A comprehensive analysis of buildability of 3D-printed concrete and the use of bi-linear stress-strain criterion-based failure curves towards their prediction
A comprehensive analysis of buildability of 3D-printed concrete and the use of bi-linear stress-strain criterion-based failure curves towards their prediction
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DOI：
10.1016/j.cemconcomp.2022.104424
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发表时间：
2022-02-01
影响因子：
10.5
通讯作者：
Neithalath，Narayanan
中科院分区：
文献类型：
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作者：
Tripathi，Avinaya;Nair，Sooraj A. O.;Neithalath，Narayanan
胶凝材料的可建造性，以及其可挤压性，决定了用于混凝土3D打印的混凝土混合物的可打印性。可构造性被定义为印刷过程中失败的临界高度，是材料属性(与时间相关)、灯丝尺寸和印刷几何形状的函数。这项研究采用了一种新的方法来评估3D打印混凝土的可建性，方法包括：(I)对从3D打印棱柱(而不是铸造圆柱体)提取的圆柱体在从搅拌到屈服点的不同时间进行改进的绿色压缩试验(GCT)，以提取直到屈服点的双线性应力-应变响应，并根据该试验得出材料特性；(Ii)考虑材料破坏(例如塑性崩溃)或失稳(例如屈曲/破坏)的模型，使用GCT改进的材料参数(弹性和初始塑性屈服应力和模数)。利用由不同破坏模型预测的不同时刻的破坏高度下界，绘制了不同3D可打印砂浆混合料的破坏曲线。实验室规模的壁面和中空圆柱体单元打印结果表明，该模型可以很好地预测失效高度。准确预测临界(故障)高度的能力使优化材料设计和印刷工艺的控制得到加强。
The buildability of cementitious materials, along with its extrudability, determines the printability of the concrete mixtures used in 3D printing of concrete. Buildability, defined as the critical height to failure during printing, is a function of the material properties (time-dependent), filament dimensions, and print geometry. This study employs a novel approach to evaluate the buildability of 3D printed concrete using a combination of: (i) modified green compression test (GCT) carried out on cylinders extracted from 3D printed prisms (in lieu of cast cylinders) at different times from mixing to extract a bi-linear stress-strain response until the yield point, from which material properties are deduced, and (ii) models considering material failure (e.g., plastic collapse) or instability (e.g., buckling/crippling) that employ refined material parameters (elastic and initial plastic yield stresses and moduli) from GCT. Failure curves are developed for different 3D printable mortar mixtures using the lower bounds of failure heights at different times predicted by the different failure models. Laboratory-scale printing of wall and hollow cylinder elements showed that the models can adequately predict failure heights. The ability to accurately predict critical (failure) height enables enhanced control in optimizing the material design and printing process.