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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Mollah, Md. Tusher
Technical University of Denmark
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (17/17 displayed)
- 2024Numerical modeling of fiber orientation in multi-layer, isothermal material-extrusion big area additive manufacturingcitations
- 2024Optimization of core groove geometry for the manufacture and operation of composite sandwich structures in wind turbine blades
- 2024Computational fluid dynamics modelling of vacuum-assisted resin infusion in composite sandwich panels during wind turbine blade manufacturing
- 2024Rheology and printability of cement paste modified with filler from manufactured sand
- 2023Modeling fiber orientation and strand shape morphology in three-dimensional material extrusion additive manufacturingcitations
- 2023Computational analysis of yield stress buildup and stability of deposited layers in material extrusion additive manufacturingcitations
- 2023Computational Fluid Dynamics Modelling and Experimental Analysis of Material Extrusion Additive Manufacturing
- 2023Numerical modeling of fiber orientation in additively manufactured compositescitations
- 2022Modelling Fiber Orientation During Additive Manufacturing-Compression Molding Processes
- 2022Modelling Fiber Orientation During Additive Manufacturing-Compression Molding Processes
- 2022Modelling of Additive Manufacturing - Compression Molding Process Using Computational Fluid Dynamics
- 2022Modelling of Additive Manufacturing - Compression Molding Process Using Computational Fluid Dynamics
- 2022Numerical Predictions of Bottom Layer Stability in Material Extrusion Additive Manufacturingcitations
- 2022A Numerical Investigation of the Inter-Layer Bond and Surface Roughness during the Yield Stress Buildup in Wet-On-Wet Material Extrusion Additive Manufacturing
- 2022A Numerical Investigation of the Inter-Layer Bond and Surface Roughness during the Yield Stress Buildup in Wet-On-Wet Material Extrusion Additive Manufacturing
- 2021Stability and deformations of deposited layers in material extrusion additive manufacturingcitations
- 2021Numerical simulation of multi-layer 3D concrete printingcitations
Places of action
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document
Rheology and printability of cement paste modified with filler from manufactured sand
Abstract
Manufactured sand is increasingly used in concrete production. We study the effects of substituting parts of the binder with manufactured filler (particle size 0.04 - 0.250 mm) on the printability of cement paste experimentally and numerically. An experimental program explored water-to-binder ratios of 0.4 and filler-to-binder mass ratios fi/b = 0.15 - 0.85. The study investigated suspension properties and rheology like maximum packing, mini-slump, plastic viscosity, and yield stress. Printability, on a lab scale, was observed by printer flow measurements (“extrudability”) and buildability (shape retention, deformation layer adhesion, deformation, macro voids). Additionally, a computational fluid dynamics model (CFD) is developed to simulate the 3D printing of the filler-modified cement paste and assess its printability. Results show that as maximum packing increases, slump flow (yield stress) decreases as expected. The best shape retention and layer adhesion were found in mixes with maximum packing = 0.94, 0.96, and 0.98. The mix with the highest yield stress showed the best shape retention but had more macro voids in the cross-section and rougher surfaces. To confirm the accuracy of the CFD model, the cross-sectional shapes of the deposited part from simulations are compared with the printed ones. It seems more work is needed to get a good correlation with the same process parameters.