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Bioinspired cellular cementitious structures for prefabricated construction: Hybrid design & performance evaluations

机译:用于预制结构的生物悬浮的细胞水泥结构:混合设计与性能评估

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摘要

Lightweight cellular structures with porous architectures and controllable mechanical characteristics are pro-mising candidates for a broad range of prefabricated engineering applications. A triply periodic minimal surface (TPMS) structure that is a naturally inspired continuous non-self-intersecting surface is a bioinspired cellular structure. In this work, we investigate a novel approach based on a combination of primitive-TPMS cells and cubic blocks along with lattice and gyroid-TPMS cells achieving 50% volume fraction cellular structures. Lightweight cellular specimens made of cement mortar with 3D printed sacrificial thermoplastic Polylactic Acid (PLA) moulds are subjected to uniaxial compressive loadings. Compression tests are carried out on the cement cubes, while tensile behaviours follow the simplified damage plasticity model, which is used to obtain the material properties for the input model data. Finite element (FE) analysis is employed to predict mechanical performances such as stress distributions, stress-strain curves, and the damage mechanisms of three representative cellular structures (primitive, lattice, and gyroid). Compressive experiment tests are conducted on these blocks and validated by the FE model. Results indicate that the mechanical responses of the cellular structure, wherein primitive cellular structures yield the highest compressive strength, could be predicted accurately through the FE analysis, and outcomes from both numerical models and experimental tests are validated.
机译:具有多孔架构和可控机械特性的轻质蜂窝结构是针对广泛预制工程应用的探索候选者。图三周期性最小表面(TPMS)结构是自然启发的连续非自相交表面是生物悬浮的细胞结构。在这项工作中,我们研究了一种基于原始TPMS细胞和立方块的组合以及晶格和陀螺仪的组合的新方法以及实现50%体积级分细胞结构的晶格和陀螺TPMS细胞。用3D印刷牺牲热塑性聚乳酸(PLA)模具的水泥砂浆制成的轻质蜂窝试样进行单轴压缩载荷。压缩测试在水泥立方体上进行,而拉伸行为遵循简化的损伤可塑性模型,其用于获得输入模型数据的材料特性。使用有限元(Fe)分析来预测应力分布,应力 - 应变曲线等机械性能,以及三种代表性蜂窝结构的损伤机制(原始,晶格和陀螺)。压缩实验测试在这些块上进行并由FE模型进行验证。结果表明,蜂窝结构的机械响应,其中原始蜂窝结构产生最高的抗压强度,可以通过FE分析准确预测,验证了来自数值模型和实验测试的结果。

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