Mix proportion design method of recycled brick aggregate concrete based on aggregate skeleton theory

Ge, Pei; Huang, Wei; Zhang, Jiarui; Quan, Wenli; Guo, Yuting

doi:10.1016/j.conbuildmat.2021.124584

Cited by 31 publications

(7 citation statements)

References 55 publications

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“…At present, the demolition of waste buildings in the brick structure and masonry structure accounted for a considerable proportion, research shows that [5][6][7] the main components of construction solid waste for waste concrete and waste brick, of which waste concrete accounted for 41%, waste bricks accounted for up to 40% or more; and in small and mediumsized cities and rural areas, waste bricks accounted for a higher proportion of the even reached more than 70%. Therefore, in the face of the problem of solid waste utilization in construction, not only to deal with a large number of waste concrete, but also to solve a considerable number of waste bricks.…”

Section: Introductionmentioning

confidence: 98%

Review of Fracture Properties and Research Methods of Fiber Recycled Concrete

Tong

2024

AJST

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Aiming at the background of the application of fracture mechanics in fiber recycled concrete as well as the shortcomings of the current research, the relevant results and progress are summarized from three aspects, namely, the basic theory of fracture mechanics of fiber recycled concrete and the research progress of the fracture properties of fiber recycled concrete as well as the testing methods of the fracture of fiber recycled concrete, respectively. The development history of the application of fracture mechanics in concrete is described, three fracture forms, fracture process zones and three softening curve models of concrete are introduced, and it is proposed to combine the bilinear softening curve and the virtual crack zone model to construct the ontological relationship of the whole process of concrete cracking. The current research status of recycled brick aggregate concrete and polypropylene coarse fiber concrete is introduced. The incorporation of recycled brick aggregate adversely affects the workability, basic mechanical properties and fracture properties of concrete. The reinforcing effect of polypropylene fibers on concrete can effectively improve the adverse effects of brick aggregate on concrete, which opens up the research prospect of green concrete and has high research value. The applications of three-point bending test, four-point bending test and DIC technique in the study of concrete fracture characteristics are introduced.

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Section: Introductionmentioning

confidence: 98%

Review of Fracture Properties and Research Methods of Fiber Recycled Concrete

Tong

2024

AJST

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“…In recent years, vegetation lightweight porous concrete (VLPC) has emerged as an innovative integration of traditional concrete technology with the advantages of horticulture [ 1 , 2 ]. VLPC boasts a considerable pore volume and a distinctive pore structure [ 3 , 4 , 5 , 6 ], resulting in enhanced water permeability [ 7 ], efficient heat dissipation capacity [ 8 ], and notable sound absorption capability [ 9 ]. These inherent characteristics render VLPC highly valuable for mitigating urban waterlogging [ 10 ], minimizing noise pollution [ 11 ], and fostering urban ecological development.…”

Section: Introductionmentioning

confidence: 99%

Study on the Preparation and Properties of Vegetation Lightweight Porous Concrete

Cao,

Zhou,

et al. 2024

Materials

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The objective of this study is to formulate vegetated light porous concrete (VLPC) through the utilization of various cementing materials, the design of porosity, and the incorporation of mineral additives. Subsequently, the study aims to assess and analyze key properties, including the bulk density, permeability coefficient, mechanical characteristics, and alkalinity. The findings indicate a linear decrease in the volume weight of VLPC as the designed porosity increases. While higher design porosity elevates the permeability coefficient, the measured effective porosity closely aligns with the design values. The examined VLPC exhibits a peak compressive strength of 17.7 MPa and a maximum bending strength of 2.1 MPa after 28 days. Notably, an escalation in porosity corresponds to a decrease in both the compressive and the bending strength of VLPC. Introducing mineral additives, particularly silicon powder, is shown to be effective in enhancing the strength of VLPC. Furthermore, substituting slag sulfonate cement for ordinary cement significantly diminishes the alkalinity of VLPC, resulting in a pH below 8.5 at 28 days. Mineral additives also contribute to a reduction in the pH of concrete. Among them, silica fume, fly ash, fly ash + slag powder, and slag powder exhibit a progressively enhanced alkaline reduction effect.

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“…At present, there are substantial experimental, numerical and theoretical studies on the strength of RAC. Researchers proposed methods based on aggregate skeleton theory, gray correlation analysis, finite element analysis and so on to predict the compressive strength of RAC and analyze its influencing factors [ 4 , 5 , 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Ensemble Machine-Learning-Based Prediction Models for the Compressive Strength of Recycled Powder Mortar

et al. 2023

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Recycled powder (RP) serves as a potential and prospective substitute for cementitious materials in concrete. The compressive strength of RP mortar is a pivotal factor affecting the mechanical properties of RP concrete. The application of machine learning (ML) approaches in the engineering problems, particularly for predicting the mechanical properties of construction materials, leads to high prediction accuracy and low experimental costs. In this study, 204 groups of RP mortar compression experimental data are collected from the literature to establish a dataset for ML, including 163 groups in the training set and 41 groups in the test set. Four ensemble ML models, namely eXtreme Gradient-Boosting (XGBoost), Random Forest (RF), Light Gradient-Boosting Machine (LightGBM) and Adaptive Boosting (AdaBoost), were selected to predict the compressive strength of RP mortar. The comparative results demonstrate that XGBoost has the highest prediction accuracy when the a10-index, MAE, RMSE and R2 of the training set are 0.926, 1.596, 2.155 and 0.950 and the a10-index, MAE, RMSE and R2 of the test set are 0.659, 3.182, 4.285 and 0.842, respectively. SHapley Additive exPlanation (SHAP) is adopted to interpret the prediction process of XGBoost and explain the influence of influencing factors on the compressive strength of RP mortar. According to the importance of influencing factors, the order is the mass replacement rate of RP, the size of RP, the kind of RP and the water binder ratio of RP. The compressive strength of RP mortar decreases with the increase in the RP mass replacement rate. The compressive strength of RBP mortar is slightly higher than that of RCP mortar. Machine learning technologies will benefit the construction industry by facilitating the rapid and cost-effective evaluation of RP material properties.

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Mix proportion design method of recycled brick aggregate concrete based on aggregate skeleton theory

Cited by 31 publications

References 55 publications

Review of Fracture Properties and Research Methods of Fiber Recycled Concrete

Review of Fracture Properties and Research Methods of Fiber Recycled Concrete

Study on the Preparation and Properties of Vegetation Lightweight Porous Concrete

Ensemble Machine-Learning-Based Prediction Models for the Compressive Strength of Recycled Powder Mortar

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