International Concrete Abstracts Portal

Due to global warming, the temperature of earth surface increased by 0.95 to 1.20℃ in the past 4 decades. The increase in temperature has significant effects on the concrete industry, causing alterations in concrete curing conditions and degradation in strength and durability properties. The understanding of changes in concrete properties due to variations in curing conditions from climate change is an imminent task that has to be resolved. Among the durability properties of concrete, freeze-thaw (FT) resistance is most directly affected by climate change. However, in all of the studies conducted on the FT behavior of concrete, the dramatic changes in environmental conditions due to climate change were not considered. Therefore, the focus of this study is to understand the FT performance of concrete from extreme temperature and relative humidity (RH) changes in curing conditions. To find the relationship between the curing condition change and FT resistance levels as a function of time, a 3-D satisfaction surface graph was developed using the Bayesian probabilistic method. Then, an example of drawing the 3-D satisfaction surface diagrams for FT resistance based on the weather conditions in New York City between 2001 and 2100 was shown. Furthermore, considering the reduction rate of the average annual FT cycle due to climate change, this study confirmed that FT resistance performance increased. This approach contributes to a performance-based evaluation (PBE) strategy for concrete exposed to FT cycles under various environmental conditions. The study details and results are discussed in the paper.

To address the autogenous shrinkage issue of ultra-high-performance concrete (UHPC), internal curing technology has shown great potential in resolving this challenge by providing additional moisture. To further improve its curing efficiency, this study proposes an innovative internal curing technology that can significantly reduce autogenous shrinkage without increasing the amount of internal curing water or compromising mechanical strength. This approach utilizes perforated cenospheres (PCs) as internal curing agents while substituting internal curing water with urea solutions. In addition to replenishing water, urea solutions, once released into the cement paste, can react with portlandite. This reaction generates CaCO₃; owing to the intrinsic properties of CaCO₃, it has a larger macroscopic volume and a much higher elastic modulus than portlandite. This approach effectively reduces chemical shrinkage while concurrently increasing the stiffness of the cement paste, thereby achieving a significant reduction in autogenous shrinkage. As a result, replacing water with 3% urea solution in PCs enhances the autogenous shrinkage of UHPC, reducing it from less than 50% to over 90%.

Crack densities obtained from on-site surveys of 74 bridge deck placements containing concrete mixtures with paste contents between 22.8 and 29.4% are evaluated. Twenty of the placements were constructed with a crack-reducing technology (shrinkage- reducing admixtures, internal curing, or fiber reinforcement) and 54 without; three of the decks with fiber reinforcement and nine of the decks without crack-reducing technologies involved poor construction practices. The results indicate that using a concrete mixture with a low paste content is the most effective way to reduce bridge deck cracking. Bridge decks with paste contents exceeding 27.3% had a significantly higher crack density than decks with lower paste contents. Crack-reducing technologies can play a role in reducing cracking in bridge decks, but they must be used in conjunction with a low-paste-content concrete and good construction practices to achieve minimal cracking in a deck. Failure to follow proper procedures to consolidate, finish, or cure concrete will result in bridge decks that exhibit increased cracking, even when low paste contents are used.

Portland-limestone cement (PLC) currently has gained widespread use as the most accessible and sustainable blended cement in the market. However, in many African countries, including Ghana, the use of clay pozzolana (CP) in the concrete industry has primarily relied on ordinary portland cement (OPC). In this study, PLC Type II/B-L was partially replaced with CP at levels ranging from 10 to 50% by weight. The investigation included compressive strength testing, nondestructive evaluations using electrical surface resistivity, pulse velocity, and chloride penetration tests, targeting a characteristic strength of 30 MPa (4351.13 psi). Additionally, an environmental impact assessment based on the carbon footprint of both control and CP concretes was conducted. The mixture design followed the EN 206 standard. A total of 72 cubic molds were produced for the strength test. The results showed that CP concretes with between 10 and 20% replacement achieved strength values of 35 and 33 MPa (5076.4 and 4786.32 psi), respectively, higher than the target of 30 MPa (4351.13 psi) strength at 28 days. However, mixtures with 30 to 50% replacement required extended curing periods of 60 to 90 days to reach the desired strength. At extended curing, 10 to 50% CP replacement attained strength between 32 and 41 MPa (4641.28 and 5946.64 psi). Nondestructive test results showed no direct correlation with compressive strength, confirming that different factors govern strength, resistivity, and pulse velocity. The environmental impact assessment revealed a 14 to 51% reduction in carbon strength index (CSi) and a 19 to 36% increase in carbon durability index (CRi) with 10 to 50% CP (for CSi) and 10 to 40% (for CRi). The thermodynamic modeling also revealed that pozzolana contents below 30% primarily promoted pozzolanic reactions, enhancing performance compared to the control mixture. Based on these results, 20 to 30% CP replacement is recommended to ensure reliable performance, while higher levels (>30%) require further durability evaluation for long-term use.

This study presents a machine learning–driven framework for the sustainable design of ultra-high-performance concrete (UHPC) mixtures with a focus on maximizing flexural strength while minimizing material cost and embodied CO₂ emissions. A curated dataset of 333 UHPC mixtures was developed, incorporating 13 input features including binder composition, steel fiber dosage, and curing parameters. A Bayesian Neural Network (BNN) was trained to predict flexural strength with high accuracy (R² = 0.936, RMSE = 1.37 MPa, MAE = 1.09 MPa), supported by residual analysis confirming minimal prediction bias and robust generalization. SHAP analysis was used to interpret model predictions and identify key drivers of flexural behavior—namely, curing time, steel fiber dosage, and silica fume content. The BNN was coupled with the NSGA-III algorithm to perform multi-objective optimization and generate Pareto-optimal UHPC mixtures. A utility-based scoring method was introduced to select designs aligned with different project priorities—enabling the identification of fiber-rich, high-strength mixtures as well as low-emission, cost-efficient alternatives. The framework supports field-level implementation and is well-suited for integration with sustainability rating systems such as LEED or Envision. It provides a transparent, generalizable, and industry-ready tool for intelligent UHPC mixture optimization, advancing data-driven design practices for green infrastructure applications.