Experimental study on long-term compressive strength of concrete with manufactured sand

Ding, Xinxin; Li, Changyong; Xu, Yangyang; Li, Fenglan; Zhao, Shunbo

doi:10.1016/j.conbuildmat.2016.01.028

Cited by 116 publications

(49 citation statements)

References 20 publications

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“…For other curing ages such as 14, 60, 70, 84, 90 and 180, the number of samples is lower than 10 and thus not be considered in the comparison. In Table 6, ∆ is the deviation (in %) of performance indicators between the present work ANFIS-TLBO/P model and Ding et al [14]. Noting that the values of ∆ with respect to R and slope were calculated based on the deviation around 1, whereas the values of ∆ corresponding to RMSE, MAE and Error Std were computed based on changes regarding zero, as indicated by the following equation:…”

Section: Comparison With Existing Models In the Literaturementioning

confidence: 99%

“…In this study, the target output is the compressive strength (both cubic and cylinder) of MSC at different curing ages ranging from 3 to 388 days. The database was collected from experimental tests in the available literature [14,[81][82][83]. A number of 289 MSC samples have been mixed by raw materials such as: (i) ordinary silicate cements; (ii) admixture consisted of fly ash, slag and silica fume; (iii) crushed stone and (iv) manufactured sand.…”

Section: Collection Of Datamentioning

confidence: 99%

“…In this section, the prediction performance of ANFIS-TLBO/P model is compared with existing formula in literature. In the work of Ding et al [14], an empirical equation has been proposed in order to estimate the MSC compressive strength based on the cement compressive strength at 28 days, the Figure 4b shows that the most three distinguished important input are curing age (I 3 ), following by fineness modulus of sand (I 6 ) and maximum diameter of crushed stone (I 4 ). The sand ratio (I 10 ), compressive strength of cement at 28 days (I 1 ), water to cement ratio (I 8 ), tensile strength of cement at 28 days (I 2 ) and water to binder ratio (I 7 ) form the second group of degree of importance.…”

Section: Comparison With Existing Models In the Literaturementioning

confidence: 99%

“…In this section, the prediction performance of ANFIS-TLBO/P model is compared with existing formula in literature. In the work of Ding et al [14], an empirical equation has been proposed in order to estimate the MSC compressive strength based on the cement compressive strength at 28 days, the cement density and the water to cement ratio. Table 6 indicates the value of performance indicators such as R, RMSE, MAE, Error standard deviation and slope, using ANFIS-TLBO/P and the formula proposed by Ding et al [14].…”

Section: Comparison With Existing Models In the Literaturementioning

confidence: 99%

“…In the literature, many works have focused on the quantification of how the concrete workability and durability could be influenced by using manufactured sand [6,12], especially its compressive behavior [1,11,[13][14][15]. In a series of papers, Shen et al [3,13] have identified the influence of the shape of manufactured sand and roughness on the concrete compressive strength based on digital image analysis and experimental compression tests.…”

Section: Introductionmentioning

confidence: 99%

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Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete

Pham

Dao

et al. 2019

Applied Sciences

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Use of manufactured sand to replace natural sand is increasing in the last several decades. This study is devoted to the assessment of using Principal Component Analysis (PCA) together with Teaching-Learning-Based Optimization (TLBO) for enhancing the prediction accuracy of individual Adaptive Neuro Fuzzy Inference System (ANFIS) in predicting the compressive strength of manufactured sand concrete (MSC). The PCA technique was applied for reducing the noise in the input space, whereas, TLBO was employed to increase the prediction performance of single ANFIS model in searching the optimal weights of input parameters. A number of 289 configurations of MSC were used for the simulation, especially including the sand characteristics and the MSC long-term compressive strength. Using various validation criteria such as Correlation Coefficient (R), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE), the proposed method was validated and compared with several models, including individual ANFIS, Artificial Neural Networks (ANN) and existing empirical equations. The results showed that the proposed model exhibited great prediction capability compared with other models. Thus, it appeared as a robust alternative computing tool or an efficient soft computing technique for quick and accurate prediction of the MSC compressive strength.

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Section: Comparison With Existing Models In the Literaturementioning

confidence: 99%

Section: Collection Of Datamentioning

confidence: 99%

Section: Comparison With Existing Models In the Literaturementioning

confidence: 99%

“…In this section, the prediction performance of ANFIS-TLBO/P model is compared with existing formula in literature. In the work of Ding et al [14], an empirical equation has been proposed in order to estimate the MSC compressive strength based on the cement compressive strength at 28 days, the cement density and the water to cement ratio. Table 6 indicates the value of performance indicators such as R, RMSE, MAE, Error standard deviation and slope, using ANFIS-TLBO/P and the formula proposed by Ding et al [14].…”

Section: Comparison With Existing Models In the Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete

Pham

Dao

et al. 2019

Applied Sciences

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Plastic settlement and hardened state assessments of manufactured sand made concrete for varying microfine levels

Arulmoly

Konthesingha

Nanayakkara

2022

Structural Concrete

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Manufactured sand (MS) has been started utilizing as an alternative in constructions due to the escalated demand for river sand (RS). The microfine aggregate (MFA) is a salient constituent in manufactured sand, which is a crushed reactive form of parent rocks having particles less than 0.075 mm. This paper presents the effects of varying microfine aggregate levels on bleeding, plastic shrinkage cracking (PSC) and compressive strength of MS made concrete. Two types of MS were utilized: MS from Hornblende‐Gneiss rock (MH) and MS from Charnockite rock (MC) and the MFA level was ranged from 0% to 12% at 3% increments and the reference concrete was prepared with RS alone. With the MFA levels, the bleeding of MS concretes was reduced where, at 0% MFA level the maximum bleeding rates were observed for MC (1.63 kg/m2) and MH (0.84 kg/m2) concretes. PSC results were analyzed from an image processing technique, which revealed an increasing trend of mean and maximum crack widths, crack length and crack area with the MFA levels. At 0% MFA, the mean crack width of MC (0.19 mm) and MH (0.17 mm) concretes manifested marginally similar to RS concrete (0.17 mm). The decreasing bleeding with the MFA levels can be attributed to the increasing severity to PSC. Moreover, the optimum 28 days compressive strength of MC (57.5 MPa) and MH (56.1 MPa) concretes was achieved at 3% MFA level which are higher than RS concrete (51.5 MPa). Consequently, the MFA level should be limited to 3% for better plastic and hardened performance of MS made concrete.

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Alternative Fine Aggregates to Produce Sustainable Self Compacting Concrete: A Review

Bazaz

Punia

Sharma

2022

Proceedings of International Conference on Innovative Technologies for Clean and Sustainable Development (ICITCSD – 2021)

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Experimental study on long-term compressive strength of concrete with manufactured sand

Cited by 116 publications

References 20 publications

Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete

Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete

Plastic settlement and hardened state assessments of manufactured sand made concrete for varying microfine levels

Alternative Fine Aggregates to Produce Sustainable Self Compacting Concrete: A Review

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