Cement Mortar with Nanosilica: Experiments with Mixture Design Method

Hameed, Mohamed Fattouh Abd El; Ghazy, Mariam Farouk; Elaty, Metwally Abd Allah Abd

doi:10.14359/51688632

Cited by 3 publications

(1 citation statement)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These properties of interest were measured, and empirical models for each property as a function of the input variables were determined from regression analysis; the model with the largest coefficient of multiple determinations ( R 2 ), the lowest prediction error sum of squares and the lowest standard deviation was selected. The model parameters are estimated by means of a multi-regression analysis using the least-squares method (Mariam and Metwally, 2016). The predicted-to-observed plots shown in Figure 7 indicate that the points seem to be distributed inside the confidence curves limits.…”

Section: Resultsmentioning

confidence: 99%

Optimization by mixture design approach

Abadou

Ghrieb

Bustamante³

et al. 2020

JEDT

View full text Add to dashboard Cite

Purpose The purpose of this study is to fit an appropriate mathematical model to express response variables as functions of the proportions of the mixture components. One purpose of statistical modeling in a mixture experiment is to model the blending surface such that predictions of the response for any mixture component, singly or in combination, can be made empirically. Testing of the model adequacy will also be an important part of the statistical procedure. Design/methodology/approach A series of mortar using air lime, marble and ceramic sanitary waste aggregates were prepared for statistically designed combinations. The combinations were designed based on the mixture-design concept of design of experiments; this mortar is often used as a filler material in restoration projects. The aim of this work is to find an optimal composition of a paste for the manufacture of air lime mortar with ceramic and marble waste. This investigation aims to recommend mix design for air lime-based mortar, by optimizing the input combination for different properties, and to predict properties such as mechanical strength, thermogravimetric and x-ray diffraction analysis with a high degree of accuracy, based on a statistical analysis of experimental data. Findings This paper discusses those mortar properties that architects, contractors and owners consider important. For each of these properties, the influence of ceramic and marble waste in the air lime mortar is explored. The flexibility of lime-based mortars with waste materials to meet a wide range of needs in both new construction and restoration of masonry projects is demonstrated. Originality/value The objective of the present investigation is to recommend mixture design for air lime mortar with waste, by optimizing the input combination for different properties, and to predict properties such as compressive strength, flexural strength with a high degree of accuracy, based on the statistical analysis of experimental data. The authors conducted a mixture design study that takes into account dependent parameters such as the constituents of our air lime-based mortar where we have determined an experiment matrix to which we have connected the two responses, namely, compressive and flexural strength. By introducing the desirability criteria of these two responses, using JMP software, we were able to obtain a mixture optimal for air lime mortar with ceramic and marble waste.

show abstract

Section: Resultsmentioning

confidence: 99%

Optimization by mixture design approach

Abadou

Ghrieb

Bustamante³

et al. 2020

JEDT

View full text Add to dashboard Cite

show abstract

Optimization of cementitious mixes through response surface method: a systematic review

Hurtado-Alonso,

Manso-Morato,

Revilla-Cuesta

et al. 2024

Arch. Civ. Mech. Eng.

View full text Add to dashboard Cite

The pursuit of cement-based materials with enhanced mechanical performance in the construction industry involves formulating numerous mixtures with varied contents of raw materials. However, the scarcity or contamination of these materials demands optimization methods to minimize the number of trials required. Response Surface Methodology (RSM) is a statistical experimental optimization method with which relations between sets of factors and responses can be established. This systematic review aims to analyze the existing literature on RSM models developed to achieve optimum levels in cementitious mixes. Over 100 papers were analyzed in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) format. A comprehensive review of the RSM analyses in those studies and their effectiveness is conducted, through the evaluation of their optimized factors and responses, the selection of their design models, their use of ANalysis Of VAriance (ANOVA), and the determination of their coefficients of determination (R2). Factors such as water/cement ratio and binder content prevailed in most models, the predominant responses of which were, respectively, compressive strength and workability. Although the use of ANOVA is commonly used to demonstrate the validity of the models, the studies replicating the mix with optimal levels of all factors are necessary to validate the results. On the basis of this review and depending on the responses that need to be maximized or minimized, the application of RSM can clearly be very crucial when quantifying the effects of new raw materials, whether recovered waste or natural resources, on mix behaviour.

show abstract