A critical review on the utilization of coir (coconut fiber) in cementitious materials

Ali, Babar; Hawreen, A.; Kahla, Nabil Ben; Amir, Muhammad Talha; Azab, Marc; Raza, Ali

doi:10.1016/j.conbuildmat.2022.128957

Cited by 49 publications

(27 citation statements)

References 78 publications

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“…A cementitious microstructure of high-performance concrete may give higher mechanical qualities with coir by improving its roughness through alkali treatment of the coir and protecting it with latex and pozzolana [6]. Brígida [7] reported three types of chemical treatment for coconut fibre; treatment with H2O2, treatment with NaOCl, and treatment with NaOCl and NaOH.…”

Section: Treatment Of Coir Fibresmentioning

confidence: 99%

Concrete with Coconut Fibre Treated with Sodium Hypochlorite – Compressive and Flexural Strength

Djanali¹

2023

JMechE

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Concrete needs to be reinforced to improve its engineering qualities. Coconut fibres were employed for this study since they are widely accessible and come in big numbers. The study compares the qualities of plain concrete and concrete reinforced with coconut fibre based on a laboratory experiment. Better management of these waste fibres will result from using coconut fibres. Two types of coconut fibre treatment were employed – treatment with tap water and treatment with sodium hypochlorite. It is found in this study that adding 1% of coconut fibre does not increase the concrete strength after 7 and 14 days of curing. However, it was discovered that using 1% coconut fibres treated using tap water increased the compressive and flexural strength of the concrete after 28 days of curing by roughly 4% and 3%, respectively. Compressive and flexural strength development agrees very well with each other. Hence, it is concluded that 1% was the ideal fibre concentration (by weight of cement) to obtain a better 28th day of compressive and flexural strength, although not for 7 and 14 days. However, concrete with the highest strengths demonstrated a very low slump value, only 20 mm. A smaller or bigger slump value showed smaller concrete strengths.

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Section: Treatment Of Coir Fibresmentioning

confidence: 99%

Concrete with Coconut Fibre Treated with Sodium Hypochlorite – Compressive and Flexural Strength

Djanali¹

2023

JMechE

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“…Hence different fibers, including artificial and steel fibers, have been commonly incorporated to enhance composites' impact resistance and ductility (Zhang and Huang, 2022). Multiple researchers have explored the addition of steel/synthetic/natural fibers to concrete as reinforcement for improving characteristics like fatigue resistance, toughness, ductility, and resist propagation of cracks in concrete Ali et al, 2021;Li et al, 2021b;Cao and Khan, 2021;Deifalla et al, 2021;Khan et al, 2021;Xie et al, 2021;Ali et al, 2022a;Khan et al, 2022a;Li et al, 2022b;Ali et al, 2022c;Ali et al, 2022d;Farooqi and Ali, 2022;Hu et al, 2022;Meng et al, 2022;Zhang N et al, 2022). Steel fibers are incorporated into concrete to enhance its post-cracking phenomenon and toughness (Deifalla, 2020;Li et al, 2021a;Li et al, 2022a;Raza et al, 2022a;Khan et al, 2022b;Khan et al, 2022c;Khan et al, 2022d).…”

Section: Introductionmentioning

confidence: 99%

Application of machine learning algorithms to evaluate the influence of various parameters on the flexural strength of ultra-high-performance concrete

et al. 2023

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The effect of various parameters on the flexural strength (FS) of ultra-high-performance concrete (UHPC) is an intricate mechanism due to the involvement of several inter-dependent raw ingredients. In this digital era, novel artificial intelligence (AI) approaches, especially machine learning (ML) techniques, are gaining popularity for predicting the properties of concrete composites due to their better precision than typical regression models. In addition, the developed ML models in the literature for FS of UHPC are minimal, with limited input parameters. Hence, this research aims to predict the FS of UHPC considering extensive input parameters (21) and evaluate each their effect on its strength by applying advanced ML approaches. Consequently, this paper involves the application of ML approaches, i.e., Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), and Gradient Boosting (GB), to predict the FS of UHPC. The GB approach is more effective in predicting the FS of UHPC precisely than the SVM and MLP algorithms, as evident from the outcomes of the current study. The ensembled GB model determination coefficient (R2) is 0.91, higher than individual SVM with 0.75 and individual MLP with 0.71. Moreover, the precision of applied models is validated by employing the k-fold cross-validation technique. The validity of algorithms is ensured by statistical means, i.e., mean absolute error and root mean square errors. The exploration of input parameters (raw materials) impact on FS of UHPC is also made with the help of SHAP analysis. It is revealed from the SHAP analysis that the steel fiber content feature has the highest influence on the FS of UHPC.

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“…Numerous research is conducted to evaluate the properties of cementitious composites; nevertheless, compressive strength (CS), particularly 28-day CS, is regarded as important [ 31 ]. The CS of cementitious composites gives vital knowledge of its many characteristics [ 48 , 49 ]. The CS of cementitious composites is linked to its various other characteristics [ 50 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the effectiveness of waste glass powder for the compressive strength improvement of cement mortar using experimental and machine learning methods

Khan,

Ahmad,

Amin

et al. 2023

Heliyon

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A critical review on the utilization of coir (coconut fiber) in cementitious materials

Cited by 49 publications

References 78 publications

Concrete with Coconut Fibre Treated with Sodium Hypochlorite – Compressive and Flexural Strength

Concrete with Coconut Fibre Treated with Sodium Hypochlorite – Compressive and Flexural Strength

Application of machine learning algorithms to evaluate the influence of various parameters on the flexural strength of ultra-high-performance concrete

Evaluating the effectiveness of waste glass powder for the compressive strength improvement of cement mortar using experimental and machine learning methods

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