Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate
The compressive strength of recycled concrete is acknowledged to be largely conditioned by the incorporation ratio of Recycled Concrete Aggregate (RCA), although that ratio needs to be carefully assessed to optimize the design of structural applications. In this study, Self-Compacting Concrete (SCC)...
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MDPI AG
2020-12-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/8/12/2190 |
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| author | Víctor Revilla-Cuesta Marta Skaf Ana B. Espinosa Amaia Santamaría Vanesa Ortega-López |
| author_facet | Víctor Revilla-Cuesta Marta Skaf Ana B. Espinosa Amaia Santamaría Vanesa Ortega-López |
| author_sort | Víctor Revilla-Cuesta |
| collection | DOAJ |
| description | The compressive strength of recycled concrete is acknowledged to be largely conditioned by the incorporation ratio of Recycled Concrete Aggregate (RCA), although that ratio needs to be carefully assessed to optimize the design of structural applications. In this study, Self-Compacting Concrete (SCC) mixes containing 100% coarse RCA and variable amounts, between 0% and 100%, of fine RCA were manufactured and their compressive strengths were tested in the laboratory for a statistical analysis of their strength variations, which exhibited robustness and normality according to the common statistical procedures. The results of the confidence intervals, the one-factor ANalysis Of VAriance (ANOVA), and the Kruskal–Wallis test showed that an increase in fine RCA content did not necessarily result in a significant decrease in strength, although the addition of fine RCA delayed the development of the final strength. The statistical models presented in this research can be used to define the optimum incorporation ratio that would produce the highest compressive strength. Furthermore, the multiple regression models offered accurate estimations of compressive strength, considering the interaction between the incorporation ratio of fine RCA and the curing age of concrete that the two-factor ANOVA revealed. Lastly, the probability distribution predictions, obtained through a log-likelihood analysis, fitted the results better than the predictions based on current standards, which clearly underestimated the compressive strength of SCC manufactured with fine RCA and require adjustment to take full advantage of these recycled materials. This analysis could be carried out on any type of waste and concrete, which would allow one to evaluate the same aspects as in this research and ensure that the use of recycled concrete maximizes both sustainability and strength. |
| first_indexed | 2024-03-10T14:13:25Z |
| format | Article |
| id | doaj.art-26f4cd2f8a7340f5a76ffa122aac9310 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T14:13:25Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-26f4cd2f8a7340f5a76ffa122aac93102023-11-20T23:59:49ZengMDPI AGMathematics2227-73902020-12-01812219010.3390/math8122190Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete AggregateVíctor Revilla-Cuesta0Marta Skaf1Ana B. Espinosa2Amaia Santamaría3Vanesa Ortega-López4Department of Civil Engineering, University of Burgos, 09001 Burgos, SpainDepartment of Construction, University of Burgos, 09001 Burgos, SpainDepartment of Construction, University of Burgos, 09001 Burgos, SpainDepartment of Mechanical Engineering, University of the Basque Country, 48013 Bilbao, SpainDepartment of Civil Engineering, University of Burgos, 09001 Burgos, SpainThe compressive strength of recycled concrete is acknowledged to be largely conditioned by the incorporation ratio of Recycled Concrete Aggregate (RCA), although that ratio needs to be carefully assessed to optimize the design of structural applications. In this study, Self-Compacting Concrete (SCC) mixes containing 100% coarse RCA and variable amounts, between 0% and 100%, of fine RCA were manufactured and their compressive strengths were tested in the laboratory for a statistical analysis of their strength variations, which exhibited robustness and normality according to the common statistical procedures. The results of the confidence intervals, the one-factor ANalysis Of VAriance (ANOVA), and the Kruskal–Wallis test showed that an increase in fine RCA content did not necessarily result in a significant decrease in strength, although the addition of fine RCA delayed the development of the final strength. The statistical models presented in this research can be used to define the optimum incorporation ratio that would produce the highest compressive strength. Furthermore, the multiple regression models offered accurate estimations of compressive strength, considering the interaction between the incorporation ratio of fine RCA and the curing age of concrete that the two-factor ANOVA revealed. Lastly, the probability distribution predictions, obtained through a log-likelihood analysis, fitted the results better than the predictions based on current standards, which clearly underestimated the compressive strength of SCC manufactured with fine RCA and require adjustment to take full advantage of these recycled materials. This analysis could be carried out on any type of waste and concrete, which would allow one to evaluate the same aspects as in this research and ensure that the use of recycled concrete maximizes both sustainability and strength.https://www.mdpi.com/2227-7390/8/12/2190self-compacting concrete (SCC)recycled concrete aggregate (RCA)RCA content optimizationrobustnessanalysis of variance (ANOVA)compressive strength prediction |
| spellingShingle | Víctor Revilla-Cuesta Marta Skaf Ana B. Espinosa Amaia Santamaría Vanesa Ortega-López Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate Mathematics self-compacting concrete (SCC) recycled concrete aggregate (RCA) RCA content optimization robustness analysis of variance (ANOVA) compressive strength prediction |
| title | Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate |
| title_full | Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate |
| title_fullStr | Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate |
| title_full_unstemmed | Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate |
| title_short | Statistical Approach for the Design of Structural Self-Compacting Concrete with Fine Recycled Concrete Aggregate |
| title_sort | statistical approach for the design of structural self compacting concrete with fine recycled concrete aggregate |
| topic | self-compacting concrete (SCC) recycled concrete aggregate (RCA) RCA content optimization robustness analysis of variance (ANOVA) compressive strength prediction |
| url | https://www.mdpi.com/2227-7390/8/12/2190 |
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