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BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI

Yıl 2020, , 361 - 378, 30.04.2020
https://doi.org/10.17482/uumfd.644684

Öz

Betonarme elemanların geleneksel yöntemlere göre tasarımına bir seçenek olan optimum tasarım süreçleri, yapay zekâ tekniklerinin gelişimine paralel olarak araştırmacıların daha çok ilgisini çekmektedir. Özellikle kaynakların giderek azalmasıyla mühendislik problemlerinde optimizasyon yapma gereksinimi hızla artmaktadır. Bu çalışmada betonarme kısa konsolların TS 500’e göre minimum maliyetle tasarımı Yapay Arı Koloni (ABC), Öğretme-Öğrenme Tabanlı Optimizasyon (TLBO) ve Öğretme-Öğrenme Tabanlı Dayalı Yapay Arı Koloni (TLABC) algoritmalarıyla gerçekleştirilmiştir. Algoritmaların başarımları çeşitli istatistiksel yöntemlerle karşılaştırılmış olup, TLABC algoritmasının başarımının diğer algoritmalara göre daha iyi olduğu belirlenmiştir. Gerçekleştirilen parametrik çalışmalarla konsol açıklığının, düşey ve yatay yük değişiminin maliyetleri nasıl etkilediği incelenmiştir. 

Kaynakça

  • 1. Akay, B. ve Karaboga, D. (2012) A modified Artificial Bee Colony algorithm for real-parameter optimization, Information Sciences, 192, 120–142. https://doi.org/10.1016/j.ins.2010.07.015
  • 2. Akin, A. ve Saka, M. P. (2015) Harmony search algorithm based optimum detailed design of reinforced concrete plane frames subject to ACI 318-05 provisions, Computers and Structures, 147, 79–95. https://doi.org/10.1016/j.compstruc.2014.10.003
  • 3. Amir, O. ve Shakour, E. (2018) Simultaneous shape and topology optimization of prestressed concrete beams, Structural and Multidisciplinary Optimization, 57(5), 1831–1843. https://doi.org/10.1007/s00158-017-1855-5
  • 4. Arroyo, O. ve Gutiérrez, S. (2017) A seismic optimization procedure for reinforced concrete framed buildings based on eigenfrequency optimization, Engineering Optimization, 49(7), 1166–1182. https://doi.org/10.1080/0305215X.2016.1241779
  • 5. Bekdaş, G. ve Temür, R. (2018) Grey wolf optimizer for optimum design of reinforced concrete cantilever retaining walls, AIP Conference Proceedings, 1978(July): https://doi.org/10.1063/1.5043893
  • 6. Bruno, D., Lonetti, P. ve Pascuzzo, A. (2016) An optimization model for the design of network arch bridges, Computers and Structures, 170, 13–25. https://doi.org/10.1016/j.compstruc.2016.03.011
  • 7. Cai, H., Aref, A. J. (2015a) A genetic algorithm-based multi-objective optimization for hybrid fiber reinforced polymeric deck and cable system of cable-stayed bridges, Structural and Multidisciplinary Optimization, 52(3), 583–594. https://doi.org/10.1007/s00158-015-1266-4
  • 8. Cai, H. ve Aref, A. J. (2015b) On the design and optimization of hybrid carbon fiber reinforced polymer-steel cable system for cable-stayed bridges, Composites Part B: Engineering, 68, 146–152. https://doi.org/10.1016/j.compositesb.2014.08.031
  • 9. Camp, C. V. ve Huq, F. (2013) CO2 and cost optimization of reinforced concrete frames using a big bang-big crunch algorithm, Engineering Structures, 48, 363–372. https://doi.org/10.1016/j.engstruct.2012.09.004
  • 10. Caratelli, A., Meda, A., Rinaldi, Z., Spagnuolo, S. ve Maddaluno, G. (2017) Optimization of GFRP reinforcement in precast segments for metro tunnel lining, Composite Structures, 181, 336–346. https://doi.org/10.1016/j.compstruct.2017.08.083
  • 11. Carbonell, A., González-Vidosa, F. ve Yepes, V. (2011) Design of reinforced concrete road vaults by heuristic optimization, Advances in Engineering Software, 42(4), 151–159. https://doi.org/10.1016/j.advengsoft.2011.01.002
  • 12. Esfandiari, M. J., Urgessa, G. S., Sheikholarefin, S. ve Dehghan Manshadi, S. H. (2018) Optimization of reinforced concrete frames subjected to historical time-history loadings using DMPSO algorithm, Structural and Multidisciplinary Optimization, 58(5), 2119–2134. https://doi.org/10.1007/s00158-018-2027-y
  • 13. Fabbrocino, F., Modano, M., Farina, I., Carpentieri, G. ve Fraternali, F. (2017) Optimal prestress design of composite cable-stayed bridges, Composite Structures, 169, 167–172. https://doi.org/10.1016/j.compstruct.2016.09.008
  • 14. Gandomi, A. H. ve Kashani, A. R. 2018. Automating pseudo-static analysis of concrete cantilever retaining wall using evolutionary algorithms, Measurement: Journal of the International Measurement Confederation, 115(July 2017), 104–124. https://doi.org/10.1016/j.measurement.2017.10.032
  • 15. García-Segura, T. ve Yepes, V. (2016) Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety, Engineering Structures, 125, 325–336. https://doi.org/10.1016/j.engstruct.2016.07.012
  • 16. García-Segura, T., Yepes, V., Frangopol, D. M. ve Yang, D. Y. (2017) Lifetime reliability-based optimization of post-tensioned box-girder bridges, Engineering Structures, 145, 381–391. https://doi.org/10.1016/j.engstruct.2017.05.013
  • 17. Ghaleini, E. N., Koopialipoor, M., Momenzadeh, M., Sarafraz, M. E. ve Mohamad, E. T., Gordan, B. (2019), A combination of artificial bee colony and neural network for approximating the safety factor of retaining walls, Engineering with Computers, 35(2), 647–658. https://doi.org/10.1007/s00366-018-0625-3
  • 18. Ghodoosi, F., Abu-Samra, S., Zeynalian, M. ve Zayed, T. (2018) Maintenance cost optimization for bridge structures using system reliability analysis and genetic algorithms, Journal of Construction Engineering and Management, 144(2), 1–10. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001435
  • 19. Gordan, B., Koopialipoor, M., Clementking, A., Tootoonchi, H. ve Tonnizam Mohamad, E. (2019) Estimating and optimizing safety factors of retaining wall through neural network and bee colony techniques, Engineering with Computers, 35(3), 945–954. https://doi.org/10.1007/s00366-018-0642-2
  • 20. Kalateh-Ahani, M. ve Sarani, A. (2019) Performance-based Optimal Design of Cantilever Retaining Walls, Periodica Polytechnica Civil Engineering, 63(2), 660–673. https://doi.org/10.3311/ppci.13201
  • 21. Karaboga, D. ve Akay, B. (2009) A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 214(1), 108–132. https://doi.org/10.1016/j.amc.2009.03.090
  • 22. Kaveh, A., Maniat, M. ve Arab Naeini, M. (2016) Cost optimum design of post-tensioned concrete bridges using a modified colliding bodies optimization algorithm, Advances in Engineering Software, 98, 12–22. https://doi.org/10.1016/j.advengsoft.2016.03.003
  • 23. Martí, J. V., García-Segura, T. ve Yepes, V. (2016) Structural design of precast-prestressed concrete U-beam road bridges based on embodied energy, Journal of Cleaner Production, 120:, 231–240. https://doi.org/10.1016/j.jclepro.2016.02.024
  • 24. Martí, J. V., Yepes, V. ve González-Vidosa, F. (2015) Memetic algorithm approach to designing precast-prestressed concrete road bridges with steel fiber reinforcement, Journal of Structural Engineering, 141(2), 1–9. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001058
  • 25. Martins, A. M. B., Simões, L. M. C. ve Negrão, J. H. J. O. (2016a) Optimum design of concrete cable-stayed bridges. Engineering Optimization, 48(5), 772–791. https://doi.org/10.1080/0305215X.2015.1057057
  • 26. Martins, A. M. B., Simões, L. M. C. ve Negrão, J. H. J. O. (2016b) Optimum design of concrete cable-stayed bridges with prestressed decks. International Journal of Computational Methods in Engineering Science and Mechanics, 17(5–6), 339–349. https://doi.org/10.1080/15502287.2016.1231237
  • 27. Mergos, P. E. ve Mantoglou, F. (2019) Optimum design of reinforced concrete retaining walls with the flower pollination algorithm, Structural and Multidisciplinary Optimization. https://doi.org/10.1007/s00158-019-02380-x
  • 28. Mukhopadhyay, T., Dey, T. K., Chowdhury, R., Chakrabarti, A. ve Adhikari, S. (2015) Optimum design of FRP bridge deck: an efficient RS-HDMR based approach. Structural and Multidisciplinary Optimization, 52(3), 459–477. https://doi.org/10.1007/s00158-015-1251-y
  • 29. Öztürk, H.T., Türkeli, E. ve Durmuş, A. (2016) Optimum design of RC shallow tunnels in earthquake zones using artificial bee colony and genetic algorithms. Computers and Concrete, 17(4), 435–453. http://dx.doi.org/10.12989/cac.2016.17.4.435
  • 30. Ozturk, H. T., ve Durmus, A. (2013). Optimum cost design of RC columns using artificial bee colony algorithm, Structural Engineering and Mechanics, 45(5), 643-654. : http://dx.doi.org/10.12989/sem.2013.45.5.643
  • 31. Öztürk, H. T. ve Türkeli, E. 2019. Optimum design of rc retaining walls with key section using jaya algorithm, Journal of Polytechnic, 22(2), 283–291. https://doi.org/10.2339/politeknik.432031
  • 32. Quaranta, G., Fiore, A. ve Marano, G. C. (2014) Optimum design of prestressed concrete beams using constrained differential evolution algorithm, Structural and Multidisciplinary Optimization, 49(3), 441–453. https://doi.org/10.1007/s00158-013-0979-5
  • 33. Rao, R. V. ve Patel, V. (2013) An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems, Scientia Iranica, 20(3), 710–720. https://doi.org/10.1016/j.scient.2012.12.005
  • 34. Rao, R. V., Savsani, V. J. ve Balic, J. (2012) Teaching-learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems, Engineering Optimization, 44(12), 1447–1462. https://doi.org/10.1080/0305215X.2011.652103
  • 35. Sánchez-Olivares, G. ve Tomás, A. (2017) Improvements in meta-heuristic algorithms for minimum cost design of reinforced concrete rectangular sections under compression and biaxial bending, Engineering Structures, Elsevier Ltd: , 162–179. https://doi.org/10.1016/j.engstruct.2016.10.010
  • 36. Shaqfa, M. ve Orbán, Z. (2019) Modified parameter-setting-free harmony search (PSFHS) algorithm for optimizing the design of reinforced concrete beams, Structural and Multidisciplinary Optimization, 60(3), 999–1019. https://doi.org/10.1007/s00158-019-02252-4
  • 37. Uray, E., Çarbaş, S., Erkan, İ. H. ve Tan, Ö. (2019) Parametric investigation for discrete optimal design of a cantilever retaining wall, Challenge Journal of Structural Mechanics, 5(3), 108. https://doi.org/10.20528/cjsmec.2019.03.004
  • 38. Van Loon, R. R. L., Pujadas-Gispert, E., Moonen, S. P. G. ve Blok, R. (2019) Environmental Optimization of Precast Concrete Beams Using Fibre Reinforced Polymers. Sustainability, 11(7):, 2174. https://doi.org/10.3390/su11072174
  • 39. Yepes, V., Martí, J. V. ve García-Segura, T. (2015) Cost and CO2 emission optimization of precast-prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm, Automation in Construction, 49, 123–134. https://doi.org/10.1016/j.autcon.2014.10.013
  • 40. Yoon, Y. C., Kim, K. H., Lee, S. H. ve Yeo, D. (2018) Sustainable design for reinforced concrete columns through embodied energy and CO2 emission optimization, Energy and Buildings, 174:, 44–53. https://doi.org/10.1016/j.enbuild.2018.06.013

Performance of ABC, TLBO and TLABC Algorithms in Optimal Design of RC Corbel According to TS 500

Yıl 2020, , 361 - 378, 30.04.2020
https://doi.org/10.17482/uumfd.644684

Öz

Optimal design processes, which are an alternative to the design of reinforced concrete elements compared to traditional methods, attract the attention of researchers in parallel with the development of artificial intelligence techniques. The need for optimization in engineering problems is increasing rapidly, especially as resources are becoming scarce. In this study, the design of reinforced concrete corbels with minimum cost according to TS 500 was realized with Artificial Bee Colony (ABC), Teaching-Learning Based Optimization (TLBO) and Teaching-Learning Based Artificial Bee Colony (TLABC) algorithms. The performance of the algorithms was compared with various statistical methods that the performance of the TLABC algorithm is better than other algorithms. The parametric studies carried out have examined how the cantilever span, vertical and horizontal load changes affect the costs.

Kaynakça

  • 1. Akay, B. ve Karaboga, D. (2012) A modified Artificial Bee Colony algorithm for real-parameter optimization, Information Sciences, 192, 120–142. https://doi.org/10.1016/j.ins.2010.07.015
  • 2. Akin, A. ve Saka, M. P. (2015) Harmony search algorithm based optimum detailed design of reinforced concrete plane frames subject to ACI 318-05 provisions, Computers and Structures, 147, 79–95. https://doi.org/10.1016/j.compstruc.2014.10.003
  • 3. Amir, O. ve Shakour, E. (2018) Simultaneous shape and topology optimization of prestressed concrete beams, Structural and Multidisciplinary Optimization, 57(5), 1831–1843. https://doi.org/10.1007/s00158-017-1855-5
  • 4. Arroyo, O. ve Gutiérrez, S. (2017) A seismic optimization procedure for reinforced concrete framed buildings based on eigenfrequency optimization, Engineering Optimization, 49(7), 1166–1182. https://doi.org/10.1080/0305215X.2016.1241779
  • 5. Bekdaş, G. ve Temür, R. (2018) Grey wolf optimizer for optimum design of reinforced concrete cantilever retaining walls, AIP Conference Proceedings, 1978(July): https://doi.org/10.1063/1.5043893
  • 6. Bruno, D., Lonetti, P. ve Pascuzzo, A. (2016) An optimization model for the design of network arch bridges, Computers and Structures, 170, 13–25. https://doi.org/10.1016/j.compstruc.2016.03.011
  • 7. Cai, H., Aref, A. J. (2015a) A genetic algorithm-based multi-objective optimization for hybrid fiber reinforced polymeric deck and cable system of cable-stayed bridges, Structural and Multidisciplinary Optimization, 52(3), 583–594. https://doi.org/10.1007/s00158-015-1266-4
  • 8. Cai, H. ve Aref, A. J. (2015b) On the design and optimization of hybrid carbon fiber reinforced polymer-steel cable system for cable-stayed bridges, Composites Part B: Engineering, 68, 146–152. https://doi.org/10.1016/j.compositesb.2014.08.031
  • 9. Camp, C. V. ve Huq, F. (2013) CO2 and cost optimization of reinforced concrete frames using a big bang-big crunch algorithm, Engineering Structures, 48, 363–372. https://doi.org/10.1016/j.engstruct.2012.09.004
  • 10. Caratelli, A., Meda, A., Rinaldi, Z., Spagnuolo, S. ve Maddaluno, G. (2017) Optimization of GFRP reinforcement in precast segments for metro tunnel lining, Composite Structures, 181, 336–346. https://doi.org/10.1016/j.compstruct.2017.08.083
  • 11. Carbonell, A., González-Vidosa, F. ve Yepes, V. (2011) Design of reinforced concrete road vaults by heuristic optimization, Advances in Engineering Software, 42(4), 151–159. https://doi.org/10.1016/j.advengsoft.2011.01.002
  • 12. Esfandiari, M. J., Urgessa, G. S., Sheikholarefin, S. ve Dehghan Manshadi, S. H. (2018) Optimization of reinforced concrete frames subjected to historical time-history loadings using DMPSO algorithm, Structural and Multidisciplinary Optimization, 58(5), 2119–2134. https://doi.org/10.1007/s00158-018-2027-y
  • 13. Fabbrocino, F., Modano, M., Farina, I., Carpentieri, G. ve Fraternali, F. (2017) Optimal prestress design of composite cable-stayed bridges, Composite Structures, 169, 167–172. https://doi.org/10.1016/j.compstruct.2016.09.008
  • 14. Gandomi, A. H. ve Kashani, A. R. 2018. Automating pseudo-static analysis of concrete cantilever retaining wall using evolutionary algorithms, Measurement: Journal of the International Measurement Confederation, 115(July 2017), 104–124. https://doi.org/10.1016/j.measurement.2017.10.032
  • 15. García-Segura, T. ve Yepes, V. (2016) Multiobjective optimization of post-tensioned concrete box-girder road bridges considering cost, CO2 emissions, and safety, Engineering Structures, 125, 325–336. https://doi.org/10.1016/j.engstruct.2016.07.012
  • 16. García-Segura, T., Yepes, V., Frangopol, D. M. ve Yang, D. Y. (2017) Lifetime reliability-based optimization of post-tensioned box-girder bridges, Engineering Structures, 145, 381–391. https://doi.org/10.1016/j.engstruct.2017.05.013
  • 17. Ghaleini, E. N., Koopialipoor, M., Momenzadeh, M., Sarafraz, M. E. ve Mohamad, E. T., Gordan, B. (2019), A combination of artificial bee colony and neural network for approximating the safety factor of retaining walls, Engineering with Computers, 35(2), 647–658. https://doi.org/10.1007/s00366-018-0625-3
  • 18. Ghodoosi, F., Abu-Samra, S., Zeynalian, M. ve Zayed, T. (2018) Maintenance cost optimization for bridge structures using system reliability analysis and genetic algorithms, Journal of Construction Engineering and Management, 144(2), 1–10. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001435
  • 19. Gordan, B., Koopialipoor, M., Clementking, A., Tootoonchi, H. ve Tonnizam Mohamad, E. (2019) Estimating and optimizing safety factors of retaining wall through neural network and bee colony techniques, Engineering with Computers, 35(3), 945–954. https://doi.org/10.1007/s00366-018-0642-2
  • 20. Kalateh-Ahani, M. ve Sarani, A. (2019) Performance-based Optimal Design of Cantilever Retaining Walls, Periodica Polytechnica Civil Engineering, 63(2), 660–673. https://doi.org/10.3311/ppci.13201
  • 21. Karaboga, D. ve Akay, B. (2009) A comparative study of Artificial Bee Colony algorithm. Applied Mathematics and Computation, 214(1), 108–132. https://doi.org/10.1016/j.amc.2009.03.090
  • 22. Kaveh, A., Maniat, M. ve Arab Naeini, M. (2016) Cost optimum design of post-tensioned concrete bridges using a modified colliding bodies optimization algorithm, Advances in Engineering Software, 98, 12–22. https://doi.org/10.1016/j.advengsoft.2016.03.003
  • 23. Martí, J. V., García-Segura, T. ve Yepes, V. (2016) Structural design of precast-prestressed concrete U-beam road bridges based on embodied energy, Journal of Cleaner Production, 120:, 231–240. https://doi.org/10.1016/j.jclepro.2016.02.024
  • 24. Martí, J. V., Yepes, V. ve González-Vidosa, F. (2015) Memetic algorithm approach to designing precast-prestressed concrete road bridges with steel fiber reinforcement, Journal of Structural Engineering, 141(2), 1–9. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001058
  • 25. Martins, A. M. B., Simões, L. M. C. ve Negrão, J. H. J. O. (2016a) Optimum design of concrete cable-stayed bridges. Engineering Optimization, 48(5), 772–791. https://doi.org/10.1080/0305215X.2015.1057057
  • 26. Martins, A. M. B., Simões, L. M. C. ve Negrão, J. H. J. O. (2016b) Optimum design of concrete cable-stayed bridges with prestressed decks. International Journal of Computational Methods in Engineering Science and Mechanics, 17(5–6), 339–349. https://doi.org/10.1080/15502287.2016.1231237
  • 27. Mergos, P. E. ve Mantoglou, F. (2019) Optimum design of reinforced concrete retaining walls with the flower pollination algorithm, Structural and Multidisciplinary Optimization. https://doi.org/10.1007/s00158-019-02380-x
  • 28. Mukhopadhyay, T., Dey, T. K., Chowdhury, R., Chakrabarti, A. ve Adhikari, S. (2015) Optimum design of FRP bridge deck: an efficient RS-HDMR based approach. Structural and Multidisciplinary Optimization, 52(3), 459–477. https://doi.org/10.1007/s00158-015-1251-y
  • 29. Öztürk, H.T., Türkeli, E. ve Durmuş, A. (2016) Optimum design of RC shallow tunnels in earthquake zones using artificial bee colony and genetic algorithms. Computers and Concrete, 17(4), 435–453. http://dx.doi.org/10.12989/cac.2016.17.4.435
  • 30. Ozturk, H. T., ve Durmus, A. (2013). Optimum cost design of RC columns using artificial bee colony algorithm, Structural Engineering and Mechanics, 45(5), 643-654. : http://dx.doi.org/10.12989/sem.2013.45.5.643
  • 31. Öztürk, H. T. ve Türkeli, E. 2019. Optimum design of rc retaining walls with key section using jaya algorithm, Journal of Polytechnic, 22(2), 283–291. https://doi.org/10.2339/politeknik.432031
  • 32. Quaranta, G., Fiore, A. ve Marano, G. C. (2014) Optimum design of prestressed concrete beams using constrained differential evolution algorithm, Structural and Multidisciplinary Optimization, 49(3), 441–453. https://doi.org/10.1007/s00158-013-0979-5
  • 33. Rao, R. V. ve Patel, V. (2013) An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems, Scientia Iranica, 20(3), 710–720. https://doi.org/10.1016/j.scient.2012.12.005
  • 34. Rao, R. V., Savsani, V. J. ve Balic, J. (2012) Teaching-learning-based optimization algorithm for unconstrained and constrained real-parameter optimization problems, Engineering Optimization, 44(12), 1447–1462. https://doi.org/10.1080/0305215X.2011.652103
  • 35. Sánchez-Olivares, G. ve Tomás, A. (2017) Improvements in meta-heuristic algorithms for minimum cost design of reinforced concrete rectangular sections under compression and biaxial bending, Engineering Structures, Elsevier Ltd: , 162–179. https://doi.org/10.1016/j.engstruct.2016.10.010
  • 36. Shaqfa, M. ve Orbán, Z. (2019) Modified parameter-setting-free harmony search (PSFHS) algorithm for optimizing the design of reinforced concrete beams, Structural and Multidisciplinary Optimization, 60(3), 999–1019. https://doi.org/10.1007/s00158-019-02252-4
  • 37. Uray, E., Çarbaş, S., Erkan, İ. H. ve Tan, Ö. (2019) Parametric investigation for discrete optimal design of a cantilever retaining wall, Challenge Journal of Structural Mechanics, 5(3), 108. https://doi.org/10.20528/cjsmec.2019.03.004
  • 38. Van Loon, R. R. L., Pujadas-Gispert, E., Moonen, S. P. G. ve Blok, R. (2019) Environmental Optimization of Precast Concrete Beams Using Fibre Reinforced Polymers. Sustainability, 11(7):, 2174. https://doi.org/10.3390/su11072174
  • 39. Yepes, V., Martí, J. V. ve García-Segura, T. (2015) Cost and CO2 emission optimization of precast-prestressed concrete U-beam road bridges by a hybrid glowworm swarm algorithm, Automation in Construction, 49, 123–134. https://doi.org/10.1016/j.autcon.2014.10.013
  • 40. Yoon, Y. C., Kim, K. H., Lee, S. H. ve Yeo, D. (2018) Sustainable design for reinforced concrete columns through embodied energy and CO2 emission optimization, Energy and Buildings, 174:, 44–53. https://doi.org/10.1016/j.enbuild.2018.06.013
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İnşaat Mühendisliği
Bölüm Araştırma Makaleleri
Yazarlar

Hasan Tahsin Öztürk 0000-0001-8479-9451

Yayımlanma Tarihi 30 Nisan 2020
Gönderilme Tarihi 9 Kasım 2019
Kabul Tarihi 14 Mart 2020
Yayımlandığı Sayı Yıl 2020

Kaynak Göster

APA Öztürk, H. T. (2020). BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, 25(1), 361-378. https://doi.org/10.17482/uumfd.644684
AMA Öztürk HT. BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI. UUJFE. Nisan 2020;25(1):361-378. doi:10.17482/uumfd.644684
Chicago Öztürk, Hasan Tahsin. “BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 25, sy. 1 (Nisan 2020): 361-78. https://doi.org/10.17482/uumfd.644684.
EndNote Öztürk HT (01 Nisan 2020) BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 25 1 361–378.
IEEE H. T. Öztürk, “BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI”, UUJFE, c. 25, sy. 1, ss. 361–378, 2020, doi: 10.17482/uumfd.644684.
ISNAD Öztürk, Hasan Tahsin. “BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 25/1 (Nisan 2020), 361-378. https://doi.org/10.17482/uumfd.644684.
JAMA Öztürk HT. BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI. UUJFE. 2020;25:361–378.
MLA Öztürk, Hasan Tahsin. “BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, c. 25, sy. 1, 2020, ss. 361-78, doi:10.17482/uumfd.644684.
Vancouver Öztürk HT. BETONARME KISA KONSOLLARIN TS 500’E GÖRE OPTİMUM TASARIMINDA ABC, TLBO VE TLABC ALGORİTMALARININ BAŞARIMI. UUJFE. 2020;25(1):361-78.

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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