Abstract
This paper investigates the application of three artificial intelligence methods, including multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), and least squares support vector regression (LSSVR) for the prediction of the mechanical behavior of recycled aggregate concrete (RAC). A large and reliable experimental test database containing the results of 650 compressive strength, 421 elastic modulus, 152 flexural strength, and 346 splitting tensile strength tests of RACs with no pozzolanic admixtures assembled from the published literature was used to train, test, and validate the three data-driven-based models. The results of the model assessment show that the LSSVR model provides improved accuracy over the existing models in the prediction of the compressive strength of RACs. The results also indicate that, although all three models provide higher accuracy than the existing models in the prediction of the splitting tensile strength of RACs, only the performance of the LSSVR model exceeds those of the best-performing existing models for the flexural strength of RACs. The results of this study indicate that MARS, M5Tree, and LSSVR models can provide close predictions of the mechanical properties of RACs by accurately capturing the influences of the key parameters. This points to the possibility of the application of these three models in the pre-design and modeling of structures manufactured with RACs.
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Xie T, Gholampour A, Ozbakkaloglu T (2018) Toward the development of sustainable concretes with recycled concrete aggregates: comprehensive review of studies on mechanical properties. J Mater Civil Eng. https://doi.org/10.1061/(ASCE)MT.1943-5533.0002304
Ozbakkaloglu T, Gholampour A, Xie T (2017) Mechanical and durability properties of recycled aggregate concrete: effect of recycled aggregate properties and content. J Mater Civil Eng. https://doi.org/10.1061/(ASCE)MT.1943-5533.0002142
Kou SC, Poon CS, Wan HW (2012) Properties of concrete prepared with low-grade recycled aggregates. Constr Build Mater 36:881–889
Torgal FP, Ding Y, Miraldo S, Abdollahnejad Z, Labrincha JA (2012) Are geopolymers more suitable than portland cement to produce high volume recycled aggregates HPC. Constr Build Mater 36:1048–1052
Gholampour A, Ozbakkaloglu T (2018) Time-dependent and long-term mechanical properties of concretes incorporating different grades of coarse recycled concrete aggregates. Eng Struct 157:224–234
Limbachiya M, Meddah MS, Ouchagour Y (2012) Performance of Portland/silica fume cement concrete produced with recycled concrete aggregate. ACI Mater J 109(1):91–100
Manzi S, Mazzotti C, Bignozzi MC (2013) Short and long-term behavior of structural concrete with recycled concrete aggregate. Cem Concr Compos 37:312–318
de Brito J, Ferreira J, Pacheco J, Soares D, Guerreiro M (2015) Structural, material, mechanical and durability properties and behaviour of recycled aggregates concrete. J Build Eng 6:1–16
Afroughsabet V, Biolzi L, Ozbakkaloglu T (2017) Influence of double hooked-end steel fibers and slag on mechanical and durability properties of high-performance recycled aggregate concrete. Compos Struct 181:273–284
Kou SC, Poon CS (2015) Effect of the quality of parent concrete on the properties of high performance recycled aggregate concrete. Constr Build Mater 77:501–508
Pedro D, de Brito J, Evangelista L (2017) Evaluation of high-performance concrete with recycled aggregates: use of densified silica fume as cement replacement. Constr Build Mater 147:803–814
Dimitriou G, Savva P, Petrou MF (2018) Enhancing mechanical and durability properties of recycled aggregate concrete. Constr Build Mater 158:228–235
Ravindrarajah RS, Tam CT (1985) Properties of concrete made with crushed concrete as coarse aggregate. Mag Concr Res 37(130):29–38
Zilch K, Roos F (2001) An equation to estimate the modulus of elasticity of concrete with recycled aggregates. Civil Eng 76(4):187–191
Xiao JZ, Li JB, Zhang C (2006) On relationships between the mechanical properties of recycled aggregate concrete: an overview. Mater Struct 39(6):655–664
Lovato PS, Possan E, Dal Molin DCC, Masuero AB, Ribeiro JLD (2012) Modeling of mechanical properties and durability of recycled aggregate concretes. Constr Build Mater 26(1):437–447
Xuan DX, Houben LJM, Molenaar AAA, Shui ZH (2012) Mechanical properties of cement-treated aggregate material–a review. Mater Des 33:496–502
Peng Y, Chu H, Pu J (2016) Numerical simulation of recycled concrete using convex aggregate model and base force element method. Adv Mater Sci Eng 2016:1–10
Taffese WZ, Sistonen E (2017) Machine learning for durability and service-life assessment of reinforced concrete structures: recent advances and future directions. Automat Constr 77:1–14
Hoang N, Chen C, Liao K (2017) Prediction of chloride diffusion in cement mortar using multi-gene genetic programming and multivariable adaptive regression splines. Measurement 112:141–149
Yaseen ZM, Deo RC, Hilal A, Abd AM, Bueno LC, Salcedo-Sanz S, Nehdi ML (2018) Predicting compressive strength of lightweight foamed concrete using extreme learning machine model. Adv Eng Softw 115:112–125
Naderpour H, Rafiean AH, Fakharian P (2018) Compressive strength prediction of environmentally friendly concrete using artificial neural networks. J Build Eng 16:213–219
Younis KH, Pilakoutas K (2013) Strength prediction model and methods for improving recycled aggregate concrete. Constr Build Mater 49:688–701
Duan ZH, Kou SC, Poon CS (2013) Prediction of compressive strength of recycled aggregate concrete using artificial neural networks. Constr Build Mater 40:1200–1206
Sahoo K, Sarkar P, Davis R (2016) Artificial neural networks for prediction of compressive strength of recycled aggregate concrete. Inter J Chem Metall Civil Eng 3(1):81–85
Deshpande N, Londhe S, Kulkarni S (2014) Modeling compressive strength of recycled aggregate concrete by artificial neural network, model tree and non-linear regression. Inter J Sustain Built Environ 3:187–198
Duan ZH, Kou SC, Poon CS (2013) Using artificial neural networks for predicting the elastic modulus of recycled aggregate concrete. Constr Build Mater 44:524–532
Behnood A, Olek J, Glinicki MA (2015) Predicting modulus elasticity of recycled aggregate concrete using M5’ model tree algorithm. Constr Build Mater 94:137–147
Gonzalez-Taboada I, Gonzalez-Fonteboa B, Martinez-Abella F, Perez-Ordonez J (2016) Prediction of the mechanical properties of structural recycled concrete using multivariable regression and genetic programming. Constr Build Mater 106:480–499
Gholampour A, Gandomi AH, Ozbakkaloglu T (2017) New formulations for mechanical properties of recycled aggregate concrete using gene expression programming. Constr Build Mater 130:122–145
Friedman JH (1991) Multivariate adaptive regression splines (with discussion). Ann Stat 19(1):1–141
Quinlan JR (1992) Learning with continuous classes. In: Proceedings of the fifth Australian joint conference on artificial intelligence, Hobart, Australia, 16–18 November. World Scientific, Singapore, pp 343–348
Suykens JAK, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3):293–300
Cheng M, Cao M (2014) Evolutionary multivariate adaptive regression splines for estimating shear strength in reinforced-concrete deep beams. Eng Appl Artif Intell 28:86–96
Aiyer BG, Kim D, Karingattikkal N, Samui P, Rao PR (2014) Prediction of compressive strength of self-compacting concrete using least square support vector machine and relevance vector machine. KSCE J Civil Eng 18(6):1753–1758
Pham A, Hoang N, Nguyen Q (2016) Predicting compressive strength of high-performance concrete using metaheuristic-optimized least squares support vector regression. J Comput Civil Eng 30(3):06015002
Sriravindrarajah R, Wang NDH, Ervin LJW (2012) Mix design for pervious recycled aggregate concrete. Inter J Concr Struct Mater 6(4):239–246
Pereira P, Evangelista L, de Brito J (2012) The effect of superplasticisers on the workability and compressive strength of concrete made with fine recycled concrete aggregates. Constr Build Mater 28(1):722–729
Thomas C, Setién J, Polanco JA, Alaejos P, de Juan MS (2013) Durability of recycled aggregate concrete. Constr Build Mater 40:1054–1065
Rahal K (2007) Mechanical properties of concrete with recycled coarse aggregate. Build Environ 42(1):407–415
Corinaldesi V (2010) Mechanical and elastic behaviour of concretes made of recycled-concrete coarse aggregates. Constr Build Mater 24(9):1616–1620
Hoffmann C, Schubert S, Leemann A, Motavalli M (2012) Recycled concrete and mixed rubble as aggregates: influence of variations in composition on the concrete properties and their use as structural material. Constr Build Mater 35:701–709
Pereira P, Evangelista L, de Brito J (2012) The effect of superplasticizers on the mechanical performance of concrete made with fine recycled concrete aggregates. Cem Concr Compos 34(9):1044–1052
Wardeh G, Ghorbel E, Gomart H (2014) Mix design and properties of recycled aggregate concretes: applicability of Eurocode 2. Inter J Concr Struct Mater 9:1–20
Bairagi NK, Ravande K, Pareek VK (1993) Behaviour of concrete with different proportions of natural and recycled aggregates. Resour Conserv Recycl 9(1):109–126
Tavakoli M, Soroushian P (1996) Strengths of recycled aggregate concrete made using field-demolished concrete as aggregate. ACI Mater J 93(2):182–190
Kheder GF, Al-Windawi SA (2005) Variation in mechanical properties of natural and recycled aggregate concrete as related to the strength of their binding mortar. Mater Struct 38(7):701–709
Xiao J, Li P, Qin W (2006) Study on bond-slip between recycled concrete and rebars. J Tongji Univ 34(1):13
Andres JD, Lorca P, de Cos Juez FJ, Sanchez-Lasheras F (2010) Bankruptcy forecasting: a hybrid approach using fuzzy c-means clustering and multivariate adaptive regression splines (MARS). Expert Syst Appl 38:1866–1875
Sharda V, Prasher SO, Patel RM, Ojavasi PR, Prakash C (2006) Modeling runoff from middle Himalayan watersheds employing artificial intelligence techniques. Agric Water Manag 83:233–242
Pal M, Deswal S (2009) M5 model tree based modelling of reference evapotranspiration. Hydrol Process 23:1437–1443
Adnan RM, Yuan X, Kisi O, Anam R (2017) Improving accuracy of river flow forecasting using LSSVR with gravitational search algorithm. Adv Meteorol 2017:1–23
Suykens JAK, Van Gestel T, De Brabanter J, De Moor B, Vandewalle J (2002) Least squares support vector machines. Word Scientific, Singapore
Cawley GC, Talbot NLC (2010) On over-fitting in model selection and subsequent selection bias in performance evaluation. J Mach Learn Res 11:2079–2107
Kumutha R, Vijai K (2010) Strength of concrete incorporating aggregates recycled from demolition waste. ARPN J Eng Appl Sci 5(5):64–71
Hou YL, Zheng G (2013) Mechanical properties of recycled aggregate concrete in different age. J Build Mater 16(4):683–687
Ismail S, Ramli M (2013) Engineering properties of treated recycled concrete aggregate (RCA) for structural applications. Constr Build Mater 44:464–476
Andreu G, Miren E (2014) Experimental analysis of properties of high performance recycled aggregate concrete. Constr Build Mater 52:227–235
Duan ZH, Poon CS (2014) Properties of recycled aggregate concrete made with recycled aggregates with different amounts of old adhered mortars. Mater Des 58:19–29
Casuccio M, Torrijos MC, Giaccio G, Zerbino R (2008) Failure mechanism of recycled aggregate concrete. Constr Build Mater 22(7):1500–1506
Yang KH, Chung HS, Ashour AF (2008) Influence of type and replacement level of recycled aggregates on concrete properties. ACI Mater J 105(3):289–296
Fathifazl G, Razaqpur AG, Isgor OB, Abbas A, Fournier B, Foo S (2011) Creep and drying shrinkage characteristics of concrete produced with coarse recycled concrete aggregate. Cem Concr Compos 33(10):1026–1037
Dilbas H, Simsek M, Çakır Ö (2014) An investigation on mechanical and physical properties of recycled aggregate concrete (RAC) with and without silica fume. Constr Build Mater 61:50–59
Ajdukiewicz A, Kliszczewicz A (2002) Influence of recycled aggregates on mechanical properties of HS/HPC. Cem Concr Compos 24(2):269–279
Kakizaki M, Harada M, Soshiroda T, Kubota S, Ikeda T, Kasai Y (1988) Strength and elastic modulus of recycled aggregate concrete. In: Proceedings of the second international RILEM symposium on demolition and reuse of concrete and masonry, vol 2, pp 565–574
de Oliveira MB, Vazquez E (1996) The influence of retained moisture in aggregates from recycling on the properties of new hardened concrete. Waste Manag 16(1):113–117
Dillmann R (1998) Concrete with recycled concrete aggregate. In: Sustainable construction: use of recycled concrete aggregate-producing of the international symposium held at department of trade and industry conference Centre, London, UK, pp 11–12
Dhir RK (1999) Sustainability of recycled concrete aggregate for use IN BS 5328 designated mixes. Proc ICE Struct Build 134(3):257–274
Serifou M, Sbartai ZM, Yotte S, Boffoue MO, Emeruwa E, Bos F (2013) A study of concrete made with fine and coarse aggregates recycled from fresh concrete waste. J Constr Eng 2013:1–5
AS3600-2009 (2009) Australian standard for concrete structures. SA, North Sydney
ACI 318-11 (2011) Building code requirements for structural concrete and commentary, PCA notes on ACI 318-11: with design applications. ACI International, Farmington Hills
Canadian Standard. C S A. A23.3-04 (2004) Design of concrete structures, Canadian Standard Association
British Standards Institution (2004) Eurocode 2: design of concrete structures: part 1–1: general rules and rules for buildings. British Standards Institution
Japan Society of Civil Engineers (2007) Standard specification for concrete structure. JSCE No. 15, Tokyo, Japan
Japanese Civil Institute (2008) Guidelines for control of cracking of mass concrete 2008, Japan Concrete Institute
New Zealand Standard (2006) Concrete structures standard. NZS 3101:2006. The design of concrete structures, Wellington, New Zealand
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Gholampour, A., Mansouri, I., Kisi, O. et al. Evaluation of mechanical properties of concretes containing coarse recycled concrete aggregates using multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), and least squares support vector regression (LSSVR) models. Neural Comput & Applic 32, 295–308 (2020). https://doi.org/10.1007/s00521-018-3630-y
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DOI: https://doi.org/10.1007/s00521-018-3630-y