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DoE Approach to Setting Input Parameters for Digital 3D Printing of Concrete for Coarse Aggregates up to 8 mm

This paper is primarily concerned with determining and assessing the properties of a cement-based composite material containing large particles of aggregate in digital manufacturing. The motivation is that mixtures with larger aggregate sizes offer benefits such as increased resistance to cracking,...

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Detalles Bibliográficos
Autores principales: Vespalec, Arnošt, Podroužek, Jan, Koutný, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179870/
https://www.ncbi.nlm.nih.gov/pubmed/37176300
http://dx.doi.org/10.3390/ma16093418
Descripción
Sumario:This paper is primarily concerned with determining and assessing the properties of a cement-based composite material containing large particles of aggregate in digital manufacturing. The motivation is that mixtures with larger aggregate sizes offer benefits such as increased resistance to cracking, savings in other material components (such as Portland cement), and ultimately cost savings. Consequently, in the context of 3D Construction/Concrete Print technology (3DCP), these materials are environmentally friendly, unlike the fine-grained mixtures previously utilized. Prior to printing, these limits must be established within the virtual environment’s process parameters in order to reduce the amount of waste produced. This study extends the existing research in the field of large-scale 3DCP by employing coarse aggregate (crushed coarse river stone) with a maximum particle size of 8 mm. The research focuses on inverse material characterization, with the primary goal of determining the optimal combination of three monitored process parameters—print speed, extrusion height, and extrusion width—that will maximize buildability. Design Of Experiment was used to cover all possible variations and reduce the number of required simulations. In particular, the Box—Behnken method was used for three factors and a central point. As a result, thirteen combinations of process parameters covering the area of interest were determined. Thirteen numerical simulations were conducted using the Abaqus software, and the outcomes were discussed.