Effects of different industrial waste materials as partial replacement of fine aggregate on strength and microstructure properties of concrete

Kaish, A. B. M. A.; Odimegwu, Temple Chimuanya; Zakaria, Ideris; Abood, Manal Mohsen

doi:10.1016/j.jobe.2020.102092

Cited by 27 publications

(13 citation statements)

References 18 publications

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“…There is an estimated 20 billion tons of concrete produced annually, making it the second most widely used substance in the world after fresh-water. Aside from its benefits, concrete has a malignant effect on the Earth and human health and has adverse long-term effects on the natural environment and atmosphere [ 8 ]. It pushes the human footprint outwards by generating living space out of the air, spreading across rich topsoil, and causing biodiversity.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Machine Learning Techniques

et al. 2021

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Silica fume (SF) is a frequently used mineral admixture in producing sustainable concrete in the construction sector. Incorporating SF as a partial substitution of cement in concrete has obvious advantages, including reduced CO2 emission, cost-effective concrete, enhanced durability, and mechanical properties. Due to ever-increasing environmental concerns, the development of predictive machine learning (ML) models requires time. Therefore, the present study focuses on developing modeling techniques in predicting the compressive strength of silica fume concrete. The employed techniques include decision tree (DT) and support vector machine (SVM). An extensive and reliable database of 283 compressive strengths was established from the available literature information. The six most influential factors, i.e., cement, fine aggregate, coarse aggregate, water, superplasticizer, and silica fume, were considered as significant input parameters. The evaluation of models was performed by different statistical parameters, such as mean absolute error (MAE), root mean squared error (RMSE), root mean squared log error (RMSLE), and coefficient of determination (R2). Individual and ensemble models of DT and SVM showed satisfactory results with high prediction accuracy. Statistical analyses indicated that DT models bested SVM for predicting compressive strength. Ensemble modeling showed an enhancement of 11 percent and 1.5 percent for DT and SVM compressive strength models, respectively, as depicted by statistical parameters. Moreover, sensitivity analyses showed that cement and water are the governing parameters in developing compressive strength. A cross-validation technique was used to avoid overfitting issues and confirm the generalized modeling output. ML algorithms are used to predict SFC compressive strength to promote the use of green concrete.

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Section: Introductionmentioning

confidence: 99%

Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Machine Learning Techniques

et al. 2021

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“…The destructive method of compressive strength testing was used to determine the strength of concrete produced without industrial waste (control) and with industrial waste (air-dried and treated alum sludge, limestone dust and quarry dust). The graph presented in Figure 3 shows that the compressive strength of all the samples increased with an increase in curing age (7, 28 and 180 days) [31]. The strength of the concrete increased when industrial waste material was added to the mix, and when the waste was increased the compressive strength increased too.…”

Section: Compressive Strength Of Concretementioning

confidence: 97%

“…It was reported that alum sludge as a replacement for cement had no negative effect on the concrete structure but had higher resistance to chemical attack. Alum sludge in different conditions utilized in concrete as a replacement for fine aggregate has been studied [31]. The study disclosed that alum sludge as a replacement for fine aggregate increased the concrete density and strength properties and improved concrete durability.…”

Section: Introductionmentioning

confidence: 99%

Nondestructive Determination of Strength of Concrete Incorporating Industrial Wastes as Partial Replacement for Fine Aggregate

Odimegwu

Kaish

Zakaria

et al. 2021

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Schmidt rebound hammer test was employed in this study as a nondestructive test. This test method has been universally utilized due to its non-destructiveness for quick and easy assessment of material strength properties and quality of concrete of an existing structure. Industrial waste materials (air-dried alum sludge, treated alum sludge, limestone dust and quarry dust) were employed as replacement material for fine aggregates in this study. A normal strength concrete was designed to achieve 35 MPa at 28 days, with industrial waste materials replacing fine aggregate at different percentages (0%, 5%, 10% and 15%), and then cured for 7, 28 and 180 days. The compressive strength values and rebound numbers for all the mixes obtained were correlated, and a regression equation was established between compressive strength and Schmidt rebound number. The correlation result showed an excellent relationship between rebound number and compressive strength of concrete produced in this study at all curing ages, with correlation coefficients of R2 = 0.98, R2 = 0.99 and R2 = 0.98. The predicted equation showed a strong relationship with the experimental compressive strength. Therefore, it can be used for the prediction of compressive strength of concrete with industrial waste as a replacement for fine aggregate.

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“…Concrete as a building material is the most durable and commonly used material for a wide variety of construction activities [1]. The availability of the mixing ingredients, namely sand, water, granite and raw materials for cement making in many parts of the globe, causes concrete to be easily produced and used everywhere.…”

Section: Introductionmentioning

confidence: 99%

Periwinkle Shell as Mixing Ingredient in Concrete: A Review

et al. 2021

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Growing population which also pushes for rising demand for seafood results in a generation of seashells which are thrown as environmental pollution waste after the edible meat is consumed. Meanwhile, the utilisation of natural resources as mixing ingredients for the production of concrete materials continues to increase over the year. The use of periwinkle shells as mixing ingredients in concrete materials can lower the dependency on natural aggregate supply. This paper discusses the properties of periwinkle shell and method of treatment prior to their usage as a cement and coarse aggregate as well as the mechanical properties of concrete produced using this seashell waste. Overall, the replacement of periwinkle shell as cement and coarse aggregate must be integrated in a specified percentage to enhance the performance of the concrete. For cement replacement, 5% of replacement gives the highest strength, meanwhile 10% of replacement as coarse aggregate can meet the desired strength. The increase in the use of periwinkle shell quantity as cement or coarse aggregate replacement reduces concrete workaibility. The integration of periwinkle shell influences the compresssive strength of concrete. Accomplishment in replacing periwinkle shell as cement and coarse aggregate would reduce pollutiion due to shell dumping and save natural resources. However, further investigation in terms of durability properties is recommended.

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Effects of different industrial waste materials as partial replacement of fine aggregate on strength and microstructure properties of concrete

Cited by 27 publications

References 18 publications

Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Machine Learning Techniques

Modeling of Mechanical Properties of Silica Fume-Based Green Concrete Using Machine Learning Techniques

Nondestructive Determination of Strength of Concrete Incorporating Industrial Wastes as Partial Replacement for Fine Aggregate

Periwinkle Shell as Mixing Ingredient in Concrete: A Review

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