Approximately 90% of the carbon footprint from concrete production is from portland cement (assuming portland cement is used as the sole cementitious binder). Therefore to reduce its carbon footprint, the amount of Portland cement clinker needs to be reduced. There are different ways of doing this, including optimization of combined aggregate gradations, use of water reducing admixtures, use of portland-limestone cements (PLC), and use of supplementary cementitious materials (SCMs). All of these measures can be taken simultaneously, but there is also concern that extreme measures (such as high SCM replacement levels) will reduce the robustness of concrete to abuse during construction, resulting in lower durability. Durability is important to obtain long service lives of concrete structures, and has a large impact on their carbon footprint.

This paper includes discussion of how each these measures if used prudently, can achieve significant reductions in carbon footprint while simultaneously improving durability in aggressive exposure conditions.

Recent studies focused on the quality of the interfacial transition zone (ITZ) of ordinary concretes made from recycled aggregates (RA), without however focusing on High Performance Concretes (HPC).

This paper aims to formulate HPC from RA that are exclusively derived from concrete, whose composition is controlled. These concretes are made in a ready-mixed concrete plant and then undergo a crushing and riddling process to produce RA. Partially saturated gravels are substituted up to 100% in the HPC composition in order to accentuate internal cure phenomenon. This phenomenon was observed and demonstrated using a scanning electron microscope (SEM) in the low Water/Cement (W/C) paste up to a distance of 150 μm from the RA and compared by image processing, to a reference concrete made from natural aggregates (NA).

The comparison of the mechanical performances and the microscopic analysis of HPC show that the characteristics transfer of the RA seem to favor a hydration of the paste by a mechanism of desorption of their absorbed water, in a process of “internal cure”. The internal cure appears optimal for concrete C60. In addition to this observation, there was an increase in the strength of the recycled HPCs compared to control natural-aggregate HPCs.

Alkali-activated slag/fly ash concretes activated with combined sodium silicate and sodium hydroxide show good mechanical and durability properties in general. When tested in terms of resistance to freezing and thawing cycling in watersaturated conditions, the concretes tested in this study show final values of relative dynamic modulus averaging 100% after 300 cycles. However, all tested concretes showed poor performance towards freezing and thawing in presence of de-icing salts with only one tested mixture showing a final average scaling value below 0.5 kg/m^². Early-age microcracking is observed on all tested concretes and is correlated to high values of autogenous shrinkage in equivalent paste mixtures. Increasing the fly ash content reduces both the observed autogenous shrinkage and early-age cracking. Low drying shrinkage values ranging from 470 to 530 μm/m after 448 days of measurements at 50% RH and 23°C are noted. The use of fly ash in these alkali-activated concretes reduces the expansion levels of concrete specimens incorporating alkali-silica reactive aggregates. With increasing fly ash contents (20, 30 and 40% replacement), decreasing expansions are observed for any given reactive aggregate. In general, the durability properties measured in this study were improved by partially substituting slag with fly ash as binder material.

This paper focuses on developing ambient-cured alkali-activated concrete incorporating recycled concrete aggregates (RA). The binder was either slag or a blend of slag and fly ash (3:1, by mass). Hook-ended steel fibers were added, in 2% volumetric fraction, to improve the properties of concrete made with RA. The alkaline activator solution was a blend of sodium silicate and sodium hydroxide. Concrete mixtures were proportioned to achieve three target compressive strengths, namely 30, 45, and 60 MPa. The performance of concrete mixtures was assessed based on 1, 7, and 28-day compressive strengths. Experimental results showed that full replacement of natural aggregates by RA caused up to 28% reduction in compressive strength of plain alkali-activated slag concretes, with greater reductions being reported in mixtures with higher target strength and tested at 28 days. The incorporation of 2% steel fibers enhanced the strength and caused limited strength reductions of up to 7%. Compared to alkali-activated slag RA concretes, mixtures with 25% fly ash replacement exhibited lower strengths at 1 and 7 days, but their 28-day strength was superior. Analytical multi-linear regression models were developed to identify statistical significance of concrete components and examine their impact on the compressive strength.

This study presents an accurate corrosion prediction through an intelligent approach based on deep learning. The deep learning is used to predict the time-to-corrosion induced cover cracking in reinforced concrete elements exposed to chlorides ions. The key parameters taken into consideration include thickness, quality and condition of the concrete cover. The prediction performance of the deep learning model is compared against traditional machine learning approaches using neural network and genetic algorithms. Results show that the proposed approach provides better prediction with higher generalization ability. The efficiency of the method is validated by an accelerated corrosion test conducted on 91 and 182-day moist cured reinforced fly ash concrete samples with different water-to-binder ratios. The results are in agreement with the model predictions. They also show that using the proposed model for numerical investigations is very promising, particularly in extracting the effect of fly ash on reducing the extent of corrosion. Such an intelligent prediction will serve as an important input in order to assist in service life prediction of corroding reinforced concrete structures as well as repair evaluation.