Journal Pre-proof Waste tire rubber and pozzolans in concrete: a trade-off between cleaner production and mechanical properties in a greener concrete. Mostafa Jalal, Navid Nassir, Hamid Jalal PII:
S0959-6526(19)32752-0
DOI:
https://doi.org/10.1016/j.jclepro.2019.117882
Reference:
JCLP 117882
To appear in:
Journal of Cleaner Production
Received Date: 28 June 2018 Revised Date:
6 July 2019
Accepted Date: 1 August 2019
Please cite this article as: Mostafa Jalal, Navid Nassir, Hamid Jalal, Waste tire rubber and pozzolans in concrete a trade-off between cleaner production and mechanical properties in a greener concrete., (2019), doi: 10.1016/j.jclepro.2019.117882 This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
Greener Concrete & Cleaner Production
Waste tire rubber and pozzolans in concrete: a trade-off between cleaner production and mechanical properties in a greener concrete.
Mostafa Jalal1,2∗, Navid Nassir3, Hamid Jalal4 1 2
Zachry Department of Civil engineering, Texas A&M University, College Station, TX 77843, USA
Texas A&M Transportation Institute, Texas A&M University, 3135 TAMU, College Station, TX, 77843, USA 3
Department of Civil Engineering, Pouyandegan Danesh University, Chalus, Mazandaran, Iran 4
Department of Civil Engineering, Semnan University, Semnan, Iran
Abstract This study presents a cleaner production of a concrete by incorporating waste rubber chips and pozzolans to make a greener concrete through partial replacement of aggregates and cement. For this purpose, aggregate was replace by 10 and 15% by graded waste rubber (RB) and cement was partially replaced by pozzolans, namely silica fume (SF) and zeolite (ZE) by 10%. Fresh and hardened properties of the concrete was investigated through slump, compressive strength and elasticity modulus. The effect of RB, SF and ZE addition on fresh properties was assessed which indicated 5% and 14.6% slump reduction for 10% and 15% rubber replacement, 4% increase due to SF addition, and 4% decrease as a result of ZE addition. The microstructure of the pozzolans was also investigated using SEM micrographs. Compressive strengths of the samples were measured at different ages of 3, 7, 28, and 42 days and compared with ACI 318 equation in order to modify the coefficients for the greener concrete. Elasticity moduli of the concrete mixes were determined according to ASTM C469. The results indicated that 10% and 15% rubber replacement led to 30% and 50% strength drop, respectively. The corresponding reduction in elastic modulus was observed as 14% and 32%. The elastic modulus was also estimated using relationships presented in different standards based on compressive strength. It was found that ACI 318 relationship underestimates the elastic modulus for which the correction factors were determined. Three different regression models namely Linear, Logarithmic, and Power were also developed in order to predict the compressive strength of greener concrete. Power regression with R2=0.92 proved to be more powerful among other assessed regression models. Keywords: greener concrete; cleaner product; waste tire rubber; pozzolans; mechanical properties, strength prediction
∗
Corresponding author Email:
[email protected];
[email protected] Phone: +1 979 676 4787
1. Introduction Concrete is the most widely used building material in the world for which the aggregates and cement are the main constituents. The former comprises about 70% of the concrete which is a high demand. Aggregate products play an important role in the everyday life as these materials are used in almost all forms of built infrastructure, such as roads, sidewalks, foundations, sewers, and the buildings themselves (MNR, 2010a). Aggregate extraction has been identified as one of the controversial land-uses which is largely due to the environmental consequences and the social costs associated with aggregate extraction activities (Winfield & Taylor, 2005; Kellett, 1995). On the other hand, the latter is environmentally and economically challenging due to its carbon footprint and production costs. As a results, recycling remains the best alternative to reduce the impact that the environment in terms of the consumption of raw materials, CO2 emission, and the accumulation of waste materials. In this regard, the construction and concrete industry can be considered as one of the best alternatives to consume recycled materials and industrial by-products. Several studies have addressed the application of waste tires in concrete in different aspects such as fibers and aggregate partial replacement. Some studies have already confirmed the viability of using the vulcanized rubber fiber into construction materials (Chiu, 2008; Estevez, 2009; Hernández-Olivares et al., 2007; Milanez and Bührs, 2009; Sunthonpagasit and Duffey, 2004). Some others have investigated the mechanical and darability properties of the concrete containing up to 30% of waste tire rubber (Khaloo et al. 2008, Turatsinze and Garros, 2008, Tortum et al., 2005). Many studies have also been conducted on cement replacement by various pozzolans and industrial by-products in different types of concrete. This supplementary cementitious materials include nanomaterials (Jalal et al., 2012; 2013; 2014; 2015), fly ash (Jalal et al., 2012), silica fume (Arabali and Shekarchi, 2015; Jalal et a., 2015), slag (Teimortashlu et al. 2018; Jalal et al. 2019), zeolite (Nagrockiene and Girskas 2016; Tran et al. 2019; jokar et al. 2019), and some other types of pozzolans that can help reduce the cement content, and hence leading to a cleaner and more sustainable production. The Zeolite that is investigated in this study is known as a natural pozzolan that has been studied by a few studies. However, it can be classified as zeolite clinoptilolite-Na, which does not thoroughly conform to the maximum limit of SO3 described in ASTM C618 for a pozzolan, but it has pozzolanic behavior in concrete mixture (Raggiotti et al.
2018). Regarding its influence on fresh properties of concrete, it was reported that zeolite can lead to decreased workability and setting time of conventional concrete (Najimi et al. 2012), and viscosity increase of the fresh state of self-compacting concrete (Samimi et al. 2018). Nagrockiene and Girskas (2016) showed that the density of concrete increases by increasing the zeolite content. Most of the studies have investigated the zeolite content in concrete up to 30% and shown that durability properties improve by increasing the zeolite up to 30% (Tran et a. 2019; Samimi et al. 2018; Ramezanianpour et al. 2015;Najimi at al. 2012). However, majority of the studies show that the optimum content of zeolite for enhancement of mechanical properties is 10% (Nagrockiene and Girskas 2016; Markiv et al. 2016; Tran et al. 2019; jokar et al. 2019; Ramezanianpour et al. 2015; Najimi et al. 2012). Therefore, 10% cement replacement by zeolite was considered as the optimum content in this study. Potential applications of rubberized cement composites include impact barriers, asphalt or concrete pavements, playground floors, and sports area pavements, which have been suggested by various sectors in industry (Jiang et al. 2018; Akhtar and Sarmah 2018, Jalal et al. 2019). It is preferred in some applications for a concrete to have lower unit weight, higher energy absorption, and impact strength (Topçu 1997). Besides, rubberized concrete with reduced mechanical properties can also be used for hollow concrete blocks (Mohammed et al. 2012). Tire rubber particle size have been classified into three groups, namely shredded or chipped, crumb and ground rubber with particle size range of 150-13 mm, 0.425-4.75 mm, 0.075-0.475 mm, respectively (Ganjian et al. 2009). In this study, 10 and 15% of the aggregate was replaced by waste rubber chips, and the effect of 10% cement replacement by silica fume and zeolite was investigated. Nine mixes were designed with different replacement levels. Fresh properties of concrete were assessed through slump test and the mechanical properties were investigated by compressive strength and elastic modulus. The compressive results were compared with ACI equation and the coefficients were modified for the rubberized concrete. The elastic moduli were measured according to ASTM C469. Regression models namely linear, logarithmic, and power were also developed to predict the compressive strength.
2. Research Significance This research has investigated a greener concrete as a cleaner product mainly from two aspects, namely aggregate and powder as two main ingredients of concrete. Due to concrete being the
most widely used made-made material in the world, replacing even a small portion of its ingredients with waste materials can be of huge significance. In this study, a cleaner concrete product is investigated from two perspectives: aggregate replacement by waste rubber, and cement replacement by silica fume (SF) as an industrial by-product, and zeolite (ZE) as a natural pozzolan. In this way, less cement is consumed which leads to less CO2 footprint. Moreover, cutting down on natural aggregates’ consumption by waste rubber replacement will result in more environment- friendly product. Even though several studies have investigated a wide range of rubber fractions in concrete (Li et al., 2003; Huang et al. 2004, 2013; Shu and Huang 2014; Dong et al. 2013), however, this research has focused on optimum percentage, namely up to 15%, to make a trade-off between waste management and structural concrete strength. This study also investigates for the first time the comparative effects of SF and ZE on rubberized concrete. The optimum fractions of pozzolans to replace cement was selected as 10% according to available literature for SF (Cohen et al. 1990; Mohammed et al. 2012; Gupta et al. 2016) and ZE (Nagrockiene and Girskas 2016; Tran et al. 2019; jokar et al. 2019). Another significance of this study is that regression models as simple and robust tools were utilized for the first time in this study for strength prediction of the rubberized concrete mixtures. It should be mentioned that the models developed in this study are valid within the range of variables studies herein and similar type of materials.
3. Materials 3.1. Mineral admixtures 3.1.1.
Silica fume (SF)
As defined in ASTM C1240, silica fume is a very fine white to grayish pozzolanic, amorphous powder which is a by-product of production of silicon or ferrosilicon alloys in electric arc furnaces. The main field of application is as pozzolanic material for high performance concrete. Standard specifications for silica fume used in cementitious mixtures can be found in ASTM standard (ASTM C1240, 2003) Prior to the mid-1970s, nearly all silica fume was discharged into the atmosphere. After environmental concerns necessitated the collection and landfilling of silica fume, it became economically viable to use silica fume in various applications, in particular high-performance concrete (ACI 234R-06, 2006). Chemical and Physical Characteristics of the SF used in this study are listed in Table 1.
3.1.2.
Zeolite (ZE)
Natural zeolite called Clinoptilolite is comprising a microporous arrangement of silica and alumina tetrahedrals. It has a complex formula as following: ( , , , ) . 24
(1)
It forms as white to light greenish crystals with an ion exchange capacity of 140-160 milliequivalent per gram (mEq/g). The zeolite used had a density of 1-1.83 g/cm3 and minerals purity of 85-95 %. Chemical composition of zeolite is as listed in Table 1. 3.2. Cement
In this study, cement type II was used for which the physical and chemical characteristics are presented in Table 1.
3.3. Aggregate properties 3.3.1.
Sand
The sand used for this study was prepared form river sand, crushed, washed and sieved with maximum size as retained on sieve #4. Water absorption and specific gravity in SSD state for the sand were 2% and 2.51, respectively. Sand equivalent as well as fineness modulus (FM) were determined as 79% and 3.09, based on ASTM D2419 and ASTM C33 respectively. The gradation curve of the sand used is shown in Fig. 1a, which is lied between upper and lower limits specified by ASTM C33. Fineness modulus is supposed to be between 2.3 and 3.1 to ensure it is neither too rough nor too fine; since very fine particles increase the water demand and too rough sand leads to reduced workability and possible entrapped voids while placing the concrete. 3.3.2.
Gravel
Maximum nominal size of the gravel used was 19 mm. Other properties such as water absorption and specific gravity in saturated surface dry (SSD) state for the gravels were determined as 2.37% and 2.57 respectively. Coarse aggregate gradation was carried out in the lab conforming
to ASTM C33 standard. The gradation curve is presented in Fig. 1b which is between upper and lower specs as specified in the standard.
3.4. Waste tire rubber chips
The rubber chips for this study were provided from waste tires chopped up, washed and sieved so that different sizes of the tire chips can be stored separately. A view of the plant with crushing machine where waste tire rubber chips were prepared for the experiment is displayed in fig. 2a. Most of the tires include reinforcing threads and wires. On the one hand, the aim of this study is to investigate the effect of rubber chips as a partial replacement of coarse aggregates and on the other hand, rusting of wires may lead to some strength reduction. Hence, an attempt was made to put all the rubber chips in a huge water container so that in addition to having them washed, the threads can be separated from the rubber chips. Then a big magnet was passed over the rubber chips to get the remaining steel wires separated from them. A sample of rubber chips after processing and preparation is illustrated in Fig.2b. Since the rubbers chips are prepared from waste tires, and there is no particular standard and industrial production unit for them, the particle shape and gradations may not be desirable, and thereby leading to some variability and error in the results of concrete samples. Nevertheless, it was tried to follow the gravel gradation conforming to ASTM C33 for the rubber chips, which is shown in Fig. 1b. The maximum size of the rubber particles used was 19 mm.
3.5. Super plasticizer (SP)
Due to selection of water to cement ratio of 0.4 from one hand, and incorporation of rubber chips on the other hand, super plasticizer needed to be used in this study to maintain a desirable workability of the concrete. Polycarboxylate-based super plasticizer conforming to ASTM C494 Type F, G was used in this research which is compatible with different types of pozzolanic admixtures. The properties of the SP used along with the recommended dosage of the manufacturer are summarized in Table 2. In this study, a constant optimum value of 0.37% of
cement weight was chosen for SP amount for all mixes, based on trial and error carried out on preliminary samples.
4. Test methods 4.1. Mix Design
In this study, original concrete mixture was designed based on ACI-211-92 and accordingly the amount of coarse and fine aggregates, water, cement and other admixtures were determined. To determine the coarse aggregate volume, according to fineness modulus of the sand, the ratio of gravel to sand was roughly selected as 60 to 40%. It was tried to use the relative optimum percentage of silica fume and zeolite found in the literature, i.e. 10% of cement, to partially make up the strength loss due to rubber chips addition to the concrete as a partial replacement of coarse aggregates. Cement content was considered as 400 kg/m3 and a relatively low water to binder ratio (w/b) was selected as 0.4. Waste tire rubber chips were also added to the concrete as 10 and 15% replacement of coarse aggregate. The designation for each mix design is composed of RB as for "rubber" preceded by rubber replacement percentage, followed by C, SF or ZE as for "control", "silica fume" and "zeolite" respectively. Presented in table 3 are the mix design details along with the sample designations for each mixture.
4.2. Mixing and Sample preparation
In this research, cubic and cylindrical molds were used with dimensions of 150*150*150 and 150*300 mm to cast concrete samples to measure mechanical properties such as compressive strength and elasticity modulus. SP was added to the mixing water and was mixed properly. To mix the concrete ingredients, a drum mixer of 62lit capacity with speed of 18 rpm was used. Since for this type of concrete containing rubber chips, mixture uniformity is of utmost importance and may easily affect the workability and mechanical properties of the samples, especial care was taken to the mixing process and after several trial and error, the following steps were determined to be taken for all mixtures:
First, the inner surface of the mixture was washed and the excessive water was removed. Then coarse aggregates along with rubber chips were placed in the mixer and while mixing, half of the mixing water was added and mixing continued for 30 s. After that the fine aggregates were added while mixing for another 60s. Cement was then added while mixing was going on for 30 s. Afterwards, other binders i.e. zeolite and silica fume were added and allowed to be mix for 30 s. Rest of water was gradually added to the mixture in 30 s while mixing being carried out. Finally, mixing continued for 3 minutes to ensure a totally uniform mixture would be achieved. Therefore, mixing process of the concrete was carried out in 6 minutes. After getting the mixture prepared, cubic and cylindrical molds with dimensions of 150*150*150 and 150*300 were cast for compressive test and elasticity modulus respectively. After 24 hours, the samples were demoded and placed in water tank for curing until the day of testing.
4.3. Fresh and hardened concrete tests 4.3.1.
Slump test
Slump test was conducted to evaluate the effect of rubber addition as a partial replacement of coarse aggregates, and pozzolanic admixtures as a partial replacement of cement on workability of rubberized concrete. In this study, the concrete slump test was performed conforming ASTM C 143. 4.3.2.
Compressive tests
Cubic samples with 150*150*150 dimensions were prepared for compressive strength test (BS, EN, 2001). Loading rate of the apparatus was specified as 680 kgf/sec for cubic samples. Three
samples were cast for each mix and the average value was considered as the compressive strength. 4.3.3.
Elasticity modulus test
The test was carried out on cylindrical samples of 150*300 mm dimensions conforming ASTM C469 to measure static modulus of elasticity of the rubberized concrete. In this experiment, to eliminate the effects of creep, the main loading was preceded by a quite number of loading and unloading. During load application, the applied load and axial strain were recorded in two steps:
(1) when strain value of 0.000050 was reached ( = 50 ∗ 10 ), (2) Once 40% of ultimate load is reached ( ). Then the static elasticity modulus can be calculated by Eq. (2): = ( − )/( − 50 ∗ 10 )
(2)
where, E, S1, S2, and ε2 are chord modulus of elasticity, stress corresponding to a longitudinal strain of ε1 at 0.000050, stress corresponding to 40% of the ultimate load of the concrete, and longitudinal strain produced by S2, respectively.
5. Regression-based prediction model for compressive strength Computer-aided techniques are robust tools that have been efficiently used in engineering design (Goharzay et al. 2017; Jalal et al. 2018), optimization (Garmsiri and Jalal 2014), and modeling (Jodaei et al. 2013; Jalal et al. 2013) and prediction (Fathi et al. 2015; Saeidi Marzangoo and Jalal 2014). Prediction models using regressions are among the most widely-used models which are quite straight forward, practical and accurate. In this study, several multivariable regression models namely linear, power and logarithmic were used to predict compressive strength of rubberized concrete by taking into account five variables. Table 4 shows the equations along with the variables and coefficients used for the regression models. Variables comprise cement (C), Silica Fume (SF), Zeolite (ZE), rubber (RB), and Age, while a0, … an are calibration coefficients of the models. However, in experimental and practical applications, sometimes the predictor variables are interdependent. This interdependency can result in some analysis problems by magnifying the strength of relationships between the variables. This is a simple case commonly known as the problem of multicollinearity (Dunlop and Smith 2003). If the absolute vale of the correlation coefficient (R) between two variables is higher than 0.8, there is a strong correlation between these variables (Smith 1986). Hence, in order to assess the interdependency of the variables in this study, the correlation coefficient between each pair of variables were calculated by using Eq. (3), the results of which are presented in Table 5. As is noted form the table, the maximum absolute R value is 0.5. Consequently, all of the five variables were considered to develop the regression models.
"=
& ̅ ∑) %*+($% $% )('% '% )
& - ) ̅ ,∑) %*+($% $% ) ∑%*+('% '% )
(3)
6. Results and Discussion 6.1. Workability
The results of slum tests for different mixes are reported in Fig. 3. For better comparison of the workability results of various mixes, slump values are also displayed in the figure. As is noted from the Fig. 3, workability of the concrete reduces with increased percentage of the rubber chips so as 14% slump reduction occurred for the mixtures containing 15% rubber particles. This fact has been proved also by other researchers (Sgobba et al., 2010) which was attributed to more specific surface area of rubber chips compared to coarse aggregates, and thereby leading to more water consumption for surface coverage of the rubber particles as a sort of lubrication and less free water to maintain a higher workability. As is obvious from the plot, silica fume and zeolite additions reduce the workability as well, which results from higher specific surface area of these admixtures compared to cement. An interesting point regarding workability of mixture containing SF and ZE is that lower workability of ZE mixtures compared to SF mixtures can be explained by microstructure of these mineral admixtures. As illustrated in the SEM micrographs of Fig. 4. ZE particles are porous and amorphous and the lattice structure can restrict the particles form skidding on top of each other and ease of movement in the mixture, and thereby limiting the ball-bearing effect of the admixture particles. However, the SF particles are more spherical and even in case of flocculated particles, the surfaces are more smooth which make the particles or floccules capable of better skidding and moving through the mixture. On the other hand, even though the SF particles are spherical and can move more easily compared to cement particles in control samples, however, the SF particles are several times finer than cement particles. This can lead to higher water or SP demand to lubricate all of the SF particles in fresh concrete, and thereby leading to reduced workability of SF-contained mixtures compared to control mixtures.
6.2. Compressive strength
The samples were tested at the age of 3, 7, 28, and 42 days. For more reliability, average of three samples for each mix was taken and reported as the compressive strength. Plotted in Fig. 5 are the compressive strengths of different mixtures. For the sake of better comparison of the effects of rubber chips and mineral admixtures, the strength values are also displayed in Fig. 5 for all mixtures. As obviously is clearly noted from the figure, compressive strengths decrease with increased percentage of waste rubber replacement. The curves also show a consistent ascending trend in compressive strength due to strength evolution in later ages. To scrutinize the compressive strength increase by time, the incremental strength evolution bar chart is presented in Fig. 6. As is observed from the plots, the compressive strengths differences at early ages are relatively low compared to those of later ages. This phenomenon can be attributed to two main reasons. Firstly, as the mixing water is consumed for cement hydration by time, the interface of rubber chips and binder gets drier. Since the bonding of rubber and binder is not as well as aggregate and binder on the one hand, and the potential shrinkage occurrence is relatively high for rubber compared to aggregate on the other hand, microcracks may form around the rubber particles which can be the source of stress concentration and crack propagation. Secondly, as rubber is a flexible material, once the load is applied to the concrete sample, deformation of rubber particles will be higher relative to that of binder and thereby leading to some incompatibility of deformation resulting in microcrack formation at the interface of rubber particle and binder. It is observed from this bar chart that a higher strength evolution have occurred in 0-3 day and 728 day intervals, with the highest strength gain at 7-28 period for samples congaing mineral admixtures. This observation may indicate that most of pozzolanic activity of the admixtures has occurred in this period to enhance the strength of the concrete samples. According to the results gained from compressive strength tests, it can be said that incorporation of waste tire rubber chips as a partial replacement of the coarse aggregates as a solution to cleaner production for greener concrete, to some extent compromise the compressive strength of the concrete product at different ages. It is observed in this study that 10% and 15% addition of
rubber chips can lead to 35% and 50% strength reduction respectively. Ganjian et al. (2008) replaced up to 10% of coarse aggregates by waste rubber and reported around 23% strength loss. The 12% less strength loss could be due to the higher specific gravity of coarse aggregates they used (2.65) compared to that used in this study (2.51) (Pelliser et al. 2010). However, application of 10% rubber crumbs as replacement of fine aggregates has led to less strength loss, as studied by a few researchers (Richardson et al. 2016; Thomas et al. 2014; Huang et al. 2013). Khatip et al. (1999) have attributes this strength reduction to two main factor as flexibility of rubber particles under loading and improper bonding of rubber and binder. The former is considered the main factor (Pham et al. 2018), while the latter can be improved by rubber pre-treatment (Huang et al. 2013;Pham et al. 2018) and addition of admixtures (Raffoul et al. 2016) in order to improve the interfacial transition zone (ITZ) between the rubber particles and the paste. Another reason of weak bonding can be attributed to hydrophobicity of rubber particles that forms a thin layer of air around the rubber. This could lead to incomplete cement hydration, weaker bond and ITZ, and thereby stress concentration and crack initiation at loading (Raffoul et al. 2016). However, addition of pozzolans such as SF and ZE can enhance the bonding between rubber and binder by improving the interfacial transition zone (ITZ) that can lead to less strength loss (Ramezanianpour et al. 2015; Tran et al. 2019). It can be explained by the fact that the calcium hydroxide (CH) formed during cement hydration has a weak structure and can be also dissolved in moisture (Tran et al. 2019). On the other hand, pozzolans contain high content of SiO2 and Al2O3 that react with CH to form calcium silicate hydrate (CSH) gel (3CaO.2SiO2.3H2O) and calcium aluminate hydrate gel (3CaO.2Al2O3.3H2O), as shown in the following (Mehta 1987): 2 +3() → 3. 2 . 3
+3() + 3 → 3. . 6
(CSH)
(4) (5)
The these gels are mainly responsible for concrete compressive strength (Tran et al. 2019) that are provided by pozzolans, and thereby leading to a denser microstructure of concrete. According to the results, 10% SF enhanced the compressive strength of the concrete without and with rubber chips at the age of 42 days by 4% and 12% respectively. 3% and 8% strength improvement was also observed for 10% ZE addition at the same age for plain and rubberized concrete respectively. This strength enhancement could be attributed to filler effect of the
admixtures and especially pozzolanic activity (Tran et al. 2019; Mohammed et al. 2012). Besides, addition of SF and ZE results in the phase modification of hydration products due to extra formation of CSH, ettringite, and hydrogelenites (Markiv et al. 2016). It is worth mentioning that strength enhancement performance of ZE is kind of sensitive to water to binder ration (w/b). Najimi et al. (2012) reported that for w/b=0.5, concrete containing ZE showed strength decrease around 37% in some cases, however for w/b=0.4 strength enhancement was observed in all ages. 6.3. Elasticity modulus
The results obtained from static elasticity modulus tests on cylindrical samples are plotted in Fig. 7. For the sake of clarity, the values of the static elasticity modulus at different ages are also displayed in this figure. As is noted from the figure, rubberized concrete samples obviously show lower modulus relative to control samples so as the values obtained for samples containing 10% and 15% of rubber chips at the age of 28 days were respectively lower than control samples by 14% and 32%. However, the modulus loss decreased to 10% and 16% at 42 days of age. It is observed that the reduction in compressive strength is less that elastic modulus, as proved by other researchers (Pelliser et al. 2010). In a study by Ganjian et al. (2008), 10% rubber chips replacement resulted in 25% of reduction in elastic modulus. Jokar et al. (2019) reported 22% and 41% elastic modulus reduction for 10% and 15% of rubber crumb replacement, respectively. They concluded that rubber pre-treatment can also improve the elastic modulus by 11% compared to that of untreated rubber due to bond improvement of rubber particles and cement paste. Pelliser et al. (2010) reported 49% loss of elastic modulus due to 10% replacement of rubber crumb, which is quite higher compared to others. They concluded this modulus loss is due to much lower elastic modulus of rubber relative to that of sand. It can also be due to the fact that rubber shows larger strain compared to aggregate at a given stress (Pelliser et al. 2010). Besides, reduced strength of the rubberized samples can lead to lower stress to strain ratio which means lower elasticity modulus (Pham et al. 2018). On the other hand, 10% of SF and ZE led to a little increase in the static elastic modulus of concrete. However, this increase was negligible and respectively around 2% and 1% for SF and ZE, for both 10% and 15% of rubber replacement. It is observed that mitigation of modulus loss by admixtures addition is less effective compared to that of compressive strength, as proved by Onuaguluchi and Panesar (2014). A few researches have
shown that rubber pre-treatment and admixtures can enhance the pore structure and ITZ of rubberized concrete, and thereby greatly affect the transport properties (Pham et al. 2018; Onuaguluchi and Panesar 2014; Pelisser et al. 2010). Again it can be attributed to filler effect of the
admixtures which refines the pore structure of the concrete and shift the pores to a less harmful pore size distribution which strengthens the binder of the concrete, as well as bonding enhancement of the binder and rubber particles (Mohammed et al. 2012). This fact has been verified by Magda et al (Magda et al., 2014). They have also maintained that binder content increase and w/b decrease can improve the elasticity modulus of concrete. However, the admixtures effect on elastic modulus would be slight (Pham et al. 2018). Jokar et al. (2019) also found that pre-treatment and addition of 5% zeolite could improve the elastic modulus only by 5%.
6.4. Comparison with standards and potential applications
Since compressive strength is the most important characteristic of concrete to which other properties are somehow related. Various standards recommend different relationships to estimate elastic modulus of concrete from its compressive strength. For better comparison in this study, different relationships from four different standards are employed and compared for estimation of elastic modulus, as presented in the following. American standard (ACI 318): = 470034′6
(6)
Canadian Standard Association (CSA A23.3): = 450034′6
(7)
British Standard (BS 8110): 6,7 = 89 + 0.246:,7 where, ko is 20 kN/mm2, and fcu,28 is concrete compressive strength at 28 days.
(8)
Euro Code (EC): 6; = 22[(46; )/10]>.
(9)
where, Ecm is mean modulus of elasticity, and fcm is mean compressive strength of concrete at 28 days. The values of elasticity modulus obtained from compressive strength based on the above relationships form different standards are plotted and compared with the experimental values in Fig. 8a, along with the estimation error in Fig. 8b. As is noted from the figure, BS relationship gives the closet estimation of elastic modulus to the experimental values. ACI and CSA though underestimate the elastic modulus, and overestimation is observed in the results obtained from EC relationship. Since ACI relationship underestimates the values of elastic modulus in this study, an attempt was made to correct the equation by adding a calibration coefficient (correction factor) to modify it for rubberized concrete. The correction factor for each data was calculated as the ratio of measured elasticity modulus to calculated elasticity modulus from Eq. (6). Then, as there was three levels of rubber replacement as 0, 10, and 15%, so average of three factors for each level was calculated as the correction factor of that replacement level which resulted in three correction factors as following for this study: = ∗ 470034 ? 6 , = 1.06 ; for concrete without rubber chips
(10)
= @ ∗ 470034 ? 6 , @ = 1.31; for concrete containing 10% rubber chips
(11)
= A ∗ 470034 ? 6 , A = 1.38; for concrete containing 15% rubber chips
(12)
The results of elasticity modulus vs. compressive strength for ACI original and modified equations are plotted in Fig. 9. Thomas et al (2014) have recommended the application of rubberized concrete for pavements, non-structural works, and structural works (up to 7.5% leading to compressive strength of over 35 MPa). It has also been suggested for lightweight structures (20 MPa reference) and building panels, as well as facades for the purpose of energy saving (Pelisser et al. 2010). Richardson et
al. (2015) recommended that rubberized concrete is promising due to the synergy of enhanced toughness and freeze-thaw performance. Rubber fiber concrete with 10% replacement of fine aggregates also maintained compressive strength over 35 MPa, for which applications such as earthquake shockwave absorbers, foundation pad of machinery, highway pavement, airport barrier, and crash barrier have been recommended (Gupta et al. 2015). In a research by Mohammed et al. (2012), it was recommended that load-bearing hollow blocks and non loadbearing ones can be produced by using up to 6.5% and 40.7% rubber crumbs, respectively. Elchalakani (2014) studied and designed the reinforced rubberized concrete for roadside barrier application and observed more resilient behavior compared to pain concrete. He concluded that the new design is applicable to medium performance concrete road sided barrier but not to special performance ones. ACI 318 and International Building Code (IBC) indicate 17 MPa (2500 psi) as the minimum strength of structural concrete. However, there are different grades of concrete for various applications. British standard (BS 8500, 2006) classifies the concrete with compressive strength of less than 25 MPa as normal grade and above that as standard grade. Based on the standards such as BS, ACI 318 and Eurocode 2, it can be concluded that the rubberized concrete with specified strength of 17-25 MPa (2500-3500 psi) can be suggested for applications such as driveways, garages, and floor slabs. However, for pavements with heavy traffic, specified strength of 30 MPa is required (Arabali et al. 2017). Therefore, according to this study, the rubberized with up to 10% rubber replacement is recommended for driveways, garages, and floor slabs. Since building codes and standards have specified different applications based on compressive strength, elastic modulus of rubberized concrete for various applications can be accordingly determined form the relationships given in each, where the a specific modulus is required in certain applications.
6.5. Prediction models results
In order for regression models development, analysis of variance (ANOVA) was performed and significance of each variable was investigated to better understand the contribution of each variable to the model. Presented in Table 6 are the results of the statistical analysis. The variables are listed in this table in descending order of significance, i.e. Age is the most significant and ZE
is the least significant one. Beta is also a parameter indicating the relative strength of the variables. Once the significance of the variables were determined, the regression models were developed and the models’ coefficients were obtained. The coefficients of the Eqs (3), (4), and (5) pertaining to the multiple regression models are listed in table 7. By using the close form equations of the models, compressive strengths of the rubberized concrete were predicted that can be seen in Fig. 13. As can be seen from the plots, even though the correlation factor (R2) of the models are rather close, nonetheless, the power regression models shows the highest correlation.
7. Conclusion In this research, cleaner concrete was produced and studied by incorporation of 10-15% of waste tire rubber as a partial replacement of the aggregates and 10% of cement replacement by SF and ZE. Fresh properties of the greener concrete was tested and it was found that rubber and ZE addition decreases the workability, while SF increases. The effect of SF and ZE on workability was investigated through SEM images of SF and ZE powders. The results obtained indicated 5% and 14.6% slump reduction at 10% and 15% rubber replacement, 4% increase in slump due to SF addition, and 4% slump decrease as a result of ZE addition. Compressive strengths of the rubberized concretes were measured at different ages and around 30% and 50% reductions were observed for 10% and 15% rubber replacements, respectively. The strength results were compared with ACI equation and the coefficients were modified for rubberized concrete. Elastic moduli of rubberized concrete were measured according to ASTM C469. It was found that 10% and 15% rubber replacement can respectively lead to reduction in elastic modulus around 14% and 32% at 28 days and 10% and 16% at 42 days. Comparison of the elastic modulus values obtained from relationships in different standards such as ACI, CSA, EC, and BS with those of experiment showed that ACI 318 relationship underestimates the elastic modulus of rubberized concrete, for which the correction factors was determined based on the results in this study. Regression models namely linear, logarithmic, and power were also used to predict the compressive strength of the rubberized concrete in terms of the influencing variable such as
cement, SF%, ZE%, RB%, and age. Power regression model was found to be more accurate to predict the compressive strength of the rubberized concrete. It should also be noted that the predictions of the models are valid within the range of the variables used and for similar materials used in this study.
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Tables’ Captions
Table 1. Properties of cement, silica fume, and zeolite Table 2. Properties of superplasticizer (SP) Table 3. Mix design proportions of a batch of 3 samples of 15*15*15 cm dimensions
Table 4. Equations of multiple regression models Table 5. Correlation coefficients between all pairs of the variables
Table 6. Statistical analysis of the variables used in regression models Table 7. Coefficients of multiple regression models
Table 1. Properties of cement, silica fume, and zeolite Chemical analysis (wt%) Composition Cement Silica fume Zeolite
SiO2 21.37 93.16 66.5
Initial setting time (min) 135 Form powder
Al2O3 4.83 1.13 11.81
Fe2O3 3.34 0.72 1.3
CaO 62.46 3.11
MgO 3.62 1.6 0.72
SO3 1.76 0.05 0.26
Na2O 0.18 2.01
Physical Characteristics of Cement 3- day 7- day Initial setting time compressive compressive (min) strength (MPa) strength (MPa) 175 19.2 26.9 Physical Characteristics of Silica fume Color Specific gravity gray 1.3-1.5
Table 2. Properties of superplasticizer (SP) Phase
Liquid
Color
Dark brown
Density (g/ml)
1.08-1.10
pH
6-7
Optimum (wt % of cement)
0.3-0.7
pH 8.5-9
K2O 0.51 3.12
L.O.I 1.87 1.58 12.05
28- day compressive strength (MPa) 39.7
Table 3. Mix design proportions of a batch of 3 samples of 15*15*15 cm dimensions Sample
Binder
ID
content
w/b
SP
Rubber Gravel
Sand
Water Zeolite
Silica
Cement
fume (kg)
(kg/m3)
(kg)
(kg)
(kg)
(kg)
(kg)
(kg) (kg)
0RB.C
400
0.4
0.005
0
3.726
2.487
0.54
0
0
1.350
0RB.SF
400
0.4
0.005
0
3.726
2.487
0.54
0
0.135
1.215
0RB.ZE
400
0.4
0.005
0
3.726
2.487
0.54
0.135
0
1.215
10RB.C
400
0.4
0.005
0.373
3.352
2.487
0.54
0
0
1.350
10RB.SF
400
0.4
0.005
0.373
3.352
2.487
0.54
0
0.135
1.215
10RB.ZE
400
0.4
0.005
0.373
3.352
2.487
0.54
0.135
0
1.215
15RB.C
400
0.4
0.005
0.558
3.168
2.487
0.54
0
0
1.350
15RB.SF
400
0.4
0.005
0.558
3.168
2.487
0.54
0
0.135
1.215
15RB.ZE
400
0.4
0.005
0.558
3.168
2.487
0.54
0.135
0
1.215
Regression Type
Equation
Linear
݂ = ܽ + ܽଵ ܥ+ܽଶ ܵ ܨ+ ܽଷ ܼ ܧ+ ܽସ ܴ ܤ+ ܽହ ݁݃ܣ
(3)
Logarithmic
݂ = ܽ + ܽଵ )ܥ(݊ܮ+ܽଶ )ܨܵ(݊ܮ+ ܽଷ )ܧܼ(݊ܮ+ ܽସ )ܤܴ(݊ܮ+ ܽହ )݁݃ܣ(݊ܮ
(4)
Power
݂ = ܽ + ܽଵ ܥమ +ܽଷ ܵ ܨర + ܽହ ܼ ܧల + ܽ ܴ ܤఴ + ܽଽ ݁݃ܣభబ
(5)
Table 4. Equations of multiple regression models
Table 5. Correlation coefficients between all pairs of the variables Variables
C
SF
ZE
RB
Age
C
1
-0.5
-0.5
0
0
SF
-0.5
1
-0.5
0
0
ZE
-0.5
-0.5
1
0
0
RB
0
0
0
0
0
Age
0
0
0
0
0
Table 6. Statistical analysis of the variables used in regression models variable
Beta
t
Sig.
Age
0.731
13.979
0.000
RB
-0.613
-11.719
0.000
C
-0.046
-0.387
0.701
SF
0.047
0.398
0.693
ZE
-0.001
-0.011
0.991
Table 7. Coefficients of multiple regression models Regression Linear Logarithmic Power
a0
a1
a2
a3
a4
a5
a6
a7
a8
a9
a10
-2754.85
6.93
6.97
6.95
-1.04
0.47
-
-
-
-
-
82.11
-13.94
0.02
-0.06
-1.45
7.11
-
-
-
-
-
-331.30
-5.62
0.80
-91.05
0.06
-56.21
0.10
1095.66
0.001
6.86
0.39
Figures’ Captions
Fig. 1. Gradation curve of the (a) sand, (b) gravel and rubber Fig. 2. A view of tire crushing plant (a), and ready rubber chips (b) Fig. 3. Comparison of slump results for different RB, SF, and ZE percentage Fig. 4. SEM micrographs of (a) zeolite and (b) silica fume Fig. 5. Comparative strength results for different percentages of RB, SF, and ZE Fig. 6. Strength evolution of the concrete mixes at different ages Fig. 7. Elastic modulus comparison for different mixes at various ages Fig. 8. Comparison of elastic modulus obtained from experiment with different standards Fig. 9. Experimental results vs. ACI 318 (a) original and (b) modified equations Fig. 10. Strength prediction results by multiple regressions: (a) linear, (b) logarithmic, (c) power
Fig. 1. Gradation curve of the (a) sand, (b) gravel and rubber
(a)
(b)
Fig. 2. A view of tire crushing plant (a), and ready rubber chips (b)
Fig. 3. Comparison of slump results for different RB, SF, and ZE percentage
(a)
(b)
Fig. 4. SEM micrographs of (a) zeolite and (b) silica fume
Fig. 5. Comparative strength results for different percentages of RB, SF, and ZE
Fig. 6. Strength evolution of the concrete mixes at different ages
Fig. 7. Elastic modulus comparison for different mixes at various ages
Fig. 8. Comparison of elastic modulus obtained from experiment with different standards
Fig. 9. Experimental results vs. ACI 318 (a) original and (b) modified equations
Fig. 10. Strength prediction results by multiple regressions: (a) linear, (b) logarithmic, (c) power
Highlights
-
Greener concrete production using wastes and industrial by-products
-
A trade-off between cleaner production and concrete properties
-
Waste tire, Silica fume, and zeolite as partial replacements in concrete
-
Strength and modulus assessment and comparison with standards
-
Multiple regression models for strength prediction