Research Article
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Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi

Year 2022, Volume: 34 Issue: 2, 889 - 898, 30.09.2022

Rabia Nur Sağlam Merve Açıkgenç Ulaş Kürşat Esat Alyamaç

https://doi.org/10.35234/fumbd.1133877
Cited By: 3

Abstract

Bu çalışmanın amacı hafif beton üretilirken hedef mukavemet için gerekli olan hafif agrega miktarının tayin edilmesi ve gelecek çalışmalarda üretilecek hafif betonlar için pratik bir karışım tasarımı sunmaktır. Bu amaçla literatürde yer alan hafif beton ile ilgili çalışmalar detaylı bir şekilde incelenmiştir. Bu çalışmalarda bulunan hafif betonlara ait veriler sınıflandırılmış ve listelenmiştir. Literatürden hafif betonlara ait karışım bileşenleri ve hedef basınç dayanımı değerleri alınmıştır. Literatürden alınan deneysel veriler ile bir Yapay Sinir Ağı (YSA) modeli geliştirilmiştir. Bu modelde su, çimento, normal agrega, toz, kimyasal katkı, hedef basınç mukavemet ve hafif agrega tipi giriş olarak kullanılmıştır. Modelin çıkışı ise hafif agrega miktarı olarak belirlenmiştir. Düzenlenen veriler geliştirilen YSA modeli kullanılarak hafif beton bileşimindeki hafif agrega miktarının tahmininde kullanılmıştır. Geliştirilen model çıkışları ile literatürden alınmış deneysel veriler karşılaştırılmıştır. Geliştirilen YSA modeli ile elde edilen sonuçlar ile deneysel veriler arasındaki farklar uygun sınırlar içerisinde bulunmuştur. Sonuç olarak geliştirilen YSA modelinin hedeflenen çıkışı başarılı bir şekilde ve yüksek doğrulukta tahmin ettiği görülmektedir. Böylece hedef basınç dayanımı belirlenmiş olan bir hafif beton karışımı için hafif agrega miktarı hızlı, pratik ve yüksek doğrulukta tahmin edilmiş olacaktır.

Keywords

Hafif beton Hafif agrega Hedef basınç dayanımı Yapay sinir ağı

Supporting Institution

Fırat Üniversitesi Bilimsel Araştırma Proje Fonu

Project Number

MF.19.38

Thanks

Makalenin yazarlarından Rabia Nur SAĞLAM YÖK 100/2000 bursiyeridir. Katkılarından dolayı YÖK’e teşekkür ederiz. Bu çalışma Fırat Üniversitesi Bilimsel Araştırma Proje Fonu tarafından, MF.19.38 proje numarası ile desteklenmiştir.

References

  • B. Baradan, Yapı Malzemesi II. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Basım Ünitesi, 2000.
  • S. (Satish) Chandra and L. Berntsson, Lightweight aggregate concrete : science, technology, and applications. 2002.
  • V. Khonsari, E. Eslami, and A. Anvari, “Effects of expanded perlite aggregate (EPA) on the mechanical behavior of lightweight concrete,” in Proceedings of the 7th international conference on fracture and mechanics of concrete & concrete structure (FraMCoS-7), Jeju, Korea, 2010, pp. 1354–1361.
  • “TS EN 206-1,” 2002, vol. 13535, no. 1998.
  • M. Açikgenç, M. Ulaş, and K. E. Alyamaç, “Using an Artificial Neural Network to Predict Mix Compositions of Steel Fiber-Reinforced Concrete,” Arab. J. Sci. Eng., vol. 40, no. 2, pp. 407–419, 2015, doi: 10.1007/s13369-014-1549-x.
  • H.-G. Ni and J.-Z. Wang, “Prediction of compressive strength of concrete by neural networks,” Cem. Concr. Res., vol. 30, no. 8, pp. 1245–1250, 2000.
  • M. I. Waris, J. Mir, V. Plevris, and A. Ahmad, “Predicting compressive strength of CRM samples using Image processing and ANN,” IOP Conf. Ser. Mater. Sci. Eng., vol. 899, no. 1, 2020, doi: 10.1088/1757-899X/899/1/012014.
  • D. Nagarajan, T. Rajagopal, and N. Meyappan, “A comparative study on prediction models for strength properties of LWA concrete using artificial neural network,” Rev. la construcción, vol. 19, no. 1, pp. 103–111, 2020.
  • D. J. Armaghani and P. G. Asteris, A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength, vol. 4. Springer London, 2020.
  • A. F. Bingöl, A. Tortum, and R. Gül, “Neural networks analysis of compressive strength of lightweight concrete after high temperatures,” Mater. Des., vol. 52, pp. 258–264, 2013.
  • G. Calis, S. A. Yıldızel, and U. S. Keskin, “Application of an artificial neural network for predicting compressive and flexural strength of basalt fiber added lightweight.”
  • R. Pranamika, “Predictive study on Mechanical strength of Lightweight concrete using MRA and ANN,” Turkish J. Comput. Math. Educ., vol. 12, no. 10, pp. 7774–7792, 2021.
  • J. Y. Yoon, H. Kim, Y.-J. Lee, and S.-H. Sim, “Prediction model for mechanical properties of lightweight aggregate concrete using artificial neural network,” Materials (Basel)., vol. 12, no. 17, p. 2678, 2019.
  • H. Ergezer, M. Dikmen, and E. Özdemir, “Yapay sinir ağları ve tanıma sistemleri,” PiVOLKA, vol. 2, no. 6, pp. 14–17, 2003.
  • R. Hecht-Nielsen, “Theory of the backpropagation neural network,” in Neural networks for perception, Elsevier, 1992, pp. 65–93.
  • T. Gupta, K. A. Patel, S. Siddique, R. K. Sharma, and S. Chaudhary, “Prediction of mechanical properties of rubberised concrete exposed to elevated temperature using ANN,” Measurement, vol. 147, p. 106870, 2019.
  • E. M. Golafshani, A. Behnood, and M. Arashpour, “Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer,” Constr. Build. Mater., vol. 232, p. 117266, 2020.
  • S. C. Kou, G. Lee, C. S. Poon, and W. L. Lai, “Properties of lightweight aggregate concrete prepared with PVC granules derived from scraped PVC pipes,” Waste Manag., vol. 29, no. 2, pp. 621–628, 2009, doi: 10.1016/j.wasman.2008.06.014.
  • S. Yang, X. Yue, X. Liu, and Y. Tong, “Properties of self-compacting lightweight concrete containing recycled plastic particles,” Constr. Build. Mater., vol. 84, pp. 444–453, 2015, doi: 10.1016/j.conbuildmat.2015.03.038.
  • K. M. A. Sohel, K. Al-Jabri, M. H. Zhang, and J. Y. R. Liew, “Flexural fatigue behavior of ultra-lightweight cement composite and high strength lightweight aggregate concrete,” Constr. Build. Mater., vol. 173, pp. 90–100, 2018, doi: 10.1016/j.conbuildmat.2018.03.276.
  • R. V. Balendran, F. P. Zhou, A. Nadeem, and A. Y. T. Leung, “Influence of steel fibres on strength and ductility of normal and lightweight high strength concrete,” Build. Environ., vol. 37, no. 12, pp. 1361–1367, 2002, doi: 10.1016/S0360-1323(01)00109-3.
  • K. S. Chia and M. H. Zhang, “Water permeability and chloride penetrability of high-strength lightweight aggregate concrete,” Cem. Concr. Res., vol. 32, no. 4, pp. 639–645, 2002, doi: 10.1016/S0008-8846(01)00738-4.
  • M. N. Haque, H. Al-Khaiat, and O. Kayali, “Strength and durability of lightweight concrete,” Cem. Concr. Compos., vol. 26, no. 4, pp. 307–314, 2004, doi: 10.1016/S0958-9465(02)00141-5.
  • J. A. Rossignolo and M. V. C. Agnesini, “Durability of polymer-modified lightweight aggregate concrete,” Cem. Concr. Compos., vol. 26, no. 4, pp. 375–380, 2004, doi: 10.1016/S0958-9465(03)00022-2.
  • J. Alduaij, K. Alshaleh, M. Naseer Haque, and K. Ellaithy, “Lightweight concrete in hot coastal areas,” Cem. Concr. Compos., vol. 21, no. 5–6, pp. 453–458, 1999, doi: 10.1016/S0958-9465(99)00035-9.
  • T. Y. Lo, H. Z. Cui, and Z. G. Li, “Influence of aggregate pre-wetting and fly ash on mechanical properties of lightweight concrete,” Waste Manag., vol. 24, no. 4, pp. 333–338, 2004, doi: 10.1016/j.wasman.2003.06.003.
  • B. Chen and J. Liu, “Experimental application of mineral admixtures in lightweight concrete with high strength and workability,” Constr. Build. Mater., vol. 22, no. 6, pp. 1108–1113, 2008, doi: 10.1016/j.conbuildmat.2007.03.001.
  • J. A. Bogas and A. Gomes, “A simple mix design method for structural lightweight aggregate concrete,” pp. 1919–1932, 2013, doi: 10.1617/s11527-013-0029-1.
  • J. A. Bogas, J. De Brito, and J. M. Figueiredo, “Mechanical characterization of concrete produced with recycled lightweight expanded clay aggregate concrete,” J. Clean. Prod., vol. 89, pp. 187–195, 2015, doi: 10.1016/j.jclepro.2014.11.015.
  • K. S. Youm, J. Moon, J. Y. Cho, and J. J. Kim, “Experimental study on strength and durability of lightweight aggregate concrete containing silica fume,” Constr. Build. Mater., vol. 114, pp. 517–527, 2016, doi: 10.1016/j.conbuildmat.2016.03.165.
  • J. A. Rossignolo, M. V. C. Agnesini, and J. A. Morais, “Properties of high-performance LWAC for precast structures with Brazilian lightweight aggregates,” Cem. Concr. Compos., vol. 25, no. 1, pp. 77–82, 2003, doi: 10.1016/S0958-9465(01)00046-4.
  • B. Zhang and C. S. Poon, “Use of Furnace Bottom Ash for producing lightweight aggregate concrete with thermal insulation properties,” J. Clean. Prod., vol. 99, pp. 94–100, 2015, doi: 10.1016/j.jclepro.2015.03.007.
  • P. Shafigh, M. Z. Jumaat, and H. Mahmud, “Oil palm shell as a lightweight aggregate for production high strength lightweight concrete,” Constr. Build. Mater., vol. 25, no. 4, pp. 1848–1853, 2011, doi: 10.1016/j.conbuildmat.2010.11.075.
  • P. Shafigh, M. Z. Jumaat, H. Bin Mahmud, and U. J. Alengaram, “A new method of producing high strength oil palm shell lightweight concrete,” Mater. Des., vol. 32, no. 10, pp. 4839–4843, 2011, doi: 10.1016/j.matdes.2011.06.015.
  • P. Shafigh, M. Z. Jumaat, H. Bin Mahmud, and U. J. Alengaram, “Oil palm shell lightweight concrete containing high volume ground granulated blast furnace slag,” Constr. Build. Mater., vol. 40, pp. 231–238, 2013, doi: 10.1016/j.conbuildmat.2012.10.007.
  • M. A. Mannan and C. Ganapathy, “Mix design for oil palm shell concrete,” Cem. Concr. Res., vol. 31, no. 9, pp. 1323–1325, 2001, doi: 10.1016/S0008-8846(01)00585-3.
  • P. Shafigh, H. Bin Mahmud, and M. Z. Jumaat, “Oil palm shell lightweight concrete as a ductile material,” Mater. Des., vol. 36, pp. 650–654, 2012, doi: 10.1016/j.matdes.2011.12.003.
  • P. Shafigh, H. Bin Mahmud, M. Z. Bin Jumaat, R. Ahmmad, and S. Bahri, “Structural lightweight aggregate concrete using two types of waste from the palm oil industry as aggregate,” J. Clean. Prod., vol. 80, pp. 187–196, 2014, doi: 10.1016/j.jclepro.2014.05.051.
  • P. Shafigh, U. Johnson Alengaram, H. Bin Mahmud, and M. Z. Jumaat, “Engineering properties of oil palm shell lightweight concrete containing fly ash,” Mater. Des., vol. 49, no. 2013, pp. 613–621, 2013, doi: 10.1016/j.matdes.2013.02.004.
  • M. A. Mannan and C. U. Ganapathy, “Engineering-properties-of-concrete-with-oil-palm-shell-as-coarse-aggregate_2002_Construction-and-Building-Materials,” Constr. Build. Mater., vol. 16, pp. 29–34, 2002.
  • F. K. Alqahtani, G. Ghataora, M. I. Khan, and S. Dirar, “Novel lightweight concrete containing manufactured plastic aggregate,” Constr. Build. Mater., vol. 148, pp. 386–397, 2017, doi: 10.1016/j.conbuildmat.2017.05.011.
  • M. J. Shannag, “Characteristics of lightweight concrete containing mineral admixtures,” Constr. Build. Mater., vol. 25, no. 2, pp. 658–662, 2011, doi: 10.1016/j.conbuildmat.2010.07.025.
  • Behnood A, Golafshani EM.2018, Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves. J Clean Prod.;202:54–64.
  • Acikgenc Ulas M,2022,. Development of an artificial neural network model to predict waste marble powder demand in eco-efficient self-compacting concrete. Structural Concrete.

Year 2022, Volume: 34 Issue: 2, 889 - 898, 30.09.2022

Rabia Nur Sağlam Merve Açıkgenç Ulaş Kürşat Esat Alyamaç

https://doi.org/10.35234/fumbd.1133877
Cited By: 3

Abstract

Project Number

MF.19.38

References

  • B. Baradan, Yapı Malzemesi II. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Basım Ünitesi, 2000.
  • S. (Satish) Chandra and L. Berntsson, Lightweight aggregate concrete : science, technology, and applications. 2002.
  • V. Khonsari, E. Eslami, and A. Anvari, “Effects of expanded perlite aggregate (EPA) on the mechanical behavior of lightweight concrete,” in Proceedings of the 7th international conference on fracture and mechanics of concrete & concrete structure (FraMCoS-7), Jeju, Korea, 2010, pp. 1354–1361.
  • “TS EN 206-1,” 2002, vol. 13535, no. 1998.
  • M. Açikgenç, M. Ulaş, and K. E. Alyamaç, “Using an Artificial Neural Network to Predict Mix Compositions of Steel Fiber-Reinforced Concrete,” Arab. J. Sci. Eng., vol. 40, no. 2, pp. 407–419, 2015, doi: 10.1007/s13369-014-1549-x.
  • H.-G. Ni and J.-Z. Wang, “Prediction of compressive strength of concrete by neural networks,” Cem. Concr. Res., vol. 30, no. 8, pp. 1245–1250, 2000.
  • M. I. Waris, J. Mir, V. Plevris, and A. Ahmad, “Predicting compressive strength of CRM samples using Image processing and ANN,” IOP Conf. Ser. Mater. Sci. Eng., vol. 899, no. 1, 2020, doi: 10.1088/1757-899X/899/1/012014.
  • D. Nagarajan, T. Rajagopal, and N. Meyappan, “A comparative study on prediction models for strength properties of LWA concrete using artificial neural network,” Rev. la construcción, vol. 19, no. 1, pp. 103–111, 2020.
  • D. J. Armaghani and P. G. Asteris, A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength, vol. 4. Springer London, 2020.
  • A. F. Bingöl, A. Tortum, and R. Gül, “Neural networks analysis of compressive strength of lightweight concrete after high temperatures,” Mater. Des., vol. 52, pp. 258–264, 2013.
  • G. Calis, S. A. Yıldızel, and U. S. Keskin, “Application of an artificial neural network for predicting compressive and flexural strength of basalt fiber added lightweight.”
  • R. Pranamika, “Predictive study on Mechanical strength of Lightweight concrete using MRA and ANN,” Turkish J. Comput. Math. Educ., vol. 12, no. 10, pp. 7774–7792, 2021.
  • J. Y. Yoon, H. Kim, Y.-J. Lee, and S.-H. Sim, “Prediction model for mechanical properties of lightweight aggregate concrete using artificial neural network,” Materials (Basel)., vol. 12, no. 17, p. 2678, 2019.
  • H. Ergezer, M. Dikmen, and E. Özdemir, “Yapay sinir ağları ve tanıma sistemleri,” PiVOLKA, vol. 2, no. 6, pp. 14–17, 2003.
  • R. Hecht-Nielsen, “Theory of the backpropagation neural network,” in Neural networks for perception, Elsevier, 1992, pp. 65–93.
  • T. Gupta, K. A. Patel, S. Siddique, R. K. Sharma, and S. Chaudhary, “Prediction of mechanical properties of rubberised concrete exposed to elevated temperature using ANN,” Measurement, vol. 147, p. 106870, 2019.
  • E. M. Golafshani, A. Behnood, and M. Arashpour, “Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer,” Constr. Build. Mater., vol. 232, p. 117266, 2020.
  • S. C. Kou, G. Lee, C. S. Poon, and W. L. Lai, “Properties of lightweight aggregate concrete prepared with PVC granules derived from scraped PVC pipes,” Waste Manag., vol. 29, no. 2, pp. 621–628, 2009, doi: 10.1016/j.wasman.2008.06.014.
  • S. Yang, X. Yue, X. Liu, and Y. Tong, “Properties of self-compacting lightweight concrete containing recycled plastic particles,” Constr. Build. Mater., vol. 84, pp. 444–453, 2015, doi: 10.1016/j.conbuildmat.2015.03.038.
  • K. M. A. Sohel, K. Al-Jabri, M. H. Zhang, and J. Y. R. Liew, “Flexural fatigue behavior of ultra-lightweight cement composite and high strength lightweight aggregate concrete,” Constr. Build. Mater., vol. 173, pp. 90–100, 2018, doi: 10.1016/j.conbuildmat.2018.03.276.
  • R. V. Balendran, F. P. Zhou, A. Nadeem, and A. Y. T. Leung, “Influence of steel fibres on strength and ductility of normal and lightweight high strength concrete,” Build. Environ., vol. 37, no. 12, pp. 1361–1367, 2002, doi: 10.1016/S0360-1323(01)00109-3.
  • K. S. Chia and M. H. Zhang, “Water permeability and chloride penetrability of high-strength lightweight aggregate concrete,” Cem. Concr. Res., vol. 32, no. 4, pp. 639–645, 2002, doi: 10.1016/S0008-8846(01)00738-4.
  • M. N. Haque, H. Al-Khaiat, and O. Kayali, “Strength and durability of lightweight concrete,” Cem. Concr. Compos., vol. 26, no. 4, pp. 307–314, 2004, doi: 10.1016/S0958-9465(02)00141-5.
  • J. A. Rossignolo and M. V. C. Agnesini, “Durability of polymer-modified lightweight aggregate concrete,” Cem. Concr. Compos., vol. 26, no. 4, pp. 375–380, 2004, doi: 10.1016/S0958-9465(03)00022-2.
  • J. Alduaij, K. Alshaleh, M. Naseer Haque, and K. Ellaithy, “Lightweight concrete in hot coastal areas,” Cem. Concr. Compos., vol. 21, no. 5–6, pp. 453–458, 1999, doi: 10.1016/S0958-9465(99)00035-9.
  • T. Y. Lo, H. Z. Cui, and Z. G. Li, “Influence of aggregate pre-wetting and fly ash on mechanical properties of lightweight concrete,” Waste Manag., vol. 24, no. 4, pp. 333–338, 2004, doi: 10.1016/j.wasman.2003.06.003.
  • B. Chen and J. Liu, “Experimental application of mineral admixtures in lightweight concrete with high strength and workability,” Constr. Build. Mater., vol. 22, no. 6, pp. 1108–1113, 2008, doi: 10.1016/j.conbuildmat.2007.03.001.
  • J. A. Bogas and A. Gomes, “A simple mix design method for structural lightweight aggregate concrete,” pp. 1919–1932, 2013, doi: 10.1617/s11527-013-0029-1.
  • J. A. Bogas, J. De Brito, and J. M. Figueiredo, “Mechanical characterization of concrete produced with recycled lightweight expanded clay aggregate concrete,” J. Clean. Prod., vol. 89, pp. 187–195, 2015, doi: 10.1016/j.jclepro.2014.11.015.
  • K. S. Youm, J. Moon, J. Y. Cho, and J. J. Kim, “Experimental study on strength and durability of lightweight aggregate concrete containing silica fume,” Constr. Build. Mater., vol. 114, pp. 517–527, 2016, doi: 10.1016/j.conbuildmat.2016.03.165.
  • J. A. Rossignolo, M. V. C. Agnesini, and J. A. Morais, “Properties of high-performance LWAC for precast structures with Brazilian lightweight aggregates,” Cem. Concr. Compos., vol. 25, no. 1, pp. 77–82, 2003, doi: 10.1016/S0958-9465(01)00046-4.
  • B. Zhang and C. S. Poon, “Use of Furnace Bottom Ash for producing lightweight aggregate concrete with thermal insulation properties,” J. Clean. Prod., vol. 99, pp. 94–100, 2015, doi: 10.1016/j.jclepro.2015.03.007.
  • P. Shafigh, M. Z. Jumaat, and H. Mahmud, “Oil palm shell as a lightweight aggregate for production high strength lightweight concrete,” Constr. Build. Mater., vol. 25, no. 4, pp. 1848–1853, 2011, doi: 10.1016/j.conbuildmat.2010.11.075.
  • P. Shafigh, M. Z. Jumaat, H. Bin Mahmud, and U. J. Alengaram, “A new method of producing high strength oil palm shell lightweight concrete,” Mater. Des., vol. 32, no. 10, pp. 4839–4843, 2011, doi: 10.1016/j.matdes.2011.06.015.
  • P. Shafigh, M. Z. Jumaat, H. Bin Mahmud, and U. J. Alengaram, “Oil palm shell lightweight concrete containing high volume ground granulated blast furnace slag,” Constr. Build. Mater., vol. 40, pp. 231–238, 2013, doi: 10.1016/j.conbuildmat.2012.10.007.
  • M. A. Mannan and C. Ganapathy, “Mix design for oil palm shell concrete,” Cem. Concr. Res., vol. 31, no. 9, pp. 1323–1325, 2001, doi: 10.1016/S0008-8846(01)00585-3.
  • P. Shafigh, H. Bin Mahmud, and M. Z. Jumaat, “Oil palm shell lightweight concrete as a ductile material,” Mater. Des., vol. 36, pp. 650–654, 2012, doi: 10.1016/j.matdes.2011.12.003.
  • P. Shafigh, H. Bin Mahmud, M. Z. Bin Jumaat, R. Ahmmad, and S. Bahri, “Structural lightweight aggregate concrete using two types of waste from the palm oil industry as aggregate,” J. Clean. Prod., vol. 80, pp. 187–196, 2014, doi: 10.1016/j.jclepro.2014.05.051.
  • P. Shafigh, U. Johnson Alengaram, H. Bin Mahmud, and M. Z. Jumaat, “Engineering properties of oil palm shell lightweight concrete containing fly ash,” Mater. Des., vol. 49, no. 2013, pp. 613–621, 2013, doi: 10.1016/j.matdes.2013.02.004.
  • M. A. Mannan and C. U. Ganapathy, “Engineering-properties-of-concrete-with-oil-palm-shell-as-coarse-aggregate_2002_Construction-and-Building-Materials,” Constr. Build. Mater., vol. 16, pp. 29–34, 2002.
  • F. K. Alqahtani, G. Ghataora, M. I. Khan, and S. Dirar, “Novel lightweight concrete containing manufactured plastic aggregate,” Constr. Build. Mater., vol. 148, pp. 386–397, 2017, doi: 10.1016/j.conbuildmat.2017.05.011.
  • M. J. Shannag, “Characteristics of lightweight concrete containing mineral admixtures,” Constr. Build. Mater., vol. 25, no. 2, pp. 658–662, 2011, doi: 10.1016/j.conbuildmat.2010.07.025.
  • Behnood A, Golafshani EM.2018, Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves. J Clean Prod.;202:54–64.
  • Acikgenc Ulas M,2022,. Development of an artificial neural network model to predict waste marble powder demand in eco-efficient self-compacting concrete. Structural Concrete.
There are 44 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section MBD
Authors

Rabia Nur Sağlam 0000-0003-3015-0766

Merve Açıkgenç Ulaş 0000-0001-8986-7791

Kürşat Esat Alyamaç 0000-0002-3226-4073

Project Number MF.19.38
Publication Date September 30, 2022
Submission Date June 21, 2022
Published in Issue Year 2022 Volume: 34 Issue: 2

Cite

APA Sağlam, R. N., Açıkgenç Ulaş, M., & Alyamaç, K. E. (2022). Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 34(2), 889-898. https://doi.org/10.35234/fumbd.1133877
AMA Sağlam RN, Açıkgenç Ulaş M, Alyamaç KE. Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. September 2022;34(2):889-898. doi:10.35234/fumbd.1133877
Chicago Sağlam, Rabia Nur, Merve Açıkgenç Ulaş, and Kürşat Esat Alyamaç. “Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı Ile Tahmin Edilmesi”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 34, no. 2 (September 2022): 889-98. https://doi.org/10.35234/fumbd.1133877.
EndNote Sağlam RN, Açıkgenç Ulaş M, Alyamaç KE (September 1, 2022) Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 34 2 889–898.
IEEE R. N. Sağlam, M. Açıkgenç Ulaş, and K. E. Alyamaç, “Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi”, Fırat Üniversitesi Mühendislik Bilimleri Dergisi, vol. 34, no. 2, pp. 889–898, 2022, doi: 10.35234/fumbd.1133877.
ISNAD Sağlam, Rabia Nur et al. “Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı Ile Tahmin Edilmesi”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi 34/2 (September 2022), 889-898. https://doi.org/10.35234/fumbd.1133877.
JAMA Sağlam RN, Açıkgenç Ulaş M, Alyamaç KE. Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2022;34:889–898.
MLA Sağlam, Rabia Nur et al. “Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı Ile Tahmin Edilmesi”. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, vol. 34, no. 2, 2022, pp. 889-98, doi:10.35234/fumbd.1133877.
Vancouver Sağlam RN, Açıkgenç Ulaş M, Alyamaç KE. Hafif Beton Üretimi İçin Gerekli Olan Hafif Agrega Miktarının Yapay Sinir Ağı ile Tahmin Edilmesi. Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 2022;34(2):889-98.

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