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http://dx.doi.org/10.12989/cac.2020.26.4.309

Optimization of cost and mechanical properties of concrete with admixtures using MARS and PSO  

Benemaran, Reza Sarkhani (Department of Civil Engineering, Faculty of Geotechnical Engineering, University of Tabriz)
Esmaeili-Falak, Mahzad (Department of Civil Engineering, Tehran North Branch, Islamic Azad University)
Publication Information
Computers and Concrete / v.26, no.4, 2020 , pp. 309-316 More about this Journal
Abstract
The application of multi-variable adaptive regression spline (MARS) in predicting he long-term compressive strength of a concrete with various admixtures has been investigated in this study. The compressive strength of concrete specimens, which were made based on 24 different mix designs using various mineral and chemical admixtures in different curing ages have been obtained. First, The values of fly ash (FA), micro-silica (MS), water-reducing admixture (WRA), coarse and fine aggregates, cement, water, age of samples and compressive strength were defined as inputs to the model, and MARS analysis was used to model the compressive strength of concrete and to evaluate the most important parameters affecting the estimation of compressive strength of the concrete. Next, the proposed equation by the MARS method using particle swarm optimization (PSO) algorithm has been optimized to have more efficient equation from the economical point of view. The proposed model in this study predicted the compressive strength of the concrete with various admixtures with a correlation coefficient of R=0.958 rather than the measured compressive strengths within the laboratory. The final model reduced the production cost and provided compressive strength by reducing the WRA and increasing the FA and curing days, simultaneously. It was also found that due to the use of the liquid membrane-forming compounds (LMFC) for its lower cost than water spraying method (SWM) and also for the longer operating time of the LMFC having positive mechanical effects on the final concrete, the final product had lower cost and better mechanical properties.
Keywords
high strength concrete; compressive strength prediction; fly ash; micro-silica; MARS; PSO; cost optimization;
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1 Seyedpoor, S.M., Salajegheh, J., Salajegheh, E. and Gholizadeh, S. (2011), "Optimal design of arch dams subjected to earthquake loading by a combination of simultaneous perturbation stochastic approximation and particle swarm algorithms", Appl. Soft Comput., 11(1), 39-48. https://doi.org/10.1016/j.asoc.2009.10.014.   DOI
2 ASTM C309-19 (2019), Standard Specification for Liquid Membrane-Forming Compounds for Curing Concrete, ASTM International, West Conshohocken. PA.
3 Atici, U. (2011), "Prediction of the strength of mineral admixture concrete using multivariable regression analysis and an artificial neural network", Exp. Syst. Appl., 38(8), 9609-9618. https://doi.org/10.1016/j.eswa.2011.01.156.   DOI
4 Atis, C.D. (2005), "Strength properties of high-volume fly ash roller compacted and workable concrete, and influence of curing condition", Cement Concrete Res., 35(6), 1112-1121. https://doi.org/10.1016/j.cemconres.2004.07.037.   DOI
5 Babu, K.G. and Rao, G.S.N. (1994), "Early strength behavior of fly ash concretes", Cement Concrete Res., 24(2), 277-284. https://doi.org/10.1016/0008-8846(94)90053-1.   DOI
6 Cabrera, J.G. and Claisse, P.A. (1990), "Measurement of chloride penetration into silica fume concrete", Cement Concrete Compos., 12(3), 157-161. https://doi.org/10.1016/0958-9465(90)90016-Q.   DOI
7 Adamowski, J.F. (2008), "Development of a short-term river flood forecasting method for snowmelt driven floods based on wavelet and cross wavelet analysis", J. Hydrol., 353(3-4), 247-266. https://doi.org/10.1016/j.jhydrol.2008.02.013.   DOI
8 Agrawal, V. and Sharma, A. (2010), "Prediction of slump in concrete using artificial neural networks", World Acad. Sci., Eng. Technol., 45, 25-32.
9 Chou, J.H. and Ghaboussi, J. (2001), "Genetic algorithm in structural damage detection", Comput. Struct., 79(14), 1335-1353. https://doi.org/10.1016/S0045-7949(01)00027-X.   DOI
10 Chou, J.S. and Pham, A.D. (2013), "Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength", Constr. Build. Mater., 49, 554-563. https://doi.org/10.1016/j.conbuildmat.2013.08.078.   DOI
11 Craven, P. and Wahba, G. (1978), "Smoothing noisy data with spline functions", Numerische Mathematik, 31(4), 377-403. https://doi.org/10.1007/BF01404567.   DOI
12 Davraz, M., Ceylan, H., Topcu, I.B. and Uygunoglu, T. (2018), "Pozzolanic effect of andesite waste powder on mechanical properties of high strength concrete", Constr. Build. Mater., 165, 494-503. https://doi.org/10.1016/j.conbuildmat.2018.01.043.   DOI
13 Detwiler, R.J., Bhatty, J.I. and Battacharja, S. (1996), Supplementary Cementing Materials for Use in Blended Cements, No. R&D Bulletin RD112T.
14 Dutta, S., Samui, P. and Kim, D. (2018), "Comparison of machine learning techniques to predict compressive strength of concrete", Comput. Concrete, 21(4), 463-470. https://doi.org/10.12989/cac.2018.21.4.463.   DOI
15 Esmaeili-Falak, M. (2017), "Effect of system's geometry on the stability of frozen wall in excavation of saturated granular soils", Doctoral dissertation, University of Tabriz.
16 Esmaeili-Falak, M., Katebi, H. and Javadi, A.A. (2020b), "Effect of freezing on stress-strain characteristics of granular and cohesive soils", J. Cold Reg. Eng., 34(2), 05020001. https://doi.org/10.1061/(ASCE)CR.1943-5495.0000205.   DOI
17 Esmaeili-Falak, M., Katebi, H., Vadiati, M. and Adamowski, J. (2019), "Predicting triaxial compressive strength and Young's modulus of frozen sand using artificial intelligence methods", J. Cold Reg. Eng., 33(3), 04019007. https://doi.org/10.1061/(ASCE)CR.1943-5495.0000188.   DOI
18 Felekoglu, B., Turkel, S. and Baradan, B. (2007), "Effect of water/cement ratio on the fresh and hardened properties of self-compacting concrete", Build. Environ., 42(4), 1795-1802. https://doi.org/10.1016/j.buildenv.2006.01.012.   DOI
19 Esmaeili-Falak, M., Sarkhani Benemaran, R. and Seifi, R. (2020a), "Improvement of the mechanical and durability parameters of construction concrete of the Qotursuyi Spa", Concrete Res., 13(2), 81-90. https://doi.org/10.22124/JCR.2020.14518.1395.
20 Esmaeili, F.M., Lotfi, E.A. and Nematzadeh, S. (2019), "Improvement of mechanical parameters of concrete yielded from pozzolanic cement for irrigation and drainage projects", 6(23), 43-58. https://doi.org/10.22065/JSCE.2017.100834.1349.
21 Ghrici, M., Kenai, S. and Said-Mansour, M. (2007), "Mechanical properties and durability of mortar and concrete containing natural pozzolana and limestone blended cements", Cement Concrete Compos., 29(7), 542-549. https://doi.org/10.1016/j.cemconcomp.2007.04.009.   DOI
22 Hubertova, M. and Hela, R. (2007), "The effect of metakaolin and silica fume on the properties of lightweight self consolidating concrete", Spec. Publ., 243, 35-48.
23 Kennedy, J. and Eberhart, R. (1995), "Particle swarm optimization", Proceedings of ICNN'95-International Conference on Neural Networks, 4, 1942-1948. https://doi.org/10.1109/ICNN.1995.488968.
24 Kjellsen, K.O., Wallevik, O.H. and Hallgren, M. (1999), "On the compressive strength development of high-performance concrete and paste-effect of silica fume", Mater. Struct., 32(1), 63. https://doi.org/10.1007/BF02480414.   DOI
25 Lam, L., Wong, Y.L. and Poon, C.S. (1998), "Effect of fly ash and silica fume on compressive and fracture behaviors of concrete", Cement Concrete Res., 28(2), 271-283. https://doi.org/10.1016/S0008-8846(97)00269-X.   DOI
26 Friedman, J.H. (1991), "Multivariate adaptive regression splines", Ann. Statist., 1-67. https://www.jstor.org/stable/2241837.
27 Lee, S.C. (2003), "Prediction of concrete strength using artificial neural networks", Eng. Struct., 25(7), 849-857. https://doi.org/10.1016/S0141-0296(03)00004-X.   DOI
28 Mahdavi Adeli, M. and Hormozi, N. (2014), "Comparison between traditional and modern methods of concrete curing and maintenance concrete in hot climates from a cost and performance viewpoint", First National Conference on Architecture, Civil and Environmental Environment, Hamedan, Hegmataneh Environmental Assessors Association.
29 Mahmodi, K. and Ketabdari, M.J. (2017), "High performance concrete using artificial neural network and multiple linear regression", Civil Eng., 105-115. https://doi.org/10.24200/j30.2018.1010.1586.
30 Tavakkol, S., Alapour, F., Kazemian, A., Hasaninejad, A., Ghanbari, A. and Ramezanianpour, A.A. (2013), "Prediction of lightweight concrete strength by categorized regression, MLR and ANN", Comput. Concrete, 12, 151-167. https://doi.org/10.12989/cac.2013.12.2.151.   DOI
31 Yaprak, H., Karaci, A. and Demir, I. (2013), "Prediction of the effect of varying cure conditions and w/c ratio on the compressive strength of concrete using artificial neural networks", Neur. Comput. Appl., 22(1), 133-141. https://doi.org/10.1007/s00521-011-0671-x.   DOI
32 Topcu, I.B. and Saridemir, M. (2008), "Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic", Comput. Mater. Sci., 41(3), 305-311. https://doi.org/10.1016/j.commatsci.2007.04.009.   DOI
33 Toutanji, H., Delatte, N., Aggoun, S., Duval, R. and Danson, A. (2004), "Effect of supplementary cementitious materials on the compressive strength and durability of short-term cured concrete", Cement Concrete Res., 34(2), 311-319. https://doi.org/10.1016/j.cemconres.2003.08.017.   DOI
34 Turk, K., Turgut, P., Karatas, M. and Benli, A. (2010), "Mechanical properties of selfcompacting concrete with silica fume/fly ash", 9th International Congress on Advances in Civil Engineering, 27-30.
35 Mohamed, O. (2018), "Durability and compressive strength of high cement replacement ratio self-consolidating concrete", Build., 8(11), 153. https://doi.org/10.3390/buildings8110153.   DOI
36 Mohamed, O. and Najm, O. (2019), "Effect of curing methods on compressive strength of sustainable self-consolidated concrete", IOP Conf. Ser.: Mater. Sci. Eng., 471(3), 032059. https://doi.org/10.1088/1757-899X/471/3/032059.   DOI
37 Mohamed, O.A. (2019), "Effect of mix constituents and curing conditions on compressive strength of sustainable self-consolidating concrete", Sustain., 11(7), 2094. https://doi.org/10.3390/su11072094.   DOI
38 Mohamed, O.A. and Najm, O.F. (2016), "Splitting tensile strength of self-consolidating concrete containing slag", Proceedings of AES-ATEMA International Conference, Advances and Trends in Engineering Materials and their Applications, 109-114. https://doi.org/10.1016/j.proeng.2016.04.157.
39 Nassr, A., Esmaeili-Falak, M., Katebi, H. and Javadi, A. (2018), "A new approach to modeling the behavior of frozen soils", Eng. Geol., 246, 82-90. https://doi.org/10.1016/j.enggeo.2018.09.018.   DOI
40 Muduli, P.K., Das, S.K. and Das, M.R. (2013), "Prediction of lateral load capacity of piles using extreme learning machine", Int. J. Geotech. Eng., 7(4), 388-394. https://doi.org/10.1179/1938636213Z.00000000041.   DOI
41 Nochaiya, T., Wongkeo, W. and Chaipanich, A. (2010), "Utilization of fly ash with silica fume and properties of Portland cement-fly ash-silica fume concrete", Fuel, 89(3), 768-774. https://doi.org/10.1016/j.fuel.2009.10.003.   DOI
42 Oreta, A.W. and Ongpeng, J. (2011), "Modeling the confined compressive strength of hybrid circular concrete columns using neural networks", Comput. Concrete, 8(5), 597-616. https://doi.org/10.12989/cac.2011.8.5.597.   DOI
43 Pala, M., Ozbay, E., Oztas, A. and Yuce, M.I. (2007), "Appraisal of long-term effects of fly ash and silica fume on compressive strength of concrete by neural networks", Constr. Build. Mater., 21(2), 384-394. https://doi.org/10.1016/j.conbuildmat.2005.08.009.   DOI
44 Rasoli, M. and Abbasi, B. (2008), "Investigation of the effect of silica soot on the properties of concrete generated", isn.ac/XYKB-BHKHB.
45 Samui, P. (2013), "Determination of compressive strength of concrete by statistical learning algorithms", Eng. J., 17(1), 111-120. https://doi.org/10.4186/ej.2013.17.1.111.   DOI
46 Saridemir, M. (2014), "Effect of specimen size and shape on compressive strength of concrete containing fly ash: Application of genetic programming for design", Mater. Des., 56, 297-304. https://doi.org/10.1016/j.matdes.2013.10.073.   DOI