Relation between rheological and mechanical properties on behaviour of self-compacting concrete (SCC) containing recycled plastic fibres: a review

Frhaan, Waseem Khairi Mosleh; Bakar, B.H. Abu; Hilal, Nahla; Al‐Hadithi, Abdulkader Ismail

doi:10.1080/19648189.2020.1868344

Cited by 10 publications

(3 citation statements)

References 54 publications

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“…Therefore, part of cement can be replaced by a certain part of mineral additives and fillers such as (silica fume, fly ash, and limestone) in SCC to achieve that. In addition, chemical additives such as superplasticizer can be used to obtain high strength by reducing the ratio of water Asmaa S. Hussien, Mahmoud K. Mohammed to powder (w/p) and improve the workability and durability properties of the SCC [5]. Further, different types of natural and industrial byproducts have been used to produce environmentally friendly concrete at low cost instead of traditional building materials [6].…”

Section: Introductionmentioning

confidence: 99%

“…Frhaan et. al said that the addition a different volume fraction ratio of the fibers improved the mechanical properties , and the results showed that the optimum tensile strength was achieved at a fiber content of 1.5% [5], but Vijaya et.al claimed that the average splitting tensile strength increased by increasing the percentage of fibers up to 1.0% [10]. PET is known to be chemically inert and stable due to its hydrophobic nature.…”

Section: Introductionmentioning

confidence: 99%

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Properties of Sustainable Self- compacting Concrete Containing Treated and Modified Waste Plastic Fibers

Hussien¹,

Mohammed²

2022

AJES

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This study aims to improve different properties of sustainable self-compacting concrete SCC containing treated and modified polyethylene terephthalate PET fibers. For this purpose, gamma ray surface treatment and geometric modification were utilized for the used PET fibers. Concrete fresh properties include slump flow, T500mm, L-box and sieve segregation while mechanical properties include compressive, split tensile strength, flexural strength, static modulus of elasticity and impact strength. Further, physical properties and related durability properties comprise dry density, ultrasonic pulse velocity, porosity and water absorption. The results obtained demonstrated that the treatment and the modification used for the PET fibers slightly reduced the fresh properties of produced sustainable SCC (slump flow, T500 mm, L-Box and sieve segregation). However, they were within the limits of the SCC specification as reported in EFNERC guidelines. Further, concrete hardened properties in terms of compressive strength, splitting tensile strength, flexural strength, modulus of elasticity, impact strength, ultrasonic pulse velocity, decrease in the dry density, decrease in porosity and water absorption increased significantly.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Properties of Sustainable Self- compacting Concrete Containing Treated and Modified Waste Plastic Fibers

Hussien¹,

Mohammed²

2022

AJES

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“…Fly ash [4,5], rice husk ash [6,7], palm oil fuel ash [8,9], nano-silica [10,11], and pumice powder [12,13] are some of the replacement materials used in the concrete industry. The utilization of supplementary cementitious materials (e.g., fly ash, rice husk ash, palm oil fuel ash, nanosilica, pumice powder, metakaolin) has had a very positive impact regarding the protection of the environment [14]. complications, especially in the case of large and complex structures.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Prediction of the Compressive Strength of Environmentally Friendly Concrete Modified with Eggshell Powder Using the Hybrid ANN-SFL Optimization Algorithm

et al. 2021

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The aim of this article is to predict the compressive strength of environmentally friendly concrete modified with eggshell powder. For this purpose, an optimized artificial neural network, combined with a novel metaheuristic shuffled frog leaping optimization algorithm, was employed and compared with a well-known genetic algorithm and multiple linear regression. The presented results confirm that the highest compressive strength (46 MPa on average) can be achieved for mix designs containing 7 to 9% of eggshell powder. This means that the strength increased by 55% when compared to conventional Portland cement-based concrete. The comparative results also show that the proposed artificial neural network, combined with the novel metaheuristic shuffled frog leaping optimization algorithm, offers satisfactory results of compressive strength predictions for concrete modified using eggshell powder concrete. Moreover, it has a higher accuracy than the genetic algorithm and the multiple linear regression. This finding makes the present method useful for construction practice because it enables a concrete mix with a specific compressive strength to be developed based on industrial waste that is locally available.

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Retracted: Predicting the compressive strength of modified recycled aggregate concrete

Yang

Feng

Esmaeili‐Falak

2022

Structural Concrete

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Reuse and recycling of construction wastes effectively prevent further destruction of the environment and nature due to the construction industry. One of the conventional methods is the reapplication of recycled aggregates (RAs) in concrete mix design and construction. Compressive strength (CS) is a considerable representation of the mechanical properties of recycled aggregate concrete (RAC). The present study is divided into two parts of experimental and predicting. In the laboratory studies phase, RA was used with 100% replacement. Due to the proven defects in RAC, glass fibers and silica fume (variables) have been used to compensate for these defects. Different mixing designs were used to construct concrete samples, and then the CS of each specimen was measured in the laboratory. Afterward, these data were used as training and testing in various conventional, ensembled and hybrid models as the tree-based learning algorithms, rules, Lazy-learning Algorithms, Functions, and Meta classifiers. Considering the applied performance statistical criteria (R 2 , root mean squared error, mean absolute error, and mean absolute percentage error), all models have provided excellent and acceptable results, which the precision of the multilayer perceptron single model and additive regression-random Forest hybrid model have the best agreement with measured values of CS of RAC.

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Relation between rheological and mechanical properties on behaviour of self-compacting concrete (SCC) containing recycled plastic fibres: a review

Cited by 10 publications

References 54 publications

Properties of Sustainable Self- compacting Concrete Containing Treated and Modified Waste Plastic Fibers

Properties of Sustainable Self- compacting Concrete Containing Treated and Modified Waste Plastic Fibers

Metaheuristic Prediction of the Compressive Strength of Environmentally Friendly Concrete Modified with Eggshell Powder Using the Hybrid ANN-SFL Optimization Algorithm

Retracted: Predicting the compressive strength of modified recycled aggregate concrete

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