Effect of Aggregate on the Performance of Fly-Ash-Based Geopolymer Concrete
Abstract
:1. Introduction
2. Background on the Effect of Aggregate on Geopolymer Concrete
3. Experimental Program
3.1. Materials
3.2. Design of Mixtures
3.3. Preparation and Testing of Specimens
4. Results and Discussion
4.1. Effect of AVFs
Effect of AVFs on the Concrete Microstructure
4.2. Effect of CAR
4.3. Effect of MAS
4.4. Effect of FFM
4.5. SEM-EDX Analysis
4.6. Statistical Analysis and Response Surfaces
4.7. Multi-Objective Optimization of Responses
5. Conclusions
- The statistical analysis indicated that the investigated aggregate parameters do have a significant effect on the compressive strength, slump, AVPP, and air content of geopolymer concrete. A wide range of consistencies and compressive strengths can be achieved by controlling these parameters.
- Considering that the geopolymer paste phase nominally provides the same strength, the strength variations in mixtures having different aggregate parameters can mainly be attributed to the variation in the microstructure and ITZ. Moreover, SEM-EDS analysis revealed statistically significant variations in the elemental concentrations of the produced geopolymer paste for different aggregate mixtures. This means that aggregate can also alter the geopolymerization process.
- The most influential aggregate parameter in terms of compressive strength, AVPP, and air content was the AVF, while the FFM had the least effect. Yet, the FFM was the main parameter affecting the geopolymer concrete slump.
- Within limits, a higher fine content seems to increase the homogeneity of the mix and enhance the strength of geopolymer concrete. This is dissimilar to the behavior known for cement concrete, where a higher AVF and larger MAS usually increase the strength of cement concrete. This could be attributed to the strong geopolymer binder and its different rheological properties.
- Unlike the current thinking, in the case of geopolymer concrete, aggregate had a significant effect on the air content of freshly mixed concrete. Additionally, the air content is much higher than that in cement concrete. A possible reason for this is the higher viscosity of the geopolymer concrete mixtures. An inverse relationship was found between the slump and air content, which is opposite to the trend known for cement concrete, where entrained air boosts workability as the small size of the air bubbles brings them to work as a lubricant.
- Aggregate plays a significant role in the AVPP of geopolymer concrete, which confutes the hypothesis that the total porosity of geopolymer concrete is only linked to its water content and that the addition of aggregate will not create additional porosity.
- RSM can provide a time-efficient and reliable statistical method for the design of geopolymer concrete with a counterbalance among the design parameters. Yet, the development of statistical models will need a large database beforehand.
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Source | Sum of Square | df | Mean Square | F-Value | p-Value | VIF | Coefficient Estimate |
---|---|---|---|---|---|---|---|
Model | 76,848.42 | 14 | 5489.17 | 23.71 | <0.0001 | ||
A-AVF | 46,276.88 | 1 | 46,276.88 | 199.93 | <0.0001 | 1.28 | 146.41 |
B-CAR | 3554.17 | 1 | 3554.17 | 15.35 | 0.0020 | 1.28 | −49.77 |
C-MAS | 1778.27 | 1 | 1778.27 | 7.68 | 0.0169 | 1.13 | 13.79 |
D-FFM | 6171.71 | 1 | 6171.71 | 26.66 | 0.0002 | 1.28 | 10.14 |
AB | 400.00 | 1 | 400.00 | 1.73 | 0.2132 | 1.00 | 18.17 |
AC | 30.33 | 1 | 30.33 | 0.1310 | 0.7237 | 1.28 | 5 |
AD | 6.25 | 1 | 6.25 | 0.0270 | 0.8722 | 1.00 | −1.64 |
BC | 0.1476 | 1 | 0.1476 | 0.0006 | 0.9803 | 1.28 | −0.63 |
BD | 6.25 | 1 | 6.25 | 0.0270 | 0.8722 | 1.00 | 0.11 |
CD | 21.73 | 1 | 21.73 | 0.0939 | 0.7645 | 1.28 | 0.63 |
A2 | 1006.66 | 1 | 1006.66 | 4.35 | 0.0591 | 1.27 | 1.39 |
B2 | 0.0486 | 1 | 0.0486 | 0.0002 | 0.9887 | 1.27 | −6.92 |
C2 | 242.16 | 1 | 242.16 | 1.05 | 0.3266 | 1.38 | −0.05 |
D2 | 2800.91 | 1 | 2800.91 | 12.10 | 0.0046 | 1.27 | −3.25 |
Residual | 2777.65 | 12 | 231.47 | ||||
Lack of Fit | 2760.99 | 10 | 276.10 | 33.13 | 0.0296 | ||
Pure Error | 16.67 | 2 | 8.33 |
Source | Sum of Square | df | Mean Square | F-Value | p-Value | VIF | Coefficient Estimate |
---|---|---|---|---|---|---|---|
Model | 164.65 | 14 | 11.76 | 27.27 | <0.0001 | ||
A-AVF | 98.20 | 1 | 98.20 | 227.68 | <0.0001 | 1.28 | 12.3 |
B-CAR | 6.43 | 1 | 6.43 | 14.91 | 0.0023 | 1.28 | 2.29 |
C-MAS | 11.48 | 1 | 11.48 | 26.61 | 0.0002 | 1.13 | 0.59 |
D-FFM | 1.80 | 1 | 1.80 | 4.16 | 0.0064 | 1.28 | 0.81 |
AB | 1.77 | 1 | 1.77 | 4.10 | 0.0657 | 1 | 0.31 |
AC | 1.30 | 1 | 1.30 | 3.01 | 0.1081 | 1.28 | 0.33 |
AD | 0.5852 | 1 | 0.5852 | 1.36 | 0.2667 | 1 | 0.34 |
BC | 0.1038 | 1 | 0.1038 | 0.2406 | 0.6326 | 1.28 | 0.19 |
BD | 0.0064 | 1 | 0.0064 | 0.0148 | 0.9051 | 1 | 0.1 |
CD | 0.0561 | 1 | 0.0561 | 0.1300 | 0.7247 | 1.28 | −0.02 |
A2 | 5.91 | 1 | 5.91 | 13.70 | 0.0030 | 1.27 | 0.07 |
B2 | 11.40 | 1 | 11.40 | 26.43 | 0.0002 | 1.27 | 0.53 |
C2 | 0.5376 | 1 | 0.5376 | 1.25 | 0.2861 | 1.38 | 0.74 |
D2 | 11.25 | 1 | 11.25 | 26.07 | 0.0003 | 1.27 | −0.15 |
Residual | 5.18 | 12 | 0.4313 | ||||
Lack of Fit | 5.17 | 10 | 0.5173 | 397.92 | 0.0025 | ||
Pure Error | 0.0026 | 2 | 0.0013 |
Source | Sum of Square | df | Mean Square | F-Value | p-Value | VIF | Coefficient Estimate |
---|---|---|---|---|---|---|---|
Model | 175.05 | 4 | 43.76 | 56.32 | <0.0001 | ||
A-AVF | 166.43 | 1 | 166.43 | 214.18 | <0.0001 | 1 | 2.63 |
B-CAR | 6.00 | 1 | 6.00 | 7.72 | 0.0109 | 1 | −0.5 |
C-MAS | 1.02 | 1 | 1.02 | 1.32 | 0.1637 | 1 | −0.23 |
D-FFM | 1.60 | 1 | 1.60 | 2.06 | 0.1652 | 1 | −0.26 |
Residual | 17.09 | 22 | 0.7770 | ||||
Lack of Fit | 17.09 | 20 | 0.8544 | 256.32 | 0.0039 | ||
Pure Error | 0.0067 | 2 | 0.0033 | ||||
Cor Total | 192.15 | 26 |
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Al2O3 | Fe2O3 | SiO2 | CaO | MgO | SO3 | P2O5 | K2O | Na2O | LOI |
---|---|---|---|---|---|---|---|---|---|
19.5 | 17.3 | 40.6 | 9.9 | 1.8 | 0.7 | 1.3 | 2.1 | 0.29 | 2.6 |
Designation | Parameter | Low | High |
---|---|---|---|
A | AVF (%) | 60 | 80 |
B | CAR (%) | 45 | 85 |
C | MAS (mm) | 9.5 | 25 |
D | FFM | 2.4 | 3.2 |
Mix Designation | AVF (%) | CAR (%) | MAS (mm) | FFM | Slump (mm) | σ28d (MPa) | Air Content (%) | AVPP (%) |
---|---|---|---|---|---|---|---|---|
GC1 | 75 | 55 | 12.5 | 2.6 | 40 | 30.5 ± 1.6 | 9.9 | 13.3 |
GC2 | 60 | 65 | 16 | 2.8 | 220 | 48.3 ± 0.7 | 1.7 | 10.8 |
GC3 | 70 | 65 | 16 | 2.8 | 145 | 37.6 ± 0.4 | 6.7 | 12.2 |
GC4 | 75 | 75 | 19 | 2.6 | 95 | 18.7 ± 4.1 | 8.6 | 17.1 |
GC5 | 65 | 55 | 12.5 | 2.6 | 140 | 50.1 ± 0.8 | 4.2 | 10.3 |
GC6 | 75 | 55 | 19 | 3 | 75 | 19.6 ± 3.7 | 8.7 | 16.5 |
GC7 | 75 | 55 | 19 | 2.6 | 50 | 23.9 ± 2.4 | 9.2 | 15.4 |
GC8 | 70 | 65 | 9.5 | 2.8 | 110 | 55.6 ± 0.6 | 7.2 | 9.6 |
GC9 | 80 | 65 | 16 | 2.8 | 10 | 16.9 ± 3.7 | 9.8 | 19.2 |
GC10 | 70 | 85 | 16 | 2.8 | 175 | 21.2 ± 3.3 | 7 | 15.4 |
GC11 | 65 | 75 | 12.5 | 3 | 180 | 42.1 ± 3.2 | 2.2 | 12.1 |
GC12 | 65 | 55 | 19 | 3 | 185 | 39.6 ± 2.6 | 3.4 | 11.7 |
GC13 | 65 | 75 | 19 | 3 | 200 | 35.3 ± 3.2 | 1.5 | 11.1 |
GC14 | 65 | 75 | 12.5 | 2.6 | 155 | 46.8 ± 2.9 | 2.6 | 11.1 |
GC15 | 75 | 75 | 12.5 | 2.6 | 70 | 23.4 ± 3.8 | 9 | 15.6 |
GC16 | 65 | 75 | 19 | 2.6 | 170 | 40.2 ± 3.9 | 1.9 | 11.9 |
GC17 | 75 | 75 | 19 | 3 | 110 | 15.5 ± 4.2 | 7.6 | 18.5 |
GC18 | 65 | 55 | 19 | 2.6 | 165 | 44.7 ± 1.1 | 3 | 11.1 |
GC19 | 70 | 65 | 16 | 2.4 | 33 | 22.8 ± 2.7 | 7.1 | 15.9 |
GC20 | 65 | 55 | 12.5 | 3 | 155 | 45.2 ± 0.9 | 3.8 | 11.4 |
GC21 | 75 | 75 | 12.5 | 3 | 90 | 20.8 ± 3.9 | 8.1 | 17.0 |
GC22 | 70 | 65 | 16 | 2.8 | 140 | 37.9 ± 1.0 | 6.8 | 11.5 |
GC23 | 70 | 65 | 16 | 2.8 | 145 | 37.5 ± 1.3 | 6.7 | 12.8 |
GC24 | 70 | 65 | 25 | 2.8 | 155 | 29.9 ± 2.3 | 6.4 | 14.2 |
GC25 | 75 | 55 | 12.5 | 3 | 60 | 24.8 ± 2.2 | 8.5 | 15.1 |
GC26 | 70 | 45 | 16 | 2.8 | 110 | 27.1 ± 2.4 | 8.4 | 14.3 |
GC27 | 70 | 65 | 16 | 3.2 | 160 | 25.2 ± 2.4 | 6.3 | 13.1 |
Mix | Element | Distance (μm) | ||||
---|---|---|---|---|---|---|
20 | 40 | 60 | 80 | 100 | ||
GC8 | Si | 36.7 ± 4.1 | 35.3 ± 3.7 | 34.6 ± 1.8 | 33.8 ± 3.9 | 34 ± 1.9 |
Al | 10.1 ± 1.9 | 10 ± 2.1 | 9.9 ± 3.3 | 10.3 ± 1.9 | 9.8 ± 3.6 | |
Na | 2.4 ± 0.5 | 2.3 ± 0.6 | 2.1 ± 0.5 | 1.9 ± 0.5 | 2.1 ± 0.4 | |
Ca | 5.3 ± 0.9 | 5.1 ± 0.8 | 5.2 ± 1.2 | 4.5 ± 0.8 | 5 ± 0.6 | |
GC24 | Si | 40.9 ± 5.1 | 39.4 ± 6.1 | 34.4 ± 3.7 | 33.1 ± 3.7 | 33.2 ± 2.4 |
Al | 10.8 ± 2.1 | 10.7 ± 2 | 9.9 ± 1.5 | 10 ± 1.8 | 9.9 ± 1.3 | |
Na | 3 ± 0.5 | 2.9 ± 0.5 | 2.3 ± 0.3 | 2 ± 0.5 | 2.3 ± 0.4 | |
Ca | 5.9 ± 1.6 | 5.7 ± 1.5 | 5 ± 1.5 | 4.9 ± 1.4 | 4.8 ± 1.3 | |
GC19 | Si | 37.3 ± 2.7 | 36.9 ± 4.4 | 32.5 ± 3.5 | 33.1 ± 1.6 | 33.5 ± 3.5 |
Al | 13.6 ± 2.4 | 13.3 ± 2.2 | 13.1 ± 1.9 | 13.2 ± 1.8 | 13.4 ± 1.2 | |
Na | 2.5 ± 0.5 | 2.5 ± 0.2 | 2.4 ± 0.4 | 2.3 ± 0.3 | 2.4 ± 0.2 | |
Ca | 6.9 ± 1.2 | 6.8 ± 1.3 | 6.5 ± 1.4 | 6.4 ± 0.9 | 6.2 ± 0.8 | |
GC27 | Si | 41.7 ± 2.2 | 41.4 ± 3.2 | 36.1 ± 2.8 | 32.1 ± 2.1 | 32.2 ± 4 |
Al | 10.1 ± 1.6 | 10.1 ± 1 | 10.3 ± 1.3 | 9.9 ± 1.6 | 10.6 ± 2 | |
Na | 2.4 ± 0.6 | 2.3 ± 0.4 | 1.9 ± 0.5 | 2.1 ± 0.3 | 2.1 ± 0.2 | |
Ca | 5.4 ± 1.2 | 5.4 ± 2.5 | 5.5 ± 1.1 | 5.2 ± 0.8 | 5.3 ± 0.7 |
Source | Sum of Square | df | Mean Square | F-Value | p-Value | VIF | Coefficient Estimate |
---|---|---|---|---|---|---|---|
Model | 3280.82 | 14 | 234.34 | 16.22 | <0.0001 | ||
A-AVF | 1674.72 | 1 | 1674.72 | 115.95 | <0.0001 | 1.28 | −9.467 |
B-CAR | 73.47 | 1 | 73.47 | 5.09 | 0.0436 | 1.28 | −1.983 |
C-MAS | 304.60 | 1 | 304.60 | 21.09 | 0.0006 | 1.13 | −4.196 |
D-FFM | 28.40 | 1 | 28.40 | 1.97 | 0.01862 | 1.28 | −1.233 |
AB | 1.69 | 1 | 1.69 | 0.1170 | 0.7382 | 1.00 | −0.325 |
AC | 0.8339 | 1 | 0.8339 | 0.0577 | 0.8142 | 1.28 | 0.272 |
AD | 0.9025 | 1 | 0.9025 | 0.0625 | 0.8068 | 1.00 | 0.237 |
BC | 0.0053 | 1 | 0.0053 | 0.0004 | 0.9850 | 1.28 | −0.022 |
BD | 1.32 | 1 | 1.32 | 0.0916 | 0.7674 | 1.00 | 0.287 |
CD | 0.1506 | 1 | 0.1506 | 0.0104 | 0.9204 | 1.28 | 0.116 |
A2 | 35.63 | 1 | 35.63 | 2.47 | 0.1422 | 1.27 | −1.303 |
B2 | 244.94 | 1 | 244.94 | 16.96 | 0.0014 | 1.27 | −3.415 |
C2 | 26.96 | 1 | 26.96 | 1.87 | 0.1970 | 1.38 | 1.085 |
D2 | 250.35 | 1 | 250.35 | 17.33 | 0.0013 | 1.27 | −3.453 |
Residual | 173.33 | 12 | 14.44 | ||||
Lack of Fit | 173.24 | 10 | 17.32 | 399.78 | 0.0025 | ||
Pure Error | 0.0867 | 2 | 0.0433 |
Parameters/Responses | Goal | Lower Limit | Upper Limit |
---|---|---|---|
A: AVF (%) | maximize | 65 | 75 |
B: CAR (%) | is in range | 55 | 75 |
C: MAS (mm) | is in range | 12.5 | 19 |
D: FFM | is in range | 2.6 | 3 |
Slump (mm) | is in range | 50 | 100 |
Compressive Strength (MPa) | is in range | 25 | 55 |
Air Content (%) | minimize | 1.5 | 9.9 |
AVPP (%) | minimize | 9.6 | 19.2 |
Mix Designation | AVF (%) | CAR (%) | MAS (mm) | FFM |
---|---|---|---|---|
V1 | 70.6 | 66.3 | 12.5 | 2.7 |
V2 | 72.3 | 58.6 | 12.5 | 2.9 |
V3 | 70 | 74.9 | 25 | 3 |
V4 | 66 | 74 | 25 | 2.7 |
V5 | 66 | 68 | 19 | 2.6 |
V6 | 68 | 57 | 12.5 | 2.8 |
Slump (mm) | σ28d (MPa) | Air Content (%) | AVPP (%) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Exp. | Pred. | %Error | Exp. | Pred. | %Error | Exp. | Pred. | %Error | Exp. | Pred. | %Error |
110 | 112.9 | −2.6 | 42.5 | 43 | −1.2 | 6.6 | 6.4 | 3 | 11.9 | 11.6 | 2.5 |
95 | 102.1 | −7.5 | 35 | 37 | −5.7 | 8.5 | 7.9 | 7.1 | 13.4 | 12.5 | 6.7 |
170 | 185.7 | −9.2 | 19.3 | 21 | −8.8 | 5.2 | 5.7 | −9.6 | 17 | 15.6 | 8.2 |
190 | 201.4 | −6 | 31.6 | 30.7 | 2.8 | 3.4 | 3.6 | −5.9 | 12.8 | 13.5 | −5.5 |
165 | 158.8 | 3.8 | 39.2 | 40.1 | −2.3 | 4 | 3.9 | 2.5 | 11.2 | 11.8 | −5.4 |
140 | 136.3 | 2.6 | 51.1 | 50.3 | 1.6 | 5.4 | 5.5 | −1.9 | 10.7 | 10.4 | 2.8 |
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Malkawi, A.B. Effect of Aggregate on the Performance of Fly-Ash-Based Geopolymer Concrete. Buildings 2023, 13, 769. https://doi.org/10.3390/buildings13030769
Malkawi AB. Effect of Aggregate on the Performance of Fly-Ash-Based Geopolymer Concrete. Buildings. 2023; 13(3):769. https://doi.org/10.3390/buildings13030769
Chicago/Turabian StyleMalkawi, Ahmad B. 2023. "Effect of Aggregate on the Performance of Fly-Ash-Based Geopolymer Concrete" Buildings 13, no. 3: 769. https://doi.org/10.3390/buildings13030769