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SUPPORT LOCATION OPTIMIZATIONS IN BEAM AND SHEET PLATE STRUCTURES WITH ARTIFICIAL NEURAL NETWORKS

Yıl 2023, Cilt: 26 Sayı: 3, 637 - 652, 03.09.2023
https://doi.org/10.17780/ksujes.1245046

Öz

Beam and sheet plate structures are used for various purposes in many fields. Deformation occurs on a load carrying beam by bending. Similar to beams, sheet and plate structures deform with their own weights or by carrying forces perpendicular to their surfaces. In such structures, besides carrying load safely, minimum deformation is desired. In this study, to obtain minimum deformation, cross-section, length and loading conditions of beam and sheet structures were taken constant and support location optimization were performed. Locations of supports were parameterized, and deformation values correspond to different support locations were obtained from parametric finite element model. Artificial neural networks and optimization code were developed in Python and deformation values were predicted by given support locations. Method was used on two and three supported beams, sheet plate and welded two sheet plates examples and optimization results were obtained. It was found that supports should be positioned symmetrically for minimum deformation under distributed load in each beam and sheet plate problem. It was found that optimum support locations should be at a distance of 21.89%, 13.57%, 19.13% and 14.42% from the edges for two supported beam, three supported beam, sheet plate and welded two sheet plates examples respectively.

Kaynakça

  • Abbasi, B. and Mahlooji, H., (2012). Improving response surface methodology by using artificial neural network and simulated annealing. Expert Systems with Applications, 39(3), 3461-3468. https://doi.org/10.1016/j.eswa.2011.09.036
  • Aderiani, A.R., Warmefjord, K., Söderberg, R., Lindkvist, L. and Lindau, B., (2020). Optimal design of fixture layouts for compliant sheet metal assemblies. The International Journal of Advanced Manufacturing Technology, 110, 2181-2201. https://doi.org/10.1007/s00170-020-05954-y
  • Ahmad, Z., Sultan, T., Asad, M., Zoppi, M. and Molfino, R., (2018). Fixture layout optimization for multi point respot welding of sheet metals. Journal of Mechanical Science and Technology, 32(4), 1749-1760. https://doi.org/10.1007/s12206-018-0331-5
  • Alteyeb, M.S. and Jolgaf, M., (2017, September). Optimization of cantilever beam for minimum weight using finite element analysis. First Libyan Conference on Metal Casting and Processing Technologies. FLCMCPT2017.
  • Arora, J.S., (2017). Introduction to Optimum Design. Elsevier, UK, 945.
  • Arslan, İ., (2019). Python ile Veri Bilimi. Pusula, İstanbul, 406.
  • Darshan, S., Varik, A., Katti, A.N., Singh, A.K. and Kamath R.R., (2013). Size and topological optimization of cantilever beam. International Journal of Engineering Trends and Technology (IJETT), 4(5), ISSN:2231-5381.
  • Gürel, D.B. (2016). Cevap yüzeyi yöntemi kullanılarak stevia özü içeren düşük kalorili böğürtlen reçeli formülasyonunun belirlenmesi, Yüksek Lisans Tezi. T.C. Namık Kemal Üniversitesi Fen Bilimleri Enstitüsü Gıda Mühendisliği Anabilim Dalı. Tekirdağ 71s.
  • Jang, G.W., Shim, H.S. and Kimi, Y.Y., (2009). Optimization of support locations of beam and plate structures under self-weight by using a sprung structure model. Journal of Mechanical Design, 131(2), 021005. https://doi.org/10.1115/1.3042154
  • Jaskot, A. (2017). Steel cantilever beam optimization with ANSYS software. Zeszyty Naukowe Politechniki Częstochowskiej. Budownictwo, t. 27 (177), Politechnika Częstochowska. https://doi.org/10.17512/znb.2021.1.11
  • Kaya, N., (2006). Machining fixture locating and clamping position optimization using genetic algorithms. Computers in industry, 57, 112-120. https://doi.org/10.1016/j.compind.2005.05.001
  • Kayabekir, A.C. (2018). Yapı mühendisliğinde metasezgisel algoritmalar ile optimizasyon uygulamaları. Yüksek Lisans Tezi. T.C. İstanbul Üniversitesi Fen Bilimleri Enstitüsü. Makina Mühendisliği Anabilim Dalı, İstanbul 101s.
  • Keras (2022). https://keras.io Accessed 18,12,2022.
  • Konstantinos, V., Marie-Ange, D. (2019). Benchmarking multivariate solvers of scipy on the noise-less testbed. -The Genetic and Evolutionary Computation Conference, Jul 2019, Prague, Czech Republic. https://doi.org/10.1145/3319619.3326891
  • Köroglu, S.A. (2013). Gemi yapısal dizaynında vekil model kullanımı. Doktora Tezi. İstanbul Teknik Üniversitesi Fen Bilimleri Enstitüsü Gemi İnşaatı ve Gemi Makinaları Mühendisliği Anabilim Dalı Gemi İnşaatı ve Gemi Makinaları Mühendisliği Programı. İstanbul 130s.
  • Kraft, D., (1998). A Software package for sequential quadratic programming. DLR German Aerospace Center – Institute for Flight Mechanics, Köln, 33.
  • Lam, Y. C., Santhikumar, S. (2003). Automated rib location and optimization for plate structures. Structural and Multidisciplinary Optimization, 25(1), 35–45. https://doi.org/10.1007/s00158-002-0270-7
  • Li, B. and Melkote, S.N., (1999). Improved workpiece location accuracy through fixture layout optimization. International Journal of Machine Tools &Manufacture, 39, 871-883. https://doi.org/10.1016/S0890-6955(98)00072-8
  • Li, B., Tang, H., Yang, X. and Wang, H., (2006). Quality design of fixture planning for sheet metal assembly. The International Journal of Advanced Manufacturing Technology, 32, 690-697. https://doi.org/10.1007/s00170-005-0385-2
  • Lipovetsky, S., (2009). Pareto 80/20 law: derivation via random partitioning. International Journal of Mathematical Education in Science and Technology, 40, 271-277. https://doi.org/10.1080/00207390802213609
  • Lu, C. and Zhao, H.W., (2015). Fixture layout optimization for deformable sheet metal workpiece. The International Journal of Advanced Manufacturing Technology, 78, 85-98. https://doi.org/10.1007/s00170-014-6647-0
  • Prabhaharan, G., Padmanaban, K.P. and Krishnakumar, R., (2007). Machining fixture layout optimization using fem and evolutionary techniques. The International Journal of Advanced Manufacturing Technology, 32, 1090-1103. https://doi.org/10.1007/s00170-006-0441-6
  • Selvakumar, S., Arulshri, K.P., Padmanaban, K.P. and Sasikumar, K.S.K., (2013). Design and optimization of machining fixture layout using ann and doe. The International Journal of Advanced Manufacturing Technology, 65, 1573-1586. https://doi.org/10.1007/s00170-012-4281-2
  • Scipy (2022). https://docs.scipy.org Accessed 15.08.2022.
  • Silva, H. M., and de Meireles, J. F. B. (2018). Design optimisation of internally reinforced beams subjected to bending loading. Advanced Engineering Forum, 28, 18–32. https://doi.org/10.4028/www.scientific.net/aef.28.18
  • Simpson, T.W., Poplinski, J.D., Koch, P.N. and Allen, J.K., (2001). Metamodels for computer-based engineering design: survey and recommendations. Engineering with Computers, 17, 129-150. https://doi.org/10.1007/PL00007198
  • Viana, F.A.C., (2015). A tutorial on latin hypercube design of experiments. Quality and Reliability Engineering International, 32(5), 1975-1985. https://doi.org/10.1002/qre.1924
  • Waia, C.M., Rivai, A. and Bapokutty, O., (2013). Modelling optimization involving different types of elements in finite element analysis. Materials Science and Engineering, 50(1), 1-8. https://doi.org/10.1088/1757-899X/50/1/012036
  • Yang, B., Wang, Z., Yang, Y., Kang, Y. and Li, C., (2017). Optimization of fixture locating layout for sheet metal part by cuckoo search algorithm combined with finite element analysis. Advances in Mechanical Engineering, 9(6), 1-10. https://doi.org/10.1177/168781401770
  • Zolghadr-Asli, B., Bozorg-Haddad, O., Chu, X., (2018). Advanced optimization by nature-ınspired algorithms., Studies In Computational Intelligence, Vol. 720, Ed.: Bozorg-Haddad, O., Singapore, p. 166. https://doi.org/10.1007/978-981-10-5221-7

KİRİŞ VE SAC PLAKA YAPILARDA YAPAY SİNİR AĞLARI İLE MESNET KONUM OPTİMİZASYONLARI

Yıl 2023, Cilt: 26 Sayı: 3, 637 - 652, 03.09.2023
https://doi.org/10.17780/ksujes.1245046

Öz

Kiriş ve sac plaka yapılar otomotiv, havacılık, inşaat ve mimarlık gibi birçok alanda çeşitli amaçlarla kullanılırlar. Yük taşıyan kirişte eğilme ile deformasyon meydana gelir. Kirişlere benzer şekilde sac veya levha şeklindeki yapılarda kendi ağırlıkları ile veya yüzeylerine dik yönde kuvvet taşırken deforme olurlar. Bu tür yapılarda yükün emniyetle taşınmasının yanında, en az deformasyonun oluşması istenir. Bu çalışmada, kiriş ve sac parçaların kesiti, uzunluğu ve yükleme durumu sabit alınarak minimum deformasyonun elde edilmesi için mesnet noktalarının optimizasyonu gerçekleştirilmiştir. Mesnet konumları parametre olarak alınmış ve geliştirilen yazılım ile mesnet noktalarının konum optimizasyonları gerçekleştirilmiştir. Parametrik sonlu elemanlar modelinden farklı mesnet konumlarına karşılık gelen deformasyon değerleri elde edilmiştir. Python kodu ile yapay sinir ağı ve optimizasyon kodu geliştirilmiş ve deformasyon değerleri verilen mesnet konumlarına göre hesaplanmıştır. Geliştirilen yöntem iki ve üç mesnetli kirişler ile sac levha ve kaynakla birleştirilecek iki sac levha örnekleri üzerinde denenerek optimizasyon sonuçları elde edilmiştir. Her bir kiriş ve sac levha probleminde yayılı yük altında minimum deformasyon için mesnetlerin birbirlerine simetrik konumlandırılmaları gerektiği bulunmuştur. Optimum mesnet noktaları; iki mesnetli kirişte kenarlardan %21.89, üç mesnetli kirişte %13.57, sac levhada %19.13, kaynakla birleştirilecek iki sac levhada ise %14.42 uzaklıkta hesaplanmıştır.

Kaynakça

  • Abbasi, B. and Mahlooji, H., (2012). Improving response surface methodology by using artificial neural network and simulated annealing. Expert Systems with Applications, 39(3), 3461-3468. https://doi.org/10.1016/j.eswa.2011.09.036
  • Aderiani, A.R., Warmefjord, K., Söderberg, R., Lindkvist, L. and Lindau, B., (2020). Optimal design of fixture layouts for compliant sheet metal assemblies. The International Journal of Advanced Manufacturing Technology, 110, 2181-2201. https://doi.org/10.1007/s00170-020-05954-y
  • Ahmad, Z., Sultan, T., Asad, M., Zoppi, M. and Molfino, R., (2018). Fixture layout optimization for multi point respot welding of sheet metals. Journal of Mechanical Science and Technology, 32(4), 1749-1760. https://doi.org/10.1007/s12206-018-0331-5
  • Alteyeb, M.S. and Jolgaf, M., (2017, September). Optimization of cantilever beam for minimum weight using finite element analysis. First Libyan Conference on Metal Casting and Processing Technologies. FLCMCPT2017.
  • Arora, J.S., (2017). Introduction to Optimum Design. Elsevier, UK, 945.
  • Arslan, İ., (2019). Python ile Veri Bilimi. Pusula, İstanbul, 406.
  • Darshan, S., Varik, A., Katti, A.N., Singh, A.K. and Kamath R.R., (2013). Size and topological optimization of cantilever beam. International Journal of Engineering Trends and Technology (IJETT), 4(5), ISSN:2231-5381.
  • Gürel, D.B. (2016). Cevap yüzeyi yöntemi kullanılarak stevia özü içeren düşük kalorili böğürtlen reçeli formülasyonunun belirlenmesi, Yüksek Lisans Tezi. T.C. Namık Kemal Üniversitesi Fen Bilimleri Enstitüsü Gıda Mühendisliği Anabilim Dalı. Tekirdağ 71s.
  • Jang, G.W., Shim, H.S. and Kimi, Y.Y., (2009). Optimization of support locations of beam and plate structures under self-weight by using a sprung structure model. Journal of Mechanical Design, 131(2), 021005. https://doi.org/10.1115/1.3042154
  • Jaskot, A. (2017). Steel cantilever beam optimization with ANSYS software. Zeszyty Naukowe Politechniki Częstochowskiej. Budownictwo, t. 27 (177), Politechnika Częstochowska. https://doi.org/10.17512/znb.2021.1.11
  • Kaya, N., (2006). Machining fixture locating and clamping position optimization using genetic algorithms. Computers in industry, 57, 112-120. https://doi.org/10.1016/j.compind.2005.05.001
  • Kayabekir, A.C. (2018). Yapı mühendisliğinde metasezgisel algoritmalar ile optimizasyon uygulamaları. Yüksek Lisans Tezi. T.C. İstanbul Üniversitesi Fen Bilimleri Enstitüsü. Makina Mühendisliği Anabilim Dalı, İstanbul 101s.
  • Keras (2022). https://keras.io Accessed 18,12,2022.
  • Konstantinos, V., Marie-Ange, D. (2019). Benchmarking multivariate solvers of scipy on the noise-less testbed. -The Genetic and Evolutionary Computation Conference, Jul 2019, Prague, Czech Republic. https://doi.org/10.1145/3319619.3326891
  • Köroglu, S.A. (2013). Gemi yapısal dizaynında vekil model kullanımı. Doktora Tezi. İstanbul Teknik Üniversitesi Fen Bilimleri Enstitüsü Gemi İnşaatı ve Gemi Makinaları Mühendisliği Anabilim Dalı Gemi İnşaatı ve Gemi Makinaları Mühendisliği Programı. İstanbul 130s.
  • Kraft, D., (1998). A Software package for sequential quadratic programming. DLR German Aerospace Center – Institute for Flight Mechanics, Köln, 33.
  • Lam, Y. C., Santhikumar, S. (2003). Automated rib location and optimization for plate structures. Structural and Multidisciplinary Optimization, 25(1), 35–45. https://doi.org/10.1007/s00158-002-0270-7
  • Li, B. and Melkote, S.N., (1999). Improved workpiece location accuracy through fixture layout optimization. International Journal of Machine Tools &Manufacture, 39, 871-883. https://doi.org/10.1016/S0890-6955(98)00072-8
  • Li, B., Tang, H., Yang, X. and Wang, H., (2006). Quality design of fixture planning for sheet metal assembly. The International Journal of Advanced Manufacturing Technology, 32, 690-697. https://doi.org/10.1007/s00170-005-0385-2
  • Lipovetsky, S., (2009). Pareto 80/20 law: derivation via random partitioning. International Journal of Mathematical Education in Science and Technology, 40, 271-277. https://doi.org/10.1080/00207390802213609
  • Lu, C. and Zhao, H.W., (2015). Fixture layout optimization for deformable sheet metal workpiece. The International Journal of Advanced Manufacturing Technology, 78, 85-98. https://doi.org/10.1007/s00170-014-6647-0
  • Prabhaharan, G., Padmanaban, K.P. and Krishnakumar, R., (2007). Machining fixture layout optimization using fem and evolutionary techniques. The International Journal of Advanced Manufacturing Technology, 32, 1090-1103. https://doi.org/10.1007/s00170-006-0441-6
  • Selvakumar, S., Arulshri, K.P., Padmanaban, K.P. and Sasikumar, K.S.K., (2013). Design and optimization of machining fixture layout using ann and doe. The International Journal of Advanced Manufacturing Technology, 65, 1573-1586. https://doi.org/10.1007/s00170-012-4281-2
  • Scipy (2022). https://docs.scipy.org Accessed 15.08.2022.
  • Silva, H. M., and de Meireles, J. F. B. (2018). Design optimisation of internally reinforced beams subjected to bending loading. Advanced Engineering Forum, 28, 18–32. https://doi.org/10.4028/www.scientific.net/aef.28.18
  • Simpson, T.W., Poplinski, J.D., Koch, P.N. and Allen, J.K., (2001). Metamodels for computer-based engineering design: survey and recommendations. Engineering with Computers, 17, 129-150. https://doi.org/10.1007/PL00007198
  • Viana, F.A.C., (2015). A tutorial on latin hypercube design of experiments. Quality and Reliability Engineering International, 32(5), 1975-1985. https://doi.org/10.1002/qre.1924
  • Waia, C.M., Rivai, A. and Bapokutty, O., (2013). Modelling optimization involving different types of elements in finite element analysis. Materials Science and Engineering, 50(1), 1-8. https://doi.org/10.1088/1757-899X/50/1/012036
  • Yang, B., Wang, Z., Yang, Y., Kang, Y. and Li, C., (2017). Optimization of fixture locating layout for sheet metal part by cuckoo search algorithm combined with finite element analysis. Advances in Mechanical Engineering, 9(6), 1-10. https://doi.org/10.1177/168781401770
  • Zolghadr-Asli, B., Bozorg-Haddad, O., Chu, X., (2018). Advanced optimization by nature-ınspired algorithms., Studies In Computational Intelligence, Vol. 720, Ed.: Bozorg-Haddad, O., Singapore, p. 166. https://doi.org/10.1007/978-981-10-5221-7
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Makine Mühendisliği
Bölüm Makine Mühendisliği
Yazarlar

Onur Ünlü 0000-0001-8154-8104

Hakan Demir 0000-0001-9819-2167

Necmettin Kaya 0000-0002-8297-0777

Yayımlanma Tarihi 3 Eylül 2023
Gönderilme Tarihi 31 Ocak 2023
Yayımlandığı Sayı Yıl 2023Cilt: 26 Sayı: 3

Kaynak Göster

APA Ünlü, O., Demir, H., & Kaya, N. (2023). KİRİŞ VE SAC PLAKA YAPILARDA YAPAY SİNİR AĞLARI İLE MESNET KONUM OPTİMİZASYONLARI. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 26(3), 637-652. https://doi.org/10.17780/ksujes.1245046