An Integrated Framework for Image Acquisition, Processing, and Analysis Procedures for Automated Damage Evaluation of Concrete Surfaces.

Concrete surface cracks serve as early indicators of potential structural threats. Visual inspection, a commonly used and versatile concrete condition assessment technique, is employed to assess concrete degradation by observing signs of damage on the surface level. However, the method tends to be qualitative and needs to be more comprehensive in providing accurate information regarding the extent of damage and its evolution, notwithstanding its time-consuming and environment-sensitive nature. As such, the integration of image analysis techniques with artificial intelligence (AI) has been increasingly proven efficient as a tool to capture damage signs on concrete surfaces. However, to improve the performance of automated crack detection, it is imperative to intensively train a machine learning model, and questions remain regarding the required image quality and image collection methodology needed to ensure the model's accuracy and reliability in damage quantitative analysis. This study aims to establish a procedure for image acquisition and processing through the application of an image-based measurement approach to explore the capabilities of concrete surface damage diagnosis. Digitizing crack intensity measurements were found to be feasible; however, larger datasets are required. Due to the anisotropic behavior of the damage, the model's ability to capture crack directionality was developed, presenting no statistically significant differences between the observed and predicted values used in this study with correlation coefficients of 0.79 and 0.82.

The Impact of Distinct Superplasticizers on the Degradation of Concrete Affected by Alkali-Silica Reaction (ASR).

The effect of two superplasticizers (SPs) with various equivalent (eq.) alkali contents (i.e., with 0.00009% and 4.1% of Na2Oeq, respectively) on the development of an alkali-silica reaction (ASR) was investigated through the use of multilevel assessment. This testing protocol showed promising results for evaluating concrete damage due to ASRs based on mechanical and microscopical testing protocols, specifically the stiffness damage test (SDT) and the damage rating index (DRI). Concrete specimens that incorporated the aforementioned SPs and distinct reactive aggregates (coarse and fine) were manufactured and then stored in conditions that enabled ASR development and were monitored over time. Upon reaching the desired expansion levels of this study, the concrete specimens were prepared for the multilevel assessment. The results show that the SP-incorporated concrete specimens with lower and higher alkali content yielded lower and higher deterioration results, respectively. This clearly confirms that while SP-incorporated concrete that contains SPs with a higher alkali content could increase the risk of ASR deterioration, those SPs with a very low amount of alkali content could act as a mitigation strategy against ASRs. Finally, an investigation into the influence of distinct SPs on the chemical composition of an ASR gel was conducted, which confirmed that the SP with a higher alkali content had the highest potential for further deterioration.

Damage Generated and Propagated by the AAR Reactive Aggregate from Kingston, Ontario, Canada.

It remains unclear in the literature what the cause of the so-called alkali-carbonate reaction (ACR) damage to concrete is. However, expansion and cracks as distress features are often attributed to the alkali-silica reaction (ASR). Therefore, this work aims to assess the damage to concrete generated and propagated by the so-called ACR-susceptible reactive aggregate through mechanical testing (i.e., the direct shear test), microscopy (the damage rating index-DRI), and other techniques. Distinct induced expansion levels (i.e., 0%, 0.05%, 0.12%, and 0.20%) were selected to compare the distress caused by ACR to concrete affected by ASR. The results show that the behavior of ACR, namely, as captured through the DRI, is inconsistent with that of ASR, thus attesting to ACR being a distinct distress mechanism. The damage captured through mechanical testing does not distinguish ACR from ASR; however, microscopy reveals that cracks in the cement paste are the main damage mechanism. The proportions of cracks in the cement paste are 40-50% of the total number of cracks, whereas open cracks in the aggregates normally characterizing ASR represent only up to 20% of the total cracks.

Freezing and Thawing Resistance of Fine Recycled Concrete Aggregate (FRCA) Mixtures Designed with Distinct Techniques.

The pressure to use sustainable materials and adopt practices reducing the carbon footprint of the construction industry has risen. Such materials include recycled concrete aggregates (RCA) made from waste concrete. However, concrete made with RCA often presents poor fresh and hardened properties along with a decrease in its durability performance, especially when using its fine fraction (i.e., FRCA). Most studies involving FRCA use direct replacement methods (DRM) to proportion concrete although other techniques are available such as the Equivalent Volume (EV) and Particle Packing Models (PPMs); yet their impact on the durability performance, especially its performance against freezing and thawing (F/T), remains unknown. This work, therefore, appraises the F/T resistance of FRCA mixtures proportioned through various mix proportioning techniques (i.e., DRM, EV and PPMs), produced with distinct crushing processes (i.e., crusher's fines vs. finely ground). The results show that the mix design technique has a significant influence on the FRCA mixture's F/T resistance where PPM-proportioned mixtures demonstrate the best overall performance, exceeding the specified requirements while DRM-proportioned mixtures failed F/T resistance requirements. Moreover, the crushing process plays an important role in the recycled mixtures' cracking behavior under F/T cycles, where less processing leads to fewer cracks while remaining the most sustainable option overall.