1. Introduction
With the development of concrete construction, a large number of old buildings with brick and concrete structures will be demolished. Recycled coarse aggregate (RCA) and recycled fine aggregate (RFA) are the main products after the demolishment of brick and concrete structures [
1]. For the RFA, recycled fine aggregate of waste concrete (RFA1) and recycled fine aggregate of waste clay brick (RFA2) are two common types [
2]. Recycling RFA can effectively solve the shortage of natural river sand resources. Recently, the mechanical properties and durability of concrete containing RFA1 and RFA2 have been studied. Wang et al. [
3] found that the compressive strength of recycled fine aggregate concrete (RFAC) containing RFA1 at 28 days was greater than the ordinary concrete. Kirthika et al. [
4] systematically studied the durability of RFAC with RFA1 and results showed that concrete with 30% RFA1 had better resistance to chloride penetration and carbonation. Dang et al. [
5] found that the compressive strength of RFAC containing 50% RFA2 with no extra water was comparable with ordinary concrete. It is a significant issue to study the performance of RFAC for the utilization of RFA.
Recycled aggregate thermal insulation concrete (RATIC) is a new type of green structural concrete, with the glazed hollow beads (GHB) and recycled aggregate [
6,
7]. It not only alleviates environmental problems caused by construction and demolition waste but also reduces the overall energy consumption of buildings [
8]. At present, research mainly focuses on the mechanical properties and thermal conductivity of RATIC. Wang et al. [
9] carried out a systematic study on the mechanical properties of RATIC prepared with RCA, and the results showed that the compressive strength, splitting tensile strength and elastic modulus of RATIC were all lower than those of the GHB thermal insulation concrete (TIC). Xiao et al. [
10] found that the thermal conductivity of recycled concrete decreased with the increase of the replacement ratio of RCA. The test results of Zhao et al. [
11] showed that the thermal conductivity of concrete decreased significantly with the increase of GHB content. Nevertheless, few reports related to the performance of RATIC containing RFA.
As a new green structural concrete, the shrinkage of concrete causes micro-cracks [
12] and plays an important role in the design of the service limit state of structural members [
13]. According to EN1992 [
14], the total shrinkage of concrete is composed of two parts: autogenous shrinkage and drying shrinkage of concrete. Autogenous shrinkage of concrete is defined as the volume reduction that occurs without moisture exchange between the internal concrete and external environment [
15]. Delsaute et al. [
16] found that RFA1 was beneficial to reducing the autogenous shrinkage of concrete, which attributed to the combined effect of additional water and elastic modulus of RFA1. Zhang et al. [
17] found there was a rapid increase in the autogenous shrinkage of RFAC during the first 60 days, and then the increasing rate reduced. Moreover, Zhang et al. [
18] find that the autogenous shrinkage strain of RFAC prepared by RFA2 decreased with the increase of the RFA2 replacements. Drying shrinkage is the volume reduction of hardened concrete caused by evaporation of water under the effect of unsaturated environmental humidity [
19]. Khatib et al. [
20] made a comparative study on the drying shrinkage of RFAC prepared by RFA1 and RFA2, and the 90-day drying shrinkage of RFAC prepared by RFA2 was significantly smaller than that prepared by RFA1. Zhang et al. [
21] selected two different types of RFA1 and found that the water absorption and elastic modulus of RFA1 were the main reasons for the large difference in the final drying shrinkage strain of RFAC; based on the results, Zhang et al. [
21] introduced the correction coefficients
kwa and
kv to modify the drying shrinkage model of ordinary concrete in EN1992 [
14], which considered the influence of water absorption on the drying shrinkage development and the influence of elastic modulus on the final drying shrinkage strain of RFA1, respectively. Dang et al. [
1] attributed the increase of drying shrinkage of RFAC prepared by RFA2 to the low elastic modulus of RFA2. Although many researches on the shrinkage of RFAC have been conducted, little information on the shrinkage of RATIC can be found in the literature.
At present, it is not common to conduct long-term shrinkage test as a routine test for every single concrete mixture, the structural engineer can only assess the risk of concrete cracking using existing prediction models [
22]. In order to better represent the shrinkage of concrete in precast components, a large number of autogenous shrinkage, drying shrinkage and total shrinkage models have been established [
23]. Maghfouri et al. [
22] used five existing concrete shrinkage models to compare the shrinkage strain behavior of light weight concrete containing coarse aggregate and found that the EC2 model was the best prediction model to simulate the early shrinkage of light weight aggregate concrete. Bunderen et al. [
24] compared the error between the total shrinkage model and the drying shrinkage model of concrete, and found that EC2 model could also be used to predict the drying shrinkage of concrete. Lai [
25] et al. considered the influence of cementitious paste volume and wet packing density on the total shrinkage of concrete, and reduced the root mean square error of total shrinkage by optimizing the drying shrinkage in the AS3600 shrinkage equation. However, the prediction model of total shrinkage of RATIC containing GHB cannot be found in the literature.
In the present study, the shrinkage performance of RATIC containing GHB was investigated. Considering the influence of RFA and GHB, a time-dependent shrinkage model was proposed to predict the total shrinkage of RATIC. Besides, the mechanical properties, thermal insulation performance and the scanning electron microscope (SEM) of RATIC were also studied.
4. Time-Dependent Shrinkage Model
The total shrinkage strain (
εcs,0) considered in the EC2 [
41] prediction model is the sum of the autogenous shrinkage strain (
εca) and the drying shrinking strain (
εcd). The specific calculation formulas of
εca and
εcd are shown in Equations (1) and (2).
where
t is the concrete age, in days;
εca(∞) is related to cylinder strength (
fck) of concrete at 28 days;
t0 is the concrete age, in days, at the beginning of drying shrinkage;
h0 is the nominal thickness of concrete, and 2 times the ratio of the sectional area to the section circumference of the concrete member is taken;
εcd,0 is the nominal unrestrained drying shrinkage values, which can be found in EN1992 [
14];
kh is the coefficient depending on the notional size
h0.
The time-dependent shrinkage model for RATIC cites the time-dependent factor
kwa [
21], considers the autogenous shrinkage strain amplification factor
kb and drying shrinkage strain amplification factor
ka of RATIC. The specific expression is shown in Equation (3):
where
kb is the coefficient depending on the content of GHB;
kwa and
ka are the coefficients depending on water absorption and elastic modulus of RFA, respectively.
4.1. Shrinkage Model for TIC
In the process of concrete solidification and hardening, GHBs inevitably shrink in volume. Therefore, in Equation (5), an amplification factor
kb is introduced to
εca to modify the variation of shrinkage strain caused by the volume deformation of GHBs in TIC. By regression analysis of the experimental results of TIC, the autogenous shrinkage strain amplification factor
kb can be calculated. However, GHB is similar to the solid air-entraining agent, which increases the air content of TIC, thus increasing the
εcd of TIC. According to the volume difference of concrete mixture [
8], the volume fraction of GHB is about 25%, which can be considered as the air content intake of TIC and RATIC. The ACI-209-92 [
41] model takes into account the influence of concrete air content on the total shrinkage strain of concrete, and gives the correction coefficient
γα, whose specific value is shown in Equation (4):
where
γα is the air content factor,
α is the air content expressed as a percentage.
The total shrinkage (
εcs,b) of TIC modified by the autogenous shrinkage strain amplification factor
kb and the air content correction factor
γα is shown in Equation (5). The autogenous shrinkage strain amplification factor
kb in this experiment was 3.17 by regression analysis.
Figure 11a shows the prediction curve of NAC total shrinkage
εcs based on the EC2 model, and
Figure 11b is the prediction curve of TIC total shrinkage
εcs,b optimized by the GHB influence factor
kb on the basis of the EC2 model. As shown in
Figure 11, the EC2 model can well predict the change trend of the total shrinkage of NAC, but the predicted value of the total shrinkage of TIC differs greatly from the experimental results. However, the model shown in Equation (5) can well predict the variation trend of TIC total shrinkage, indicating that the modification of the EC2 model by introducing
kb is effective.
4.2. Time-Dependent Shrinkage Model for RATIC
Researchers found that even if RFA replaces NFA with 100% replacement ratio, the reduction of autogenous shrinkage strain
εca of recycled concrete is not more than 20% [
17]. Therefore, the autogenous shrinkage model (
εca,b) for TIC (Equation (6)) can be used as the RATIC autogenous shrinkage model, and Equation (7) is the TIC drying shrinkage model (
εcd,b). Due to the delayed effect of RFA on the development of drying shrinkage of RATIC,
εcd,b cannot predict the drying shrinkage strain of RATIC well. Therefore, the model of
εcd,b should be modified.
4.2.1. The Citation of Time-Dependent Factor (kwa)
The drying shrinkage development coefficient (
β(
t,t0)) of ordinary concrete in EC2 is shown in Equation (8). In order to describe the experimental phenomenon that the drying shrinkage development time of recycled concrete is longer than that of ordinary concrete, the researchers put forward the time-dependent factor
kwa [
21]. The modified drying shrinkage development coefficient (
βa(
t,t0)) is shown in Equations (9)–(12).
where
kwa-C and
kwa-F are the influence coefficients of shrinkage development of coarse aggregate and fine aggregate, respectively; ω
a-RFA is the water absorption of RFA;
rRFA is the replacement ratio of RFA;
ωa-NFA and
ωa-NCA are the water absorption of NFA and NCA, respectively.
In order to express the development of the drying shrinkage strain of RATIC, the difference between the predicted value of total shrinkage strain and autogenous shrinkage strain is normalized, that is, (
εcs(
t)-
εca,b(
t))/(
εcs(
tend)-
εca,b(
tend)).
β(
t,t0) of the EC2 model and the modified
βa(
t,t0) were used to fit the normalized experimental values, as shown in
Figure 12a–h. It is observed that the EC2 model with the time-dependent factor
kwa is more helpful to describe the total shrinkage development of RATIC, so it is effective to modify the EC2 model with
kwa.
4.2.2. Drying Shrinkage Strain Amplification Factor ka
According to ACI-209R-92 [
41], when the quality of cement matrix is the same, the drying shrinkage deformation of ordinary concrete is mainly affected by the volume content of aggregate. The difference in the drying shrinkage between TIC and RATIC mainly lies in the type of fine aggregate. The lower elastic modulus of RFAs increase the
εcd of RATIC. In order to obtain the drying shrinkage strain model of recycled concrete, researchers usually put forward the drying shrinkage amplification factor
ka based on the drying shrinkage model of ordinary concrete [
42]. In summary, time-dependent shrinkage model for RATIC is shown in Equation (3).
Based on
kb in 4.1,
γα and
kwa in 4.2.1,
Figure 13 shows the RATIC amplification factor
ka obtained by regression analysis of Equation (3) based on test results,
kv is the empirical value of RFAC amplification factor obtained by Zhang et al. [
21], as shown in Equation (13). Equations (14) and (15) are the fitting formula of
ka of RATIC1 and RATIC2 with the different replacement ratio of RFA, respectively.
where
and
are the volume content of natural aggregate in RAC and NAC,
is the effective volume content of RFA providing constraints in concrete, experience value
[
21].
rRFA1 is the replacement ratio of RFA1;
rRFA2 is the replacement ratio of RFA2.
It can be seen that the regression value of
ka is greater than
kv under the same replacement ratio. This may be because the effective volume of RFA1 and RFA2 are smaller than the experience value of Zhang et al. [
21]. At the same replacement ratio,
ka of RATIC1 is greater than that of RATIC2, which also indicates that the elastic modulus of RFA1 is less than that of RFA2.
4.3. Validation for the Model
In order to verify the accuracy of the model, the calculated value of
ka and
kb were substituted into Equation (13).
Figure 14 shows the predicted results of EC2 model and the modified model based on the EC2 model in this study. It is not difficult to find that the EC2 model optimized by
kwa,
kb,
ka, and
γα can better predict the change of the total shrinkage of RATIC. It can be observed that the time-dependent shrinkage model can predict both the development trend and final total shrinkage strain of RATIC with a maximum difference of 17%.