Residual compressive stress–strain relationship of lightweight aggregate concrete after exposure to elevated temperatures

Dabbaghi, Farshad; Dehestani, Mehdi; Yousefpour, Hossein; Rasekh, Haleh; Navaratnam, Satheeskumar

doi:10.1016/j.conbuildmat.2021.123890

Cited by 27 publications

(7 citation statements)

References 40 publications

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“…There is worldwide agreement on the need to reduce the carbon footprint of the cement industry via substantial substitution of cement in concrete. As a result, a solution for the longterm sustainability of concrete is required, as is the development of a new binder capable of overcoming the barriers associated with the manufacture and implementation of OPC [60][61][62].…”

Section: Green Concretementioning

confidence: 99%

Optimization of Green Concrete Containing Fly Ash and Rice Husk Ash Based on Hydro-Mechanical Properties and Life Cycle Assessment Considerations

et al. 2022

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The development of sustainable concrete in achieving the developmental goals of the United Nations in terms of sustainable infrastructure and innovative technology forms part of the focus of this research paper. In order to move towards sustainability, the utilization of the by-products of agro-industrial operations, which are fly ash (FA) and rice husk ash (RHA), in the production of concrete has been studied. Considering the environmental impact of concrete constituents, multiple mechanical and hydraulic properties of fly ash (FA) and rice husk ash (RHA) concrete have been proposed using intelligent techniques; artificial neural network (ANN) and evolutionary polynomial regressions (EPR). Also, an intelligent mix design tool/chart for this case under study is proposed. Multiple data points of concrete materials, which were further reduced to ratios as follows; cement to binder ratio (C/B), aggregate to binder ratio (Ag/B), and plasticizer to binder ratio (PL/B) were used in this exercise. At the end of the protocol, it is observed that the constituents’ ratios are dependent on the behavior of the whole, which can be solved by using the proposed model equations and mix design charts. The models performed optimally, as none showed any performance below 80%. However, ANN, which predicted Fc03, Fc07, Fc28, Fc60, Fc90, Ft28, Ff28 & Fb28, S, Ec28 & K28, and P with an accuracy of greater than 95% each with average error of less than 9.4% each, is considered the decisive technique in predicting all the studied concrete properties, including the life cycle assessment potential of the concrete materials. Doi: 10.28991/CEJ-2022-08-12-018 Full Text: PDF

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Section: Green Concretementioning

confidence: 99%

Optimization of Green Concrete Containing Fly Ash and Rice Husk Ash Based on Hydro-Mechanical Properties and Life Cycle Assessment Considerations

et al. 2022

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“…LWC has good fire resistance due to its lower thermal conductivity, which helps to slow the spread of fire within a building. This can improve the safety of the building occupants in the event of a fire [3][4][5][6]. Despite being lightweight, LWC can be just as durable as traditional concrete.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Durability Against a Chemical Attack of Fiber-Reinforced Lightweight Pouzzolanic Concrete under the Effect of Temperature

Belhadj¹,

Tenza-Abril²,

Mahi³

2023

ACSM

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The study of the durability of Fiber-Reinforced Lightweight Pouzzolanic Concrete (FRLPC) is a topic of research that focuses on evaluating the skills of FRLPC, because exposure to certain chemicals can cause deterioration and reduce the lifespan of the concrete. Chemical attacks can occur due to exposure to acids, sulfates, and other substances commonly found in the environment. The work presented here aims to analyze the influence of different types of fibers on the behavior of lightweight concretes (LWC) based on pozzolanic aggregates in aggressive media such as acids and under the effect of temperatures. The choice of pozzolanic aggregates is to valorize natural pozzolan as lightweight aggregates in concrete, knowing that this material is abundant in Algeria. In this sense, different tests have been carried out using metal, polyethylene, and polypropylene fibers in LWC manufactured with pozzolanic aggregates. The LWC specimens were kept in water saturated with lime until the age of testing (28, 60, and 90 days). Then, the specimens were subjected to heating under two temperatures (200°C and 600°C). After cooling, the specimens were exposed to hydrochloric acid (Hcl) and sulfuric acid (H2SO4) solutions (5% w/w). The evaluation of the durability of these concretes and the mechanical behavior was obtained by the measurement of the mass loss and the compressive strength.

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“…To enable evaluation of the performance of LWAC, its stress-strain curve, including modulus of elasticity, peak or failure strain, ultimate strain, energy absorption capacity and toughness, should be evaluated. Recent research shows that it is possible to predict the stressstrain relation of different LWAC mixtures through theoretical calculations [11][12][13]. A study has also shown that concrete containing fine light expanded clay aggregate (LECA) could achieve a 28-day compressive strength of 41 to 45 MPa [14].…”

Section: Introductionmentioning

confidence: 99%

Predicting stress-strain behavior of normal weight and lightweight aggregate concrete exposed to high temperature using LSTM recurrent neural network

Tanhadoust

Yang

Dabbaghi

et al. 2023

Construction and Building Materials

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Residual compressive stress–strain relationship of lightweight aggregate concrete after exposure to elevated temperatures

Cited by 27 publications

References 40 publications

Optimization of Green Concrete Containing Fly Ash and Rice Husk Ash Based on Hydro-Mechanical Properties and Life Cycle Assessment Considerations

Optimization of Green Concrete Containing Fly Ash and Rice Husk Ash Based on Hydro-Mechanical Properties and Life Cycle Assessment Considerations

Assessment of the Durability Against a Chemical Attack of Fiber-Reinforced Lightweight Pouzzolanic Concrete under the Effect of Temperature

Predicting stress-strain behavior of normal weight and lightweight aggregate concrete exposed to high temperature using LSTM recurrent neural network

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