چكيده به لاتين
3D printing concrete technology has emerged as a revolutionary advancement in the construction industry in recent years, offering numerous advantages such as high construction speed, reduced labor requirements, compatibility with sustainable development goals, elimination of the need for molds, and the ability to create diverse geometric and architectural designs. Despite these significant benefits, this technology faces several challenges due to its nascent nature. One major challenge is developing a mix design with suitable fresh properties for 3D printing that can retain its shape under various loads after extrusion. Additionally, achieving sufficient early-age strength is critical, as this type of concrete is cured in open air without molds. On the other hand, achieving suitable hardened properties simultaneously with desirable fresh properties for 3D printed concretes is among the challenges that have been less addressed in previous research. Based on this, this thesis comprehensively investigated the simultaneous effects of halloysite nanotubes (HNT) and xanthan gum, alginate and chitosan biopolymers on fresh, hardened and microstructural properties of concrete that can be used in 3D printing by making 19 mixed designs. The results revealed a maximum reduction of 37.41% in flow table and 47.26% in setting time for samples containing halloysite nanotubes and biopolymers. When used in appropriate amounts, biopolymers and HNT improved shape stability and green strength by 93.29% and 4.5 times, respectively, compared to the control sample. The combined presence of HNT and biopolymers increased yield stress, thixotropy, and viscosity by up to 9.048, 4.15, and 4.77 times, respectively. In terms of mechanical properties, the optimal combination of HNT and biopolymers enhanced compressive strength, flexural strength, interlayer bond strength, and ultrasonic pulse velocity by 47.24%, 54.31%, 26.01%, and 15.38%, respectively, compared to the control sample. Furthermore, this combination significantly reduced sorptivity, water absorption, and gas porosity by 58.35%, 36.75%, and 61.57%, respectively. Moreover, the results of microstructural analysis showed a much denser microstructure of samples containing halloysite and appropriate percentages of biopolymers compared to the control sample. In the end, statistical analysis (analysis of variance, response surface method) and machine learning (gene expression programming method) were employed to evaluated experimental data. These analyses not only provided insights into the relationships between variables but also presented predictive formulas for the fresh and hardened properties of 3D printing concrete.
