International Concrete Abstracts Portal

The durability of reinforced concrete is often compromised by chloride penetration, leading to corrosion of reinforcing steel and reduced structural strength. To improve the sustainability and longevity of concrete structures, it is crucial to model and predict chloride permeability (CP) accurately, thereby minimizing the time and resources required for extensive experimental testing. This paper presents a proof-of-concept study applying Artificial Neural Networks (ANN) to predict CP in concrete structures. The model was trained on a small but carefully controlled experimental dataset of 10 concrete mixtures, considering four key parameters: water-to-cementing materials ratio, silica fume content, cementing materials content, and air content. Despite the limited dataset size, which constrains generalizability and statistical robustness, the ANN captured nonlinear relationships among the input parameters and CP. The comparison between experimental and simulated CP values showed reasonable agreement, with errors ranging between –242 and 420 Coulombs. These results establish the trustworthiness and reliability of the proposed model, providing a valuable tool for predicting CP and informing the design of durable and sustainable concrete structures.

Corrosion in reinforcing steel bars is a critical factor influencing the durability and structural performance of reinforced concrete structures. This paper investigates the effects of corrosion on the mechanical properties of thermo-mechanically treated steel bars. The study parameters included bar diameter, corrosion technique, and varying corrosion levels (CLs). The impressed current technique was used to accelerate corrosion. Load-displacement data from uniaxial tensile tests were analyzed to determine stress-strain relationships of corroded bars. The results showed that the mechanical properties of the bars were unaffected by diameter or corrosion technique. However, a consistent reduction in both nominal yield strength and ultimate strength was observed with increasing CLs, while the elastic modulus remained unchanged. The strength factors for yield strength and ultimate strengths of the corroded bars varied in the range of 0.0013 to 0.015 and 0.0032 to 0.012, respectively, which were higher than reported in the literature. The fracture strain of the bars decreased at higher CLs. Predictive models were developed to estimate the residual mechanical properties, which are crucial for defining the constitutive relations needed to determine analytical stress-strain behavior. Analytical methods for determining these constitutive relations were also proposed, showing a good correlation with the experimental stress-strain curves.

This study presents a comprehensive review of eco-friendly materials and advanced repair techniques for rehabilitating reinforced-concrete (RC) structures, emphasizing their role in promoting sustainability and enhancing performance. By evaluating fifty-five research programs conducted between 2001 and 2024, the study focuses on emerging materials such as geopolymers, natural fibers, and fiber-reinforced composites, highlighting their mechanical properties, environmental benefits, and potential for integration into traditional RC systems. The review is thematically organized into four areas: (1) Sustainability and Environmental Impacts, (2) Material Innovation and Properties, (3) Repair Techniques and Efficiency, and (4) Structural Performance. Key findings reveal that these materials not only reduce the carbon footprint of construction but also significantly improve structural durability, corrosion resistance, and long-term performance under varying environmental conditions. Specifically, geopolymer concretes exhibit low CO₂ emissions and superior bond strength; bamboo and flax fibers offer strong tensile capacity with renewable sourcing; and MICP techniques deliver self-healing functionality that reduces dependency on chemical-based crack sealants. Additionally, the use of recycled and bio-based materials further contributes to cost-efficiency and environmental resilience, fostering circular economy principles. By synthesizing findings across these domains, this study provides practical insights into how eco-friendly materials can simultaneously address environmental, structural, and economic challenges in RC repair. The study underscores the importance of adopting innovative repair methods that incorporate these sustainable materials to address modern civil engineering challenges, balancing infrastructure longevity, sustainability, and reduced environmental impact.

Sudden failure of reinforced concrete (RC) dapped-end beams of bridges and viaducts has occurred all around the world in the last few years due to corrosion of steel bars. The danger of sudden and brittle failure is often due to pitting corrosion of steel bars, concrete crushing, and loss of bond in steel bars. In this paper, the risk of failure of reinforced dapped-end supports at the ultimate state under vertical and lateral loads is investigated, focusing on the consequences of pitting corrosion and loss of bond in steel bars. A simplified strut-and-tie model was developed to predict the load-carrying capacity of dapped-end supports. The model includes the effects of corrosion of steel bars, loss of bond, and concrete crushing due to the biaxial state of stresses. Several laboratory experimental tests regarding the flexural behavior of RC beams with dapped-end supports were collected to validate the proposed model.

Corrosion—one of the major threats to the integrity of concrete structures—can consequently affect structure serviceability and ultimate limit state, possibly resulting in failure. Glass fiber-reinforced polymer (GFRP) can be used as an innovative alternative for conventional steel reinforcement in concrete structures, effectively addressing corrosion issues. In addition to its corrosion resistance and high strength-to-weight ratio, GFRP is commonly selected for non-prestressed bars and stirrups due to its cost advantage over other FRP materials. The study endeavored to provide a comprehensive overview of the shear resistance in GFRP-RC beams with short shear spans. The manuscript aims to synthesize and analyze shear test data based on published studies on GFRP-RC beams with a short shear span (a/d = 1.5 to 2.5). A comprehensive literature review was conducted to compile a database comprising 64 short GFRP-RC beams to evaluate the efficiency of using the strut-and-tie model (STM) for predicting the shear resistance of GFRP-RC beams. The findings reveal that the ACI 318 (2019) STM yielded the most accurate predictions of the shear resistance of GFRP-RC beams with shear span-to-depth ratios of 1.5 to 2.5, since the current ACI 440.11 and ACI 440.1R design codes and guidelines do not include shear equations using the strut-and-tie model for predicting the shear resistance of GFRP-RC beams. Based on the findings of this study, the results could contribute to establishing shear equations in the upcoming revision of the ACI 440.11 and ACI 440.1R design codes and guidelines, specifically tailored for designing short GFRP-RC beams using the strut-and-tie model. The study also provides sufficient data to apply the strut-and-tie model in the design of GFRP-RC beams.