Mechanical strength optimization and simulation of cement kiln dust concrete using extreme vertex design method

Alaneme, George Uwadiegwu; Attah, Imoh Christopher; Mbadike, Elvis Michael; Dimonyeka, M. U.; Usanga, Idorenyin Ndarake; Nwankwo, Henry Frank

doi:10.1007/s41204-021-00175-4

Cited by 23 publications

(11 citation statements)

References 63 publications

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“…Table 12 presents the generated regression model summary with a standard regression error of 1.613 and a coe cient of determination of 99.86%, which indicates very good prediction performance as it represents the variation (%) in the response explicated by the developed regression model presented in Table 13. Figure 10 presents the multiple linear regression (MLR) residual plot that ensures that the regression model assumptions are satis ed; the statistical plots show the normal probability plot of the residuals in percent, the tted value vs. residuals ranging from −1.0 to 1.0, frequency distribution histogram of the residuals and the residuals against the observation order (%) [65,66].…”

Section: Regression Analysismentioning

confidence: 99%

Assessment of Mechanical Properties of Soil-Lime-Crude Oil-Contaminated Soil Blend Using Regression Model for Sustainable Pavement Foundation Construction

Ezeokpube

Ahaneku

Alaneme

et al. 2022

Advances in Materials Science and Engineering

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Oil pollution causes deterioration of the physical, chemical, mechanical, and geotechnical characteristics of affected soil leading to loss of soil productivity for engineering purposes. Different stabilization methods serve as a remedy for such soil to regain its loss engineering properties. This study was concerned with the utilization of lime to stabilize crude oil contaminated soil and to investigate its efficacy for soil stabilization. The study also focused on determining the geotechnical properties of crude oil contamination and matching the result with standard specifications established for engineering works. Hydrated lime, expansive clayey soil, contaminated soil, and potable water were the materials used for the experimental investigation. The contaminated soil was treated with 6.5% lime and 0–20% crude oil contaminated materials obtained from oil exploration sites in North-Eastern Nigeria and per standard test method for laboratory evaluation of consistency limits, compaction properties, California bearing ratio (CBR), and microstructural and mineralogical assessments. The experimental results obtained were further tested statistically through one-way ANOVA and F-statistics to establish the source of variation for the geotechnical properties, while multiple linear regression and correlation statistics helped draw the connection between the consistency limits, compaction, and CBR properties of the soil-lime-COCM blend. Results indicated a coefficient of determination of 99.86. The contaminated soil materials were found to show optimal performance at a 5% ratio and 6.5% of lime for civil construction purposes.

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Section: Regression Analysismentioning

confidence: 99%

Assessment of Mechanical Properties of Soil-Lime-Crude Oil-Contaminated Soil Blend Using Regression Model for Sustainable Pavement Foundation Construction

Ezeokpube

Ahaneku

Alaneme

et al. 2022

Advances in Materials Science and Engineering

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“…Using Student’s t -test and ANOVA, the adequacy of the constructed Scheffe’s model was tested using the experiment’s control points. Figure 11 illustrates the experimental or actual control laboratory flexural responses, as well as the values obtained from the developed Scheffe’s simplex-lattice quadratic model [ 72 ].…”

Section: Results Discussion and Analysismentioning

confidence: 99%

Scheffe’s Simplex Optimization of Flexural Strength of Quarry Dust and Sawdust Ash Pervious Concrete for Sustainable Pavement Construction

et al. 2023

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Pervious concrete provides a tailored surface course with high permeability properties which permit the easy flow of water through a larger interconnected porous structure to prevent flooding hazards. This paper reports the modeling of the flexural properties of quarry dust (QD) and sawdust ash (SDA) blended green pervious concrete for sustainable road pavement construction using Scheffe’s (5,2) optimization approach. The simplex mixture design method was adapted to formulate the mixture proportion to eliminate the set-backs encountered in empirical or trials and the error design approach, which consume more time and resources to design with experimental runs required to evaluate the response function. For the laboratory evaluation exercise, a maximum flexural strength of 3.703 N/mm2 was obtained with a mix proportion of 0.435:0.95:0.1:1.55:0.05 for water, cement, QD, coarse aggregate and SDA, respectively. Moreover, the minimal flexural strength response of 2.504 N/mm2 was obtained with a mix ratio of 0.6:0.75:0.3:4.1:0.25 for water, cement, QD, coarse aggregate and SDA, respectively. The test of the appropriateness of the developed model was statistically verified using the Student’ t-test and an analysis of variance (ANOVA), and was confirmed to be acceptable based on computational outcomes at the 95% confidence interval. Furthermore, the scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) were used to evaluate the morphological and mineralogical behavior of green prior concrete samples with various additive mixture compositions. The addition of QD and SDA, on the other hand, aided the creation of porous microstructures in the concrete matrix due to fabric changes in the concrete mixture, potentially aided by the formation of cementitious compounds such as calcium aluminate hydrate and calcium silicate hydrate.

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“…These adjustments consider multicollinearity conditions to enable the attainment of favorable conditions and achieve a desirability score of 1.0 within the boundary conditions of 0 ≤ d(yi) ≤ 1. The optimization component of this experimental design seeks the combination of mixture ratios in the feasible factor space, simultaneously satisfying the formulated and imposed criteria on the response parameters and corresponding factor levels 57 . The primary goal of the optimization is set to maximize the target responses, while the combination ratios of the four components are set within the in-range option to determine the optimal proportion of factor levels that yield a maximum response, as detailed in Table 13 .…”

Section: Development and Validation Of The Modelmentioning

confidence: 99%

Optimization of cassava peel ash concrete using central composite design method

Iro,

Alaneme,

Attah

et al. 2024

Sci Rep

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Cassava peel ash (CPA) is an abundant agricultural byproduct that has shown promise as an additional cementitious material in concrete manufacturing. This research study aims to optimize the incorporation of CPA in concrete blends using the central composite design (CCD) methodology to determine the most effective combination of ingredients for maximizing concrete performance. The investigation involves a physicochemical analysis of CPA to assess its pozzolanic characteristics. Laboratory experiments are then conducted to assess the compressive and flexural strengths of concrete mixtures formulated with varying proportions of CPA, cement, and aggregates. The results show that a mix ratio of 0.2:0.0875:0.3625:0.4625 for cement, CPA, fine, and coarse aggregates, respectively, yields a maximum compressive strength of 28.51 MPa. Additionally, a maximum flexural strength of 10.36 MPa is achieved with a mix ratio of 0.2:0.0875:0.3625:0.525. The experimental data were used to develop quadratic predictive models, followed by statistical analyses. The culmination of the research resulted in the identification of an optimal concrete blend that significantly enhances both compressive and flexural strength. To ensure the reliability of the model, rigorous validation was conducted using student’s t-test, revealing a strong correlation between laboratory findings and simulated values, with computed p-values of 0.9987 and 0.9912 for compressive and flexural strength responses, respectively. This study underscores the potential for enhancing concrete properties and reducing waste through the effective utilization of CPA in the construction sector.

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Mechanical strength optimization and simulation of cement kiln dust concrete using extreme vertex design method

Cited by 23 publications

References 63 publications

Assessment of Mechanical Properties of Soil-Lime-Crude Oil-Contaminated Soil Blend Using Regression Model for Sustainable Pavement Foundation Construction

Assessment of Mechanical Properties of Soil-Lime-Crude Oil-Contaminated Soil Blend Using Regression Model for Sustainable Pavement Foundation Construction

Scheffe’s Simplex Optimization of Flexural Strength of Quarry Dust and Sawdust Ash Pervious Concrete for Sustainable Pavement Construction

Optimization of cassava peel ash concrete using central composite design method

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