Experimental investigation on the bond performance of sea sand coral concrete with FRP bar reinforcement for marine environments

Sun, Li; Cha, Wang; Zhang, Chunwei; Yang, Zeyu; Li, Chuang; Qiao, Pizhong

doi:10.1177/13694332221131153

Cited by 118 publications

(24 citation statements)

References 17 publications

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“…5 It intensely impacts concrete and construction processes in general. 11,12 Nanotechnology is based on synthesizing nanoparticles with specified characteristics suitable for different applications. 13,14 A nanoparticle is a microscopic particle whose size is measured in nanometers.…”

Section: Introductionmentioning

confidence: 99%

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Properties and durability of self‐compacting concrete incorporated with nanosilica, fly ash, and limestone powder

Hakeem

Amin

Zeyad

et al. 2023

Structural Concrete

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This research focused on finding the effect of nanosilica (NS) on the properties of self‐compacting concrete (SCC). NS in various proportions of 1%, 2%, 3%, 4%, 5%, 6%, 8%, and 10% was added to SCC with 10% silica fume (SF) or 10% fly ash (FA) by weight of cement to improve the properties of SCC. While the limestone powder (LSP) was used at a fixed supplementation of 15% by cement weight for all mixes. Fifteen SCC mixtures were designed based on the European guidelines for self‐compacting concrete. The properties of fresh SCC were evaluated by several tests of the slump flow, slump T50, V‐funnel, V‐funnel T5min, L‐box J‐ring, and fill box. Meanwhile, several tests evaluated SCC's mechanical properties, including compressive strength, split tensile strength, flexural strength, bond strength, and modulus of elasticity. Moreover, the permeability properties of SCC were evaluated by water permeability and air‐content tests. The effect of applying high temperatures (100–800°C) on the compressive strength of SCC containing NS with cementitious materials (SF, FA, and LSP) was also evaluated. Results showed that adding 3% NS with 10% SF and 15% LSP by weight of cement can be used to achieve the best mechanical properties of SCC. The SFNS3 mixture achieved the highest mechanical properties of 75.1, 11.9, and 41,300 MPa for compressive strength, bond strength, and modulus of elasticity tests. While the results for the slump flow, slump T50cm, and fill box were 680 mm, 6 s, and 93%.

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Section: Introductionmentioning

confidence: 99%

“…SCC has been the most significant development in concrete technology in many ways recently 5 . It intensely impacts concrete and construction processes in general 11,12 …”

Section: Introductionmentioning

confidence: 99%

Properties and durability of self‐compacting concrete incorporated with nanosilica, fly ash, and limestone powder

Hakeem

Amin

Zeyad

et al. 2023

Structural Concrete

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“…Other problems arose in terms of building materials. For example, in traditional construction, some materials are scarce on islands and reefs, and using large ships to transport them long distances can cause damage to the natural environment during construction [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

The Influence of Recycled Cement, Fly Ash, and Magnesium Oxide on the Mechanical Performance of Sustainable Cementitious Materials

et al. 2023

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In the construction industry, cement is the most widely used material. So, to achieve greater sustainability in this industry, it is imperative to improve the sustainability of this material. One way to reduce the ecological footprint of cement is to replace it, even if partially, with other more sustainable materials that can act as binders. This paper analyses the mechanical properties of more sustainable mortars containing recycled cement (RC), fly ash (FA), and magnesium oxide (MgO). Different types of binary, ternary, and quaternary mortars were used: containing recycled cement (5% and 10%), fly ash (10% and 20%), and MgO (7.5% and 15%). An experimental campaign was carried out analysing air content, density, compressive and flexural strengths, modulus of elasticity, and ultrasonic pulse velocity. The ternary mortars showed decreases between 0.4% (M-5RC10FA) and 35.3% (M-10RC15Mg) in terms of compressive strength at 365 days (compared to RM), when the theoretically expected decrease (the sum of the decreases obtained with the individual incorporation of these materials) would be between 16.6% and 41.5%, respectively. The results obtained allow for concluding that the joint use of these materials in ternary mortars improves the mechanical capacity, relative to the individual incorporation of each material in binary mortars.

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“…Deficiency in the compressive strength of HSC may result in severe structural failures and difficult repairs, as HSC is primarily designed to bear excessive compressive forces (Al-Shamiri et al, 2019). Incorporation of different materials such as fibers (Xie et al, 2021;Shi et al, 2022;Sun et al, 2023), hinges (Huang et al, 2022;Huang et al, 2023a), and special cements (Wang et al, 2022) has also been reported to enhance the properties of cementitious composites. Moreover, researchers are more attentive nowadays to sustainable supplementary cementitious materials for sustainable development (Cao et al, 2019;Arshad et al, 2020;Khan et al, 2021;Ahmad et al, 2023;Lao et al, 2023a;Lao et al, 2023b;Qian et al, 2023;Riaz Ahmad et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based evaluation of parameters of high-strength concrete and raw material interaction at elevated temperatures

Chen¹,

Suhail

Bahrami

et al. 2023

Front. Mater.

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High-strength concrete (HSC) is vulnerable to strength loss when exposed to high temperatures or fire, risking the structural integrity of buildings and critical infrastructures. Predicting the compressive strength of HSC under high-temperature conditions is crucial for safety. Machine learning (ML) techniques have emerged as a powerful tool for predicting concrete properties. Accurate prediction of the compressive strength of HSC is important as HSC can experience strength losses of up to 80% after exposure to temperatures of 800°C–1000°C. This study evaluates the efficacy of ML techniques such as Extreme Gradient Boosting, Random Forest (RF), and Adaptive Boosting for predicting the compressive strength of HSC. The results of this study demonstrate that the RF model is the most efficient for predicting the compressive strength of HSC, exhibiting the R2 value of 0.98 and lower mean absolute error and root mean square error values than the other applied models. Furthermore, Shapley Additive Explanations analysis highlights temperature as the most significant factor influencing the compressive strength of HSC. This article provides valuable insights into the timely and effective determination of the compressive strength of HSC under high-temperature conditions, benefiting both the construction industry and academia. By leveraging ML techniques and considering the critical factors that influence the compressive strength of HSC, it is possible to optimize the design and construction process of HSC and enhance its resilience to high-temperature exposure.

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Experimental investigation on the bond performance of sea sand coral concrete with FRP bar reinforcement for marine environments

Cited by 118 publications

References 17 publications

Properties and durability of self‐compacting concrete incorporated with nanosilica, fly ash, and limestone powder

Properties and durability of self‐compacting concrete incorporated with nanosilica, fly ash, and limestone powder

The Influence of Recycled Cement, Fly Ash, and Magnesium Oxide on the Mechanical Performance of Sustainable Cementitious Materials

Machine learning-based evaluation of parameters of high-strength concrete and raw material interaction at elevated temperatures

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