Influence of the PBO-FRCM Composite Configuration on the Shear Capacity of RC Beams

Marcinczak, Dorota; Trapko, Tomasz

doi:10.1061/(asce)cc.1943-5614.0001221

Cited by 5 publications

(1 citation statement)

References 26 publications

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“…Previous studies have explored various types of binders, resulting in the development of multiple options for use in different applications (Shiping et al, 2022;Bressan et al, 2022;Cristofaro et al, 2022;Marcinczak and Trapko, 2022;Zhang et al, 2022;Zdanowicz and Marx, 2022). From the study (Du et al, 2018), developed a ne-grained matrix with a maximum aggregate size of 1.2mm.…”

Section: Introductionmentioning

confidence: 99%

A study on Mechincal Properties of Inorganic Binders used in Textile Reinforced Concrete Using Artificial Neural Network

Madhavi

2024

Preprint

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Textile-reinforced concrete (TRC) is a new and high-performance material made by embedding textile fibers into a matrix. Unlike traditional concrete, TRC doesn't contain coarse aggregate and has a higher proportion of cement paste. In this study, three different types of binders organic, inorganic geopolymer, and epoxy were examined for their impact on compressive and split tensile strengths. These binders were compared by testing mortar cubes (sized 70.6 mm) and cylinders (sized 75 × 150 mm) to see how they affect the properties of TRC. Various types of textile fabrics, including ARG, Basalt, and Hybrid, were experimented with to see how they influence compressive strength and failure modes. The study also examined how the thickness of the textile reinforcement (ranging from 5 to 15 mm) affects TRC performance. The results show that using a hybrid textile fabric with a cementitious binder leads to higher compressive strength. The experimental data underwent verification through the ANN method, where the neural network was trained akin to standard experimental research methodologies. With an impressive accuracy (R2 > 0.99), the ANN model successfully predicted mechanical properties, establishing its reliability in estimating responses and identifying parameters. Additionally, ANN techniques were instrumental in determining the optimal parameters for the study

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Section: Introductionmentioning

confidence: 99%

A study on Mechincal Properties of Inorganic Binders used in Textile Reinforced Concrete Using Artificial Neural Network

Madhavi

2024

Preprint

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A study on mechanical properties of inorganic binders used in textile reinforced concrete using artificial neural network

Madhavi

2024

Asian J Civ Eng

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Flexural behavior of warp knitted textile reinforced concrete impregnated with cementitious binder

Madhavi

2024

Case Studies in Construction Materials

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Influence of the PBO-FRCM Composite Configuration on the Shear Capacity of RC Beams

Cited by 5 publications

References 26 publications

A study on Mechincal Properties of Inorganic Binders used in Textile Reinforced Concrete Using Artificial Neural Network

A study on Mechincal Properties of Inorganic Binders used in Textile Reinforced Concrete Using Artificial Neural Network

A study on mechanical properties of inorganic binders used in textile reinforced concrete using artificial neural network

Flexural behavior of warp knitted textile reinforced concrete impregnated with cementitious binder

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