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Article

Evaluating Prediction Models of Creep and Drying Shrinkage of Self-Consolidating Concrete Containing Supplementary Cementitious Materials/Fillers

Durham School of Architectural Engineering and Construction, College of Engineering, University of Nebraska—Lincoln (UNL), 1110 South 67th Street, Omaha, NE 68182-0816, USA
*
Author to whom correspondence should be addressed.
Appl. Sci. 2021, 11(16), 7345; https://doi.org/10.3390/app11167345
Submission received: 15 July 2021 / Revised: 29 July 2021 / Accepted: 3 August 2021 / Published: 10 August 2021

Abstract

:
Supplementary cementitious materials (SCMs) and fillers play an important role in enhancing the mechanical properties and durability of concrete. SCMs and fillers are commonly used in self-consolidating concrete (SCC) mixtures to also enhance their rheological properties. However, these additives could have significant effects on the viscoelastic properties of concrete. Existing models for predicting creep and drying shrinkage of concrete do not consider the effect of SCM/filler on the predicted values. This study evaluates existing creep and drying shrinkage models, including AASHTO LRFD, ACI209, CEB-FIP MC90-99, B3, and GL2000, for SCC mixtures with different SCMs/fillers. Forty SCC mixtures were proportioned for different cast-in-place bridge components and tested for drying shrinkage. A set of eight SCC mixtures with the highest paste content was tested for creep. Shrinkage and creep test results indicated that AASHTO LRFD provides better creep prediction than the other models for SCC with different SCMs/fillers. Although all models underestimate drying shrinkage of SCC with different SCMs/fillers, the GL2000, CEB-FIP MC90-99, and ACI 209 models provide better prediction than AASHTO LRFD and B3 models. Additionally, SCC mixtures with limestone powder filler exhibited the highest creep, while those with class C fly ash exhibited the highest drying shrinkage.

1. Introduction

Self-consolidating concrete (SCC) is highly flowable, non-segregating concrete that can spread into place, fill the formwork, and encapsulate the reinforcement without any mechanical consolidation [1]. To enhance the stability of SCC, supplementary cementitious materials (SCMs)/fillers are used to improve the viscosity and quality of paste in addition to mechanical and durability properties. The binder composition of SCC, in addition to many other factors, affects its viscoelastic properties, primarily shrinkage and creep. However, existing creep and drying shrinkage prediction models do not account for the effect of SCM/filler type on the predicted values for SCC. Therefore, the objective of this study is to evaluate creep and drying shrinkage prediction models including AASHTO LRFD [2], ACI 209 [3,4], CEB-FIP MC90-99 [5], B3 [6], and GL2000 [7] for SCC mixtures containing different types of SCM/filler.
To achieve this objective, a literature review was conducted to determine the different prediction models for shrinkage and creep of SCC as well as the effect of SCMs/fillers on its viscoelastic properties. Fresh, early-age, and hardened concrete properties were evaluated in a laboratory investigation of forty SCC mixtures proportioned using: two types of coarse aggregate—crushed limestone and natural gravel; three nominal maximum sizes of aggregate (NMSA)—¾, ½, and 3/8 in.; three SCMs and one filler—25% Class F fly ash, 25% Class C fly ash, 30% ground granulated blast-furnace slag (GGBFS), and 20% Class F fly ash +15% limestone powder (LSP); and two levels of slump flow—low (22–26 in.) and high (26–30 in.). All SCC mixtures were air entrained and contained Portland cement Type I/II, which is the common practice in cast-in-place bridge construction. The laboratory tests were conducted according to AASHTO or ASTM methods. Measured properties of SCC mixtures were compared to predicted values using the five prediction models listed earlier.

1.1. Creep Models

Many researchers reported diverse conclusions regarding the viscoelastic properties of SCC due to the variations in the used mixture proportions and testing conditions. Leemann et al. [8] reported that the higher the paste volume of SCC, the higher the creep strain. Turcry et al. [9] reported no difference in creep strain between conventional vibrated concrete (CVC) and SCC, which have similar compressive strength. Heirman et al. [10] reported that the use of LSP as a filler increases creep strain as a result of the slow gain of concrete compressive strength. Kavanaugh [11] reported that the use of low water-cementitious material ratio (w/cm) decreases permeability of SCC mixtures and provides less creep compliance than CVC at all ages.
Kim et al. [12] reported that the AASHTO LRFD (2007) [13] predicts the creep compliance with the highest accuracy among all models. The AASHTO LRFD (2004) [14], ACI 209 and CEB-FIP MC90-99 models provide fairly good predictions of the creep compliance for both CVC and SCC mixtures, while the CEB-FIP MC90, B3, and GL2000 models overestimate the creep compliance. Khayat and Mitchell [15] reported that the CEB-FIP MC90-99 model provides the highest accuracy among all models for predicting creep strains. The ACI 209, AASHTO LRFD (2004), and AASHTO LRFD (2007) models underestimate creep strains at most loading ages, while the GL2000 model overestimates the creep strains. Kavanaugh [12] reported that the AASHTO LRFD (2007) underestimates the creep strain of early-age concrete and overestimates the creep strain of later-age concrete. The CEB-FIP MC90 model accurately predicts creep for both CVC and SCC. The GL 2000 model overestimates the creep strain of both the CVC and SCC mixtures. The ACI 209 model does not accurately predict the creep strain of high-strength concrete mixtures. Heirman et al. [10] reported that the CEB-FIP MC90 model can be used for predicting the creep of SCC mixtures with LSP. Landsberger and Fernandez-Gomez [16] reported that the CEB-FIP MC90, ACI 209, B3 and GL2000 models underestimate the creep strain and the ACI 209 model predicts the creep strain with the least dispersion. Naito et al. [17] reported that the ACI 209 model underestimates the creep coefficient for both CVC and SCC but dramatically for the latter one.

1.2. Drying Shrinkage Models

Higher drying (free) shrinkage of SCC is expected due to the denser matrix of the system, which leads to small capillary voids and allows faster removal of water than large voids [18]. Additionally, using finer cement leads to higher drying shrinkage due to the pore refinement [19]. On the other hand, using fly ash and GGBFS reduces the drying shrinkage of SCC, while the silica fume increases the drying shrinkage when used in binary blends [20,21]. The shrinkage of high early-strength SCC is similar to or less than that of CVC and there is no significant effect of fine aggregate ratio [22]. Naito et al. [17] presented higher viscoelastic properties of SCC than CVC due to the higher fine aggregate volume in SCC.
Khayat and Mitchell [15] reported that all models underestimate the drying shrinkage of SCC; however, the CEB-FIP MC90 model provides the best prediction of drying shrinkage of SCC as it considers the effect of cement type. Landsberger and Fernandez-Gomez [16] reported that the ACI 209R model provides the best prediction of drying shrinkage of SCC, while the CEB-FIP MC90 and GL2000 models substantially underestimate it. Schindler et al. [22] reported that the ACI 209R model accurately predicts the shrinkage of SCC at later ages (56 and 112 days), while the AASHTO LRFD (2004) model underestimates SCC shrinkage at early ages (7 and 14 days) and overestimates it at later ages (56 and 112 days). Naito et al. [17] reported that the ACI 209 model overestimates the drying shrinkage for both SCC and high early strength concrete.

2. Experimental Investigation

2.1. Material Properties

Table 1 and Figure 1 show, respectively, the chemical composition and particle size distribution of the cement type I/II, SCMs (class F fly ash, class C fly ash, GGBFS), and filler (limestone powder) used in the experimental investigation. Two different types of coarse aggregate, crushed limestone and gravel, were used in this investigation. The two types were combined with fine aggregate (natural sand) using three different fine-to-coarse aggregate ratios of 0.45, 0.47, and 0.50. All physical properties and particle size distribution of fine and coarse aggregates are shown in Table 2 and Figure 2, respectively, and the combined aggregate gradations used in SCC mixtures are listed in Table 3. Chemical admixtures included polycarboxylate type high range water reducing admixture (HRWRA) that meets the requirements of ASTM C494 type F admixture; viscosity-modifying admixture (VMA) that meets the requirement of ASTM C494 type S admixture; and air-entraining admixture (AEA) that meets the requirements of ASTM C 260. All materials used in this investigation were obtained from suppliers in the Midwest states of Nebraska, Iowa, and Minnesota.

2.2. Mixture Proportioning

Two groups of SCC mixtures were proportioned: one with crushed limestone coarse aggregate (LS), and the other with gravel (G). Each group had 20 mixtures as follows: 5 mixtures had 25% powder replacement with class C fly ash (C), 5 mixtures had 25% powder replacement with class F fly ash (F), 5 mixtures had 30% powder replacement with GGBFS (S), and 5 mixtures had 35% powder replacement with class F fly ash (20%) and limestone powder (15%) (FLP). Each group had NMSA of 19 mm (¾ in.), 12.5 mm (½ in.), and 9.5 mm (3/8 in.) with two levels of filling ability: high flow (HF), where slump flow is less than 750 mm (30 in.) but greater than or equal to 650 mm (26 in.); and low flow (LF), where slump flow is less than 650 mm (26 in.) but greater than or equal to 550 mm (22 in.). Table 4a,b present the proportions of the forty SCC mixtures containing limestone and gravel aggregate, respectively.

2.3. Workability Testing

All SCC mixtures were proportioned to achieve acceptable levels of filling ability, passing ability and stability (static and dynamic). These properties, except dynamic stability, were assessed using standard test methods to assure the quality of the fresh SCC. Filling ability was evaluated using the slump flow test of the inverted cone in accordance with ASTM C1611. As an indication of the viscosity of the mixtures, the time of reaching 500 mm spread diameter (T50) was also measured. The passing ability of fresh SCC was determined using the J-ring test method according to ASTM C1621. Two parameters were used to describe the passing ability of fresh SCC: (1) the difference between average slump flows (∆D) in restrained (with J-ring) and unrestrained conditions (without J-ring); (2) the difference between the height of concrete patty in the middle of the J-ring, and the average height of the patty at four points around the perimeter of J-ring (∆H) according to AASHTO T 345. The higher the ∆D and ∆H, the higher the probability of blockage when SCC flows around reinforcing bars. The filling capacity of fresh SCC was determined using the caisson test method and according to AASHTO T 349. The measured filling capacity represents the ability of fresh SCC to fill the forms while passing through cross bars. The static stability of SCC was determined using the four standardized test methods: penetration test according to ASTM C1712, column test according to ASTM C1610, visual stability index (VSI) according to ASTM C1611, and hardened visual stability index (HVSI) according to AASHTO PP 58. Dynamic stability was evaluated using the flow-through test according to Lange et al. [23], as no standard test method is available for this property. Additionally, mortar and concrete rheometers were used to characterize the rheological properties of SCC mixtures. Dynamic yield stress and plastic viscosity (i.e., Bingham model parameters) were determined using Brookfield mortar rheometer according to ASTM C1749, while yield torque and slope were determined using IBB concrete rheometer according to Hu and Wang [24].

2.4. Creep Testing

Creep strain was measured according to ASTM C512 for only eight SCC mixtures due to the availability of testing frame and length of test duration. SCC mixtures containing limestone and gravel aggregates with NMSA of 9.5 mm (3/8 in.) were chosen because they have the highest paste volume and, consequently, are expected to have the highest creep strains. A set of two 150 × 300 mm (6 × 12 in.) cylinders was obtained from each mixture and loaded to 40 percent of their 28-day average compressive strength after 28 days from the casting date, and another set of two similar cylinders was unloaded and monitored for deformations due to shrinkage and temperature effects as shown in Figure 3. The average temperature and humidity of the room are 20 degrees Celsius and 38%, respectively.
All cylinders were instrumented using three pairs of detachable mechanical (DEMEC) gauges distributed around the cylinders to measure the longitudinal deformations over 8 in. distance using a dial gauge. The deformations for both sets were recorded every day for a week, then every 7 days for a month, and then every 30 days up to 360 days after time of loading for all mixtures except for mixture with gravel and class C fly ash (G-C) up to 270 due to erroneous readings after 270 days. Average creep strains were calculated by subtracting the average deformation of the unloaded cylinders from those of the loaded cylinders to eliminate shrinkage strain. Additionally, measurements from the three pairs of gauges were compared to check the uniformity of loading. Table 5 lists the five creep prediction models used to estimate the creep coefficient of SCC mixtures. Descriptions of all the model parameters are presented in the notations section at the end of the paper.

2.5. Drying Shrinkage Testing

The drying shrinkage was measured in accordance with ASTM C157 for all forty SCC mixtures as shown in Figure 4. Three concrete prisms that are 76 × 76 × 286 mm 3 × 3 × 11 ¼ in.) from each mixture were moist cured for 7 days and maintained at 50% ± 4% relative humidity and 23 ± 2 °C temperature until 56 days. The readings were made at 3, 7, 14, 28, and 56 days after the curing period. Table 6 lists the five shrinkage prediction models used to estimate the drying shrinkage strains of SCC mixtures and compared then with the measured values. Descriptions of all the model parameters are presented in the notations section at the end of the paper.

3. Results and Discussion

3.1. Workability Properties

Table 7 summarizes the workability properties of all SCC mixtures considered in this investigation. SCC mixtures designed for low filling ability had slump flow between 550 and 650 mm (22 and 26 in.), while those designed for high filling ability had slump flow between 650 and 750 mm (26 and 30 mm). T50 was found to be ≤2 s for all mixtures, which indicates the low viscosity of the tested mixtures. Most mixtures had satisfactory passing ability as ∆D is ≤50 mm (2 in.) and ∆H ≤ 15 mm (0.6 in.). Only a few mixtures, mostly with NMSA = 19 mm (3/4 in.), presented higher probability of blockage. All mixtures had adequate filling capacity more than 70%. Most SCC mixtures had adequate static stability as the penetration values (average of two measurements) were less than 25 mm (1 in.) and column segregation percentage was less than 15%. A few mixtures, mostly with NMSA = 19 mm (3/4 in.), had lower static stability as penetration was equal to 25 mm (1 in.) and column segregation percentage was between 15% and 20%, which might be acceptable for some cast-in-place components. The VSI and HVSI for all SCC mixtures were either 0 or 1, which indicated adequate stability. It should be noted that VSI and HVSI are qualitative test methods that depend on the operator judgment; however, the guidelines presented in test standards were followed to minimize the subjectivity of the assessment. Dynamic stability was measured using the flow-through method for only SCC mixtures with high slump flow. Results indicated that most mixtures had exhibited either high dynamic stability (segregation ≤20%) or moderate dynamic stability (segregation ≤30%). Most SCC mixtures with high slump flow and ¾ in. NMSA had shown poor dynamic stability, making them inappropriate for long or deep components.
Two parameters were measured to evaluate the rheology of SCC mixtures: (1) yield torque, which represents yield stress; (2) slope of the rheological model, which indicates plastic viscosity. The effects of different types of SCM/filler on the rheological properties were not significant. However, the SCC mixtures with larger coarse aggregate (NMSA = 19 mm) represented higher yield torque compared to those with smaller aggregate (NMSA = 9.5 mm). Additionally, SCC mixtures containing gravel aggregate had higher yield torque and lower viscosity than SCC mixtures containing limestone aggregate.

3.2. Creep Coefficient

Figure 5 plots the measured creep strain for tested SCC mixtures, while Figure 6 plots the creep coefficient curves for these mixtures. Creep coefficient represents the ratio of the creep strain to elastic strain at a stress level of 40% of the average 28-day compressive strength. The first readings were recorded at the first day after loading. Statistical analysis was conducted to show whether there was a significant difference between predicted and measured creep coefficient ratios when different types of SCMs/fillers were used. Table 8 shows the results in terms of average and variance of predicted-to-measured creep coefficient ratio. Comparing the results of all models indicates that ACI 209 and AASHTO LRFD models slightly underestimate the creep coefficient, while CEB-FIP MC90-99 and GL2000 models significantly overestimate the creep coefficient.
Figure 7 also plots the measured and predicted creep coefficient using different models regardless of the type of SCM/filler. The slope of the line of best fit for data points presents the level of prediction accuracy of each model (slope of 1.0 is the highest accuracy). The coefficient of determination, R2, represents the goodness of fit (the higher R2, the lower the scatter of the model predictions). This figure indicates that AASHTO LRFD model has the lowest scatter in its predictions, while the GL2000 model has the highest. Table 8 also indicates that in model prediction models, the type of SCM/filler does not have a significant effect on creep coefficient with the exception of mixtures with limestone powder (FLP) that induce higher creep strains, which is in agreement with Heirman [10]. Therefore, it is recommended to use a modification factor greater than 1.0 to adjust creep coefficient prediction for SCC mixtures with limestone powder. The value of this modification factor varies depending on the model used (e.g., 1.2 for AASHTO LRFD model).

3.3. Drying Shrinkage Strains

Table 9 and Table 10 list the results of measured drying shrinkage at different ages in addition to the average compressive strength at 56 days for mixtures with limestone and gravel aggregate, respectively. Compressive strength at different ages was predicted using the ACI 209 equation if the model does not provide a prediction equation. A graphical presentation of the drying shrinkage strains for all 40 mixtures can be found in the Appendices of NCHRP Report 819 [25].
Figure 8 shows that all models underestimate the drying shrinkage; however, GL2000 model provides the closest prediction to measured values, which is in agreement with Mokarem [18]. This model shows higher scatter, as evident in the low R2 value, compared to the other models as reported by Khayat and Mitchell [15]. The B3 model has the lowest prediction accuracy, which is attributed to low sensitivity to compressive strength. Table 11 shows the statistical data for predicted-to-measured drying shrinkage ratios of SCC mixtures with different types of SCM/filler using each of the five prediction models. It indicates that CEB-FIP MC90-99 and GL2000 models do not have a significant difference in shrinkage prediction, and AASHTO LRFD, ACI 209 and B3 models provide approximately similar drying shrinkage predictions.

4. Conclusions

Evaluation of creep and drying shrinkage prediction models for SCC was conducted using forty SCC mixtures containing different types of coarse aggregate, NMSA, levels of filling ability and types of SCM/filler. Five prediction models were compared using measured data and the following conclusions were made:
  • The AASHTO LRFD model provided better prediction for creep coefficient of SCC with lower scattering of data when different types of SCM/filler were used. On the other hand, using limestone powder increased measured creep strains more than predicted and required the use of a modification factor (greater than 1.0) in all models.
  • The AASHTO LRFD and ACI 209 models provided similar predictions of creep coefficient for SCC, while CEB-FIP MC90-99, B3 and GL2000 models overestimated the creep coefficient significantly.
  • Regardless of the type of SCM/filler, CEB-FIP MC90-99 and GL2000 models provided similar prediction of creep coefficient and drying shrinkage of SCC.
  • All models provided lower prediction of drying shrinkage of SCC. However, GL2000, CEB-FIP MC90-99, and ACI 209 models provided better prediction than AASHTO LRFD and B3 models.
  • Modification factors were needed for all drying shrinkage prediction models to account for the higher drying shrinkage of SCC mixtures. The values of these factors depend on the type of SCM/filler used.

Author Contributions

Conceptualization, M.A. and G.M.; methodology, M.A. and G.M.; validation, M.A. and G.M.; formal analysis, M.A.; investigation, M.A. and G.M.; resources, G.M.; data curation, M.A.; writing—original draft preparation, M.A.; writing—review and editing, G.M.; supervision, G.M.; project administration, G.M.; funding acquisition, G.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by National Cooperative Highway Research Program (NCHRP), Project Number 18-16.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data can be found in the Appendices of the NCHRP Report 819. http://www.trb.org/NCHRP/Blurbs/174472.aspx (accessed on 3 August 2021).

Acknowledgments

The authors would like to acknowledge the financial support of National Cooperative Highway Research Program (NCHRP) for the NCHRP 18-16 Project. The research was conducted in collaboration with K. Wang, P. Taylor, and Xuhao Wang at Iowa State University (ISU).

Conflicts of Interest

The authors declare no conflict of interest.

Notations

C d ( t , t o , t c ) Compliance function for drying creep at concrete age t when loading and drying starts at ages to and tc, respectively, B3 model
C o ( t , t o ) Compliance function for basic creep at concrete age t when loading starts at age to, B3 model
E c m t o Mean modulus of elasticity of concrete when loading starts at age to, psi
d = 4V/SAverage thickness of a member, in., ACI 209R-92 model
fMember shape and size constant, days, ACI 209R-92 model
hRelative humidity expressed as a decimal
kcFactor for the effect of the volume-to-surface ratio, AASHTO 2007
kfFactor for the effect of concrete strength, AASHTO 2007
kh, β(h)Correction term for effect of humidity on shrinkage according to B3 and GL2000 models, respectively
khcHumidity factor for creep, AASHTO 2007
khsHumidity factor for shrinkage, AASHTO 2007
ksFactor for the effect of the volume-to-surface ratio, AASHTO 2007
ktdTime development factor, AASHTO 2007
kvsFactor for the effect of the volume-to-surface ratio of the component, AASHTO 2007
q1Inverse of asymptotic elastic modulus, l/psi, B3 model
S(ttc), βs(ttc) or β(ttc)Correction term for effect of time on shrinkage according to B3, CEB MC90, or GL2000 models, respectively
tAge of concrete, days
ttcDuration of drying
tcAge of concrete when drying starts at end of moist curing, days
toAge of concrete at loading, days
V/SVolume-surface ratio, in.
αMember shape and size constant, 1.0, ACI 209R-92 model
βc(tto)Correction term for effect of time on creep coefficient according to CEB MC90 and CEB MC90-99 models
εcsoNotional shrinkage coefficient, in./in., CEB MC90 model
εshu or εsh ͚Notional ultimate shrinkage strain, in./in., ACI 209R-92 and GL2000 models and B3 model, respectively
ΨRatio of fine aggregate to total aggregate by weight expressed as percentage, ACI 209R-92 model
ϕoNotional creep coefficient (dimensionless), CEB MC90-99 and GL2000 models
ϕuUltimate (in time) creep coefficient, ACI 209R-92 model
Φ(tc)The correction term for the effect of drying before loading, 1.0, GL2000 model

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Figure 1. Particle size distribution of cement, SCMs, and filler (25 mm = 1 in.).
Figure 1. Particle size distribution of cement, SCMs, and filler (25 mm = 1 in.).
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Figure 2. Particle size distribution of fine and coarse aggregates (25 mm = 1 in.).
Figure 2. Particle size distribution of fine and coarse aggregates (25 mm = 1 in.).
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Figure 3. Creep test setup and specimen dimensions (25 mm = 1 in.).
Figure 3. Creep test setup and specimen dimensions (25 mm = 1 in.).
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Figure 4. Drying shrinkage specimens.
Figure 4. Drying shrinkage specimens.
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Figure 5. Measured creep strain versus time after loading for all SCC mixtures.
Figure 5. Measured creep strain versus time after loading for all SCC mixtures.
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Figure 6. Measured creep coefficient versus time after loading for all SCC mixtures.
Figure 6. Measured creep coefficient versus time after loading for all SCC mixtures.
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Figure 7. Comparison of measured and predicted creep coefficient by using different models for all mixtures with different types of SCM/filler.
Figure 7. Comparison of measured and predicted creep coefficient by using different models for all mixtures with different types of SCM/filler.
Applsci 11 07345 g007aApplsci 11 07345 g007b
Figure 8. Comparison of measured and predicted drying shrinkage of SCC mixtures using different models.
Figure 8. Comparison of measured and predicted drying shrinkage of SCC mixtures using different models.
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Table 1. Chemical composition of cement, SCMs, and filler.
Table 1. Chemical composition of cement, SCMs, and filler.
Chemical
Component
Type I/II
Cement (%)
Class C
Fly Ash (%)
Class F
Fly Ash (%)
Limestone
Powder (%)
GGBFS (%)
SiO220.1042.4650.871.5631.63
Al2O34.4419.4620.17-11.30
Fe2O33.095.515.270.480.34
SO33.181.200.611.773.30
CaO62.9421.5415.7852.7741.31
MgO2.884.673.190.4810.77
Na2O0.101.420.690.030.19
K2O0.610.681.090.090.36
P2O50.060.840.44-0.02
TiO20.241.481.29-0.56
SrO0.090.320.35-0.04
BaO-0.670.35--
LOI2.220.190.0742.50-
Table 2. Physical properties of aggregates (25 mm = 1 in.).
Table 2. Physical properties of aggregates (25 mm = 1 in.).
PROPERTYLimestone NMSAGravel NMSARiver Sand
19.0 mm12.5 mm9.5 mm19.0 mm12.5 mm9.5 mm
Specific Gravity (SSD)2.662.662.662.742.682.692.62
Absorption %1.31.31.31.11.41.40.5
S/A Ratio0.450.470.500.450.470.50N/A
Combined DRUW (kg/m3)187418901890203519861970N/A
Voids, %29.028.428.423.725.927.0N/A
Table 3. Combined aggregate gradations (25 mm = 1 in.).
Table 3. Combined aggregate gradations (25 mm = 1 in.).
Sieve SizeSand and LimestoneSand and Gravel
S/A RatioS/A Ratio
No.mm0.450.470.500.450.470.50
19.0 mm12.5 mm9.5 mm19.0 mm12.5 mm9.5 mm
1″25.4100.0100.0100.0100.0100.0100.0
3/4″1993.4100.0100.097.8100.0100.0
1/2″12.577.5100.0100.079.795.899.9
3/8″9.561.581.399.467.682.597.0
#44.7548.753.762.448.348.460.9
#82.3646.748.050.843.945.448.8
#161.1837.238.239.234.636.138.5
#300.622.923.623.520.821.723.1
#500.37.87.76.65.76.06.4
#1000.152.62.20.60.50.50.5
#2000------
Table 4. (a) Proportions for SCC mixtures containing limestone aggregate (25 mm = 1 in.; 1000 kg/m3 = 1686 lb/cy; 65 mL/100 kg = 1 oz/cwt). (b) Proportions for SCC mixtures containing gravel aggregate (25 mm = 1 in.; 1000 kg/m3 = 1686 lb/cy; 65 mL/100 kg = 1 oz/cwt).
Table 4. (a) Proportions for SCC mixtures containing limestone aggregate (25 mm = 1 in.; 1000 kg/m3 = 1686 lb/cy; 65 mL/100 kg = 1 oz/cwt). (b) Proportions for SCC mixtures containing gravel aggregate (25 mm = 1 in.; 1000 kg/m3 = 1686 lb/cy; 65 mL/100 kg = 1 oz/cwt).
(a)
Coarse AggregateCrushed Limestone (LS)
SCMs and Fillers25% Class C Fly Ash (C)25% Class F Fly Ash (F)30% GGBFS (S)20% Class F Fly Ash + 15% LSP (FLP)
Filling AbilityLow Flow
(LF)
High Flow
(HF)
Low Flow
(LF)
High Flow
(HF)
Low Flow
(LF)
High Flow
(HF)
Low Flow
(LF)
High Flow
(HF)
NMAS19 mm12.5 mm19 mm12.5 mm9.5 mm19 mm12.5 mm19 mm12.5 mm9.5 mm19 mm12.5 mm19 mm12.5 mm9.5 mm19 mm12.5 mm19 mm12.5 mm9.5 mm
Cement I/II, kg/m3315317337339348315317337339348309311320322331271273289292299
SCM, kg/m31051061121131161051061121131161321331371381428384899092
Filler, kg/m30000000000000006263676769
Coarse Agg., kg/m3915867900853792915867900853792915867908860798915867900853792
Natural Sand, kg/m3749769737757792749769737757792749769743763798749769737757792
Water, kg/m3166175166175181166175166175181166175166175181166175166175181
HRWRA, mL/100 kg780910780104084539026052052084578065011701040975715585780780975
VMA, mL/100 kg003900019501953900001951950001953900
AEA, mL/100 kg9898989898989898989898989898989898989898
Paste Volume %37.038.038.039.040.037.038.038.039.040.037.038.037.538.539.537.038.038.039.040.0
(b)
Coarse AggregateGravel (G)
SCMs and Fillers25% Class C Fly Ash (C)25% Class F Fly Ash (F)30% GGBFS (S)20% Class F Fly Ash + 15% LSP (FLP)
Filling AbilityLow Flow
(LF)
High Flow
(HF)
Low Flow
(LF)
High Flow
(HF)
Low Flow
(LF)
High Flow
(HF)
Low Flow
(LF)
High Flow
(HF)
NMSA19 mm12.5 mm19 mm12.5 mm9.5 mm19 mm12.5 mm19 mm12.5 mm9.5 mm19 mm12.5 mm19 mm12.5 mm9.5 mm19 mm12.5 mm19 mm12.5 mm9.5 mm
Cement I/II, kg/m3293295337339348293295337339348287290320344331261263289292299
SCM, kg/m3989811211311698981121131161231241371471428081899092
Filler, kg/m30000000000000006061676769
Coarse Agg., kg/m3937888908860797937888908860797937888915853804930881908860797
Natural Sand, kg/m3767788743763797767788743763797767788749757804761782743763797
Water, kg/m3166175166175181166175166175181166175166175181166175166175181
HRWRA, mL/100 kg32598585325520455260455325358390325650455488195195390488390
VMA, mL/100 kg001950195001301951950019500001301950
AEA, mL/100 kg9898989898989898989898989898989898989898
Paste Volume %36.037.038.039.040.036.037.038.039.040.036.037.037.539.539.536.537.538.039.040.0
Table 5. Creep coefficient prediction models.
Table 5. Creep coefficient prediction models.
Model Name Creep   Coefficient   Prediction   Equation ,   ϕ (t,to)
AASHTO LRFD [2] 1.9 ks khc kf ktd t i 0.118
ACI 209 [3,4] ( t t o ) Ψ d + ( t t o ) Ψ . ϕu
CEB-FIP MC90-99 [5] ϕ o  βc(tto)
B3 [6] E c m t o ( q 1 + C o ( t , t o ) + C d ( t , t o , t c ) ) 1
GL 2000 [7]Φ ( t c ) [ 2   ( t t o ) 0.3 ( t t o ) 0.3 + 14   + ( 7 t o ) 0.5 ( ( t t o ) ( t t o ) + 7 )   0.5 + 2.5 ( 1 1.086 h 2 ) ( t t o t t o + 0.12 ( v s ) 2 ) 0.5   ]
Table 6. Drying shrinkage strain prediction models.
Table 6. Drying shrinkage strain prediction models.
Model NameDrying Shrinkage Strain Prediction Equation, ε (t,tc)
AASHTO LRFD [2] ks khs kf ktd 0.48 × 10 3
ACI 209 [3,4] ( t t c ) α ƒ + ( t t c ) α .  εshu
CEB-FIP MC90-99 [5]εcso βs(ttc)
B3 [6]εsh ͚ kh S(ttc)
GL 2000 [7] ε s h u  β(h) β(ttc)
Table 7. Workability properties of SCC mixtures (25 mm = 1 in.; 1000 pa = 0.145 psi; 1 N-m = 8.85 lb-in.).
Table 7. Workability properties of SCC mixtures (25 mm = 1 in.; 1000 pa = 0.145 psi; 1 N-m = 8.85 lb-in.).
Coarse Aggregate TypeNMSA (mm)IDSlump FlowJ-RingCaissonPenetrationColumn TechniqueLong TroughStatic StabilityDynamic Yield StressPlastic ViscosityYield TorqueSlope
Dav (mm)T50 (s)VSI∆D (mm)∆H (mm)FC (%)Pd (mm)Seg. (%)Seg. (%)HVSIPaPa-sN-mN-m-s
Limestone19C_LF6541.901021475.5%45.2%7.2%178.71.071.112.95
19F_LF6671.211141479.0%213.2%N/A061.950.931.012.94
19S_LF5781.70831680.6%64.2%N/A153.541.171.143.34
19FLP_LF5721.90381670.2%32.1%N/A049.870.831.022.87
19C_HF6352.0019675.5%30.4%32.0%137.871.730.783.89
19F_HF6861.21641486.1%63.9%35.7%126.80.870.613.32
19S_HF6862.01131378.3%1010.8%10.2%010.731.950.544.78
19FLP_HF6602.01191181.4%613.9%24.3%153.111.080.883.83
12.5C_LF6292.0132580.8%32.0%N/A045.440.971.033.29
12.5F_LF6412.0022491.5%610.1%N/A051.561.070.843.13
12.5S_LF5722.00131481.7%60.0%N/A147.081.3913.96
12.5FLP_LF6602.0161091.2%64.9%N/A040.730.890.842.48
12.5C_HF6602.006371.4%42.1%5.21%129.290.710.652.03
12.5F_HF6732.00381179.6%55.2%39.9%139.51.030.83.08
12.5S_HF7752.0025095.8%35.50%35.6%114.771.080.683.3
12.5FLP_HF6922.016394.2%138.1%23.4%130.880.820.863.11
9.5C_HF6792.00131383.3%43.4%25.5%024.6110.873.35
9.5F_HF7372.0113691.4%20.0%11.9%127.60.880.872.47
9.5S_HF6672.700889.5%143.0%18.3%020.291.730.784.69
9.5FLP_HF7051.706N/A93.7%63.8%N/A033.31.090.72.64
Gravel19C_LF6221.61511386.2%312.7%N/A187.631.893.791.28
19F_LF6221.2132690.2%69.5%N/A150.720.792.711.04
19S_LF5971.90191682.8%39.8%N/A045.161.423.241.5
19FLP_LF5651.4061973.2%017.4%N/A143.50.642.511.17
19C_HF6921.3119691.8%133.7%19.3%138.631.233.010.98
19F_HF7241.2113096.2%1918.9%45.0%118.580.822.630.76
19S_HF7052.3119695.1%2518.4%45.5%113.51.982.151.19
19FLP_HF7111.6132694.1%1619.3%37.6%112.830.572.110.65
12.5C_LF6351.0025387.6%61.0%N/A155.20.772.681.18
12.5F_LF5651.40701971.2%04.8%N/A044.470.622.320.99
12.5S_LF5911.8001382.3%62.7%6.9%131.11.152.721.06
12.5FLP_LF5971.0032689.6%35.1%N/A025.920.591.910.72
12.5C_HF6601.5025694.4%134.1%25.5%025.980.522.170.84
12.5F_HF6601.1013688.4%61.4%4.3%08.360.41.490.79
12.5S_HF6862.3001392.4%612.7%16.8%01.390.681.380.58
12.5FLP_HF6990.9113693.9%139.0%20.9%115.770.461.560.87
9.5C_HF6991.4038693.9%165.1%15.6%018.930.882.610.56
9.5F_HF7301.3119693.5%2511.4%15.8%09.750.741.440.68
9.5S_HF6671.8113689.5%618.1%5.0%000.531.490.53
9.5FLP_HF6861.1019095.2%1612.4%2.4%011.360.692.030.45
Table 8. Statistical analysis results of creep predictions for SCC with different types of SCM/filler.
Table 8. Statistical analysis results of creep predictions for SCC with different types of SCM/filler.
SCM/Filler
Prediction Model
Ratio of Predicted-to-Measured Creep Coefficient
FSCFLPAll Mixtures
Number of Data PointsAverageVarianceNumber of Data PointsAverageVarianceNumber of Data PointsAverageVarianceNumber of Data PointsAverageVarianceAverageVariance
AASHTO LRFD380.870.08190.980.02340.780.09330.690.070.820.07
ACI 209380.980.02191.490.15340.980.04330.690.010.970.09
CEB-FIP MC90-99382.380.75192.090.87341.800.67331.820.142.050.54
B3381.760.11191.830.47342.180.17331.440.171.710.24
GL2000382.190.08193.241.47342.180.21331.550.022.150.50
Table 9. Measured drying shrinkage of SCC mixtures containing limestone aggregate (25 mm = 1 in.; 1 kg/cm2 = 14.2 psi).
Table 9. Measured drying shrinkage of SCC mixtures containing limestone aggregate (25 mm = 1 in.; 1 kg/cm2 = 14.2 psi).
Limestone MixturesMeasured Drying Shrinkage (μ-Strain)Compressive Strength (kg/cm2)
IDNMAS3 Day 7 Day14 Day 28 Day56 Day
LS_F_19_LF19 mm 21526536541048045
LS_F_19_HF19 mm 15022534043046045
LS_F_12.5_LF12.5 mm 3514025542052552
LS_F_12.5_HF12.5 mm27026034540043549
LS_F_9.5_HF9.5 mm 17027036549055548
LS_FLP_19_LF19 mm 15517541042547039
LS_FLP_19_HF19 mm 5537033545053540
LS_FLP_12.5_LF12.5 mm 8017529038045041
LS_FLP_12.5_HF12.5 mm15019027036048545
LS_FLP_9.5_HF9.5 mm 13020036041043043
LS_S_19_LF19 mm 12026038046047545
LS_S_19_HF19 mm 13520525531033544
LS_S_12.5_LF12.5 mm 20537544547057054
LS_S_12.5_HF12.5 mm24029033033540555
LS_S_9.5_HF9.5 mm 20025033547061053
LS_C_19_LF19 mm 16026039549560545
LS_C_19_HF19 mm 12527528534540555
LS_C_12.5_LF12.5 mm 20530040051068061
LS_C_12.5_HF12.5 mm15537041045550056
LS_C_9.5_HF9.5 mm 24535546064075054
Table 10. Measured drying shrinkage of SCC mixtures containing gravel aggregate (25 mm = 1 in.; 1 kg/cm2 = 14.2 psi).
Table 10. Measured drying shrinkage of SCC mixtures containing gravel aggregate (25 mm = 1 in.; 1 kg/cm2 = 14.2 psi).
Gravel MixturesMeasured Drying Shrinkage (μ-Strain)Compressive Strength (kg/cm2)
IDNMAS3 Day 7 Day14 Day 28 Day56 Day
G_F_19_LF19 mm 13522536044049532
G_F_19_HF19 mm 14027538046552536
G_F_12.5_LF12.5 mm 15025533039550530
G_F_12.5_HF12.5 mm22027025532547547
G_F_9.5_HF9.5 mm 13032050558066038
G_FLP_19_LF19 mm 7522034042053540
G_FLP_19_HF19 mm 10529043555560533
G_FLP_12.5_LF12.5 mm 5015534542558533
G_FLP_12.5_HF12.5 mm16025537045560540
G_FLP_9.5_HF9.5 mm 150375515.362672532
G_S_19_LF19 mm 21035536547054037
G_S_19_HF19 mm 16531539043047036
G_S_12.5_LF12.5 mm 17024033542556034
G_S_12.5_HF12.5 mm14022035040549053
G_S_9.5_HF9.5 mm 17539551559068539
G_C_19_LF19 mm 20530040544561040
G_C_19_HF19 mm 17027044551061039
G_C_12.5_LF12.5 mm 22535051562576032
G_C_12.5_HF12.5 mm24026044051067047
G_C_9.5_HF9.5 mm 10538556564073543
LS = crushed limestone G = gravel F = class F fly ash C = class C fly ash S = GGBFS; FLP = class F fly ash plus limestone powder HF = high flow LF = low flow.
Table 11. Statistical analysis results of drying shrinkage predictions for SCC containing different types of SCM/filler.
Table 11. Statistical analysis results of drying shrinkage predictions for SCC containing different types of SCM/filler.
SCM/Filler
Prediction Model
Ratio of Predicted-to-Measured Drying Shrinkage Strain
FFLPSCAll Mixtures
Number of Data PointsAverageVarianceNumber of Data PointsAverageVarianceNumber of Data PointsAverageVarianceNumber of Data PointsAverageVarianceAverageVariance
AASHTO LRFD500.630.07500.680.05500.580.06500.480.030.590.06
ACI 209500.750.08500.770.05500.710.08500.600.040.710.07
GL2000500.990.24501.090.30500.890.05500.740.030.930.17
CEB-FIP MC90-99500.960.22501.080.27500.840.03500.720.030.900.15
B3500.760.13500.820.13500.690.02500.600.020.720.06
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Asaad, M.; Morcous, G. Evaluating Prediction Models of Creep and Drying Shrinkage of Self-Consolidating Concrete Containing Supplementary Cementitious Materials/Fillers. Appl. Sci. 2021, 11, 7345. https://doi.org/10.3390/app11167345

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Asaad M, Morcous G. Evaluating Prediction Models of Creep and Drying Shrinkage of Self-Consolidating Concrete Containing Supplementary Cementitious Materials/Fillers. Applied Sciences. 2021; 11(16):7345. https://doi.org/10.3390/app11167345

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Asaad, Micheal, and George Morcous. 2021. "Evaluating Prediction Models of Creep and Drying Shrinkage of Self-Consolidating Concrete Containing Supplementary Cementitious Materials/Fillers" Applied Sciences 11, no. 16: 7345. https://doi.org/10.3390/app11167345

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