Discrete element modelling of mechanical behaviour of pervious concrete

Pieralisi, Ricardo; Cavalaro, Sérgio Henrique Pialarissi; Aguado, Antonio

doi:10.1016/j.cemconcomp.2021.104005

Cited by 21 publications

(3 citation statements)

References 37 publications

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“…11a). The most decisive factor is the loose compactness of the CDW aggregates in the pervious concrete system (Pieralisi et al, 2021;Yang et al, 2021). Unlike ordinary concrete that must experience vibrations during specimen casting to enhance the compactness and expel the air voids out of the cement matrix, pervious concrete with severe vibrations was not recommended in order to prevent pore clogging caused by the sinking of paste (Cui et al, 2020).…”

Section: Discussion Of Mechanismsmentioning

confidence: 99%

Total recycling of low-quality urban-fringe construction and demolition waste towards the development of sustainable cement-free pervious concrete: The proof of concept

Zeng

Jike

et al. 2022

Journal of Cleaner Production

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Section: Discussion Of Mechanismsmentioning

confidence: 99%

Total recycling of low-quality urban-fringe construction and demolition waste towards the development of sustainable cement-free pervious concrete: The proof of concept

Zeng

Jike

et al. 2022

Journal of Cleaner Production

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“…Dry shrinkage and brittleness are outstanding problems with the concrete in road bridges. The components with seams also suffer from durability problems like rebar corrosion, strength degradation, surface cracking, and peeling, which arise from carbonation, chloride ion penetration, and multiple freezethaw cycles [4,5]. To solve these problems, a common practice is to mix fibers into the concrete for road bridges.…”

Section: Introductionmentioning

confidence: 99%

Physical Properties and Durability of Green Fiber-Reinforced Concrete for Road Bridges

Ma¹

2021

ACSM

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Dry shrinkage and brittleness are outstanding problems with the concrete in road bridges. However, the road bridge concrete has not been systematically studied. No research has fully considered the influence of age on the physical-mechanical properties of road bridge concrete. There are few reports on how the green fiber dosage affects road bridge concrete. This paper analyzes the physical properties and durability of green fiber-reinforced concrete for road bridges (RBGFRC). Firstly, calculation methods were provided for physical-mechanical properties of RBGFRC, such as crack resistance, shear capacity of oblique section, and bending capacity of normal section. Next, the physical-mechanical properties of RBGFRC were investigated in terms of flexural strength, compressive strength, splitting tensile strength, and early cracking strength; the durability of the material was discussed from three aspects: carbonation resistance, resistance to freeze-thaw cycles, and porosity. Experimental results verify the good physical properties and durability of RBGFRC. The research provides a reference for applying RBGFRC in other scenarios.

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“…Furthermore, when changes occur in actual engineering conditions, extensive laboratory tests are required to re-evaluate the hydromechanical properties of materials, causing significant financial and labor investments. In light of this deficiency, a variety of alternative methods have been employed to evaluate the mechanical strength and infiltration properties of pervious concrete, including the random lattice discrete particle method 37 , discrete element method (DEM) [38][39][40] , finite element method (FEM) 41,42 , computational fluid dynamics (CFD) method 43 , and other self-developed numerical simulation methods [44][45][46] . The aim of these methods is to reduce the expenses associated with laboratory tests and expedite the material design process.…”

mentioning

confidence: 99%

Kriging-based surrogate data-enriching artificial neural network prediction of strength and permeability of permeable cement-stabilized base

Wang,

Xiao,

et al. 2024

Nat Commun

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Limited test data hinder the accurate prediction of mechanical strength and permeability of permeable cement-stabilized base materials (PCBM). Here we show a kriging-based surrogate model assisted artificial neural network (KS-ANN) framework that integrates laboratory testing, mathematical modeling, and machine learning. A statistical distribution model was established from limited test data to enrich the dataset through the combination of markov chain monte carlo simulation and kriging-based surrogate modeling. Subsequently, an artificial neural network (ANN) model was trained using the enriched dataset. The results demonstrate that the well-trained KS-ANN model effectively captures the actual data distribution characteristics. The accurate prediction of the mechanical strength and permeability of PCBM under the constraint of limited data validates the effectiveness of the proposed framework. As compared to traditional ANN models, the KS-ANN model improves the prediction accuracy of PCBM’s mechanical strength by 21%. Based on the accurate prediction of PCBM’s mechanical strength and permeability by the KS-ANN model, an optimization function was developed to determine the optimal cement content and compaction force range of PCBM, enabling it to concurrently satisfy the requirements of mechanical strength and permeability. This study provides a cost-effective and rapid solution for evaluating the performance and optimizing the design of PCBM and similar materials.

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Discrete element modelling of mechanical behaviour of pervious concrete

Cited by 21 publications

References 37 publications

Total recycling of low-quality urban-fringe construction and demolition waste towards the development of sustainable cement-free pervious concrete: The proof of concept

Total recycling of low-quality urban-fringe construction and demolition waste towards the development of sustainable cement-free pervious concrete: The proof of concept

Physical Properties and Durability of Green Fiber-Reinforced Concrete for Road Bridges

Kriging-based surrogate data-enriching artificial neural network prediction of strength and permeability of permeable cement-stabilized base

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