Modelling and multi-objective optimization of the fresh and mechanical properties of self-compacting high volume fly ash ECC (HVFA-ECC) using response surface methodology (RSM)

Abdulkadir, Isyaka; Mohammed, Bashar S.; Liew, M. S.; Wahab, Mohamed Mubarak Abdul

doi:10.1016/j.cscm.2021.e00525

Cited by 23 publications

(16 citation statements)

References 23 publications

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“…Response surface methodology (RSM), which is recognised as a robust optimisation tool, has been extensively used in several previous studies [ 56 , 57 , 58 ]. It utilises statistical and mathematical approaches to accurately evaluate the significant interaction between the independent variables and outputs (dependent variables or responses).…”

Section: Materials and Optimisation Modellingmentioning

confidence: 99%

Optimisation of GBFS, Fly Ash, and Nano-Silica Contents in Alkali-Activated Mortars

et al. 2021

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Although free-cement-based alkali-activated paste, mortar, and concrete have been recognised as sustainable and environmental-friendly materials, a considerable amount of effort is still being channeled to ascertain the best binary or ternary binders that would satisfy the requirements of strength and durability as well as environmental aspects. In this study, the mechanical properties of alkali-activated mortar (AAM) made with binary binders, involving fly ash (FA) and granulated blast-furnace slag (GBFS) as well as bottle glass waste nano-silica powder (BGWNP), were opti-mised using both experimentally and optimisation modelling through three scenarios. In the first scenario, the addition of BGWNP varied from 5% to 20%, while FA and GBFS were kept constant (30:70). In the second and third scenarios, BGWNP (5–20%) was added as the partial replacement of FA and GBFS, separately. The results show that the combination of binary binders (FA and GBFS) and BGWNP increased AAM’s strength compared to that of the control mixture for all scenarios. In addition, the findings also demonstrated that the replacement of FA by BGWNP was the most significant, while the effect of GBFS replacement by BGWNP was less significant. In particular, the highest improvement in compressive strength was recorded when FA, GBFS, and BGWNP were 61.6%, 30%, and 8.4%, respectively. Furthermore, the results of ANOVA (p values < 0.0001 and high F-values) as well as several statistical validation methods (R > 0.9, RAE < 0.1, RSE < 0.013, and RRSE < 0.116) confirmed that all the models were robust, reliable, and significant. Similarly, the data variation was found to be less than 5%, and the difference between the predicted R2 and adj. R2 was very small (<0.2), thus confirming that the proposed non-linear quadratic equations had the capability to predict for further observation. In conclusion, the use of BGWNP in AAM could act as a beneficial and sustainable strategy, not only to address environmental issues (e.g., landfill) but to also enhance strength properties.

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Section: Materials and Optimisation Modellingmentioning

confidence: 99%

Optimisation of GBFS, Fly Ash, and Nano-Silica Contents in Alkali-Activated Mortars

et al. 2021

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“…Moreover, the CR led to increased porosity of the composite, thereby negatively affecting the strength. Furthermore, the soft nature and lower elastic modulus of the CR compared with the fine aggregate particles contributed to the lower strength of the concrete, serving as weak points within the composite, as reported in previous works [2,4,19,27]. Figure 8 displays the 28-day compressive strength of the HVFA-CRC mixes.…”

Section: Hvfa-crc Compressive Strengthmentioning

confidence: 54%

“…Furthermore, the reduction in the higher density cement particles by the FA led to a decrease in the yield stress, allowing for a greater fluidity of the mix. Moreover, the tendency of cement particles to trap water through flocculation is reduced with the FA replacement, as explained by Abdulkadir et al [ 27 ].…”

Section: Resultsmentioning

confidence: 98%

“…For the actual versus predicted graphs, the alignment of the points around the fitted line for all the responses shows how close the predicted responses were to the actual responses. Similarly, in the normal plots of residuals for all the responses, the linear distribution of the data points around the line of fit shows that the models were strong and the error terms were normally distributed [ 27 ].…”

Section: Response Surface Models and Anova Validationmentioning

confidence: 99%

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Utilization of Crumb Rubber and High-Volume Fly Ash in Concrete for Environmental Sustainability: RSM-Based Modeling and Optimization

et al. 2021

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Waste tire and fly ash (FA) are two waste materials whose disposal and rapid rate of accumulation are among the pressing sources of concern and threat to the environment. Although much research exists on the use of these materials in cementitious composites, very little literature is available on the effectiveness of combining them in high volumes for concrete production. This work aimed to utilize crumb rubber (CR) from waste tires as a partial replacement of fine aggregate at 15%, 22.25%, and 30% by volume, and high-volume fly ash (HVFA) replacement of cement at 50%, 60%, and 70% (by weight of cementitious materials) to produce high-volume fly ash–crumb rubber concrete (HVFA–CRC). Using the central composite design (CCD) option of the response surface methodology (RSM), 13 mixes were produced with different combinations and levels of the CR and FA (the input factors) on which the responses of interest (compressive, flexural, and tensile strengths) were experimentally investigated. Furthermore, the composite influence of CR and HVFA on the workability of the concrete was assessed using the slump test. The results showed a decline in the mechanical properties with increasing replacement levels of the CR and HVFA. However, up to 22.25% and 60% of CR and HVFA replacements, respectively, produced a structural HVFA–CRC with a compressive strength of more than 20 MPa at 28 days. Response predictive models were developed and validated using ANOVA at a 95% confidence level. The models had high R2 values ranging from 95.26 to 97.74%. Multi-objective optimization was performed and validated with less than 5% error between the predicted and experimental responses.

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“…Similarly, the quality of the developed models was assessed using the R 2 (coefficient of determination) value as one of the model validation parameters shown in Table 4 . The high R 2 values of 0.9709, 0.7872, 0.9677, and 0.9803 for the CS, FS, TS, and S indicate a high degree of correlation between predicted and experimental results and the adequacy of the models in predicting the responses with high accuracy [ 40 ]. Furthermore, the adequate precision value (Adeq.…”

Section: Rsm Analysesmentioning

confidence: 99%

Mechanical, Microstructural and Drying Shrinkage Properties of NaOH-Pretreated Crumb Rubber Concrete: RSM-Based Modeling and Optimization

et al. 2022

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One of the primary causes of the low mechanical properties of rubberized concrete is the weak bond between crumb rubber (CR) and hardened cement paste. Many CR pretreatment techniques have been researched in an attempt to mitigate this problem. The NaOH pretreatment method is one of the most widely used, although the reported results are inconsistent due to the absence of standardized NaOH pretreatment concentrations and CR replacement levels. This study aims to develop models for predicting the mechanical and shrinkage properties of NaOH-pretreated CR concrete (NaOH-CRC) and conduct multi-objective optimization using response surface methodology (RSM). The RSM generated experimental runs using three levels (0, 5, and 10%) of both NaOH pretreatment concentration and the CR replacement level of fine aggregate by volume as the input factors. At 28 days, the concrete’s compressive, flexural, and tensile strengths (CS, FS, and TS), as well as its drying shrinkage (S), were evaluated as the responses. The results revealed that higher CR replacements led to lower mechanical strengths and higher shrinkage. However, the strength loss and the shrinkage significantly reduced by 22%, 44%, 43%, and 60% for CS, FS, TS, and S, respectively, after the pretreatment. Using field-emission scanning electron microscopy (FESEM), the microstructural investigation indicated a significantly reduced interfacial transition zone (ITZ) with increasing NaOH pretreatment. The developed RSM models were evaluated using ANOVA and found to have high R2 values ranging from 78.7% to 98%. The optimization produced NaOH and CR levels of 10% and 2%, respectively, with high desirability of 71.4%.

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Modelling and multi-objective optimization of the fresh and mechanical properties of self-compacting high volume fly ash ECC (HVFA-ECC) using response surface methodology (RSM)

Cited by 23 publications

References 23 publications

Optimisation of GBFS, Fly Ash, and Nano-Silica Contents in Alkali-Activated Mortars

Optimisation of GBFS, Fly Ash, and Nano-Silica Contents in Alkali-Activated Mortars

Utilization of Crumb Rubber and High-Volume Fly Ash in Concrete for Environmental Sustainability: RSM-Based Modeling and Optimization

Mechanical, Microstructural and Drying Shrinkage Properties of NaOH-Pretreated Crumb Rubber Concrete: RSM-Based Modeling and Optimization

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