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Article

A Practical Equation for the Elastic Modulus of Recycled Aggregate Concrete

1
Architectural Engineering Institute, Zhejiang Tongji Vocational College of Science and Technology, Hangzhou 311231, China
2
Civil Engineering College, Zhejiang University of Technology, Hangzhou 310014, China
*
Author to whom correspondence should be addressed.
Buildings 2022, 12(2), 187; https://doi.org/10.3390/buildings12020187
Submission received: 11 January 2022 / Revised: 31 January 2022 / Accepted: 1 February 2022 / Published: 6 February 2022
(This article belongs to the Collection Green and Sustainable Building Materials)

Abstract

:
For greater sustainability in construction, coarse recycled aggregate concrete (RAC) is becoming popular as a replacement for natural aggregate concrete (NAC) in structures. The elastic modulus of concrete (E) is a fundamental parameter in structure design. However, the empirical equations for E of NAC cannot apply to RAC because E of RAC is lower than NAC of equal strength, which hinders the widespread use of RAC to a certain extent. This paper provides a practical equation for E of RAC based on a comprehensive statistical analysis of 1383 mixes from 154 publications, allowing designers to easily estimate E of RAC by known parameters at the design stage, such as compressive strength, replacement rate and quality of recycled aggregate. This equation is developed by introducing a reduction factor η into the empirical equation for NAC and verified by the additional experimental results. Compared with JGJ/T443-2018 (a Chinese standard), this paper provides a more reasonable and accurate estimate by analysing much more data and taking into account other factors, such as aggregate type and the volume ratio of aggregate to paste.

1. Introduction

The elastic modulus of concrete is a fundamental parameter for designing concrete structures. Thus, current building codes propose practical equations for the elastic modulus, such as Equations (1)–(3) [1,2,3]. The elastic modulus in these equations is a function of compressive strength, a known parameter at the design stage.
CEB-FIP : ENAC,pred = 21500(fcy/10)1/3
ACI 318 : ENAC,pred = 4730fcy0.5
GB 50010 : ENAC,pred = 105/(2.2 + 34.7/fcu)
where ENAC,pred is the estimation of elastic modulus of NAC, MPa; fcy is the compressive strength measured on cylinders 150/300 mm at an age of 28 days, MPa; fcu is the compressive strength measured on cubes of 150 mm size at an age of 28 days, MPa.
For greater sustainability in construction, RAC has been considered as a replacement for NAC in structures. However, due to the old mortar and crushed bricks in coarse recycled aggregate (RA), the elastic modulus of RAC is lower than NAC of equal compressive strength, meaning that the equations for the elastic modulus of NAC, such as Equations (1)–(3), cannot apply to RAC. Therefore, many equations for the elastic modulus of RAC have been developed [4,5,6,7,8,9,10,11]. However, most of them are not practical for the estimation as they use many parameters unknown at the design stage, such as the detailed mix proportion of concrete, the aggregate type, the cement type, the aggregate size, the elastic modulus of the control concrete and so on.
JGJ/T443-2018 [11] (a Chinese code for recycled concrete structures) proposes a practical equation, as shown in Equation (4), for the elastic modulus of RAC by introducing a reduction factor η that depends on the quality and replacement level of RA, as shown in Equation (5). This is justified by the fact that it takes into account the influence of the elastic modulus of the mixed aggregate that mainly depends on the porosity of the aggregate affected by the quality and replacement level of RA. However, there are two problems due to the limited data for the analysis (only about 500 mixes):
  • It shows that Class I RA has no adverse effect on the elastic modulus. However, a little old mortar may be attached to Class I RA that reduces the elastic modulus, and Ohemeng et al. [4] report that RCA made with high-quality RA may gain equal or higher compressive strength but lower elastic modulus, which means η for Class I RA should be less than 1.
  • It does not distinguish the influence of Class II and III RA on the elastic modulus. However, a significant difference in porosity between Class II and III RA may lead to a different η for them.
ERAC,pred = ηENAC,pred = η(105/(2.2 + 34.7/fcu))
η = {1, for Class I RA; 0.9 + (0.3 − r)/7, for Class II and III RA}
where RA is classified by GB 25177-2010 [12]; ERAC,pred is the estimation of elastic modulus of RAC, MPa; r is the replacement rate of RA by weight.
This paper does similar works with JGJ/T443-2018 but analyses more data to enable a better evaluation of the reduction factor η. A total of 1383 mixes from 154 publications are collected and analysed statistically. The correlation between η and r for different quality of RA is quantified. From this, a practical equation for the elastic modulus of RAC in the form of Equation (4) is proposed. Finally, the equation is validated by the additional laboratory tests. Designers and engineers can use the simple equation to determine the elastic modulus of RAC by known parameters at the design stage.

2. Materials and Methods

2.1. Data Collection

First, the publications related to the elastic modulus of RCA are collected.
Second, for each publication, the key information, such as the apparent density (ρa) and water absorption (wa) of RA, the replacement rate of RA, the compressive strength and the elastic modulus at 28 days and the shape and size of specimens for strength test, is identified carefully and transcribed into a spreadsheet. We cross-check it to avoid incorrect entries or repeated entries.
Notes:
  • The ρa can be calculated from the oven-dry density (ρod) and wa, or the saturated surface dry density (ρssd) and wa, or the ρssd and ρod based on Equations (6) and (7), although some publications give the ρod or ρssd of RA rather than the ρa.
  • This paper uses the weight replacement rate as JGJ/T443-2018 does. Some publications use the volume replacement rate while others use the weight replacement rate. In fact, there is little difference between the volume replacement rate and weight replacement rate in most cases.
  • The size effect of strength is considered in this paper. The 150 mm cube compressive strength is the standard compressive strength in this paper. The conversion factors of compressive strength are shown in Table 1 [13,14,15,16] and similar conversions can be seen in References [17,18]. For example, for C60 concrete, according to Table 1, we can multiply the 100 mm × 200 mm cylinder compressive strength by the specific conversion factor 1.12 to obtain the 150 mm cube compressive strength. The specific conversion factor 1.12 derives from Reference [15]. In Reference [15], for C60 concrete, the 150 mm cube compressive strength is approximately 1.16 times the 150 mm × 300 mm cylinder compressive strength, which is also seen in CEB-FIP model code 2010 [1], while the 150 mm × 300 mm cylinder compressive strength is approximately 0.97 times the 100 mm × 200 mm cylinder compressive strength. Therefore, the 150 mm cube compressive strength can be considered as approximately 1.12 (≈1.16 × 0.97) times the 100 mm × 200 mm cylinder compressive strength. Different kinds of tested specimens for compressive strength and elastic modulus are adopted in different publications. The size effect on elastic modulus does not exist as the elastic modulus is the property of concrete in the elastic stage while the size effect is related to the concrete fracture [19]; however, the size effect on strength is significant. The influence factors include the cross-sectional shape, the cross-sectional diameter and the height to diameter ratio; however, the decrease in strength is not significant when the height to diameter ratio is larger than 2 [13,14].
ρa = ρod/(1 + ρod/1000 − ρssd/1000)
wa = 100(ρssd/ρod − 1)
where ρa, ρod and ρssd are the apparent density, oven-dried density and saturated surface dry density, respectively, (kg/m3); wa is the water absorption, %.

2.2. Statistic Analysis

The elastic modulus of RCA normally decreases with the increasing replacement level of RA, the degree of which depends on the quality of RA. Therefore, before the statistical analysis, the data is divided into several groups according to the quality of RA. GB 25177-2010 [12] (a Chinese code for coarse recycled aggregate) provides a performance-based classification for RA, as shown in Table 2. We use it to classify data as JGJ/T443-2018 does. It is worth noting that GB 25177-2010 only specifies Class I, II and III RA; we add Class IV RA since we find that low-quality RA beyond the requirements of Class III RA can also produce usable concrete that meets the performance requirements, which uses for reference the work of Silva et al. [20]. It is also worth noting that “>2450” means the apparent density of Class I RA should be larger than 2450 kg/m3 and that if the apparent density of a RA is equal to 2450 kg/m3, the RA belongs to Class II RA rather than Class I RA.
The basic form of the equation we aim to develop is shown in Equation (8). The equation changes to Equation (3) when r = 0. Moreover, the coefficient ki represents the loss in the elastic modulus due to RA. The ki is different for each class of RA, as shown in Equation (9). Obviously, k4 > k3 > k2 > k1 > 0.
It seems that the ki can be determined by linear regression based on Equation (10). However, there are problems. Here, we take the data from Luo et al. [21] and Fonseca et al. [22] as examples. As shown in Figure 1a, the elastic modulus of 100% RAC using Class I RA decreases slightly compared with NAC, while the elastic modulus of 100% RAC using Class III RA decreases significantly, which is in line with our expectations. However, when we fit the data based on Equation (10), there is an error that k3 < 0 < k1. This is because the elastic modulus of the control concrete in the work of Luo et al. (Class I RA) is much lower than the estimation from Equation (3) [21], while that of Fonseca et al. (Class III RA) is much higher [22]. The essence is that only the compressive strength of concrete, the quality class and replacement rate of RA are considered in the equation, but the other factors affecting the elastic modulus, such as aggregate type (e.g., basalt, limestone, etc.), the volume ratio of aggregate to paste, the volume ratio of coarse aggregate to fine aggregate, aggregate size and so on, are ignored. Therefore, a correction factor α, as shown in Equation (11), is introduced to Equation (12) instead of Equation (10) to consider the other factors, and ERACENAC,pred mainly depends on the quality class and replacement rate of RA, as shown in Equation (12). At this point, the accurate ki can be gained through linear regression based on Equation (12), as shown in Figure 1b.
α shows the variation of ENAC for a given compressive strength due to other factors, e.g., aggregate type and volume ratio of aggregate to paste. As shown in Figure 2, the value range of α is (0.65, 1.29), calculated through the statistical analysis of the 332 mixes of control concrete. It should be noted that α in eight mixes from the references [23,24,25,26,27] is beyond the range (μ − 3σ, μ + 3σ), where μ is the mean and σ is the Standard Deviation, so α in the eight mixes are outliers. The data in these references is marked in the database and is not involved in the statistical analysis. Then, a practical equation for the elastic modulus of RCA is in the form of Equations (13)–(15).
ERAC,pred = ηENAC,pred = (1-kir)(105/(2.2 + 34.7/fcu))
ki = {k1, for Class I RA; k2, for Class II RA; k3, for Class III RA; k4, for Class IV RA}
ERAC/(105/(2.2 + 34.7/fcu)) = (1 − kir)
α = Econtrol/ENAC,pred
ERAC/(α (105/ (2.2 + 34.7/fcu))) = (1 − kir)
ERAC,pred = 0.97(1 − kir)(105/(2.2 + 34.7/fcu))
ERAC,max = 1.29(1 − kir)(105/(2.2 + 34.7/fcu))
ERAC,min = 0.65(1 − kir)(105/(2.2 + 34.7/fcu))
where Econtrol is the elastic modulus of the control concrete and the control concrete is a NAC that uses the same mix as RAC but uses natural aggregate rather than RA; ERAC is the measured/actual value of elastic modulus of RAC, MPa; ERAC,pred is the estimation of elastic modulus of RAC, MPa; and ERAC,max/ERAC,min are the upper/lower bound value of estimation of elastic modulus of RAC, MPa.

2.3. Laboratory Tests for Verification of the Equation

The compressive strength and elastic modulus of RCA made with four classes of RA are measured, and the results are used for verification of the equation proposed in this paper.

2.3.1. Materials

The materials used are shown in Table 3. The properties of coarse aggregate are shown in Table 4. No admixture is used. RA is treated by presoaking and used under saturated surface dry (SSD) conditions.

2.3.2. Preparation of Specimens

Three groups of control concrete are prepared with water to cement ratios of 0.6, 0.5 and 0.4, respectively. The detailed mix proportions are shown in Table 5. Sixty groups of RAC are prepared with water to cement ratios of 0.6, 0.5 and 0.4, weight replacement rates of 20%, 40%, 60%, 80%, 100% and four classes of RA, respectively. Control-0.6 means the control concrete prepared with the water to cement ratio of 0.6, while RAC-I-20-0.6 means RAC prepared with Class I RA, the weight replacement rate of 20% and a water to cement ratio of 0.6.

2.3.3. Test for Compressive Strength and Elastic Modulus

To save raw materials, three 100 mm cubes are cast for each group for the strength test and three 100 mm × 200 mm cylinders for each group are cast for the elastic modulus test. The specimens are cured in a standard curing room for 28 days and then their compressive strength and elastic modulus are measured according to GB 50081-2019 [175]. The 100 mm cube strength is converted to the 150 mm cube strength and the 100 mm × 200 mm cylinder strength according to Table 1.

3. Dataset

A total of 1383 mixes from 154 publications are collected, as listed in Supplementary Materials [21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174]. The dataset includes 1051 RAC mixes and 332 mixes of the control concrete. However, 43 RAC mixes of data are identified as outliers and not involved in the statistical analysis, as the elastic modulus of the control concrete in these publications is too high or too low [23,24,25,26,27].
Most RAC mixes use the conventional replacement method, while a few mixes (26 mixes) use the equivalent mortar volume (EMV) method [86,93,101,111,115,120,126,168]. The EMV method considers the old mortar in RA as a mortar rather than a part of coarse aggregate and adjusts the coarse aggregate and fresh mortar content of the mix accordingly to achieve the same total mortar volume as the control mix. Due to the same total mortar volume, the elastic modulus of the RAC mixes designed by the EMV method is independent of quality and replacement rate of RA and not lower than NAC of equal strength, as shown in Figure 3. However, studies of the EMV method are limited [176]. Therefore, this paper still focuses on the RAC mixes designed by the conventional method.
Figure 4a,b present the distribution of ERAC/ENAC,pred and the relationship between ERAC and fcu of 982 RAC mixes produced with different quality and replacement levels of RA, respectively. Ninety-five per cent of ERAC are in the range (0.552ENAC,pred, 1.168ENAC,pred), while 95% of ENAC are in the range (0.65ENAC,pred, 1.29ENAC,pred), as shown in Section 2.2 (Figure 2). A significant reduction in the elastic modulus due to RA can be seen. The lower bound value of ERAC/ENAC,pred in this work is 0.552 while the value calculated by R.V. Silva et al. is 0.61 [5]. The figure of 0.552 may be more accurate as we use much more data. If the quality and replacement level of RA in RAC are unknown, Equations (16)–(18) can be used to estimate the elastic modulus of RAC. Note that the use of increasing RA content has a significant impact on the elastic modulus, and more so if these exhibit low quality. Therefore, the prediction of the elastic modulus of RAC can be improved if the quality and replacement level of RA are taken into account.
ERAC,pred = 0.86(105/(2.2 + 34.7/fcu))
ERAC,max = 1.168(105/(2.2 + 34.7/fcu))
ERAC,min = 0.552(105/(2.2 + 34.7/fcu))

4. Practical Equation for the Elastic Modulus

Figure 5a–h present the relationships between ERACENAC,pred, ERAC/ENAC,pred and r of RAC mixes produced with different quality of RA, respectively. Although the R2 obtained in this work seems low, there is a very strong correlation between ERACENAC,pred and r considering the large sample size. It should be noted that R2 is influenced by the sample size. From a statistical point of view, the critical value of R2 decreases with the increase of sample size and R2 > the critical value means there is a very strong correlation, and the critical value is 0.033 (0.18292) when the sample size is 82 [177]. The R2 obtained in this work is much higher than the critical value.
The results reveal that even if Class I RA is used, the elastic modulus of RAC is still lower than NAC and only slightly higher than RAC made with Class II RA, while the elastic modulus of RAC made with Class II RA is also only slightly higher than RAC made with Class III RA. However, it is acceptable that RAC made with Class I, II and III RA have a reduced value of elastic modulus up to approximately 20% at maximum compared to NAC of equal strength as the value is within the scatter band for NAC. It should be noted that the elastic modulus of RAC made with Class IV RA is significantly lower than NAC of equal strength when high RA replacement levels are used. Class IV RA shall be used with caution.
α shows the variation of E due to other factors, e.g., aggregate type and volume ratio of aggregate to paste. It shows the effectiveness of the introduction of α that the obtained ki is consistent with our expectations and most of the RAC mixes (about 94%) are in the range proposed by this work. If the quality and replacement level of RA in RAC are known, Equations (19)–(24) can be used to estimate the elastic modulus of RAC.
It should be noted that the basic equation of ENAC,pred uses Equation (3) proposed by the Chinese code GB 50010 [3]. Obviously, other basic equations such as Equations (1) and (2) can be also used, and the corresponding α and ki can be easily gained by the same method as shown in Section 2.2.
ERAC,pred = 0.97(1 − 0.1229r)(105/(2.2 + 34.7/fcu)), for Class I RA
ERAC,pred = 0.97(1 − 0.1429r)(105/(2.2 + 34.7/fcu)), for Class II RA
ERAC,pred = 0.97(1 − 0.1744r)(105/(2.2 + 34.7/fcu)), for Class III RA
ERAC,pred = 0.97(1 − 0.2816r)(105/(2.2 + 34.7/fcu)), for Class IV RA
ERAC,max = 1.33ERAC,pred
ERAC,min = 0.67ERAC,pred

5. Verification of the Equation

The experimental results and the ERAC,pred estimated by Equations (19)–(22) are listed in Table 6. As shown in Table 6, ERAC/ERAC,pred in the experiments are in the range (0.92, 1.12) which is much narrower than the range (0.67, 1.33) allowed by Equations (23) and (24). It verifies Equations (19)–(24) that the ERAC,pred is near ERAC. In order to see this more intuitively, ERAC vs. ERAC,pred is plotted in Figure 6.

6. Comparison with JGJ/T443-2018

Table 7 shows values of the reduction factor η in JGJ/T443-2018 and this work for different quality of RA when r = 1, respectively. The η values in this work is more in line with our expectations as the η value for Class I RA is less than 1 and the η value for Class II RA is larger than that Class III RA, as shown in Table 7. Compared with this work, JGJ/T443 overestimates the elastic modulus of RAC using Class I RA and underestimates that of RAC using Class II RA. However, the estimation for the elastic modulus of RAC using Class III RA by JGJ/T443-2018 and this work is close.

7. Conclusions

Although RAC may exhibit similar compressive strength to NAC, as the RA content increases the elastic modulus decreases, the degree of which depends on the quality of RA. This paper aims to use the reduction factor η to quantify the loss of the elastic modulus and propose a practical equation for the elastic modulus of RAC based on a comprehensive statistical analysis of 1383 concrete mixes from 154 publications. Based on the results of this investigation, the following conclusions can be drawn:
  • For a given compressive strength, the elastic modulus of RAC in most studies is in the range (0.552ENAC,pred, 1.168ENAC,pred). It should be noted that this prediction interval is applicable only when the compressive strength is known while the other factors are unknown.
  • The correlation between the reduction factor η and the replacement rate for different quality of RA is determined. The results show that the reduced elastic modulus of RAC made with Class I, II or III RA is acceptable; however, the reduced elastic modulus of RAC made with high replacement rates of Class IV RA is so low that Class IV RA must be used with caution.
  • The prediction interval (scatter band) of the elastic modulus of RAC is provided considering the variation of the elastic modulus due to other factors, e.g., aggregate type and volume ratio of aggregate to paste.
  • JGJ/T443-2018 overestimates the elastic modulus of RAC made with Class I RA and underestimates that of RAC made with Class II RA.
  • The experimental results verify the equation proposed in this work. If the replacement rate and quality (classified by the apparent density and water absorption) of RA are known, designers and engineers can use the simple equation to determine the elastic modulus of RAC by means of the compressive strength.
It should be noted that these conclusions only apply to RAC designed by the conventional method. The elastic modulus of RAC designed by the EMV method is not lower than NAC of equal strength due to the same mortar volume. However, the related studies are limited. Therefore, further studies need to be conducted to ensure the effectiveness of the EMV method and the reliability of the results.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/buildings12020187/s1.

Author Contributions

Conceptualization, Y.Z.; methodology, J.C.; validation, J.C. and F.Y.; investigation, J.C.; writing—original draft preparation, J.C.; writing—review and editing, Y.Z.; funding acquisition, Y.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research and the APC were funded by the Science and technology project of Zhejiang provincial water resource department (grant number: RC1945) and the Basic Scientific Research Business Fees of Provincial Colleges and Universities (grant number: FRF20QN006).

Data Availability Statement

All data can be seen in the text and Supplementary Materials.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript or in the decision to publish the results.

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Figure 1. Introducing α to consider other factors affecting E (data source: Luo et al. [21]; Fonseca et al. [22]). (a) ERAC/ENAC,pred; (b) ERACENAC,pred.
Figure 1. Introducing α to consider other factors affecting E (data source: Luo et al. [21]; Fonseca et al. [22]). (a) ERAC/ENAC,pred; (b) ERACENAC,pred.
Buildings 12 00187 g001
Figure 2. Distribution of α and ENAC [21,22,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174]. (a) α~N (0.97,0.162); (b) 1.29ENAC,predENAC ≥ 0.65ENAC,pred.
Figure 2. Distribution of α and ENAC [21,22,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174]. (a) α~N (0.97,0.162); (b) 1.29ENAC,predENAC ≥ 0.65ENAC,pred.
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Figure 3. Comparison of elastic moduli of RAC designed by EMV method and NAC of equal strength [86,93,101,111,115,120,126,168].
Figure 3. Comparison of elastic moduli of RAC designed by EMV method and NAC of equal strength [86,93,101,111,115,120,126,168].
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Figure 4. Distribution of η and ERAC [21,22,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,169,170,171,172,173,174]. (a) η~N(0.86,0.1542); (b) 1.168ENAC,predERAC ≥ 0.552ENAC,pred.
Figure 4. Distribution of η and ERAC [21,22,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,169,170,171,172,173,174]. (a) η~N(0.86,0.1542); (b) 1.168ENAC,predERAC ≥ 0.552ENAC,pred.
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Figure 5. Relationships between ERACENAC,pred, ERAC/ENAC,pred and r of RAC [21,22,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,169,170,171,172,173,174]. (a) Relationship between ERACENAC,pred and r of Class I RAC; (b) relationship between ERAC/ENAC,pred and r of Class I RAC; (c) relationship between ERACENAC,pred and r of Class II RAC; (d) relationship between ERAC/ENAC,pred and r of Class II RAC; (e) relationship between ERACENAC,pred and r of Class III RAC; (f) relationship between ERAC/ENAC,pred and r of Class III RAC; (g) relationship between ERACENAC,pred and r of Class IV RAC; (h) relationship between ERAC/ENAC,pred and r of Class IV RAC.
Figure 5. Relationships between ERACENAC,pred, ERAC/ENAC,pred and r of RAC [21,22,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,169,170,171,172,173,174]. (a) Relationship between ERACENAC,pred and r of Class I RAC; (b) relationship between ERAC/ENAC,pred and r of Class I RAC; (c) relationship between ERACENAC,pred and r of Class II RAC; (d) relationship between ERAC/ENAC,pred and r of Class II RAC; (e) relationship between ERACENAC,pred and r of Class III RAC; (f) relationship between ERAC/ENAC,pred and r of Class III RAC; (g) relationship between ERACENAC,pred and r of Class IV RAC; (h) relationship between ERAC/ENAC,pred and r of Class IV RAC.
Buildings 12 00187 g005aBuildings 12 00187 g005b
Figure 6. Comparison of ERAC,pred and ERAC obtained in the laboratory tests.
Figure 6. Comparison of ERAC,pred and ERAC obtained in the laboratory tests.
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Table 1. Conversion factors of compressive strength [13,14,15,16].
Table 1. Conversion factors of compressive strength [13,14,15,16].
Size/Diameter × HeightShapeStrength Grade
C20–C40C50C60C70C80
150 mmCube1
100 mmCube0.95
50 mm × 100 mmCylinder1.171.131.031.010.99
75 mm × 150 mmCylinder1.191.151.071.051.04
100 mm × 200 mmCylinder1.211.171.121.101.08
120 mm × 240 mmCylinder1.231.191.141.121.10
150 mm × 300 mmCylinder1.251.201.161.141.12
160 mm × 320 mmCylinder1.261.211.171.151.13
100 mm × 300 mmPrism1.231.231.181.151.13
120 mm × 360 mmPrism1.261.261.221.191.16
150 mm × 300 mmPrism1.321.321.281.251.22
Table 2. Physical property requirements of the performance-based classification [12].
Table 2. Physical property requirements of the performance-based classification [12].
RA ClassIIIIIIIV
Apparent density (kg/m3)>2450>2350>2250No limit
Water absorption (%)<3<5<8
Table 3. Materials used in the laboratory tests.
Table 3. Materials used in the laboratory tests.
Materials Used
CementPO 42.5R
WaterTap water
Fine aggregateNatural river sand with medium size
Natural coarse aggregateCrushed natural stone
Class I RACarbonated crushed concrete
Class II RACrushed concrete
Class III RACrushed concrete
Class IV RACrushed concrete + crushed bricks
Table 4. Properties of coarse aggregate in the laboratory tests.
Table 4. Properties of coarse aggregate in the laboratory tests.
Size (mm)GradationWater Absorption (%)Apparent Density (kg/m3)
NA5–255–10 mm (20%)
10–16 mm (30%)
16–25 mm (50%)
0.72810
Class I RA2.52650
Class II RA3.62600
Class III RA5.52590
Class IV RA8.52450
Table 5. Mix proportions of the control concrete in the laboratory tests (kg/m3).
Table 5. Mix proportions of the control concrete in the laboratory tests (kg/m3).
Coarse AggregateFine AggregateCementWater
Control-0.61088725367220
Control-0.51096644440220
Control-0.41122578500200
Table 6. Experimental results and ERAC,pred estimated by Equations (19)–(22).
Table 6. Experimental results and ERAC,pred estimated by Equations (19)–(22).
fc (MPa)E (MPa)ERAC,pred (MPa)ERAC/ERAC,pred
123Mean123Mean
Control-0.641.342.942.842.333,60031,80030,50031,967
Control-0.555.156.95856.733,40035,80036,10035,100
Control-0.468.370.865.668.239,10038,00037,10038,067
RAC-I-20-0.635.842.237.938.626,70031,80029,70029,40030,5390.96
RAC-I-40-0.639.341.835.638.930,60029,50026,80028,96729,8290.97
RAC-I-60-0.637.535.838.937.429,30029,20029,70029,40028,7251.02
RAC-I-80-0.638.038.337.337.930,40027,90026,80028,36728,0661.01
RAC-I-100-0.636.538.939.538.327,40027,60029,10028,03327,3921.02
RAC-I-20-0.547.149.150.348.831,40032,90032,70032,33332,5080.99
RAC-I-40-0.553.154.947.051.731,00028,80033,70031,16732,1180.97
RAC-I-60-0.547.551.748.449.230,40030,50032,00030,96730,9251.00
RAC-I-80-0.554.553.446.951.631,40030,50031,30031,06730,4491.02
RAC-I-100-0.554.049.148.050.431,40030,80029,60030,60029,4501.04
RAC-I-20-0.452.759.762.758.435,80036,30034,50035,53333,8581.05
RAC-I-40-0.461.252.766.560.134,60033,60035,70034,63333,2121.04
RAC-I-60-0.458.657.761.259.233,40033,60035,20034,06732,2441.06
RAC-I-80-0.459.057.656.857.833,10033,20034,50033,60031,2331.08
RAC-I-100-0.459.568.465.364.432,70033,20034,50033,46731,0641.08
RAC-II-20-0.636.131.728.832.228,20029,20029,00028,80028,7491.00
RAC-II-40-0.632.131.031.031.429,10029,20028,70029,00027,6611.05
RAC-II-60-0.638.036.334.236.227,90027,90027,40027,73328,0690.99
RAC-II-80-0.635.734.432.934.328,20028,90028,10028,40026,7581.06
RAC-II-100-0.635.736.934.135.623,70025,40027,80025,63326,1800.98
RAC-II-20-0.546.948.846.247.331,40031,20031,30031,30032,1200.97
RAC-II-40-0.543.444.944.644.330,40031,90031,00031,10030,6561.01
RAC-II-60-0.544.645.543.144.430,90031,20031,30031,13329,7441.05
RAC-II-80-0.544.139.740.141.329,70030,50031,70030,63328,2581.08
RAC-II-100-0.548.045.649.847.829,70027,70030,60029,33328,4141.03
RAC-II-20-0.455.556.250.554.135,20033,60035,70034,83333,1581.05
RAC-II-40-0.454.153.656.154.635,20035,10034,10034,80032,2531.08
RAC-II-60-0.458.752.361.357.434,20033,60034,80034,20031,6251.08
RAC-II-80-0.452.357.250.153.233,30034,40033,30033,66730,1201.12
RAC-II-100-0.454.547.560.354.130,30031,70033,70031,90029,2601.09
RAC-III-20-0.633.235.235.834.727,50029,20029,00028,56729,2640.98
RAC-III-40-0.632.434.436.034.327,20027,30027,70027,40028,0870.98
RAC-III-60-0.631.734.132.932.924,00024,80025,50024,76726,6840.93
RAC-III-80-0.628.435.232.432.022,30024,00024,80023,70025,4130.93
RAC-III-100-0.636.329.829.431.821,10025,40023,50023,33324,3410.96
RAC-III-20-0.549.645.947.047.531,00030,80032,40031,40031,9450.98
RAC-III-40-0.542.647.347.545.830,00029,80029,90029,90030,5090.98
RAC-III-60-0.545.642.646.945.026,30028,00027,20027,16729,2370.93
RAC-III-80-0.544.945.944.945.226,70027,10025,60026,46728,1300.94
RAC-III-100-0.546.543.439.14323,50024,00026,00024,50026,6320.92
RAC-III-20-0.454.155.360.956.834,20034,40034,80034,46733,3001.04
RAC-III-40-0.458.058.052.756.232,60033,60033,70033,30032,0311.04
RAC-III-60-0.451.453.549.751.530,00030,60030,70030,43330,2261.01
RAC-III-80-0.454.253.246.551.329,30028,90029,00029,06729,0181.00
RAC-III-100-0.446.552.545.648.228,00027,20026,50027,23327,4270.99
RAC-IV-20-0.633.336.331.433.725,80028,30027,60027,23328,3340.96
RAC-IV-40-0.632.732.832.732.726,10027,30028,00027,13326,4021.03
RAC-IV-60-0.630.328.129.829.422,50024,80024,60023,96723,8471.00
RAC-IV-80-0.633.731.734.133.223,60023,40023,40023,46723,1491.01
RAC-IV-100-0.630.226.834.130.418,70021,40021,60020,56720,8470.99
RAC-IV-20-0.544.945.647.345.928,50028,90029,30028,90030,9720.93
RAC-IV-40-0.545.546.242.644.828,20029,90029,60029,23328,9311.01
RAC-IV-60-0.545.240.845.143.725,10026,10026,20025,80026,9240.96
RAC-IV-80-0.547.143.839.343.425,70026,50025,60025,93325,0531.04
RAC-IV-100-0.537.540.337.938.623,30021,00025,10023,13322,4811.03
RAC-IV-20-0.461.359.155.158.531,40032,30032,20031,96732,7720.98
RAC-IV-40-0.451.751.754.352.631,00031,60031,90031,50030,0951.05
RAC-IV-60-0.455.348.846.650.228,00028,50028,80028,43327,8861.02
RAC-IV-80-0.446.955.951.951.625,60027,80028,80027,40026,1571.05
RAC-IV-100-0.447.546.645.746.622,50026,00025,10024,53323,6651.04
Table 7. Values of η in JGJ/T443-2018 and this work when r = 1.
Table 7. Values of η in JGJ/T443-2018 and this work when r = 1.
Class I RAClass II RAClass III RA
JGJ/T443-2018 [11]10.80.8
This work0.850.830.8
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Chen, J.; Zhou, Y.; Yin, F. A Practical Equation for the Elastic Modulus of Recycled Aggregate Concrete. Buildings 2022, 12, 187. https://doi.org/10.3390/buildings12020187

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Chen J, Zhou Y, Yin F. A Practical Equation for the Elastic Modulus of Recycled Aggregate Concrete. Buildings. 2022; 12(2):187. https://doi.org/10.3390/buildings12020187

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Chen, Jian, Yun Zhou, and Fangfang Yin. 2022. "A Practical Equation for the Elastic Modulus of Recycled Aggregate Concrete" Buildings 12, no. 2: 187. https://doi.org/10.3390/buildings12020187

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