Impact of the properties of old mortar on creep prediction model of recycled aggregate concrete

Fan, Yongzhe; Niu, Haicheng; Zhang, Xianggang

doi:10.1016/j.conbuildmat.2019.117772

Cited by 13 publications

(6 citation statements)

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“…The establishment of a creep value database of recycled concrete is crucial for accurately revealing the mechanism of RAC creep and precisely comparing the predictions of RAC creep models. Therefore, in this paper, the existing literature on recycled concrete creep has been summarized and analyzed, and the creep test data of recycled concrete, 37,38,42,43,49,62,63,[70][71][72][73][74][75][76][77][78][79][80][81][82][83][84] featuring 106 groups and 1309 data points, were acquired to establish a RAC creep database, as listed in Table 3. The selection principle was that when selecting the test points, the abscissa time axis is roughly divided into 10 parts, and a test point was selected for every 1/10 increase in the test termination time.…”

Section: Data Collectionmentioning

confidence: 99%

Prediction of creep of recycled aggregate concrete using back‐propagation neural network and support vector machine

Rong

Liu

Chen

et al. 2022

Structural Concrete

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The promotion of recycled aggregate concrete (RAC) can effectively reduce carbon emissions from the construction industry and increase the recycling rate of waste concrete. Owing to the significantly higher creep of RAC than that of natural aggregate concrete (NAC), the accurate prediction of long-term RAC creep deformation is vital. Therefore, a predictive model for RAC is investigated in this study. A creep database of RAC with 106 groups of 1309 experimental data points considering 15 influencing parameters is established. Furthermore, back-propagation neural network (BPNN) and support vector machine (SVM) models are adopted to process and predict data. The accuracies of the prediction of the existing RAC creep, BPNN, and SVM models are comparatively analyzed. The results reveal that for the prediction of RAC creep, the BPNN and SVM models are more accurate than the existing RAC creep model. Finally, the extended parameters of the model are analyzed based on the BPNN model to further clarify the effects of the recycled coarse aggregate (RCA) replacement ratio, RCA residual mortar content, and RAC strength on the creep properties of RAC.creep model, machine learning, recycled aggregate concrete Abbreviations: a/c, aggregate-to-cement ratio of the RAC; ANN, artificial neural network; BPNN, back-propagation neural network; E NAC , elastic moduli of NAC, MPa; E RAC , elastic moduli of RAC, MPa; f, ratio of fine aggregates (<4. 8 mm) to total aggregates; f c , concrete compressive strength, MPa; ITZ, interfacial transition zone; n, sustained stress level in concrete; NAC, natural aggregate concrete; NCA, natural coarse aggregate; r, replacement ratio of RCA in RAC; RAC, recycled aggregate concrete; RCA, recycled coarse aggregate; RH, relative humidity; RMC, residual mortar content of RCA; R NCA , replacement ratio of NCA in RAC; S, slump, mm; SVM, support vector machine; t, time, representing the age of concrete in days; t', age when drying begins, in days (only t 0 < t' is considered); t 0 , age at loading, in days; V/S, volume-to-surface ratio of RAC, mm; w/c, waterto-cement ratio of the RAC; w or /c or , water-to-cement ratio of source concrete used to produce RCA; φ(t,τ), creep coefficient of RAC.Discussion on this paper must be submitted within two months of the print publication. The discussion will then be published in print, along with the authors' closure, if any, approximately nine months after the print publication.

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Section: Data Collectionmentioning

confidence: 99%

Prediction of creep of recycled aggregate concrete using back‐propagation neural network and support vector machine

Rong

Liu

Chen

et al. 2022

Structural Concrete

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“…A fluência no concreto refere-se ao aumento da deformação ao longo do tempo sob tensões constantes, sendo uma das propriedades mais importantes do concreto, além de ser uma medida de durabilidade (FAN et al, 2020;AKONO et al, 2021). A fluência pode causar uma redistribuição de esforços internos em estruturas de concreto armado, causando deformações significativas em vigas de grande vão e pontes de concreto protendido, gerando riscos (SHEN et al, 2009;BAŽANT et al, 2011).…”

Section: Análise Dos Dados Publicadosunclassified

“…Na literatura tem sido demonstrado que o uso de ARC aumenta a fluência no concreto (LYE et al, 2016). A Figura 5 mostra os autores que mais publicaram sobre o assunto, sendo Jianzhuang Xiao (XIAO et al, 2012;XIAO et al, 2013;FAN et al, 2014;TAM et al, 2015;XIAO et al, 2015;ZHANG et al, 2021) o que mais se destaca, seguido por Vivian Tam (TAM et al, 2005;TAM e TAM, 2007;FAN et al, 2014;TAM et al, 2015;TAM et al, 2020) e Yuhui Fan (XIAO et al, 2012;XIAO et al, 2013;FAN et al, 2014;XIAO et al, 2015;FAN et al, 2020).…”

Section: Análise Dos Dados Publicadosunclassified

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Fluência de concreto com agregados reciclados: uma revisão

Rocha

Farias

2022

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A fluência é uma das propriedades mais importantes do concreto, mas o uso de Agregados Reciclados de Concreto (ARC) pode afetar significativamente essa propriedade. Neste sentido, o objetivo do presente artigo foi realizar uma revisão da literatura sobre a fluência no concreto com ARC, considerando sua influência, causas e medidas de redução. A metodologia consistiu em uma Revisão Sistemática da Literatura (RSL) para o período de tempo de 2007 até 2021 (primeiro trimestre). Foram utilizadas diferentes bases de dados de busca de informação científica, limitando-se a artigos de revista e em língua inglesa. Os resultados mostram que o Agregado Graúdo Reciclado de Concreto (AGRC) é o mais utilizado nos estudos selecionados, aumentado a fluência com o grau de substituição do agregado natural; no entanto, não há uma tendência clara com Agregado Fino Reciclado de Concreto (AFRC), cujos resultados são limitados na literatura. Apresenta-se que a fluência depende de vários fatores como a relação a/c, idade da carga, etc. Entre a principais causas, a maioria dos estudos afirma que a fluência se deve à argamassa antiga aderida ao ARC, mas também algumas medidas são propostas para reduzir a fluência no concreto com ARC. Pode-se concluir que o uso de ARC é uma alternativa sustentável para a produção de concreto, mas são necessárias mais pesquisas para entender completamente a influência do ARC na fluência do concreto e consolidar seu uso para níveis industriais.

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“…And its peak tensile strain is higher than that of natural aggregate concrete. Extensive researches have been carried out on the recycled coarse aggregates of construction waste concrete after crushing, but there are few studies on the fine aggregates obtained by sieving, especially the modification of waste slurry [17,18].…”

Section: Introductionmentioning

confidence: 99%

Characterization of Mechanical Properties of Waste Slurry Modified by Recycled Sand and Cement

Lv¹,

Li²,

Kang³

et al. 2022

Journal of Renewable Materials

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In order to study the modification effect of recycled sand on cement reinforced waste slurry (CWS), triaxial test, scanning electron microscope test and X-ray diffraction test were carried out. The mechanical test of recycled sand and cement reinforced waste slurry (RCWS) shows that the deviatoric stress-strain curve of RCWS samples changes from hardening type to softening type with the increase of recycled sand content; the peak stress increases with the increase of recycled sand content; recycled sand can enhance the shear strength of CWS by increasing both cohesion and internal friction angle. The microscopic test shows that recycled sand can improve the structural compactness by cementing with hydrated calcium silicate and can reduce the void ratio and orientation index of RCWS samples. Finally, the mathematical model between shear strength parameters and void ratio is established. The research shows that adding an appropriate amount of recycled sand and cement has a good modification effect on waste slurry. This is an effective method to treat two kinds of construction wastes: construction waste slurry and waste concrete.

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Impact of the properties of old mortar on creep prediction model of recycled aggregate concrete

Cited by 13 publications

References 12 publications

Prediction of creep of recycled aggregate concrete using back‐propagation neural network and support vector machine

Prediction of creep of recycled aggregate concrete using back‐propagation neural network and support vector machine

Fluência de concreto com agregados reciclados: uma revisão

Characterization of Mechanical Properties of Waste Slurry Modified by Recycled Sand and Cement

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