Predicting the mechanical properties of lightweight aggregate concrete using finite element method

Bonifácio, Aldemon Lage; Mendes, Júlia Castro; Farage, Michèle Cristina Resende; Barbosa, Fernando Policarpo; Beaucour, Anne-Lise

doi:10.1590/s1983-41952020000400010

Cited by 3 publications

(1 citation statement)

References 18 publications

(19 reference statements)

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“…The strength of LWA and ITZ characteristics, such as porosity and the bonding strength, play an important role in optimizing the mechanical properties of LWAC [23]. A detailed stress analysis is beneficial to understand their effects.…”

Section: Introductionmentioning

confidence: 99%

Stress Distribution in Microregion of Core–Shell Structure Lightweight Aggregate Concrete

et al. 2021

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An in-depth understanding of the effect of cordierite/belite core–shell structure lightweight aggregate (CSLWA) on the mechanical performance of LWA concrete (LWAC) is critical for improving the failure resistance of LWAC. In this study, the stress distribution of the microregion in CSLWA was systematically investigated via a finite element analysis to explore its effect on the mechanical properties of LWAC. In detail, the material components, core–shell thickness ratio, porosity and width of interfacial transition zone (ITZ), and absence or presence of interfacial bonding zone (IBZ) were considered during the stress distribution analysis of the microregion of LWAC. The results showed that a reduction in the material components, with a high-elastic modulus in the core, a decrease in the core–shell thickness ratio, and the formation of the core–shell IBZ are beneficial for optimizing the stress distribution of the microregion and alleviating the stress concentration phenomenon of LWAC. Moreover, due to the continuous hydration of belite shell, the ITZ of CSLWA becomes increasingly dense, thus the stress distribution is more uniform than that of ordinary LWAC, indicating that CSLWA exhibits the potential to improve the failure resistance of LWAC. This study helps to develop an understanding of the role played by the core–shell structure in improving the toughness of LWAC, and provides a new solution and methodology for improving the brittleness of LWAC.

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Section: Introductionmentioning

confidence: 99%

Stress Distribution in Microregion of Core–Shell Structure Lightweight Aggregate Concrete

et al. 2021

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Evaluation of Concrete Characteristics Using Smart Machine Learning Techniques—A Review

Kapoor,

Popli,

Sharma

et al. 2024

Lecture Notes in Civil Engineering

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A New Formulation to Estimate the Elastic Modulus of Recycled Concrete Based on Regression and ANN

2021

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A new formulation to estimate the elastic modulus of concrete containing recycled coarse aggregate is proposed in this work using artificial neural networks (ANN) and nonlinear regression. Up to six predictors variables were used to training 243 ANN. The models were generated based on results obtained from experimental campaigns. Feedforward neural network and Levenberg–Marquardt back propagation algorithm were used for training the ANN. The best ANN was found with the architecture 6-4-2-1 (input -1st hidden layer—2nd hidden layer—output), attaining a root-mean-square error of 2.4 GPa associated with a coefficient of determination of 0.91. Once the ANN model was established, 46,656 concrete samples were created. These were employed to formulate the model using nonlinear regression. The developed model showed a highly efficient performance to predict the elastic modulus. Lastly, considering the parametric study conducted, the results pointed out that the approach can be applied to predict the concrete elastic modulus and can indicate better mix proportions for concretes containing natural and/or recycled coarse aggregates, enabling its use as a simulation tool in the development of engineering projects focused on durability and sustainability.

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Predicting the mechanical properties of lightweight aggregate concrete using finite element method

Cited by 3 publications

References 18 publications

Stress Distribution in Microregion of Core–Shell Structure Lightweight Aggregate Concrete

Stress Distribution in Microregion of Core–Shell Structure Lightweight Aggregate Concrete

Evaluation of Concrete Characteristics Using Smart Machine Learning Techniques—A Review

A New Formulation to Estimate the Elastic Modulus of Recycled Concrete Based on Regression and ANN

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