Assessing Engineering Behavior of Fly Ash-Based Geopolymer Concrete: Empirical Modeling
Abstract
1. Introduction
2. Materials and Methods
2.1. Materials and Mixtures
2.2. GPC Casting and Testing
2.3. Modeling and Dataset Preparation
3. Results and Discussion
3.1. Compressive Strength
3.2. Splitting Tensile Strength
3.3. Flexural Strength
3.4. Modulus of Elasticity
3.5. Stress–Strain Relationship
4. Conclusions
- For design purposes, the lower prediction intervals are recommended to account for safety margins, as they approximate 70% of the mean strength.
- The effect of FA type (CFA or FFA) is not critical on the splitting and compressive strengths relationship. Consequently, a single model can be used to express their relationships with good accuracy. The same note was observed in the case of flexural and compressive strength relationships.
- Design codes for OPC concrete, including ACI 318, ACI 363, and CEB-FIP, are shown to generally underestimate the splitting tensile strength when applied to FA-GPC. Notably, the CEB-FIP code’s predictions are the closest to the actual values.
- Design codes for OPC concrete, including ACI 318 and AS3600, are shown to generally underestimate the flexural tensile strength when applied to FA-GPC, while the ACI363 code’s predictions tend to overestimate the actual values.
- Existing design models for the modulus of elasticity of OPC concrete in ACI 318, ACI 363, and AS 3600 codes generally overestimate its value. However, for CFA-based GPC, these models can offer reasonably good predictions. Given the differing trends observed between CFA and FFA-based GPC, different models were proposed. Moreover, including density in such models is found to increase the model’s accuracy.
- FA-GPC provides more linear elastic behavior up to the peak stresses indicated by its lower linearity index value. On the other hand, the deformation of GPC was observed to be larger with a higher strain rate at peak stresses and higher ultimate strain as compared to OPC concrete.
- While environmental impact and economic feasibility are important considerations in the broader evaluation of GPC, the present study is focused specifically on developing and validating predictive models for its mechanical performance. Detailed environmental or cost analysis is, therefore, beyond the current scope, but it is recommended for future investigations to complement the findings presented here.
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Composition | CaO | MgO | MnO | ZnO | LOI | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Fly ash | 45.2 | 13.4 | 19.3 | 10.9 | 1.1 | 0.4 | 0.6 | 1.0 | 2.0 | 1.2 | 0.3 | 3.6 |
Designation | Alk/FA | NS/Alk | Si/Al | Na/Al |
---|---|---|---|---|
0.35A0.3N | 0.35 | 0.3 | 3.60 | 0.52 |
0.45A0.3N | 0.45 | 0.3 | 3.67 | 0.65 |
0.55A0.3N | 0.55 | 0.3 | 3.73 | 0.77 |
0.65A0.3N | 0.65 | 0.3 | 3.80 | 0.89 |
0.35A0.45N | 0.35 | 0.45 | 3.71 | 0.51 |
0.45A0.45N | 0.45 | 0.45 | 3.81 | 0.63 |
0.55A0.45N | 0.55 | 0.45 | 3.91 | 0.75 |
0.65A0.45N | 0.65 | 0.45 | 4.01 | 0.87 |
0.35A0.6N | 0.35 | 0.6 | 3.83 | 0.50 |
0.45A0.6N | 0.45 | 0.6 | 3.96 | 0.61 |
0.55A0.6N | 0.55 | 0.6 | 4.09 | 0.73 |
0.65A0.6N | 0.65 | 0.6 | 4.22 | 0.85 |
Item | Mean | Standard Deviation | Minimum | Maximum | Grubbs’ Test | p |
---|---|---|---|---|---|---|
3.59 | 1.10 | 0.94 MPa | 5.92 MPa | 2.40 | 1.000 | |
4.49 | 1.33 | 0.62 MPa | 7.39 MPa | 2.92 | 0.688 | |
24.07 | 8.73 | 1.87 GPa | 47.51 GPa | 2.68 | 1.000 | |
44.26 | 17.43 | 13.5 MPa | 87.4 MPa | 2.47 | 1.000 | |
Peak ε | 0.00252 | 0.00045 | 0.00163 | 0.00363 | 2.5 | 0.948 |
Ultimate ε | 0.00602 | 0.00364 | 0.00230 | 0.01658 | 2.89 | 0.053 |
Strength Grade (MPa) | Shape and Size of Specimen | ||
---|---|---|---|
Cylinder 10 × 20 cm | Cube 10 cm | Cube 15 cm | |
0.901 | 0.825 | 0.915 | |
G20–40 | 0.971 | 0.762 | 0.800 |
0.971 | 0.790 | 0.830 | |
0.971 | 0.819 | 0.860 | |
0.971 | 0.833 | 0.875 | |
0.971 | 0.848 | 0.890 |
Reference | m | n | Reference | m | n |
---|---|---|---|---|---|
CEB-FIP [78] (OPC) | 0.30 | 0.67 | ACI 363 [79] (OPC) | 0.59 | 0.50 |
AS 3600 [80] (OPC) | 0.4 | 0.5 | ACI318 [15] (OPC) | 0.56 | 0.50 |
Ryu et al. [23] (GPC) | 0.17 | 0.75 | Gunasekera et al. [38] (GPC) | 0.45 | 0.50 |
Luan et al. [37] (GPC) | 0.203 | 0.722 | Lee et al. [81] (GPC) | 0.47 | 0.52 |
Dissanayake [82] (GPC) | 0.27 | 0.67 | Jindal et al. [83] (GPC) | 0.426 | 0.519 |
Albitar et al. [16] (GPC) | 0.6 | 0.5 | Thomas et al. [22] (GPC) | 0.40 | 0.778 |
Reference | m | n | Reference | m | n |
---|---|---|---|---|---|
ACI 363 [79] (OPC) | 0.94 | 0.5 | AS 3600 [80] (OPC) | 0.6 | 0.5 |
ACI318 [15] (OPC) | 0.62 | 0.5 | Gunasekera et al. [38] (GPC) | 0.7 | 0.5 |
Albitar et al. [16] (GPC) | 0.75 | 0.5 | Azad et al. [63] (GPC) | 0.293 | 0.765 |
Diaz-Loya et al. [24] (GPC) | 0.69 | 0.5 | Islam R. et al. [48] (GPC) | 0.64 | 0.5 |
Gomaa E. et al. [52] (GPC) | 0.65 | 0.5 | Nath P. et al. [56] (GPC) | 0.93 | 0.5 |
Reference | Model |
---|---|
CEB-FIP [78] (OPC) | is a factor ranging from 0.7 to 1.2 to consider the effect of aggregate type |
ACI318 [15] (OPC) | ) |
ACI 363 [79] (OPC) | |
AS 3600 [80] (OPC) | |
Gunasekera et al. [38] (GPC) | |
Diaz-Loya et al. [24] (GPC) | |
Nath and Sarker [56] (GPC) | |
Lee and Lee (GPC) [85] | |
Hassan and Shariq [44] (GPC) |
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Malkawi, A.B. Assessing Engineering Behavior of Fly Ash-Based Geopolymer Concrete: Empirical Modeling. Infrastructures 2025, 10, 168. https://doi.org/10.3390/infrastructures10070168
Malkawi AB. Assessing Engineering Behavior of Fly Ash-Based Geopolymer Concrete: Empirical Modeling. Infrastructures. 2025; 10(7):168. https://doi.org/10.3390/infrastructures10070168
Chicago/Turabian StyleMalkawi, Ahmad B. 2025. "Assessing Engineering Behavior of Fly Ash-Based Geopolymer Concrete: Empirical Modeling" Infrastructures 10, no. 7: 168. https://doi.org/10.3390/infrastructures10070168
APA StyleMalkawi, A. B. (2025). Assessing Engineering Behavior of Fly Ash-Based Geopolymer Concrete: Empirical Modeling. Infrastructures, 10(7), 168. https://doi.org/10.3390/infrastructures10070168