International Concrete Abstracts Portal

Service life modeling of microbially induced concrete corrosion (MICC) is essential for assessing structural durability, optimizing maintenance, and minimizing risks in wastewater environments. ASTM C1904-20 is a recently developed biogenic benchtop method for assessing MICC that is safe, accelerated, and practical compared to conventional laboratory tests. The objective of this study is to use the benchtop test to predict the service life of concrete exposed to MICC in sewer pipes. This correlation is based on the Pomeroy model that relates the field H₂S concentrations, wastewater flow conditions, pipe and flow geometry, and the properties of the concrete. A demonstration study is provided to show how the ASTM C1904 data could be used to predict the performance of different types of concrete and antimicrobial products in realistic exposure scenarios. The projected corrosion rates in field conditions reflected the delayed and reduced corrosion rates for mixtures with antimicrobial treatment.

Analysis of reinforced-concrete damage (RC) under nonuniform corrosion has mostly been performed by adopting the two-dimensional (2-D) plane strain assumption to reduce the computational efforts compared with three-dimensional (3-D) models. This paper aims to compare results obtained from the 2-D plane strain formulation with 3-D analysis in the context of nonuniform corrosion, highlighting differences and similarities to gain valuable insights into the structural response and damage prediction. The findings indicate that both the 2-D and 3-D models yield reasonably similar damage patterns with minor discrepancies in crack orientation and predict comparable hairline crack widths on the concrete surface. During initial corrosion stages, both models exhibit similar stress and strain distributions. However, as corrosion progresses, distinct variations in stress and strain patterns emerge. Interestingly, despite these differences, the extent of damage converges as corrosion advances, suggesting a critical stage beyond which the RC response remains consistent regardless of the modeling approach. The study emphasizes stress and strain variations over time for accurate RC behavior representation.

This study examines the lateral cyclic response of a repaired damaged bridge pier originally reinforced with fiber-reinforced polymer (FRP) bars, particularly glass FRP (GFRP), as a corrosion-resistant and durable alternative to traditional steel. An as-built large-scale hybrid (GFRP-steel) reinforced concrete (RC) column had an outer cage reinforced with GFRP bars and an inner cage reinforced with steel reinforcing bars. The columns were first tested under cyclic lateral loading, where the hybrid specimen demonstrated ductility and energy dissipation capacity comparable to the conventional single-layer steel RC column. Following these initial tests, both specimens were repaired using FRP wraps and retested under the same loading protocol, resulting in a total of four tests. Enhanced structural integrity and energy dissipation demonstrate the effectiveness of innovative repair techniques in seismic engineering. These findings provide a blueprint for resilient infrastructure in earthquake-prone areas and contribute to advancements in bridge design and repair strategies.

The concentration of chloride ions involves both chemical binding and physical adsorption. This study investigated how limestone powder and supplementary cementitious materials (SCMs) synergistically affect chloride concentration in cement paste, using analyses of corrosion products, pore structure, and chloride concentration coefficient. Cement pastes with 0 to 50% limestone powder and fly ash or slag were tested. Results showed that the synergy between limestone powder and fly ash or slag promoted carboaluminate formation, which completely converted to Friedel’s salt in chloride environments. This enhanced chemical binding and increased physical adsorption of chloride ions, while reducing porosity and the most probable pore diameter. When limestone powder was 5 to 25% with fly ash less than 10%, or both limestone powder and slag were 20 to 30%, the chloride concentration coefficient reached its peak. Thus, proper limestone powder content improves chloride resistance by enhancing both chemical and physical chloride binding.

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.