Shear Performance in Reinforced Concrete Beams with Partial Aggregate Substitution Using Waste Glass: A Comparative Analysis via Digital Imaging Processing and a Theoretical Approach.

The usage of waste glass aggregate (WGA) associated with the replacement of fine aggregate (FA) and coarse aggregate (CA) is observed to reduce the number of raw materials for sustainable concrete. For this aim, a total of 15 beams were produced, and then investigational experiments were implemented to observe the shear performances. The stirrup spacing and WGA proportion were chosen as the main parameters.

Analysis of the Current State of Research on Bio-Healing Concrete (Bioconcrete).

The relatively small tensile strength of concrete makes this material particularly vulnerable to cracking. However, the reality is that it is not always possible and practically useful to conduct studies on high-quality sealing cracks due to their inaccessibility or small opening width. Despite the fact that currently there are many technologies for creating self-healing cement composites, one of the most popular is the technology for creating a biologically active self-healing mechanism for concrete.

The Influence of Three-Dimensionally Printed Polymer Materials as Trusses and Shell Structures on the Mechanical Properties and Load-Bearing Capacity of Reinforced Concrete.

Three-dimensional printing technology (3D printing) is becoming a more and more popular technology for aerospace, biology, medicine, mechanics, civil and other engineering fields. In civil engineering, researchers and engineers attempt to print construction materials such as concrete using 3D-printing technology. This study aims to investigate the reinforcement of concrete beams with 3D printing.

Computer Vision Method for Automatic Detection of Microstructure Defects of Concrete.

The search for structural and microstructural defects using simple human vision is associated with significant errors in determining voids, large pores, and violations of the integrity and compactness of particle packing in the micro- and macrostructure of concrete. Computer vision methods, in particular convolutional neural networks, have proven to be reliable tools for the automatic detection of defects during visual inspection of building structures. The study's objective is to create and compare computer vision algorithms that use convolutional neural networks to identify and analyze damaged sections in concrete samples from different structures.

Influence of ceramic waste powder on shear performance of environmentally friendly reinforced concrete beams.

This investigation considered the usability of ceramic waste powder (CWP) in altered quantities in reinforced concrete beams (RCBs). In this way, it was aimed to reduce the environmental impacts of concrete by using CWP as a raw material in RCBs. 12 small-scale shear RCBs with the dimensions of 100 × 150 × 1000 mm were tested in this study.