • 32. Šapalas, V., Daniūnas, A. ve Urbonasc, K. (2013) Built-up axial loaded column fe modelling and design according to STR and EC3, Procedia Engineering, 57, 1131 – 1137.
  • 33. Shu, T.G. ve Fan, C.S. (1989) An interactive buckling theory for built-up beam-columns and its application to centrally compressed built-up members, Journal of Constructional Steel Research, 14221-241. doi.org/10.1016/0143-974X(89)90074-6
  • 34. Storn, R., ve Price, K. (1995) Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces, Technical Report TR-ICSI, 95-012.
  • 35. Timoshenko, S.P. ve Gere, J.M. (1961)Theory of elastic stability, Second Edition McGraw-Hill Book Company New York.
  • 36. Waheed, A., Vafaei, M., Alih, S.C. ve Ullah, R. (2020) Experimental and numerical investigations on the seismic response of built-up battened columns, Journal of Constructional Steel Research, 174 https://doi.org/10.1016/j.jcsr.2020.106296
  • 37. Yang, X.S. (2010) Nature-inspired metaheuristic algorithms, Second Edition Luniver Press
  • 38. Yildiz, A.R., Abderazek, H. ve Mirjalili, S. (2020) A comparative study of recent non-traditional methods for mechanical design, Optimization Archives of Computational Methods in Engineering, 27, 1031–1048.
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İnşaat Mühendisliği
Bölüm Araştırma Makaleleri
Yazarlar

Murat Hiçyılmaz 0000-0002-4132-4285

Yayımlanma Tarihi 31 Aralık 2021
Gönderilme Tarihi 16 Nisan 2021
Kabul Tarihi 12 Eylül 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 26 Sayı: 3

Kaynak Göster

APA Hiçyılmaz, M. (2021). ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, 26(3), 937-954. https://doi.org/10.17482/uumfd.917271
AMA Hiçyılmaz M. ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI. UUJFE. Aralık 2021;26(3):937-954. doi:10.17482/uumfd.917271
Chicago Hiçyılmaz, Murat. “ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 26, sy. 3 (Aralık 2021): 937-54. https://doi.org/10.17482/uumfd.917271.
EndNote Hiçyılmaz M (01 Aralık 2021) ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 26 3 937–954.
IEEE M. Hiçyılmaz, “ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI”, UUJFE, c. 26, sy. 3, ss. 937–954, 2021, doi: 10.17482/uumfd.917271.
ISNAD Hiçyılmaz, Murat. “ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 26/3 (Aralık 2021), 937-954. https://doi.org/10.17482/uumfd.917271.
JAMA Hiçyılmaz M. ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI. UUJFE. 2021;26:937–954.
MLA Hiçyılmaz, Murat. “ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, c. 26, sy. 3, 2021, ss. 937-54, doi:10.17482/uumfd.917271.
Vancouver Hiçyılmaz M. ÇOK PARÇALI BASINÇ ÇUBUKLARININ JAYA ALGORİTMASI İLE OPTİMUM AĞIRLIK TASARIMI. UUJFE. 2021;26(3):937-54.

DUYURU:

30.03.2021- Nisan 2021 (26/1) sayımızdan itibaren TR-Dizin yeni kuralları gereği, dergimizde basılacak makalelerde, ilk gönderim aşamasında Telif Hakkı Formu yanısıra, Çıkar Çatışması Bildirim Formu ve Yazar Katkısı Bildirim Formu da tüm yazarlarca imzalanarak gönderilmelidir. Yayınlanacak makalelerde de makale metni içinde "Çıkar Çatışması" ve "Yazar Katkısı" bölümleri yer alacaktır. İlk gönderim aşamasında doldurulması gereken yeni formlara "Yazım Kuralları" ve "Makale Gönderim Süreci" sayfalarımızdan ulaşılabilir. (Değerlendirme süreci bu tarihten önce tamamlanıp basımı bekleyen makalelerin yanısıra değerlendirme süreci devam eden makaleler için, yazarlar tarafından ilgili formlar doldurularak sisteme yüklenmelidir).  Makale şablonları da, bu değişiklik doğrultusunda güncellenmiştir. Tüm yazarlarımıza önemle duyurulur.

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