Modelling the Effects of Hydrated Lime Additives on Asphalt Mixtures by Fuzzy Logic and ANN

Yıl 2019, Cilt: 30 Sayı: 6, 9533 - 9559, 01.11.2019

Mustafa Sinan Yardım , Betül Değer Şitilbay Selim Dündar

https://doi.org/10.18400/tekderg.402816

Cited By: 3

Öz

In this study, Marshall test results of hot mix
asphalt samples having various Hydrated Lime (HL) content rates were modelled
using Fuzzy Logic (FL) and Artificial Neural Networks (ANN). Test sets having
various HL content were prepared in order to investigate the effect of HL. Marshall
Stability test was performed on the samples to obtain the optimal Asphalt
Content (AC) ratio. The results were evaluated in order to determine HL
additives’ sensitivity on the mixture parameters. The Marshall Test results
were used to develop the FL and ANN models. The models developed produced
acceptable estimations of the mixture parameters.

Anahtar Kelimeler

Hot mix asphalt, Hydrated lime, Marshall mix design, Fuzzy Logic, Artificial Neural Networks

Modelling the Effects of Hydrated Lime Additives on Asphalt Mixtures by Fuzzy Logic and ANN

Öz

In this study, Marshall test results of hot mix asphalt samples having various Hydrated Lime (HL) content rates were modelled using Fuzzy Logic (FL) and Artificial Neural Networks (ANN). Test sets having various HL content were prepared in order to investigate the effect of HL. Marshall Stability test was performed on the samples to obtain the optimal Asphalt Content (AC) ratio. The results were evaluated in order to determine HL additives’ sensitivity on the mixture parameters. The Marshall Test results were used to develop the FL and ANN models. The models developed produced acceptable estimations of the mixture parameters.

Anahtar Kelimeler

Hot mix asphalt, hydrated lime, marshall mix design, fuzzy logic, artificial neural networks

Kaynakça

• NLA, Hydrated Lime – A Solution for High Performance Hot Mix Asphalt. Retrieved January 8, 2016, from http://www.lime.org/documents/publications/free_downloads/fact-asphalt.pdf
• Lesueur, D., Hydrated Lime: a Proven Additive for Durable Asphalt Pavements – Critical Literature Review, European Lime Association (EuLA) Ed., 2010, Brussels, Belgium, 2010.
• TSE, Turkish Standard 3720: Bituminous mixtures - Asphalt concrete - Mix design - Marshall method, 2010.
• Asphalt Institute, The Asphalt Handbook (MS-4), 7th. ed., Asphalt Institute: Lexington, 2007.
• Witczak, M., Bari, J., Development of a master curve (E*) database for lime modified asphaltic mixtures. Arizona State University Research Report, Tempe (Arizona, USA): Arizona State University, (July) 2004.
• Lesueur, D., Little, D., Effect of Hydrated Lime on Rheology, Fracture, and Aging of Bitumen. Transportation Research Record: Journal of the Transportation Research Board, 1661(-1), 93–105, 1999.
• Petersen, J. C., Plancher, H., Harnsberger, P. M., Lime Treatment of Asphalt to Reduce Age Hardening and Improve Flow Properties. Association of Asphalt Paving Technologists, 56-87, 632–653, 1987.
• Cross, S., Experimental Cold In-Place Recycling with Hydrated Lime. Transportation Research Record, 1684(1), 186–193, 1999.
• Sebaaly, P., Hitti, E., Weitzel, D., Effectiveness of Lime in Hot-Mix Asphalt Pavements. Transportation Research Record, 1832(1), 34–41, 2003.
• Lee, S., Seo, Y., Kim, Y. R., Effect of hydrated lime on dynamic modulus of asphalt-aggregate mixtures in the state of North Carolina. KSCE Journal of Civil Engineering, 14(6), 829–837, 2010.
• Niazi, Y., Jalili, M., Effect of Portland cement and lime additives on properties of cold in-place recycled mixtures with asphalt emulsion. Construction and Building Materials, 23(3), 1338–1343, 2009.
• Rogge, D. F., Leahy, R. B., Blair, R., Cold-In-Place (CIP) Recycling with Lime. Transportation Research Report, 95-17, 1995.
• Al-Suhaibani, A. R., Al-Mudaiheem, J., Al-Fozan, F., Effect of Filler Type and Content on Properties of Asphalt Concrete Mixes. In Effects of Aggregates and Mineral Fillers on Asphalt Mixtures Performance, 107–130, 1992.
• Niazi, Y., Jalili, M., Effect of Portland cement and lime additives on properties of cold in-place recycled mixtures with asphalt emulsion. In Construction and Building Materials 23(3):1338-1343, 2009.
• Lesueur, D., Little, D., Hydrated Lime as an Active Filler in Bitumen. Paper Presented at the Annual Meeting of the TRB, Washington, D.C., January 1999.
• Mohammad, L., Abadie, C., Gokmen, R., Puppala, A., Mechanistic Evaluation of Hydrated Lime in Hot-Mix Asphalt Mixtures. Transportation Research Record, 1723(1), 26–36, 2000.
• Kennedy, T. W., Ping, W. V., An Evaluation Of Effectiveness Of Antistripping Additives In Protecting Asphalt Mixtures From Moisture Damage (With Discussion) (pp. 230–263). Washington: Association of Asphalt Paving Technologists, 1991.
• Si, Z., Little, D. N., Asce, F., Lytton, R. L. (2002). Effects of Inorganic and Polymer Filler on Tertiary Damage Development in Asphalt Mixtures, (April), 164–172.
• Huang, S.-C., Claine Petersen, J., Robertson, R., Branthaver, J., Effect of Hydrated Lime on Long-Term Oxidative Aging Characteristics of Asphalt. Transportation Research Record, 1810(307), 17–24, 2002.
• Radenberg, M., Effect of Hydrated Lime Addition on the Deformation of Hot Mix Asphalt in the Wheel Tracking Test. In Lhoist HMA Symposium. Düsseldorf, 1998.
• Rogge, D. F., Leahy, R. B. and Blair, R., Cold In-Place (CIP) Recycling with Lime. Transportation Research Instit., OR State Univ, Corvallis, OR, July 1995.
• Şengül, C. E., Asfalt Kaplamalarda Tekerlek İzinde Oturma ve Su Hasarı Problemlerinin Azaltılması İçin Sönmüş Kireç Kullanımı. Karadeniz Technical University, 2006.
• Verhasselt, A. F., Choquet, F. S., Comparing Field And Laboratory Aging Of Bitumens On A Kinetic Basis. Transportation Research Record, 30–38, 1993.
• Hicks, R. G., Moisture Damage in Asphalt Concrete. Washington: NCHRP Transportation Research Board, 1991.
• Kennedy, T. W., Ping, W. V., Evaluation of Effectiveness of Antistripping Additives in Protecting Asphalt Mixtures from Moisture Damage. Journal of the Association of Asphalt Paving Technologists, from the Proceedings of Technical Sessions, Vol. 60, March 1991.
• Little, D. N., Epps, J. A., The Benefits of Hydrated Lime in Hot Mix Asphalt. Arlington, 2001.
• Petersen, J.C., Plancher, H., and Harnsberger, P.M., Lime Treatment of Asphalt to Reduce Age Hardening and Improve Flow Properties. AAPT, Volume 56, 1987.
• Sebaaly, P.E., Tohme, P., Hitti, E., Stansburry, K., Epps, J., Asphalt Concrete Antistripping Techniques, Pierre, 2003.
• Rogge, D. F., Leahy, R. B. and Blair, R., Cold In-Place (CIP) Recycling with Lime, Transportation Research Instit., OR State Univ, Corvallis, OR, July 1995.
• Jones, G. M., The Effect of Hydrated Lime on Asphalt in Bituminous Pavements. NLA Meeting, Utah DOT, May 22, 1997.
• Kim, Y. R., Little, D. N., Song, I., Effect of Mineral Fillers on Fatigue Resistance and Fundamental Material Characteristics. Transportation Research Record, (1832), 1–8, 2003.
• Recasens, R. M., Martinez, A., Jimenez, F. P., Bianchetto, H., Effect of Filler on the Aging Potential of Asphalt Mixtures. Transportation Research Board, (1901), 10–17, 2005.
• Cheng, D. X., Little, D. N., Lytton, R. L., Holste, J. C., Moisture Damage Evaluation of Asphalt Mixture by Considering Both Moisture Diffusion and Repeated Load Conditions. Transportation Research Board, (1832), 42–49, 2003.
• Hicks, R. G., Todd, V. S., Life Cycle Costs for Lime in Hot Mix Asphalt, 2001. Retrieved January 11, 2016, from https://lime.org/documents/publications/free_downloads/lcca_vol-2.pdf
• Yardım, M. S., Balcı, U., The Effect of Hydrated Lime on the Marshall Stability for a Specific Amount of Asphalt Content in the Hot Mix Asphalt, Proceedings of the 9th International Fracture Conference, 9th International Fracture Conference, pp. 571-580. Yıldız Technical University, Istanbul, 2011.
• Tigdemir, M., Karasahin, M., Sen, Z., Investigation of fatigue behaviour of asphalt concrete pavements with fuzzy-logic approach. International Journal of Fatigue, 24(8), 903–910, 2002.
• Saltan, M., Saltan, S., Şahiner, A., Fuzzy logic modeling of deflection behavior against dynamic loading in flexible pavements. Construction and Building Materials, 21(7), 1406–1414, 2007.
• Saltan, M. Sezgin, H., Hybrid neural network and finite element modeling of sub-base layer material properties in flexible pavements. Materials and Design, 28, 1725–1730, 2007.
• Ozsahin, T.H., Oruc, S., Neural network model for resilient modulus of emulsified asphalt mixtures. Construction and Building Materials, 22, 1436–1445, 2008.
• Ozgan, E., Artificial neural network based modelling of the Marshall Stability of asphalt concrete. Expert Systems with Applications, 38(5), 6025–6030, 2011.
• Xiao, F., Amirkhanian, S. N., Juang, C. H., Hu, S., Shen, J., Model developments of long-term aged asphalt binders. Construction and Building Materials, 37, 248–256, 2012.
• Mirzahosseini, M. R., Aghaeifar, A., Alavi, A. H., Gandomi, A. H., Seyednour, R., Permanent deformation analysis of asphalt mixtures using soft computing techniques. Expert Systems with Applications, 38(5), 6081–6100, 2011.
• Tapkin, S., Çevik, A., Uşar, Ü., Accumulated strain prediction of polypropylene modified marshall specimens in repeated creep test using artificial neural networks. Expert Systems with Applications, 36, 11186-11197, 2009.
• Tapkin, S., Çevik, A., Uşar, Ü., Prediction of Marshall test results for polypropylene modified dense bituminous mixtures using neural networks. Expert Systems with Applications, 37, 4660–4670, 2010.
• Xiao, F., Amirkhanian, S. N., Artificial Neural Network Approach to Estimating Stiffness Behavior of Rubberized Asphalt Concrete Containing Reclaimed Asphalt Pavement. Journal of Transportation Engineering, 135(8), 580–589, 2009.
• Kok, B.V., Yilmaz, M., Sengoz, B., Sengur, A., Avci, E., Investigation of complex modulus of base and SBS modified bitumen with artificial neural networks. Expert Systems with Applications, 37, 7775–7780, 2010.
• Kok, B.V., Yilmaz, M., Cakiroglu, M., Kuloglu, N. Sengur, A., Neural network modeling of SBS modified bitumen produced with different methods. Fuel, 106, 265–270, 2013.
• Cevik, A., Cabalar, A.F., Modelling damping ratio and shear modulus of sand–mica mixtures using genetic programming. Expert Systems with Applications, 36, 7749–7757, 2009.
• Aksoy, A., Iskender, E., Kahraman, H.T., Application of the intuitive k-NN Estimator for prediction of the Marshall Test (ASTM D1559) results for asphalt mixtures. Construction and Building Materials, 34, 561–569, 2012.
• Moghaddam, T.B., Shamshirband, S., Soltani, M., Petkovic, D., Karim, M.R. Baaj, H., Estimation of the rutting performance of Polyethylene Terephthalate modified asphalt mixtures by adaptive neuro-fuzzy methodology. Construction and Building Materials, 96, 550–555, 2015.
• Pourtahmasb, M. S., Karim, M.R. Shamshirband, S. Resilient modulus prediction of asphalt mixtures containing Recycled Concrete Aggregate using an adaptive neuro-fuzzy methodology. Construction and Building Materials, 82, 257–263, 2015.
• Kavak, A., Lime Stabilization in Turkey. In The Seminar of Lime in Asphalt. İstanbul: İsfalt, 2011.
• Denayer, C., Lime Stabilization. In The Seminar of Lime in Asphalt. İstanbul: İsfalt, 2011.
• Highway Technical Specifications, General Directorate of Highways, Item No. 170/2, Ankara, Turkey, 2006.
• ASTM D 6927-15, Standard Test Method for Marshall Stability and Flow of Bituminous Mixtures, 1–7, 2010.
• KGM, Karayolu Teknik Şartnamesi. Ankara: Karayolları Genel Müdürlüğü, 2006.
• Yardım, M. S., Gürsoy, M, Balcı, U., The Effect of Hydrated Lime Content Amount on Low Temperature Cracking Strength of Flexible Pavements for Various Temperature Values (in Turkish), YTÜ BAP Research Project, No. 29-05-01-KAP01, İstanbul, 2014.
• Wang, W.J., Luoh, L., Simple Computation of the Defuzzifications of Center of Sum and Center of Gravity,” Journal of Intelligent and Fuzzy Systems (9) 1-2, pp. 53-59, 2000.
• Shafabakhsh, G.H. , Jafari Ani, O., Talebsafa, M., Artificial neural network modeling (ANN) for predicting rutting performance of nano-modified hot-mix asphalt mixtures containing steel slag aggregates. Construction and Building Materials, 85, 136-143, 2015.
• Khuntia, S., Das, A.K., Mohanty M., Panda, M., Prediction of Marshall Parameters of Modified Bituminous Mixtures Using Artificial Intelligence Techniques. International Journal of Transportation Science and Technology, 3, 211-228, 2014.