An AI-driven approach for modeling the compressive strength of sustainable concrete incorporating waste marble as an industrial by-product.

A key goal of environmental policies and circular economy strategies in the construction sector is to convert demolition and industrial wastes into reusable materials. As an industrial by-product, Waste marble (WM), has the potential to replace cement and fine aggregate in concrete which helps with saving natural resources and reducing environmental harm. While many studies have so far investigated the effect of WM on compressive strength (CS), it is undeniable that conducting experimental activities requires time, money, and re-testing with changing materials and conditions. Hence, this study seeks to move from traditional experimental approaches towards artificial intelligence-driven approaches by developing three models-artificial neural network (ANN) and hybrid ANN with ant colony optimization (ACO) and biogeography-based optimization (BBO) to predict the CS of WM concrete. For this purpose, a comprehensive dataset including 1135 data records is employed from the literature. The models' performance is assessed using statistical metrics and error histograms, and a K-fold cross-validation analysis is applied to avoid overfitting problems, emphasize the models' reliable predictive capabilities, and generalize them. The statistical metrics indicated that the ANN-BBO model performed best with a correlation coefficient (R) of 0.9950 and root mean squared error (RMSE) of 1.2017 MPa. Besides, the error distribution results revealed that the ANN-BBO outperformed the ANN and ANN-ACO with a narrower range of errors so that 98% of the predicted data points in the training phase by the ANN-BBO model experienced errors in the range of [-10%, 10%], whereas for the ANN-ACO and ANN models, this percentage was 85% and 79%, respectively. Additionally, the study employed SHapley Additive exPlanations (SHAP) analysis to clarify the impact of input variables on prediction accuracy and found that the specimen's age is the most influential variable. Eventually, to validate the ANN-BBO, a comparison was performed with the results of previous studies' models.

Development of empirical equations between uniaxial compressive strength and point load index: a case study for sandy dolomite.

In this research, the Yuxi section of Central Yunnan Water Diversion Project in Southwest of China, including the tunnel and the traversed sandy dolomite along its route, was selected as the research area, and different sandification degrees classification, including strongly sandy, medium sandy, and weakly sandy, were collected. A comprehensive suite of geotechnical tests was conducted, which included CT scanning, cathodoluminescence, density, porosity, softening coefficient, saturation coefficient, point load test, and uniaxial compressive strength (UCS) test. The Point load index (Is(50)) model for predicting UCS of different sandification degrees dolomite under dry and saturated conditions were analyzed by least square regression, and the empirical equation with correlation coefficient (R2) between 0.7372 and 0.8347 are obtained. To evaluate the performance of the prediction model, some statistical parameters, including MAE, MSE and RMSE, are calculated to evaluate the effectiveness of the empirical equation. The results of this study indicate that the point load test is one of the reliable methods for estimating the UCS of sandy dolomite under both dry and saturated conditions. Furthermore, the results of the point load test on sandy dolomite hold significant reference value for their practical application and promotion in the field, suggesting a broader utility in engineering practice.

Experimental study and numerical simulation of the effect of different fiber types on the basic mechanical properties of shotcrete.

This study analyzed the enhancement effects and mechanisms of steel, glass, and polypropylene fibers on the mechanical properties of concrete, aiming to guide the selection of suitable fiber types and dosages for shotcrete projects. Through laboratory tests, numerical simulations, and field experiments, it investigated the enhancement laws of flexural and compressive strengths of concrete with different dosages of these three fibers. Results showed: (1) After 28 days of curing, flexural strength peaked with 2.0% steel, 1.5% glass, and 2.0% polypropylene fibers, increasing by 118.6%, 42.86%, and 138.6%, respectively, over plain concrete. Compressive strength increased by 2.13%, 10%, and 18.3% at optimal dosages of 0.5%, 1.0%, and 2.0% for steel, glass, and polypropylene fibers. Fiber effects on compressive strength were less significant than on flexural strength, with polypropylene fibers outperforming the others. (2) Based on ABAQUS numerical simulations, microscopic analysis indicates that fibers, due to their high yield capacity, enhance the connections between concrete elements, reduce stress concentration, and improve the mechanical properties of concrete. (3) For shotcrete, 2.0% polypropylene fibers were preferred due to high flexural strength and reduced agglomeration. (4) The optimal dosage was applied to a mine's wet shotcrete support, effectively controlling tunnel deformation. These findings provide practical guidance for shotcrete applications.

Achieving sustainable performance: synergistic effects of nano-silica and recycled expanded polystyrene in lightweight structural concrete.

Lightweight concrete, particularly polystyrene concrete, has been extensively utilized in civil engineering for decades. The incorporation of waste expanded polystyrene (EPS) as a filler material in the production of lightweight concrete presents significant advantages from a circular economy perspective. Prior research indicates that increasing the proportion of lightweight aggregates, such as EPS, typically results in reductions in strength and bulk density. The utilization of substantial amounts of EPS waste in the formulation of structural polystyrene concrete is crucial for advancing sustainable construction practices. This study investigates the effects of varying nano-silica content on the bulk density, compressive strength, flexural strength, splitting tensile strength, and water penetration depth of structural polystyrene concrete. Concrete specimens were prepared by substituting 25%, 50%, 75%, and 100% of sand with EPS waste, while evaluating nano-silica contents of 0.75%, 1%, and 1.25%. The findings reveal that increasing the volume fraction of EPS corresponds to a decrease in the concrete's bulk density. This research provides critical insights into optimizing structural lightweight concrete, thereby promoting advancements in sustainable construction applications.

Geomechanical aspects of stabilizing arsenic trioxide roaster waste in cemented paste backfill at the Giant Mine, Canada.

Giant Mine, an abandoned gold mine near Yellowknife in the Northwest Territories of Canada, generated significant arsenic trioxide roaster waste (ATRW) during its operations, posing a substantial environmental hazard. This study explored the feasibility of stabilizing ATRW by incorporating it into cemented paste backfill (CPB). Using response surface methodology (RSM), CPB samples with varying mixing ratios were analyzed to identify key parameters influencing strength. Unconfined compressive strength (UCS) tests assessed physical stability, while saturated hydraulic conductivity and computed tomography (CT) analyses examined the microstructure of the CPB. The results revealed that CPB samples prepared with general use (GU) cement exhibited significantly higher strength than those with a GU and lime kiln dust (LKD) mixture. Binder and solid contents were identified as the most critical factors influencing UCS, with binder content having a more pronounced influence. Curing time was found to be non-significant. Higher binder and solid contents correlated with higher UCS values in the CPB samples. The addition of 10% wt. ATRW reduced the UCS by over 30%, particularly in samples with lower binder and solid contents. Although microstructure differences were not evident in saturated hydraulic conductivity tests, CT scans showed increased formation of high-density arsenic-containing materials in samples with the highest UCS, especially those using GU binder. These findings suggest that optimizing binder and solid contents is crucial for enhancing CPB strength and effectively stabilizing ATRW.

Mix proportion design and carbon emission assessment of high strength geopolymer concrete based on ternary solid waste.

To achieve dual optimization of the mechanical properties and environmental impacts of geopolymer concrete (GPC), this study proposes a high-strength geopolymer concrete (HSGPC) without coarse aggregate. The mix proportion of HSGPC was optimized using the response surface methodology, targeting compressive strength and splitting tensile strength to determine the optimal mix. Additionally, the carbon emission impact of HSGPC was assessed and compared with ordinary Portland cement concrete, ultra-high-performance concrete, and reactive powder concrete. The results indicate that the optimal mix proportion for HSGPC includes 15% fly ash content, 10.30% silica fume content, alkali activator ratio of 2.5, and a NaOH molar concentration of 10 M. Simultaneously, the carbon emissions of HSGPC are reduced by about 30% compared to ordinary Portland cement concrete. Compared to ultra-high-performance concrete and reactive powder concrete of the same strength, the production of HSGPC respectively reduces carbon emissions by 59.87% and 68.24%. This study not only provides valuable technical support for the practical application of GPC in engineering but also holds significant implications for promoting sustainable development in the construction industry.

Evaluation of compressive and diametral tensile strength of novel bioactive material with conventional glass ionomer cement and silver amalgam: An in vitro study.

Aim: The aim of this study was to compare the compressive and tensile strength of two different brands of conventional glass ionomer cement (GIC), with new zirconia-reinforced GIC and silver amalgam. Materials and Methodology: Eighty specimens with 20 samples in each group were prepared (Group 1-Fuji IX GIC, Group 2-FX-II Shofu GIC, Group 3-Amalgam, and Group 4-Zirconia-reinforced glass ionomer [Zirconomer]) for compressive strength (CS) using cylinder molds with dimensions 6.0 mm diameter × 12.0 mm height. Eighty specimens using cylinder molds with dimensions 6.0 mm diameter × 3.0 mm height were prepared for testing diametral tensile strength (DTS). CS test was carried out using Micro Universal Testing Machine (Mecmesin, PPT Group, UK) having a crosshead speed of 1.0 mm/min. DTS was determined using Instron universal testing machine at a crosshead speed of 1.0 mm/min. The data were submitted to two-way analysis of varianceand post hoc Tukey tests (alpha = 0.05). The mean CS value was more for Group III (256.2), followed by Group IV (181.2 Megapascals [MPa]), Group II (129.8 MPa), and the least was Group I (117.9 MPa). Result: The mean DTS value was high in Group III (73.7 MPa), followed by Group IV (58.0 MPa), Group II (36.0 MPa), and the least was seen in Group I (23.2 MPa). Conclusion: It can be concluded that although Zirconomer has mechanical properties greater than that of unmodified GICs, additional studies are essential to evaluate its long-time ability.

Dynamic mechanical characteristics of coal in front of the mining face under different mining layouts.

To study the dynamic mechanical characteristics of coal in the area affected by mining in front of the mining face under different mining methods, an improved split Hopkinson pressure bar (SHPB) was used to apply different static loads to different positions. Then, dynamic mechanical tests were conducted on coal at different positions on the mining face, analyzing the dynamic response under strong dynamic load disturbances, under three different mining layouts. Within the range of static water pressure to the peak support pressure, the dynamic strength of coal gradually increases with increasing distance from the mining face. The dynamic strength is the smallest at the peak support pressure stress, and under strong external disturbances, instability and failure are increasingly likely to occur at the peak stress. Under the same loading rate conditions, the dynamic strength of the peak stress in coal is as follows: Protective coal-seam mining (PCM) > Top-coal caving mining (TCM) > Nonpillar mining (NM).

Mixed-Curve Model for Evaluating the Carbonation Depth of Concrete at Different Ages.

To accurately quantify the variation in concrete carbonation depth, selecting an appropriate mathematical curve model is crucial. Currently prevalent models, such as the Fick model and exponential models, confront limitations in prediction accuracy and range of application. Given that a single curve model struggles to precisely describe the pattern of concrete carbonation, this work introduces a mixed-curve-based prediction model for carbonation depth, effectively integrating the Fick model with a hyperbolic model. Compared to the Fick model, the additional term in the mixed-curve model can be viewed as a reasonable correction to better adapt to the complex and varied conditions of concrete carbonation. This hybrid model transcends the limitations of individual models, enhancing fitting precision and broadening the scope of applicability. The new model boasts a concise structure with only two fitting parameters, facilitating ease of application. To validate its superiority, rigorous comparisons were conducted between the proposed model and existing ones, leveraging experimental data from 10 distinct concrete carbonation scenarios. By comparing the average error, standard deviation, and coefficient of determination across these cases, the new model demonstrates a clear advantage over the Fick model and the exponential model. In terms of fitting errors, the average error and standard deviation of the new model are notably lower than those of the other two models. In terms of the coefficient of determination, the values achieved by the new model in all examples are closer to 1 than those of both the Fick model and the exponential model, underscoring the new model's superior fitting quality and remarkable stability. This research indicates that the combined model presented in this paper holds promising prospects for widespread application in predicting concrete carbonation depth.

Hydration and Mechanical Properties of High-Volume Fly Ash Cement under Different Curing Temperatures.

This study aimed to investigate the effects of different curing temperatures on the hydration and mechanical properties of high-volume fly ash (HVFA) concrete. The key variables were curing temperature (13 °C, 23 °C, 43 °C) and fly ash (FA) content (0%, 35%, 55%). The hydration characteristics of HVFA cement were examined by evaluating the setting time and heat of hydration under different curing temperatures. The mechanical properties of HVFA concrete were analyzed by preparing concrete specimens at various curing temperatures and measuring the compressive strength at 7, 28, 56, and 91 days. The results indicated that concrete with high FA content was more sensitive to curing temperature compared to ordinary Portland cement.

Predicting the Compressive Strength of Sustainable Portland Cement-Fly Ash Mortar Using Explainable Boosting Machine Learning Techniques.

Unconfined compressive strength (UCS) is a critical property for assessing the engineering performances of sustainable materials, such as cement-fly ash mortar (CFAM), in the design of construction engineering projects. The experimental determination of UCS is time-consuming and expensive. Therefore, the present study aims to model the UCS of CFAM with boosting machine learning methods. First, an extensive database consisting of 395 experimental data points derived from the literature was developed. Then, three typical boosting machine learning models were employed to model the UCS based on the database, including gradient boosting regressor (GBR), light gradient boosting machine (LGBM), and Ada-Boost regressor (ABR). Additionally, the importance of different input parameters was quantitatively analyzed using the SHapley Additive exPlanations (SHAP) approach. Finally, the best boosting machine learning model's prediction accuracy was compared to ten other commonly used machine learning models. The results indicate that the GBR model outperformed the LGBM and ABR models in predicting the UCS of the CFAM. The GBR model demonstrated significant accuracy, with no significant difference between the measured and predicted UCS values. The SHAP interpretations revealed that the curing time (T) was the most critical feature influencing the UCS values. At the same time, the chemical composition of the fly ash, particularly Al2O3, was more influential than the fly-ash dosage (FAD) or water-to-binder ratio (W/B) in determining the UCS values. Overall, this study demonstrates that SHAP boosting machine learning technology can be a useful tool for modeling and predicting UCS values of CFAM with good accuracy. It could also be helpful for CFAM design by saving time and costs on experimental tests.

Advanced Predictive Modeling of Concrete Compressive Strength and Slump Characteristics: A Comparative Evaluation of BPNN, SVM, and RF Models Optimized via PSO.

This study presents the development of predictive models for concrete performance, specifically targeting the compressive strength and slump value, utilizing the quantities of individual raw materials in the concrete mix design as input variables. Three distinct machine learning approaches-Backpropagation Neural Network (BPNN), Support Vector Machine (SVM), and Random Forest (RF)-were employed to establish the prediction models independently. In the model construction process, the Particle Swarm Optimization (PSO) algorithm was integrated with cross-validation to fine-tune the hyperparameters of each model, ensuring optimal performance. Following the completion of training and modeling, a comprehensive comparison of the predictive accuracy among the three models was conducted, with the aim of selecting the most suitable model for incorporation into an optimized objective function. The findings reveal that among the chosen machine learning techniques, BPNN exhibited superior predictive capabilities for the compressive strength of concrete. Specifically, in the validation set, BPNN achieved a high correlation coefficient (R) of 0.9531 between the predicted and actual outputs, accompanied by a low Root Mean Square Error (RMSE) of 4.2568 and a Mean Absolute Error (MAE) of 2.6627, indicating a precise and reliable prediction. Conversely, for the prediction of the concrete slump value, RF outperformed the other two models, demonstrating a correlation coefficient (R) of 0.8986, an RMSE of 9.4906, and an MAE of 5.5034 in the validation set. This underscores the effectiveness of RF in capturing the complexity and variability inherent in slump behavior. Overall, this research highlights the potential of integrating advanced machine learning algorithms with optimization techniques for enhancing the accuracy and efficiency of concrete performance predictions. The identified optimal models, BPNN for compressive strength and RF for slump, can serve as valuable tools for engineers and researchers in the field of construction materials, facilitating the design of concrete mixes tailored to specific performance requirements.

Effect of Phosphoric Acid and Soluble Phosphate on the Properties of Magnesium Oxychloride Cement.

This study investigates the effects of phosphoric acid (H3PO4), potassium dihydrogen phosphate (KH2PO4) and sodium dihydrogen phosphate (NaH2PO4) admixtures on the setting time, compressive strength and water resistance of magnesium oxychloride cement (MOC). MOC samples incorporating different admixtures are prepared, and their hydration products and microstructures are studied via X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results indicate that the addition of H3PO4, KH2PO4 and NaH2PO4 reduces the initial and final setting times and decreases the compressive strength. However, the compressive strength of MOC is higher than 30.00 MPa with the addition of 2.0 wt.% phosphoric acid and its phosphate after 14 days of air curing. The water resistance of modified MOC slurries is significantly improved. The softening coefficient of MOC with 2.0 wt.% H3PO4 is 1.2 after 14 days of water immersion, which is 3.44 times higher than that of the neat MOC. The enhancement in water resistance is attributed to the formation of amorphous gel facilitated by H3PO4, KH2PO4 and NaH2PO4. Furthermore, the improvement in water resistance is manifested as H3PO4 > KH2PO4 > NaH2PO4.

Hydration and Mechanical Properties of Cement Kiln Dust-Blended Cement Composite.

This study aims to investigate the effects of cement kiln dust (CKD) on the hydration reactions and mechanical properties of cement, and to evaluate its potential for use as a supplementary cementitious material (SCM). The key variables are the CKD type and the replacement ratio. Cement paste and mortar specimens containing CKD were prepared to examine their effects on the cement hydration and mechanical properties. The effect on hydration was assessed using setting time measurements, heat of hydration tests, and thermogravimetric analyses (TG). In addition, compressive strength tests were conducted to evaluate the effect of CKD on the mechanical properties of the cement. The results indicated that CKD promoted early-age cement hydration and enhanced the early-age mechanical properties. However, owing to its lack of pozzolanic reactivity, it did not significantly affect long-term hydration. Given that the effects of CKD vary slightly depending on its chemical composition, careful consideration of CKD's properties suggests that its potential use as an SCM is promising.

Study on the Compressive and Tensile Properties of Latex-Modified Cement Stone.

The integrity of wellbores is essential for the safe and efficient operation of drilling activities. Cement plays a critical role in this process, serving as a primary barrier that isolates the casing from the surrounding formation. To ensure the proper application of cement in wells, a thorough understanding of its mechanical properties is essential. Latex-modified cement stone (LMCS) offers significant advantages due to its anti-channeling, anti-corrosion, and mechanical characteristics. This study examined the mechanical properties of LMCS through uniaxial and triaxial compression and Brazilian splitting tests. Under uniaxial compression, the elastic modulus, Poisson's ratio, and compressive strength of LMCS were found to range from 4.08 to 8.29 GPa, 0.05 to 0.46, and 15.82 to 22.21 MPa, respectively. In triaxial compression tests with confining pressures of 2 MPa, 4 MPa, 6 MPa, 8 MPa, and 10 MPa, the elastic modulus ranged from 4.48 to 6.87 GPa, Poisson's ratio from 0.05 to 0.16, and compressive strength from 27.38 to 39.58 MPa. The tensile strength of LMCS ranged from 2.34 to 3.72 MPa. Moreover, the compressive strength of LMCS increased with confining pressure, showing enhanced resistance to failure due to the confining effect. However, the rate of increase gradually diminished. Strength criteria for LMCS, including Mohr-Coulomb and Drucker-Prager parameters, were derived from the triaxial compression tests. These strength criteria parameters provide a useful reference for developing the constitutive model of LMCS and for simulating triaxial compression conditions. The findings of this research offer valuable insights that can guide the construction of oil and gas wells.

Compressive Strength and Chloride Ion Penetration Resistance of GGBFS-Based Alkali-Activated Composites Containing Ferronickel Slag Aggregates.

Various studies have reported the use of alkali-activated composites to enable sustainable development in the construction industry as these composites eliminate the need for cement. However, few studies have used ferronickel slag aggregates (FSAs) as an aggregate material for alkali-activated composites. Alkali-activated composites are environmentally friendly and sustainable construction materials that can reduce carbon dioxide emissions from cement production, which accounts for 7% of global carbon emissions. In the construction industry, various research was conducted to improve the performance of alkali-activated composites, such as changing the binder, alkali activator, or aggregate. However, research on the application of ferronickel slag aggregate as an aggregate in alkali-activated composites is still insufficient. In addition, the effect of ferronickel slag aggregate on the performance of alkali-activated composites when using calcium-based or sodium-based alkali activators has not been reported yet. Thus, this study prepared ground granulated blast-furnace slag-based alkali-activated composites with 0, 10, 20, and 30% FSA as natural fine aggregate substitutes. Then, the fluidity, micro-hydration heat, compressive strength properties, and resistance to chloride ion penetration of the alkali-activated composite were evaluated. The test results showed that the maximum temperature of the CF10, CF20, and CF30 samples with FSA was 35.4-36.4 °C, which is 3.8-6.7% higher than that of the CF00 sample. The 7 d compressive strength of the sample prepared with CaO was higher than that of the sample prepared with Na2SiO3. Nevertheless, the 28 d compressive strength of the NF20 sample with Na2SiO3 and 20% FSA was the highest, with a value of approximately 55.0 MPa. After 7 d, the total charge passing through the sample with Na2SiO3 was approximately 1.79-2.24 times higher than that of the sample with CaO. Moreover, the total charge decreased with increasing FSA content.

Stress-Strain Behavior and Strength Development of High-Amount Phosphogypsum-Based Sustainable Cementitious Materials.

Phosphogypsum is a common industrial solid waste that faces the challenges of high stockpiling and low utilization rates. This study focuses on the mechanical properties and internal characteristics of cementitious materials with a high phosphogypsum content. Specifically, we examined the effects of varying amounts of ground granulated blast furnace slag (5-28%), fly ash (5-20%), and hydrated lime (0.5-2%) on the stress-strain curve, unconfined uniaxial compressive strength, and elastic modulus (E50) of these materials. The test results indicate that increasing the ground granulated blast furnace slag content can significantly enhance the mechanical properties of phosphogypsum-based cementitious materials. Additionally, increasing the fly ash content can have a similar beneficial effect with an appropriate amount of hydrated lime. Furthermore, microscopic analysis of the cementitious materials using a scanning electron microscope revealed that the high sulfate content in phosphogypsum leads to the formation of calcium aluminate as the main product. Concurrently, a continuous reaction of the raw materials contributes to the strength development of the cementitious materials over time. The results could provide a novel method for improving the reusing phosphogypsum amount in civil engineering materials.

Root canal irrigants effect on the compressive strength and calcium ion release of Biodentine.

Compressive strength and calcium ion release are integral properties of Biodentine for its enhanced efficiency. The present study evaluated the effects of Dual Rinse HEDP (DR HEDP), ethylenediaminetetraacetic acid (EDTA) and sodium hypochlorite (NaOCl) on the calcium ion release and compressive strength of Biodentine. Eighty Biodentine specimens were moulded and randomly divided into four groups (n = 20). Samples in group 1 were treated with 17 % EDTA; group 2 with DR HEDP; group 3 with 2.5 % NaOCl; and group 4 with distilled water. Samples were immersed in 10 mL of the test solutions for 1 min. The mean concentration of the calcium ion released was measured using atomic absorption spectrophotometry. The remaining 40 samples were tested for their compressive strength. Significant differences were determined among all the irrigants tested for calcium ion release and compressive strength. Samples treated with NaOCl had the lowest calcium ion release, while samples treated with 17 % EDTA had the largest calcium ions. No significant differences were measured between DR HEDP or distilled water. For compressive strength, samples treated with 2.5 % NaOCl had the lowest strength, while the highest values were obtained with distilled water. There was a significant difference between DR HEDP and EDTA, in which EDTA reduced the compressive strength significantly more than DR HEDP. DR HEDP had less detrimental effect on the calcium ion release and compressive strength of Biodentine.

Sustainable quaternary binders made from metallurgical wastes of northeast Mexico: strength, hydration products, and durability.

In this research, four industrial wastes were used for up to 80% as supplementary cementitious materials (SCMs) in cement mortar systems: ground granulated blast furnace slag, electric arc furnace slag, basic oxygen furnace slag, and waste limestone powder. Quaternary cementitious blends were prepared and studied for up to 120 days. Workability, compressive strength, durability, microstructures, and sustainability studies were performed and compared with Portland cement references. Results showed that more than 30 MPa in compressive strength can be achieved by > 50% replacement with SCMs; only 9% below the reference. Neither H2SO4 nor MgSO4 attacks resulted in critical damages; nevertheless, curing under NaCl solution showed detrimental behavior. C-S-H with a low Ca/Si ratio was identified in the mortars as the main hydration product, possibly intermixed with stratlingite, C-A-S-H and/or hydrotalcite. Environmental impact for the blended cements was determined as the CO2eq. factor from a simple life cycle assessment. The embodied greenhouse gasses varied in 260.2-541.4 kg CO2eq./ton of binder depending on the formulation. This was 40-70% less than Portland cement (922.6 kg CO2eq./ton). The production of the raw materials dominated the polluting emissions, while freight, grinding, and sieving had little environmental impact.

Influence of alkaline activators on mechanical properties of environmentally friendly geopolymer concrete under different curing regimes.

Previous studies highlighted the significance of tailoring alkaline activators (AA) to specific fly ash (FA) sources for optimal properties of geopolymer concrete (GPC). This study examines the influence of various AA's properties on mechanical properties and microstructures of local low-calcium FA-based GPC under varying curing conditions. A comprehensive investigation consists of several factors such as NaOH molarities (10 M, 12 M, 14 M, 16 M), Na 2 SiO 3 / N a O H ratios (1.5, 2.0, 2.5) and A A / F A ratios (0.5, 0.6). The results reveal a complex relationship, demonstrating that NaOH molarity positively influences compressive strength up to a threshold of 14 M, beyond which an adverse effect was observed while, the flexural strength was increased up to 16 M. Moreover, the study highlights the complex relationship between Na 2 SiO 3 / N a O H ratios and mechanical strengths. Notably, these properties exhibited an increase as the ratio rose up to 2.0, but a subsequent decrease was observed when the ratio reached 2.5. Moreover, proposed regression equations predict the compressive and flexural strengths of both ambient-cured GPC and heat-cured GPC with marginal statistical errors. The optimal GPC mix exhibited 49% lower embodied CO 2 emissions than the corresponding OPC concrete. GPC has higher cost, but it exhibited lower cost-to-strength ratio compared to OPC concrete.