Evaluation of Workability and Structuration Rate of Locally Developed 3D Printing Concrete Using Conventional Methods

Abstract

Concrete 3D printing is a novel construction method that can bring new horizons to the construction industry. However, there are still many challenges that limit its capabilities. Despite the huge research efforts, to date, there are still no standardized acceptance criteria and guidelines for the evaluation of printing concrete. Therefore, the main objective of this research was to develop 3D printing mixes with different aggregate-to-binder (a/b) ratios (1.2, 1.5, and 1.8) and evaluate it in terms of its fresh printing properties, which include the workability, extrudability, setting time, open time, and buildability. The compressive strengths of cast and printed specimens were also tested to determine the effect of the layering process. The workability was evaluated using commonly used devices in the construction industry (slump and flow table test) and was monitored over time along with the penetration test to indicate the structuration rate of concrete. From the experimental results and observations, the flow test resulted in the best indication of the structuration rate (thixotropy) of concrete, followed by the penetration and slump tests. The a/b ratio affected all the investigated properties of the printing concrete. Higher a/b ratios resulted in increased structuration rate, buildability, and compressive strength of cast specimens. However, for printed specimens, the compressive strength decreased with the increase in a/b ratio due to increased thixotropy. Therefore, from the results of the present investigation, it can be concluded that high a/b ratios (>1.5) are not desirable for printing concrete.

Using Computer Vision for Monitoring the Quality of 3D-Printed Concrete Structures

“…Studying the workability changes with time will provide valuable information about the rheology and structural change rate of concrete [26]. In a previous study, three tests, namely, slump cone test, flow table test, and penetration test, were used to study the evolution of workability with time [27]. However, these tests cannot be performed during the printing process, so they cannot be used as real-time feedback to the system to make corrective actions.…”

Forecasting the Mechanical Properties of Plastic Concrete Employing Experimental Data Using Machine Learning Algorithms: DT, MLPNN, SVM, and RF

“…Concrete is a common building material that is composed of cement, fine aggregate, coarse aggregate, and water [1]. Because of its durability, increased strength, ease of use, and other advantageous features, concrete is widely employed as a construction material [2]. It has served as the foundation of modern existence.…”