Prediction Compressive Strength of Self-Compacting Concrete Containing Fly Ash Using Fuzzy Logic Inference System
Self-compacting concrete (SCC) developed in Japan
in the late 80s has enabled the construction industry to reduce
demand on the resources, improve the work condition and also
reduce the impact of environment by elimination of the need for
compaction. Fuzzy logic (FL) approaches has recently been used to
model some of the human activities in many areas of civil
engineering applications. Especially from these systems in the model
experimental studies, very good results have been obtained. In the
present study, a model for predicting compressive strength of SCC
containing various proportions of fly ash, as partial replacement of
cement has been developed by using Fuzzy Inference System (FIS).
For the purpose of building this model, a database of experimental
data were gathered from the literature and used for training and
testing the model. The used data as the inputs of fuzzy logic models
are arranged in a format of five parameters that cover the total binder
content, fly ash replacement percentage, water content,
superplasticizer and age of specimens. The training and testing results
in the fuzzy logic model have shown a strong potential for predicting
the compressive strength of SCC containing fly ash in the considered
range.
[1] Ozawa K, Maekawa K, Kunishima H, Okamura H, “Performance of
concrete based on the durability design of concrete structures” in Proc
Sec East Asia Pacific CSEC, 1989, pp. 445–456.
[2] Rols S, Ambroise JP, Pera J, “Effects of different viscosity agents on the
properties of self-levelling concrete”, Cem Concr Res, vol 29, pp. 261-
266, 1999.
[3] Okamura H, M., Ozawa,K. and Ouchi, M, “Self-compacting high
performance concrete”, In: proceedings of the fifth EA SEC1995, pp.
2381-2388.
[4] European Guidelines for Self-Compacting Concrete: Specification,
Production and Use, European Project Group, 2005.
[5] Bartos, P.J.M. y Grauers, M, “Self-Compacting Concrete”, Concrete,
Vol. 33, nº 4, pp. 9-13, 1999.
[6] Skarendahl A, Ozawa K, Ouchi M, “Market acceptance of selfcompacting
concrete”, The Swedish experience. In. Proc. 2nd inter symp
on SCC, Coms Engineering Corporation Tokyo, pp. 1–13, 2001.
[7] Dhiyaneshwaran S, Ramanathan P, Baskar I and Venkatasubramani R,
“Study on Durability Characteristics of Self-Compacting Concrete with
Fly Ash”, Jordan Journal of Civil Engineering, Vol. 7, nº. 3, pp. 342-
352, 2013.
[8] Jino, John, Maya TM and Meenambal T, “Mathematical modeling for
durability characteristics of fly ash concrete”. International Journal of
Engineering Science and Technology, Vol. 4, n°. 1, pp. 353-361, 2012.
[9] Yahia A, Tanimura M, Shimabukuro A, Shimovama Y, “Effect of
rheological parameters on self-compactability of concrete containing
various mineral admixtures”, In International RILEM symposium on
self-compacting concrete, pp. 523-535, 1999.
[10] Kurita M, Nomura T, “Highly-flowable steel fiber-reinforced concrete
containing fly ash”. ACI Special Publication, Vol. 178, 1998.
[11] Gao, F. L, “A new way of predicting cement strength-fuzzy logic”,
Cement and Concrete Research, Vol. 27, n° 6, pp. 883-888, 1997.
[12] Muthukumaran P, Demirli K, Stiharu I, Bhat RB “Boundary
conditioning for structural tuning using fuzzy logic approach”, Comput
Struct, Vol 74, n° 5, pp. 547-557, 2000.
[13] Akkurt, S., Tayfur, G., & Can, S, “Fuzzy logic model for the prediction
of cement compressive strength”, Cement and Concrete Research, Vol.
34, n° 8, pp. 1429-1433, 2004.
[14] Nehdi ML, Bassuoni MT, “Fuzzy logic approach for estimating
durability of concrete”, Proceedings of the ICE-Construction
Materials, Vol. 62, n° 2, pp. 81-92, 2009.
[15] Gencel O, Ozel C, Koksal F, Martinez-Barrera G, Brostow W, Polat H,
“Fuzzy Logic Model for Prediction of Properties of Fiber Reinforced
Self-compacting Concrete ”, Materials Science, Vol. 19, n° 2, pp. 203-
215, 2013.
[16] Da Silva WRL, Štemberk P, “Predicting self-compacting concrete
shrinkage based on a modified fuzzy logic model”, Engineering
Mechanics, Vol. 229, pp. 1173-1183, 2012.
[17] G, Goktepe A. B, Ramyar K, Sezer A, “Prediction of sulfate expansion
of PC mortar using adaptive neuro-fuzzy methodology”. Build Environ,
Vol. 42, n° 7, pp. 1264-1269, 2007.
[18] Deka P. C and Diwate S. N, “Modeling Compressive Strength of Ready
Mix Concrete Using Soft Computing Techniques”, International Journal
of Earth Sciences and Engineering, Vol. 4, n° 6, pp. 793-796, 2011.
[19] Zadeh L. A, Klir G. J and Yuan B, “Advances in Fuzzy Systems -
Applications and Theory”, Vol. 6, River Edge, NJ: World Scientific,
1996.
[20] Yurkovich S, Passino, K. M, “A Laboratory Course of Fuzzy Control”,
IEEE Transactions on Education, Vol. 42, n° 1, pp.15-21, 1999.
[21] Sen Z, “Fuzzy Modeling in Engineering”, Class Notes, Civil
Engineering Faculty, Istanbul Technical University, Istanbul, Turkey,
1999.
[22] Demuth H, Beale M, Hagan M, “Neural Network Toolbox 5, User’s
Guide”, The MathWorks, Inc, 849 pp, 2007.
[23] Topçu İ B, Sarıdemir M, “Prediction of mechanical properties of
recycled aggregate concretes containing silica fume using artificial
neural networks and fuzzy logic”. Computational Materials Science,
Vol. 42, n° 1, pp. 74-82, 2008.
[24] Mamdani E H, Assilian S, “An experiment in linguistic synthesis with a
fuzzy logic controller”, Int J Man-Mach Stud, Vol. 7, pp. 1-13, 1975.
[25] Takagi T, Sugeno M, “Fuzzy identification of systems and its
applications to modeling and control”, IEEE Trans Syst Man Cyber,
Vol. 15, pp. 116-132, 1985. [26] Sugeno M, Kang GT. “Structure identification of fuzzy model”, Fuzzy
Sets SystMan Cyber,Vol. 23, pp. 665-685, 1993.
[27] Bingöl, Ferhat A., Tohumcu I, “Effects of different curing regimes on
the compressive strength properties of self compacting concrete
incorporating fly ash and silica fume”. Materials & Design, Vol. 51, pp.
12-18, 2013.
[28] Mahmoud, E, Ibrahim A, El-Chabib H, Patibandla V. C, “Self-
Consolidating Concrete Incorporating High Volume of Fly Ash, Slag,
and Recycled Asphalt Pavement”, International Journal of Concrete
Structures and Materials, Vol. 7, n° 2, pp. 155-163, 2013.
[29] Güneyisi E, Gesoğlu M, Özbay E, “Strength and drying shrinkage
properties of self-compacting concretes incorporating multi-system
blended mineral admixtures”, Construction and Building Materials,
Vol. 24, n° 10, pp. 1878-1887, 2010.
[30] Khatib J. M, “Performance of self-compacting concrete containing fly
ash”, Construction and Building Materials, Vol. 22, n° 9, pp. 1963-1971,
2008.
[31] Naik, T. R, Kumar R, Ramme B. W, Canpolat F, “Development of highstrength,
economical self-consolidating concrete”, Construction and
Building Materials, Vol. 30, pp. 463-469, 2012.
[32] Şahmaran M, Yaman İ. Ö, Tokyay M, “Transport and mechanical
properties of self consolidating concrete with high volume fly ash”,
Cement and concrete composites, Vol. 31, n° 2, pp. 99-106, 2009.
[33] Yazıcı H, “The effect of silica fume and high-volume Class C fly ash on
mechanical properties, chloride penetration and freeze–thaw resistance
of self-compacting concrete”, Construction and building Materials, Vol.
22, n° 4, pp. 456-462, 2008.
[1] Ozawa K, Maekawa K, Kunishima H, Okamura H, “Performance of
concrete based on the durability design of concrete structures” in Proc
Sec East Asia Pacific CSEC, 1989, pp. 445–456.
[2] Rols S, Ambroise JP, Pera J, “Effects of different viscosity agents on the
properties of self-levelling concrete”, Cem Concr Res, vol 29, pp. 261-
266, 1999.
[3] Okamura H, M., Ozawa,K. and Ouchi, M, “Self-compacting high
performance concrete”, In: proceedings of the fifth EA SEC1995, pp.
2381-2388.
[4] European Guidelines for Self-Compacting Concrete: Specification,
Production and Use, European Project Group, 2005.
[5] Bartos, P.J.M. y Grauers, M, “Self-Compacting Concrete”, Concrete,
Vol. 33, nº 4, pp. 9-13, 1999.
[6] Skarendahl A, Ozawa K, Ouchi M, “Market acceptance of selfcompacting
concrete”, The Swedish experience. In. Proc. 2nd inter symp
on SCC, Coms Engineering Corporation Tokyo, pp. 1–13, 2001.
[7] Dhiyaneshwaran S, Ramanathan P, Baskar I and Venkatasubramani R,
“Study on Durability Characteristics of Self-Compacting Concrete with
Fly Ash”, Jordan Journal of Civil Engineering, Vol. 7, nº. 3, pp. 342-
352, 2013.
[8] Jino, John, Maya TM and Meenambal T, “Mathematical modeling for
durability characteristics of fly ash concrete”. International Journal of
Engineering Science and Technology, Vol. 4, n°. 1, pp. 353-361, 2012.
[9] Yahia A, Tanimura M, Shimabukuro A, Shimovama Y, “Effect of
rheological parameters on self-compactability of concrete containing
various mineral admixtures”, In International RILEM symposium on
self-compacting concrete, pp. 523-535, 1999.
[10] Kurita M, Nomura T, “Highly-flowable steel fiber-reinforced concrete
containing fly ash”. ACI Special Publication, Vol. 178, 1998.
[11] Gao, F. L, “A new way of predicting cement strength-fuzzy logic”,
Cement and Concrete Research, Vol. 27, n° 6, pp. 883-888, 1997.
[12] Muthukumaran P, Demirli K, Stiharu I, Bhat RB “Boundary
conditioning for structural tuning using fuzzy logic approach”, Comput
Struct, Vol 74, n° 5, pp. 547-557, 2000.
[13] Akkurt, S., Tayfur, G., & Can, S, “Fuzzy logic model for the prediction
of cement compressive strength”, Cement and Concrete Research, Vol.
34, n° 8, pp. 1429-1433, 2004.
[14] Nehdi ML, Bassuoni MT, “Fuzzy logic approach for estimating
durability of concrete”, Proceedings of the ICE-Construction
Materials, Vol. 62, n° 2, pp. 81-92, 2009.
[15] Gencel O, Ozel C, Koksal F, Martinez-Barrera G, Brostow W, Polat H,
“Fuzzy Logic Model for Prediction of Properties of Fiber Reinforced
Self-compacting Concrete ”, Materials Science, Vol. 19, n° 2, pp. 203-
215, 2013.
[16] Da Silva WRL, Štemberk P, “Predicting self-compacting concrete
shrinkage based on a modified fuzzy logic model”, Engineering
Mechanics, Vol. 229, pp. 1173-1183, 2012.
[17] G, Goktepe A. B, Ramyar K, Sezer A, “Prediction of sulfate expansion
of PC mortar using adaptive neuro-fuzzy methodology”. Build Environ,
Vol. 42, n° 7, pp. 1264-1269, 2007.
[18] Deka P. C and Diwate S. N, “Modeling Compressive Strength of Ready
Mix Concrete Using Soft Computing Techniques”, International Journal
of Earth Sciences and Engineering, Vol. 4, n° 6, pp. 793-796, 2011.
[19] Zadeh L. A, Klir G. J and Yuan B, “Advances in Fuzzy Systems -
Applications and Theory”, Vol. 6, River Edge, NJ: World Scientific,
1996.
[20] Yurkovich S, Passino, K. M, “A Laboratory Course of Fuzzy Control”,
IEEE Transactions on Education, Vol. 42, n° 1, pp.15-21, 1999.
[21] Sen Z, “Fuzzy Modeling in Engineering”, Class Notes, Civil
Engineering Faculty, Istanbul Technical University, Istanbul, Turkey,
1999.
[22] Demuth H, Beale M, Hagan M, “Neural Network Toolbox 5, User’s
Guide”, The MathWorks, Inc, 849 pp, 2007.
[23] Topçu İ B, Sarıdemir M, “Prediction of mechanical properties of
recycled aggregate concretes containing silica fume using artificial
neural networks and fuzzy logic”. Computational Materials Science,
Vol. 42, n° 1, pp. 74-82, 2008.
[24] Mamdani E H, Assilian S, “An experiment in linguistic synthesis with a
fuzzy logic controller”, Int J Man-Mach Stud, Vol. 7, pp. 1-13, 1975.
[25] Takagi T, Sugeno M, “Fuzzy identification of systems and its
applications to modeling and control”, IEEE Trans Syst Man Cyber,
Vol. 15, pp. 116-132, 1985. [26] Sugeno M, Kang GT. “Structure identification of fuzzy model”, Fuzzy
Sets SystMan Cyber,Vol. 23, pp. 665-685, 1993.
[27] Bingöl, Ferhat A., Tohumcu I, “Effects of different curing regimes on
the compressive strength properties of self compacting concrete
incorporating fly ash and silica fume”. Materials & Design, Vol. 51, pp.
12-18, 2013.
[28] Mahmoud, E, Ibrahim A, El-Chabib H, Patibandla V. C, “Self-
Consolidating Concrete Incorporating High Volume of Fly Ash, Slag,
and Recycled Asphalt Pavement”, International Journal of Concrete
Structures and Materials, Vol. 7, n° 2, pp. 155-163, 2013.
[29] Güneyisi E, Gesoğlu M, Özbay E, “Strength and drying shrinkage
properties of self-compacting concretes incorporating multi-system
blended mineral admixtures”, Construction and Building Materials,
Vol. 24, n° 10, pp. 1878-1887, 2010.
[30] Khatib J. M, “Performance of self-compacting concrete containing fly
ash”, Construction and Building Materials, Vol. 22, n° 9, pp. 1963-1971,
2008.
[31] Naik, T. R, Kumar R, Ramme B. W, Canpolat F, “Development of highstrength,
economical self-consolidating concrete”, Construction and
Building Materials, Vol. 30, pp. 463-469, 2012.
[32] Şahmaran M, Yaman İ. Ö, Tokyay M, “Transport and mechanical
properties of self consolidating concrete with high volume fly ash”,
Cement and concrete composites, Vol. 31, n° 2, pp. 99-106, 2009.
[33] Yazıcı H, “The effect of silica fume and high-volume Class C fly ash on
mechanical properties, chloride penetration and freeze–thaw resistance
of self-compacting concrete”, Construction and building Materials, Vol.
22, n° 4, pp. 456-462, 2008.
@article{"International Journal of Architectural, Civil and Construction Sciences:68749", author = "O. Belalia Douma and B. Boukhatem and M. Ghrici", title = "Prediction Compressive Strength of Self-Compacting Concrete Containing Fly Ash Using Fuzzy Logic Inference System", abstract = "Self-compacting concrete (SCC) developed in Japan
in the late 80s has enabled the construction industry to reduce
demand on the resources, improve the work condition and also
reduce the impact of environment by elimination of the need for
compaction. Fuzzy logic (FL) approaches has recently been used to
model some of the human activities in many areas of civil
engineering applications. Especially from these systems in the model
experimental studies, very good results have been obtained. In the
present study, a model for predicting compressive strength of SCC
containing various proportions of fly ash, as partial replacement of
cement has been developed by using Fuzzy Inference System (FIS).
For the purpose of building this model, a database of experimental
data were gathered from the literature and used for training and
testing the model. The used data as the inputs of fuzzy logic models
are arranged in a format of five parameters that cover the total binder
content, fly ash replacement percentage, water content,
superplasticizer and age of specimens. The training and testing results
in the fuzzy logic model have shown a strong potential for predicting
the compressive strength of SCC containing fly ash in the considered
range.
", keywords = "Self-compacting concrete, fly ash, strength
prediction, fuzzy logic.", volume = "8", number = "12", pages = "1336-5", }
