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ANFIS ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması

Year 2020, Volume: 8 Issue: 4, 2388 - 2399, 29.10.2020
https://doi.org/10.29130/dubited.686047

Abstract

Teknolojik gelişmeler sayesinde asfalt üretim sıcaklıkları düşürülerek sıcak karışımlara benzer performanslı karışımlar elde edilebilmektedir. Sıcak karışım asfaltların malzemelerinin yani agrega ve bitümün yüksek sıcaklıklarda ısıtılması nedeniyle yarattıkları olumsuz çevresel etkiler, üretim maliyetlerinde meydana gelen sürekli artış ve hammadde kaynaklarındaki azalma nedenleriyle asfalt üretim sıcaklıklarının düşürülmesi eğilimi ve malzemelerin geri kazanımının popülerliği giderek artmaktadır.


Köpük bitüm ve geri kazanılmış/doğal agrega kullanılarak uygulanan köpük bitümle geri kazanım yöntemi, çevresel ve ekonomik olarak avantajları olan bir yöntemdir. Köpük bitümle uygun bir karışım hazırlayabilmek için ilk aşama, karışımda kullanılacak bitümün en ideal köpürme özelliklerinin (genleşme oranı ve yarılanma süresi) doğru şekilde belirlenebilmesidir. Bu nedenle çalışmada, farklı asfalt çimentolarının köpürme özellikleri deneysel olarak belirlenmiştir. Ayrıca deneylerde kullanılan bitümlerin köpürme özellikleri Bulanık Mantık ve ANFIS yöntemleri kullanılarak modellenmiş ve sonuçlar deneysel olarak elde edilen verilerle kıyaslanmıştır.


Elde edilen veriler ışığında kullanılan tüm bitümlerin farklı köpürtme su yüzdeleri için kullanımlarının literatürde önerilen minimum köpürme özelliklerini sağladığı ve kullanılan tahminleme yöntemlerinin benzer sonuçlarla deneysel verileri desteklediği sonucuna ulaşılmıştır.

Supporting Institution

Karayolları Genel Müdürlüğü, SDÜ BAP

Project Number

KGM-ARGE/2017-1, 4939-D1-17

Thanks

Bu çalışma, 4939-D1-17 numaralı Süleyman Demirel Üniversitesi Bilimsel Araştırma Projeleri tarafından ve KGM-ARGE/2017-1 numaralı proje ile Karayolları Genel Müdürlüğü tarafından desteklenmiştir.

References

  • [1] A. L. Wang, Z. S. Fu, F. M. Liu, “Asphalt foaming quality control model using neural network and parameters optimization,” International Journal of Pavement Research and Technology, vol. 11, pp. 401–407, 2018.
  • [2] F. Dong, X. Yu, X. Liang, G. Ding, J. Wei, “Influence of foaming water and aging process on the properties of foamed asphalt,” Construction and Building Materials, vol. 153, pp. 866–874, 2017.
  • [3] D. Rettner, “Overview of mix design and construction,” presented at 28th Annual Regional Local Road Conference Foamed Asphalt, Rapid City, USA, 2013.
  • [4] K. J. Jenkins, “Mix design considerations for cold and half-cold bituminous mixes with emphasis on foamed bitumen,” Ph.D. dissertation, University of Stellenbosch, South Africa, 2000.
  • [5] D. E. Newcomb, E. Arambula, F. Yin, J. Zhang, A. Bhasin, W. Li, Z. Arega, “Properties of foamed asphalt for warm mix asphalt applications,” National Cooperative Highway Research Program, Washington DC, USA, NCHRP Rep.807, 2015.
  • [6] M. R. M. Hasan, Z. You, X. Yang, “A comprehensive review of theory, development, and implementation of warm mix asphalt using foaming techniques,” Construction and Building Materials, vol. 152, pp. 115–133, 2017.
  • [7] K. M. Muthen, “Foamed asphalt mixes - mix design procedure,” Sabita Ltd & CSIR Transportek, Pretoria, South Africa, Rep. CR-98/077, 1998.
  • [8] M. Namutebi, B. Birgisson, A. Guarin, D. Jelagin, “Exploratory study on bitumen content determination for foamed bitumen mixes based on porosity and indirect tensile strength,” Journal of Traffic and Transportation Engineering, vol. 4, no. 2, pp. 131-144, 2017.
  • [9] G. P. He, W.G. Wong, “Decay properties of the foamed bitumens,” Construction and Building Materials, vol. 20, pp. 866–877, 2006.
  • [10] L. P. F. Abreu, J. R. M. Oliveira, H. M. R. D. Silva, D. Palha, P. V. Fonseca, “Suitability of different foamed bitumens for warm mix asphalts with increasing recycling rates,” Construction and Building Materials, vol. 142, pp. 342–353, 2017.
  • [11] G. B. Arguelles, F. Giustozzi, M. Crispino, G. W. Flintsch, “Investigating physical and rheological properties of foamed bitumen,” Construction and Building Materials, vol. 72, pp. 423-433, 2014.
  • [12] M. F. Saleh, “Effect of rheology on the bitumen foamability and mechanical properties of foam bitumen stabilized mixes,” International Journal of Pavement Engineering, vol. 8, no. 2, pp. 99-110, 2007.
  • [13] Cold recycling–Wirtgen cold recycling technology, 1st ed., Wirtgen Gmbh, Windhagen, Germany, 2012.
  • [14] C. W. Schwartz, S. Khosravifar, “Design and evaluation of foamed asphalt base materials,” State Highway Administration, Maryland, USA, Rep. SP909B4E, 2013.
  • [15] G. P. He, W. G. Wong, “Effects of moisture on strength and permanent dformation of foamed asphalt mix incorporating RAP materials,” Construction and Building Materials, vol. 22, pp. 30–40, 2008.
  • [16] Technical guideline, bitumen stabilised materials - a guideline for the design and construction of bitumen emulsion and foamed bitumen stabilized materials, 2nd ed., Asphalt Academy Co., Pretoria, South Africa, 2009.
  • [17] S. Maccarrone, G. Holleran, A. Ky, “Cold asphalt systems as an alternative to hot mix,” presented at 9th AAPA International Asphalt Conference, Surfers Paradise Qld, Australia, 1995.
  • [18] L. J. Milton, M. Earland, “Design guide and specification for structural maintenance of highway pavements by cold in situ recycling,” Transport Research Laboratory, Wokingham, United Kingdom, Rep. 386, 1999.
  • [19] J. Ramanujam, J. Griffin, “Review of insitu foam bitumen stabilization practises in Queensland,” presented at Engineering Technology Forum, Brisbane, Australia, 2016.
  • [20] L. A. Zadeh, L.A., “Fuzzy sets,” Information and Control, vol. 8, pp. 338-352, 1965.
  • [21] D. Moazami, H. Behbahani, R. Muniandy, “Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic,” Expert Systems with Applications, vol. 38, pp. 12869–12879, 2011.
  • [22] N. Mathur, I. Glesk, A. Buis, “Comparison of adaptive neuro-fuzzy inference system (ANFIS) and gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses,” Medical Engineering and Physics, vol. 38, pp. 1083-1089, 2016.
  • [23] J. S. R. Jang, “ANFIS: Adaptive-network-based fuzzy inference system,” IEEE Transactions on Systems, Man. and Cybernetics, vol. 23, no. 3, pp. 665–685, 1993.
  • [24] B. Gökçe, G. Sonugür, “ANFIS ve YSA yöntemleri ile işlenmiş doğal taş üretim sürecinde verimlilik analizi,” AKÜ FEMÜBİD, c. 16, ss. 174-185, 2016.

Investigation of the Usability of ANFIS and Fuzzy Logic Methods in Estimation of Foam Bitumen Expansion Ratio and Half Life Parameters

Year 2020, Volume: 8 Issue: 4, 2388 - 2399, 29.10.2020
https://doi.org/10.29130/dubited.686047

Abstract

Thanks to the technological advances, asphalt production temperatures can be lowered and performance mixes similar to hot mixes can be obtained. The trend of lowering asphalt production temperatures and the popularity of materials recycling are gradually increasing due to the negative environmental effects caused by the heating of hot mix asphalt materials, that is, aggregate and bitumen at high temperatures.

Recycling with foam bitumen method, applied using foam bitumen and recycled / natural aggregate is a method that has environmental and economic advantages. The first step to prepare a suitable mixture with foam bitumen is to determine the most ideal foaming properties (expansion ratio and half life) of the bitumen to be used in the mixture.

For this reason, foaming properties of different asphalt cements are determined experimentally. In addition, the foaming properties of bitumens used in experiments were modeled using Fuzzy Logic and ANFIS methods and the results were compared with the experimental data.

In the light of the data obtained, it was concluded that the use of all bitumen used for different foaming water percentages provides the minimum foaming properties recommended in the literature and the estimation methods used support experimental data with similar results.

Project Number

KGM-ARGE/2017-1, 4939-D1-17

References

  • [1] A. L. Wang, Z. S. Fu, F. M. Liu, “Asphalt foaming quality control model using neural network and parameters optimization,” International Journal of Pavement Research and Technology, vol. 11, pp. 401–407, 2018.
  • [2] F. Dong, X. Yu, X. Liang, G. Ding, J. Wei, “Influence of foaming water and aging process on the properties of foamed asphalt,” Construction and Building Materials, vol. 153, pp. 866–874, 2017.
  • [3] D. Rettner, “Overview of mix design and construction,” presented at 28th Annual Regional Local Road Conference Foamed Asphalt, Rapid City, USA, 2013.
  • [4] K. J. Jenkins, “Mix design considerations for cold and half-cold bituminous mixes with emphasis on foamed bitumen,” Ph.D. dissertation, University of Stellenbosch, South Africa, 2000.
  • [5] D. E. Newcomb, E. Arambula, F. Yin, J. Zhang, A. Bhasin, W. Li, Z. Arega, “Properties of foamed asphalt for warm mix asphalt applications,” National Cooperative Highway Research Program, Washington DC, USA, NCHRP Rep.807, 2015.
  • [6] M. R. M. Hasan, Z. You, X. Yang, “A comprehensive review of theory, development, and implementation of warm mix asphalt using foaming techniques,” Construction and Building Materials, vol. 152, pp. 115–133, 2017.
  • [7] K. M. Muthen, “Foamed asphalt mixes - mix design procedure,” Sabita Ltd & CSIR Transportek, Pretoria, South Africa, Rep. CR-98/077, 1998.
  • [8] M. Namutebi, B. Birgisson, A. Guarin, D. Jelagin, “Exploratory study on bitumen content determination for foamed bitumen mixes based on porosity and indirect tensile strength,” Journal of Traffic and Transportation Engineering, vol. 4, no. 2, pp. 131-144, 2017.
  • [9] G. P. He, W.G. Wong, “Decay properties of the foamed bitumens,” Construction and Building Materials, vol. 20, pp. 866–877, 2006.
  • [10] L. P. F. Abreu, J. R. M. Oliveira, H. M. R. D. Silva, D. Palha, P. V. Fonseca, “Suitability of different foamed bitumens for warm mix asphalts with increasing recycling rates,” Construction and Building Materials, vol. 142, pp. 342–353, 2017.
  • [11] G. B. Arguelles, F. Giustozzi, M. Crispino, G. W. Flintsch, “Investigating physical and rheological properties of foamed bitumen,” Construction and Building Materials, vol. 72, pp. 423-433, 2014.
  • [12] M. F. Saleh, “Effect of rheology on the bitumen foamability and mechanical properties of foam bitumen stabilized mixes,” International Journal of Pavement Engineering, vol. 8, no. 2, pp. 99-110, 2007.
  • [13] Cold recycling–Wirtgen cold recycling technology, 1st ed., Wirtgen Gmbh, Windhagen, Germany, 2012.
  • [14] C. W. Schwartz, S. Khosravifar, “Design and evaluation of foamed asphalt base materials,” State Highway Administration, Maryland, USA, Rep. SP909B4E, 2013.
  • [15] G. P. He, W. G. Wong, “Effects of moisture on strength and permanent dformation of foamed asphalt mix incorporating RAP materials,” Construction and Building Materials, vol. 22, pp. 30–40, 2008.
  • [16] Technical guideline, bitumen stabilised materials - a guideline for the design and construction of bitumen emulsion and foamed bitumen stabilized materials, 2nd ed., Asphalt Academy Co., Pretoria, South Africa, 2009.
  • [17] S. Maccarrone, G. Holleran, A. Ky, “Cold asphalt systems as an alternative to hot mix,” presented at 9th AAPA International Asphalt Conference, Surfers Paradise Qld, Australia, 1995.
  • [18] L. J. Milton, M. Earland, “Design guide and specification for structural maintenance of highway pavements by cold in situ recycling,” Transport Research Laboratory, Wokingham, United Kingdom, Rep. 386, 1999.
  • [19] J. Ramanujam, J. Griffin, “Review of insitu foam bitumen stabilization practises in Queensland,” presented at Engineering Technology Forum, Brisbane, Australia, 2016.
  • [20] L. A. Zadeh, L.A., “Fuzzy sets,” Information and Control, vol. 8, pp. 338-352, 1965.
  • [21] D. Moazami, H. Behbahani, R. Muniandy, “Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic,” Expert Systems with Applications, vol. 38, pp. 12869–12879, 2011.
  • [22] N. Mathur, I. Glesk, A. Buis, “Comparison of adaptive neuro-fuzzy inference system (ANFIS) and gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses,” Medical Engineering and Physics, vol. 38, pp. 1083-1089, 2016.
  • [23] J. S. R. Jang, “ANFIS: Adaptive-network-based fuzzy inference system,” IEEE Transactions on Systems, Man. and Cybernetics, vol. 23, no. 3, pp. 665–685, 1993.
  • [24] B. Gökçe, G. Sonugür, “ANFIS ve YSA yöntemleri ile işlenmiş doğal taş üretim sürecinde verimlilik analizi,” AKÜ FEMÜBİD, c. 16, ss. 174-185, 2016.
There are 24 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Kemal Muhammet Erten 0000-0001-5181-4109

Serdal Terzi 0000-0002-4776-824X

Hüseyin Akbulut 0000-0003-4504-4384

Ekinhan Erişkin 0000-0002-0087-0933

Project Number KGM-ARGE/2017-1, 4939-D1-17
Publication Date October 29, 2020
Published in Issue Year 2020 Volume: 8 Issue: 4

Cite

APA Erten, K. M., Terzi, S., Akbulut, H., Erişkin, E. (2020). ANFIS ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması. Duzce University Journal of Science and Technology, 8(4), 2388-2399. https://doi.org/10.29130/dubited.686047
AMA Erten KM, Terzi S, Akbulut H, Erişkin E. ANFIS ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması. DUBİTED. October 2020;8(4):2388-2399. doi:10.29130/dubited.686047
Chicago Erten, Kemal Muhammet, Serdal Terzi, Hüseyin Akbulut, and Ekinhan Erişkin. “ANFIS Ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı Ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması”. Duzce University Journal of Science and Technology 8, no. 4 (October 2020): 2388-99. https://doi.org/10.29130/dubited.686047.
EndNote Erten KM, Terzi S, Akbulut H, Erişkin E (October 1, 2020) ANFIS ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması. Duzce University Journal of Science and Technology 8 4 2388–2399.
IEEE K. M. Erten, S. Terzi, H. Akbulut, and E. Erişkin, “ANFIS ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması”, DUBİTED, vol. 8, no. 4, pp. 2388–2399, 2020, doi: 10.29130/dubited.686047.
ISNAD Erten, Kemal Muhammet et al. “ANFIS Ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı Ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması”. Duzce University Journal of Science and Technology 8/4 (October 2020), 2388-2399. https://doi.org/10.29130/dubited.686047.
JAMA Erten KM, Terzi S, Akbulut H, Erişkin E. ANFIS ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması. DUBİTED. 2020;8:2388–2399.
MLA Erten, Kemal Muhammet et al. “ANFIS Ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı Ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması”. Duzce University Journal of Science and Technology, vol. 8, no. 4, 2020, pp. 2388-99, doi:10.29130/dubited.686047.
Vancouver Erten KM, Terzi S, Akbulut H, Erişkin E. ANFIS ve Bulanık Mantık Yöntemlerinin Köpük Bitümün Genleşme Oranı ve Yarılanma Süresi Parametreleri Tahmininde Kullanılabilirliğinin Araştırılması. DUBİTED. 2020;8(4):2388-99.