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Effect of Curing Methods on Shrinkage Development in 3D-Printed Concrete.

ABSTRACT: Technological developments in construction have led to an increase in the use of 3D modelling using CAD environments. The popularity of this approach has increased in tandem with developments in industry branches which use 3D printers to print concrete based printing materials in construction, as these allow freedom in shaping the dimensions of supporting elements. One of the biggest challenges for researchers working on this highly innovative technology is that of cement material shrinkage. This article presents the findings of research on an original method of measuring deformations caused by shrinkage in 3D-printed concrete elements. It also discusses the results of tests on base mixes, as well as comparisons between the influence of internal and external curing methods on the development of deformations and their final outcomes. Furthermore, the article discusses differences between deformations formed after seven days of hardening without curing, with those which occur when two common, traditional concrete curing methods are used: foil insulation and shrinkage reducing admixtures. In addition, the article examines the effects of internal curing on the 1, 7, 14, 21 and 28 day mechanical properties of concrete, in accordance with EN 196-1 and EN 12390-2. Studies have shown that the optimal amount of shrinkage reducing admixtures is 4% (in relation to the mass of cement), resulting in a reduction in total shrinkage of 23%. The use of a shrinkage reducing admixture in 3D-printed concrete does not affect their strength after 28 days, but slows the strength development during the first 7 days.

SUBMITTER: Federowicz K

PROVIDER: S-EPMC7321559 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Effect of Curing Methods on Shrinkage Development in 3D-Printed Concrete.

Federowicz Karol K Kaszyńska Maria M Zieliński Adam A Hoffmann Marcin M

Materials (Basel, Switzerland) 20200606 11

Technological developments in construction have led to an increase in the use of 3D modelling using CAD environments. The popularity of this approach has increased in tandem with developments in industry branches which use 3D printers to print concrete based printing materials in construction, as these allow freedom in shaping the dimensions of supporting elements. One of the biggest challenges for researchers working on this highly innovative technology is that of cement material shrinkage. Thi ...[more]

PMID: 32517173

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Project description:The additive manufacturing of concrete, also known as 3D-printed concrete, is produced layer by layer using a 3D printer. The three-dimensional printing of concrete offers several benefits compared to conventional concrete construction, such as reduced labor costs and wastage of materials. It can also be used to build complex structures with high precision and accuracy. However, optimizing the mix design of 3D-printed concrete is challenging, involving numerous factors and extensive hit-and-trail experimentation. This study addresses this issue by developing predictive models, such as the Gaussian Process Regression model, Decision Tree Regression model, Support Vector Machine model, and XGBoost Regression models. The input parameters were water (Kg/m3), cement (Kg/m3), silica fume (Kg/m3), fly ash (Kg/m3), coarse aggregate (Kg/m3 & mm for diameter), fine aggregate (Kg/m3 & mm for diameter), viscosity modifying agent (Kg/m3), fibers (Kg/m3), fiber properties (mm for diameter and MPa for strength), print speed (mm/sec), and nozzle area (mm2), while target properties were the flexural and tensile strength of concrete (MPa data from 25 literature studies were collected. The water/binder ratio used in the dataset ranged from 0.27 to 0.67. Different types of sands and fibers have been used, with fibers having a maximum length of 23 mm. Based upon the Coefficient of Determination (R2), Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Error (MAE) for casted and printed concrete, the SVM model performed better than other models. All models' cast and printed flexural strength values were also correlated. The model's performance has also been checked on six different mix proportions from the dataset to show its accuracy. It is worth noting that the lack of ML-based predictive models for the flexural and tensile properties of 3D-printed concrete in the literature makes this study a novel innovation in the field. This model could reduce the computational and experimental effort required to formulate the mixed design of printed concrete.

Dataset Information

Effect of Curing Methods on Shrinkage Development in 3D-Printed Concrete.

Publications

Effect of Curing Methods on Shrinkage Development in 3D-Printed Concrete.

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