{"title":"Optimization techniques for mortars with self-compacting characteristics through Central Composite Design","authors":"Stéphanie Oliveira Nina Rocha, Lino Maia","doi":"10.24840/2183-6493_009-004_002166","DOIUrl":null,"url":null,"abstract":"The demand for concrete production for civil construction promotes an investment by researchers and builders to find methodologies that improve their performance, the costs and less environmental degradation. Self-compacting concrete works it possible to offer a mixture with high flowability and compaction and good mechanical properties. For a better optimization of the mixtures, the statistical tool Design of Experiments (DoE) was used. Therefore, the objective of this research was to optimize an experimental dataset of high strength self-compacting mortars, through statistical analysis, using the Response Surface Methodology (RSM) for a Central Composite Design (CCD). The results showed a strong correlation between the D-Flow and T-funnel response factors, when compared with CS14h and CS28d models that showed moderate significance. The input variable w/c was the most significant model. Numerical optimization solutions showed good accuracy and high compliance for low cost and environmental impact, maintaining high performance in fresh and hardened properties.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"U.Porto Journal of Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24840/2183-6493_009-004_002166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
The demand for concrete production for civil construction promotes an investment by researchers and builders to find methodologies that improve their performance, the costs and less environmental degradation. Self-compacting concrete works it possible to offer a mixture with high flowability and compaction and good mechanical properties. For a better optimization of the mixtures, the statistical tool Design of Experiments (DoE) was used. Therefore, the objective of this research was to optimize an experimental dataset of high strength self-compacting mortars, through statistical analysis, using the Response Surface Methodology (RSM) for a Central Composite Design (CCD). The results showed a strong correlation between the D-Flow and T-funnel response factors, when compared with CS14h and CS28d models that showed moderate significance. The input variable w/c was the most significant model. Numerical optimization solutions showed good accuracy and high compliance for low cost and environmental impact, maintaining high performance in fresh and hardened properties.