Reinforced Lime Concrete with FRP: An Alternative in the Restoration of Architectural Heritage

Almerich-Chulia, Ana; Fenollosa, E.; Martín, Pedro Luis

doi:10.4028/www.scientific.net/amm.851.751

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…The mechanical properties of wood-modified lime mortars improved by almost 25% in comparison to the reference sample; however, the cohesion of the matrix was problematic. Almerich et al [59] used Glass Fiber-Reinforced Polymer (GFRP) bars as a replacement for steel bars in reinforced lime concrete. It was observed that the lime concrete modified with GFRP had high UCS, acceptable tensile strength, a higher elastic modulus and adhesion, good compatibility, and reduced cement alkalinity.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Properties of Polyamide Fiber-Reinforced Lime–Cement Concrete

et al. 2023

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Lime–cement concrete (LCC) is a type of lime-based concrete in which lime and cement are utilized as the main binding agents. This type of concrete has been extensively used to construct support layers for shallow footings and road backfills in some warm regions. So far, there has been no systematic research conducted to investigate the mechanical characteristics of polyamide fiber-reinforced LCC. To address this gap, LCC specimens were prepared with 0%, 0.5%, 1%, and 2% of polyamide fibers (a synthetic textile made of petroleum-based plastic polymers). Specimens were then cured for 3, 7, and 28 days at room and oven temperatures. Then, the effects of the fibers’ contents, curing conditions, and curing periods on the mechanical characteristics of LCC, such as secant modulus, deformability index, bulk modulus, shear modulus, stiffness ratio, strain energy, failure strain, strength ratio, and failure patterns, was investigated. The results of the unconfined compressive strength (UCS) tests showed that specimens with 1% fiber had the highest UCS values. The curing condition and curing period had significant effects on the strength of the LCC specimens, and oven-cured specimens developed higher UCS values. The aforementioned mechanical properties of the LCC specimens and the ability of the material to absorb energy significantly improved when the curing period under the oven-curing condition was increased, as well as through the application of fibers in the mix design. Based on the test results, a simple mathematical model was also established to forecast the mechanical properties of fiber-reinforced LCC. It is concluded that the use of polyamide fibers in the mix design of LCC can both improve mechanical properties and perhaps address the environmental issues associated with waste polyamide fibers.

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Section: Introductionmentioning

confidence: 99%

Mechanical Properties of Polyamide Fiber-Reinforced Lime–Cement Concrete

et al. 2023

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“…The lime addition up to 10% did not affect the soundness of the blended cements like PSC and PPC. [30], concluded from their work that lime concrete reinforced with Glass Fibre Reinforced (GFRP) is a viable alternative to replace the reinforced concrete design in the repairs of historical eating. Highest compressive obtained was 14MPa.…”

Section: Introductionmentioning

confidence: 99%

Anticipating the Compressive Strength of Hydrated Lime Cement Concrete Using Artificial Neural Network Model

et al. 2018

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In this research work, the levernberg Marquardt back propagation neural network was adequately trained to understand the relationship between the 28th day compressive strength values of hydrated lime cement concrete and their corresponding mix ratios with respect to curing age. Data used for the study were generated experimentally. A total of a hundred and fourteen (114) training data set were presented to the network. Eighty (80) of these were used for training the network, seventeen (17) were used for validation, and another seventeen (17) were used for testing the network's performance. Six (6) data set were left out and later used to test the adequacy of the network predictions. The outcome of results of the created network was close to that of the experimental efforts. The lowest and highest correlation coefficient recorded for all data samples used for developing the network were 0.901 and 0.984 for the test and training samples respectively. These values were close to 1. T-value obtained from the adequacy test carried out between experimental and model generated data was 1.437. This is less than 2.064, which is the T values from statistical table at 95% confidence limit. These results proved that the network made reliable predictions. Maximum compressive strength achieved from experimental works was 30.83N/mm2 at a water-cement ratio of 0.562 and a percentage replacement of ordinary portland cement with hydrated lime of 18.75%. Generally, for hydrated lime to be used in making structural concrete, ordinary portland cement percentage replacement with hydrated lime must not be up to 30%. With the use of the developed artificial neural network model, mix design procedure for hydrated lime cement concrete can be carried out with lesser time and energy requirements, when compared to the traditional method. This is because, the need to prepare trial mixes that will be cured, and tested in the laboratory, will no longer be required.

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Reinforced Lime Concrete with FRP: An Alternative in the Restoration of Architectural Heritage

Cited by 2 publications

References 5 publications

Mechanical Properties of Polyamide Fiber-Reinforced Lime–Cement Concrete

Mechanical Properties of Polyamide Fiber-Reinforced Lime–Cement Concrete

Anticipating the Compressive Strength of Hydrated Lime Cement Concrete Using Artificial Neural Network Model

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