Civil Engineering ETDs
Publication Date
Summer 7-30-2024
Abstract
Additive manufacturing, also known as 3D printing, has emerged as a promising technology that can revolutionize various industrial sectors. However, in 3D concrete printing proper control and management of the mix design proportions, rheology parameters, and effective reinforcing techniques are critical to ensure that the 3D printed material achieves the desired performance characteristics. This PhD dissertation is focused on the advancement of 3D-printed engineered cementitious composites (ECCs) with the specific goal of enhancing their structural capabilities and printability. The study emphasizes the function of methylcellulose (MC) as an additive that modifies the rheology of the ECC, demonstrating that its presence greatly improves the rheology characteristics and printability of ECCs. Various aspects were significantly enhanced as a consequence of the addition of MC. In particular, it resulted in a 28% increase in fiber dispersion, a 237% increase in static yield stress, and a 950% increase in plastic viscosity. Ultimately, these enhancements led to an increase in printing quality and dimensional accuracy of ECC.
In addition, the study examined the optimization of cementitious mixtures by utilizing biopolymers such as xanthan gum (XG) and corn starch (CCS) as viscosity modifying agents (VMAs). The research employed response surface methodology (RSM) to discover the most optimal combinations of these biopolymers that enhance rheology, green strength and printability.
The final phase of study aimed to improve the effectiveness of mix designs for 3D-printed concrete by employing machine learning methods. Ensemble machine learning models were utilized to create predictive tools that improve the rheological characteristics and printability of cementitious mixtures, surpassing the constraints of conventional optimization techniques and showcasing the capability of machine learning to achieve superior 3D printing results.
Keywords
3D Concrete Printing, Engineered Cementitious Composites, Response Surface Methodology, Machine Learning, Rheology
Document Type
Dissertation
Language
English
Degree Name
Civil Engineering
Level of Degree
Doctoral
Department Name
Civil Engineering
First Committee Member (Chair)
Maryam Hojati
Second Committee Member
Mahmoud Reda Taha
Third Committee Member
Xiang Sun
Fourth Committee Member
Francisco Uviña
Fifth Committee Member
Farid Javadnejad
Recommended Citation
Zafar, Muhammad Saeed. "Towards 3D Printed Concrete for Infrastructural Applications: Fresh properties, Printability, and Reinforcement." (2024). https://digitalrepository.unm.edu/ce_etds/346
