The process of 3D Cementitious Material Printing (3DCMP) is widely used to create complex geometries in buildings and structures of various sizes. Printing through material deposition is the basis of extrusion technology and it is highly productive, labor-efficient, and cost-effective. Unlike polymeric materials, the behavior of cement-based materials has very little sensitivity to temperature, and it necessitates adjustment of the printing speed and geometry to the solidification rate of the cement material, which is controlled by the cement hydration. However, even though many rheological models are devised to address the mechanical properties of cement-based materials, still the 3DCMP process is laced with many variations and faces structural failures. In this work, we employ a case study approach to examine natural and non-natural variations occurring in two process responses, i.e., static and dynamic yield stresses. The static RDPP-SF method is combined with the GRA technique to find out the most robust combination of the input factors leading to the lesser variation of the process responses.

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Use of the RDPP-SF Method to Analyze Rheology Variation in an Am-Cement-Based Process

  • Marwen Amdouni,
  • Helmi Nasraoui,
  • Mohamed Ali Rezgui,
  • Ali Trabelsi

摘要

The process of 3D Cementitious Material Printing (3DCMP) is widely used to create complex geometries in buildings and structures of various sizes. Printing through material deposition is the basis of extrusion technology and it is highly productive, labor-efficient, and cost-effective. Unlike polymeric materials, the behavior of cement-based materials has very little sensitivity to temperature, and it necessitates adjustment of the printing speed and geometry to the solidification rate of the cement material, which is controlled by the cement hydration. However, even though many rheological models are devised to address the mechanical properties of cement-based materials, still the 3DCMP process is laced with many variations and faces structural failures. In this work, we employ a case study approach to examine natural and non-natural variations occurring in two process responses, i.e., static and dynamic yield stresses. The static RDPP-SF method is combined with the GRA technique to find out the most robust combination of the input factors leading to the lesser variation of the process responses.