BASINÇ VE EĞİLME ALTINDAKİ ELİPTİK KOLONLARIN TAŞIMA KAPASİTELERİNİN ESNEK HESAPLAMA YÖNTEMLERİ İLE TAHMİNİ

Yıl 2024, Cilt: 27 Sayı: 3, 985 – 998, 03.09.2024

Mehmet Kurt , Esra Mete Güneyisi , Kasım Mermerdaş

https://doi.org/10.17780/ksujes.1443578

Öz

Son yıllarda hem yüksek mukavemeti hem de sıcak veya soğuk haddelenmiş olarak bulunması sebebiyle, eliptik profillerin kullanımına yönelik ilgi artmaktadır. Eliptik kesitler içsel estetik özelliklerinin yanı sıra küçük ve büyük eksen özelliklerine sahip olmaları ile avantaj sağlamaktadırlar. Sunulan çalışmada esnek hesaplama yöntemlerinden gen ekspresyonu programlama ve yapay sinir ağları yöntemleri kullanılarak, basınç ve eğilme etkisindeki eliptik kesitli çelik boru profilden oluşturulmuş kolonlarının maksimum yük taşıma kapasitelerinin tahmini için sayısal modeller geliştirilmiştir. Bu amaçla, mevcut literatürdeki deneysel veriler kullanılarak modellerin eğitimi ve doğrulaması gerçekleştirilmiştir. Araştırmada kullanılan eliptik kolonlar, küçük ve büyük eksenleri dikkate alınarak dışmerkezli ve merkezi eksenel yük altında eğilme burkulması testine tabi tutulmuştur. Modellemede dokuz farklı değişken kullanılmıştır. Bunlar burkulma ekseni, y ve z yönlerindeki dışmerkezlik değeri, kesitin büyük ve küçük dış çapları, cidar kalınlığı, çeliğin akma dayanımı, çekme dayanımı ve eleman boyudur. Elde edilen bu modeller istatistik açıdan irdelenmiştir. Ayrıca, önerilen modellerin güvenilirliği ve tekrarlanabilirliği gerçek deneysel verilerle karşılaştırılmalı olarak analiz edilmiş; önerilen gen ekspresyonu programlama modeli ile deneysel veriler arasında korelasyonun test veri kümesi için 0,84 olduğu, diğer taraftan yapay sinir ağları modeli için ise bu değerin 0,99 olduğu görülmüştür.

Anahtar Kelimeler

Çelik kolon, eliptik kesit, modelleme, tahmin, yük taşıma kapasitesi

Kaynakça

• Chan, T.M., & Gardner, L. (2008a). Bending strength of hot-rolled elliptical hollow sections. Journal of Constructional Steel Research, 64(9), 971–86. https://doi.org/10.1016/j.jcsr.2007.11.001
• Chan, T.M., & Gardner, L. (2008b). Compressive resistance of hot-rolled elliptical hollow sections. Engineering Structures; 30(2), 522–32. https://doi.org/10.1016/j.engstruct.2007.04.019
• Chan, T.M., & Gardner, L. (2009). Flexural buckling of elliptical hollow section columns. ASCE, Journal of Structural Engineering, 135(5), 546-557. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000005
• Corus (2006). Celsius 355 Ovals, Corus Tubes—Structural & Conveyance Business, Corby, U.K.
• D’Aniello, M., Güneyisi, E.M., Landolfo, R. & Mermerdaş, K. (2014). Analytical prediction of available rotation capacity of cold-formed rectangular and square hollow section beams. Thin-Walled Structures, 77(April), 141-152. https://doi.org/10.1016/j.tws.2013.09.015
• D’Aniello, M., Güneyisi, E.M., Landolfo, R. & Mermerdaş, K. (2015). Predictive models of the flexural overstrength factor for steel thin-walled circular hollow section beams, Thin-Walled Structures, 94(September), 67-78. https://doi.org/10.1016/j.tws.2015.03.020
• Ferreira, C. (2001). Gene expression programming: a new adaptive algorithm for solving problems. Complex Systems, 13(2), 87-129. https://doi.org/10.48550/arXiv.cs/0102027
• Gardner, L., Chan, T.M. & Abela, J.M. (2011). Structural behaviour of elliptical hollow sections under combined compression and uniaxial bending. Advanced Steel Construction, 7(1), 86–113. https://doi.org/10.18057/IJASC.2011.7.1.6
• Gardner, L., & Chan, T.M. (2007). Cross-section classification of elliptical hollow sections. Steel and Composite Structures, 7(3), 185–200. https://doi.org/10.12989/scs.2007.7.3.185
• Gardner, L., Chan, T.M., & Wadee, M.A. (2008). Shear response of elliptical hollow sections. Proceedings of the Institution of Civil Engineers -Structures and Buildings, 161(6), 301–309.
• Goldberg, D. (1989). Genetic Algorithms in search, optimization and machine learning. MA: Addison-Welsley.
• İpek, S., & Güneyisi, E.M. (2022) Application of Eurocode 4 design provisions and development of new predictive models for eccentrically loaded CFST elliptical columns, Journal of Building Engineering, 48, 103945. https://doi.org/10.1016/j.jobe.2021.103945
• Koza, J.R. (1992). Genetic programming: On the programming of computers by means of natural selection. MIT Press.
• Law, K.H., & Gardner, L. (2013). Buckling of elliptical hollow section members under combined compression and uniaxial bending. Journal of Constructional Steel Research, 86(July), 1-16. https://doi.org/10.1016/j.jcsr.2013.03.008
• Levenberg, K. (1944). A method for the solution of certain non-linear problems in least squares. Quarterly of Applied Mathematics, 2, 164–168. https://www.jstor.org/stable/43633451.
• Nowzartash, F., & Mohareb, M. (2009). Plastic interaction relations for elliptical hollow sections. Thin-Walled Structures, 47(6–7), 681–691. https://doi.org/10.1016/j.tws.2008.11.010
• Ruiz-Teran, A.M., & Gardner, L. (2008). Elastic buckling of elliptical tubes. Thin-Walled Structures, 46(11), 1304–1318. https://doi.org/10.1016/j.tws.2008.01.036
• Theofanous, M., Chan, T.M., & Gardner, L. (2009). Flexural behaviour of stainless steel oval hollow sections. Thin-Walled Structures, 47(6–7), 776-787. https://doi.org/10.1016/j.tws.2009.01.001
• Wasserman, P.D. (1989). Neural Computing Theory and Practice. Van Nostrand Reinhold Co., New York, USA. Vinuela-Rueda, L., & Martinez-Salcedo, J. (2006). Steel structure and prestressed façade of the new terminal building, Hormigon Acero, 239(1), 71–84.
• Yang, H., Lam, D., & Gardner, L. (2008). Testing and analysis of concrete-filled elliptical hollow sections. Engineering Structures; 30(12), 3771– 3781. https://doi.org/10.1016/j.engstruct.2008.07.004
• Zadeh, L.A. (1994). Soft-computing and fuzzy logic. IEEE Software, 11(6), 48–56. https://doi.org/10.1109/52.329401
• Zhang, Z., & Friedrich, K. (2003). Artificial neural networks applied to polymer composites: a review. Composites Science and Technology, 63(14), 2029–2044. https://doi.org/10.1016/S0266-3538(03)00106-4
• Zhao, X.L., & Packer, J.A. (2009). Tests and design of concrete-filled elliptical hollow section stub columns. Thin-Walled Structures, 47(6–7), 617–628. https://doi.org/10.1016/j.tws.2008.11.004
• Zhao, X.L., Lu, H., & Galteri, S. Tests of elliptical hollow sections filled with SCC self-compacting concrete. In 2007, 5th International Conference on Advances in Steel Structures, Singapore, Research Publishing Services, Singapore, 950–955.
• Zhu, Y., & Wilkinson, T. Finite-element analysis of structural steel elliptical hollow sections in pure compression. In 2006 11th International Symposium on Tubular Structures, Québec City, Canada, Taylor & Francis, London, 179–186.

ULTIMATE CAPACITY PREDICTION OF ELLIPTICAL SECTION COLUMNS IN COMPRESSION AND BENDING BY SOFT COMPUTING METHODS

Yıl 2024, Cilt: 27 Sayı: 3, 985 – 998, 03.09.2024

Mehmet Kurt , Esra Mete Güneyisi , Kasım Mermerdaş

https://doi.org/10.17780/ksujes.1443578

Öz

In recent years, there has been a growing interest in the use of elliptical profiles as having high strength and being as hot-rolled or cold-formed. Elliptical sections provide superiority with their minor and major axis properties as well as their aesthetic features. In this study, by using soft computing methods such as gene expression programming and artificial neural network, numerical models were developed to estimate the load carrying capacity of elliptical columns under compression and bending. For this, training and testing of the models were conducted using experimental data from the existing literature. Nine different variables were utilized, namely, buckling axis, eccentricity in the y and z directions, large and small outer diameters of the section, wall thickness, yield and tensile strength of the steel and column length. The proposed models were statistically examined. Moreover, the robustness and repeatability of the proposed models were analyzed in comparison with actual experimental data; for the testing data set, it was observed that the correlation coefficient for the gene expression programming model was 0.84 while that for the artificial neural network model was 0.99.

Anahtar Kelimeler

Steel column, elliptical section, modeling, prediction, load carrying capacity

Kaynakça

• Chan, T.M., & Gardner, L. (2008a). Bending strength of hot-rolled elliptical hollow sections. Journal of Constructional Steel Research, 64(9), 971–86. https://doi.org/10.1016/j.jcsr.2007.11.001
• Chan, T.M., & Gardner, L. (2008b). Compressive resistance of hot-rolled elliptical hollow sections. Engineering Structures; 30(2), 522–32. https://doi.org/10.1016/j.engstruct.2007.04.019
• Chan, T.M., & Gardner, L. (2009). Flexural buckling of elliptical hollow section columns. ASCE, Journal of Structural Engineering, 135(5), 546-557. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000005
• Corus (2006). Celsius 355 Ovals, Corus Tubes—Structural & Conveyance Business, Corby, U.K.
• D’Aniello, M., Güneyisi, E.M., Landolfo, R. & Mermerdaş, K. (2014). Analytical prediction of available rotation capacity of cold-formed rectangular and square hollow section beams. Thin-Walled Structures, 77(April), 141-152. https://doi.org/10.1016/j.tws.2013.09.015
• D’Aniello, M., Güneyisi, E.M., Landolfo, R. & Mermerdaş, K. (2015). Predictive models of the flexural overstrength factor for steel thin-walled circular hollow section beams, Thin-Walled Structures, 94(September), 67-78. https://doi.org/10.1016/j.tws.2015.03.020
• Ferreira, C. (2001). Gene expression programming: a new adaptive algorithm for solving problems. Complex Systems, 13(2), 87-129. https://doi.org/10.48550/arXiv.cs/0102027
• Gardner, L., Chan, T.M. & Abela, J.M. (2011). Structural behaviour of elliptical hollow sections under combined compression and uniaxial bending. Advanced Steel Construction, 7(1), 86–113. https://doi.org/10.18057/IJASC.2011.7.1.6
• Gardner, L., & Chan, T.M. (2007). Cross-section classification of elliptical hollow sections. Steel and Composite Structures, 7(3), 185–200. https://doi.org/10.12989/scs.2007.7.3.185
• Gardner, L., Chan, T.M., & Wadee, M.A. (2008). Shear response of elliptical hollow sections. Proceedings of the Institution of Civil Engineers -Structures and Buildings, 161(6), 301–309.
• Goldberg, D. (1989). Genetic Algorithms in search, optimization and machine learning. MA: Addison-Welsley.
• İpek, S., & Güneyisi, E.M. (2022) Application of Eurocode 4 design provisions and development of new predictive models for eccentrically loaded CFST elliptical columns, Journal of Building Engineering, 48, 103945. https://doi.org/10.1016/j.jobe.2021.103945
• Koza, J.R. (1992). Genetic programming: On the programming of computers by means of natural selection. MIT Press.
• Law, K.H., & Gardner, L. (2013). Buckling of elliptical hollow section members under combined compression and uniaxial bending. Journal of Constructional Steel Research, 86(July), 1-16. https://doi.org/10.1016/j.jcsr.2013.03.008
• Levenberg, K. (1944). A method for the solution of certain non-linear problems in least squares. Quarterly of Applied Mathematics, 2, 164–168. https://www.jstor.org/stable/43633451.
• Nowzartash, F., & Mohareb, M. (2009). Plastic interaction relations for elliptical hollow sections. Thin-Walled Structures, 47(6–7), 681–691. https://doi.org/10.1016/j.tws.2008.11.010
• Ruiz-Teran, A.M., & Gardner, L. (2008). Elastic buckling of elliptical tubes. Thin-Walled Structures, 46(11), 1304–1318. https://doi.org/10.1016/j.tws.2008.01.036
• Theofanous, M., Chan, T.M., & Gardner, L. (2009). Flexural behaviour of stainless steel oval hollow sections. Thin-Walled Structures, 47(6–7), 776-787. https://doi.org/10.1016/j.tws.2009.01.001
• Wasserman, P.D. (1989). Neural Computing Theory and Practice. Van Nostrand Reinhold Co., New York, USA. Vinuela-Rueda, L., & Martinez-Salcedo, J. (2006). Steel structure and prestressed façade of the new terminal building, Hormigon Acero, 239(1), 71–84.
• Yang, H., Lam, D., & Gardner, L. (2008). Testing and analysis of concrete-filled elliptical hollow sections. Engineering Structures; 30(12), 3771– 3781. https://doi.org/10.1016/j.engstruct.2008.07.004
• Zadeh, L.A. (1994). Soft-computing and fuzzy logic. IEEE Software, 11(6), 48–56. https://doi.org/10.1109/52.329401
• Zhang, Z., & Friedrich, K. (2003). Artificial neural networks applied to polymer composites: a review. Composites Science and Technology, 63(14), 2029–2044. https://doi.org/10.1016/S0266-3538(03)00106-4
• Zhao, X.L., & Packer, J.A. (2009). Tests and design of concrete-filled elliptical hollow section stub columns. Thin-Walled Structures, 47(6–7), 617–628. https://doi.org/10.1016/j.tws.2008.11.004
• Zhao, X.L., Lu, H., & Galteri, S. Tests of elliptical hollow sections filled with SCC self-compacting concrete. In 2007, 5th International Conference on Advances in Steel Structures, Singapore, Research Publishing Services, Singapore, 950–955.
• Zhu, Y., & Wilkinson, T. Finite-element analysis of structural steel elliptical hollow sections in pure compression. In 2006 11th International Symposium on Tubular Structures, Québec City, Canada, Taylor & Francis, London, 179–186.

Toplam 25 adet kaynakça vardır.

Ayrıntılar

Kaynak Göster

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