Journal of Materials in Civil Engineering

Alkali activated slag concrete (AASC), based on a binder that consists of 100% blast furnace slag that is activated by an alternative alkali to conventional Portland cement, has considerable environmental benefits. Nevertheless, the durability of the exposed surface zone of AASC needs consideration. The ingress of harmful agents is highly influenced by convection-induced effects; e.g., moisture gradients caused by exposure to rainfall or the wetting and drying effects in the splash zone of a marine environment that can lead to high surface concentration of chloride. The convective effects also propagate steel reinforcement corrosion, once initiated, by making available moisture and oxygen for the cathodic reaction at the steel reinforcement, as well as changing the conductivity of the concrete surface zone. This paper reports the behavior of convection-induced uptake of water into AASC and ordinary Portland cement concrete. The sensitivity to “exposed,” “sealed,” and “bath” curing and the resultant pore structure for concrete made with different water/binder is contrasted.

Use of natural fibers in civil engineering construction practice is often advantageous as they are cheap, locally available, biodegradable, and ecofriendly. Among the available natural fibers, coir is produced in large quantities in South Asian countries, such as India, Ceylon, Indonesia, Philippines, etc. and has better mechanical properties, such as tensile strength. In this paper, results on the strength and stiffness behavior of soil reinforced with coir fibers are presented. Soil samples reinforced with coir fibers of different sizes, and made into cylindrical soil specimens were tested in triaxial shear apparatus to determine the strength and stiffness of soil response due to fiber inclusion and the results were compared with that of unreinforced soils. The results show that addition of coir (1–2%) as random reinforcing material increases both strength and stiffness of clay soil considered in the study. In addition, available theoretical models for prediction of strength of fiber-reinforced soil are examined in relation to the results of the present investigation. Analysis shows that the available models are not adequate to capture the strength and stiffness response of coir fiber-reinforced soil. A nonlinear regression model for strength and stiffness response is proposed in the present study.

Steel bars pitting corrosion is an electrochemical process that could seriously jeopardize the reliability of reinforced concrete structures. Even if detailed models exist to predict the lifetime of the concrete element when it is subject to this environmental attack, their applications present serious limitations that undergo, to the noteworthy sources of, uncertainty of many problem parameters. This restriction could produce erroneous solutions, especially when analysis deals with existing buildings or little information about problem parameters are accessible. In detail this takes place when real environmental conditions, mechanical properties as well as load conditions, could only be estimated and not known with enough accuracy. To overcome this problem, some methodologies have been developed, assuming that uncertainty variables can be suitably modeled in a probabilistic way, and therefore traditional theories for reliability assessment can be used. Nonetheless, in the analysis of this problem, there are other parameters that cannot be treated opportunely in a probabilistic way. The main purpose of this paper is to develop an efficient alternative approach for time-dependent reliability analysis regarding reinforced concrete beams subject to pitting corrosion, when probabilistic and nonprobabilistic parameters occur at the same time. With this new approach, it is possible to obtain a versatile tool to support the decision maker in planning maintenance interventions.

To increase the crack bridging capacity of concretes and mortars, fibers are often added to cement-based matrices. As a result, the fracture energy of a fiber-reinforced concrete (FRC) is the sum of the cohesive forces of the matrix and of the pullout resistance given by the fibers crossing the crack. In the case of fibers randomly inclined with respect to crack surfaces, the so-called frictional snubbing effect must be added to the previous contributions, if the energy released during crack growth has to be computed. Of course, snubbing forces are not present when fibers are perfectly orthogonal to crack surfaces. As the classical formulas are not always effective in the evaluation of snubbing phenomenon, a cohesive interface model is here proposed for a more precise definition of the frictional snubbing forces. The model is able to predict adequately the experimental results obtained by pulling out steel fibers at different inclinations angles from cement-based matrices. By analyzing fibers with different bond properties, the proposed model can be also used to define the crack bridging capacity of both bonded and unbonded steel fibers. Moreover, it seems to suggest a more simplified approach for the definition of the postcracking response of FRC.

A numerical study on the fracture behavior of steel fiber-reinforced concrete (SFRC) slabs on grade for industrial pavements is presented. Finite element analyses have been carried out by using a commercial finite element code where user subroutines based on nonlinear fracture mechanics have been implemented to describe the progressive cracking behavior of SFRC. The model is capable of simulating both primary and secondary cracks when they occur in concrete and it has been validated by comparing numerical predictions with experimental observations of full-scale tests on slabs on elastic subgrade under point loads in different positions. A real pavement with contraction or construction joints has been numerically simulated to investigate the stress and the strain fields for the most significant positions of point loads.

Self-consolidating concrete (SCC) is known for its excellent deformability, high resistance to segregation, and use in congested reinforced concrete structures characterized by difficult casting conditions without applying vibration. Research has been conducted on the development of SCC using high volumes of supplementary cementing materials (SCM) (such as fly ash and slag) and viscosity modifying admixtures (VMA). The bond characteristics of such SCCs are very important for their application in practical construction. An extensive investigation was conducted to determine the bond strength between deformed reinforcing steel bar and SCM and VMA based SCC as well as normal concrete (NC). Bond tests were conducted using a specially developed pullout test. The SCC pullout specimens were cast without applying any consolidation, whereas the NC specimens were cast by conventional practice with consolidation and vibration. It was found that the reduction in bond strength due to bleeding and inhomogeneous nature was less in SCC compared to NC. Although the variation in bond strengths at different casting elevations was observed in SCC, the extent was less significant than that of NC. SCC also exhibited a less significant top-bar effect compared to NC. This can be attributed to the more consistent nature of SCC and its superior filling capability. Performance of various code based and other existing bond equations are validated through experimental results illustrating the influence of concrete types (either SCC of different types or NC).

This paper presents findings of a research study focused on investigating influences of coarse aggregate morphologies on the strength and permanent deformation behavior of unbound aggregate materials. Angularity and surface texture properties of six different types of aggregates were evaluated using two shape indices, angularity index (AI) and surface texture index (ST), based on image analysis. Twenty-one unbound aggregate blends having the same gradation and voids content but different crushed percentages were prepared by mixing the imaging evaluated aggregates and tested using triaxial tests for strength and permanent deformation. The laboratory permanent strain—load application $({\epsilon }_p–N)$ curves evaluated using a phenomenological power model showed the $A$ and $b$ parameters to be heavily dependent on applied stress levels. Aggregate blends with higher AI and ST indices were consistently associated with lower magnitudes of $A$ and $b$ . The angularity property was found to contribute mainly to the strength and stability of aggregate structure through confinement by bulk stress, whereas the surface texture property tended to mitigate the dilation effects through increasing friction between individual aggregate particles.

Artificial neural network (ANN) and regression models are developed for the estimation of concrete slump using concrete constituent data. The concrete mix constituent and slump data from laboratory tests have been employed to develop all models. The results obtained in this study demonstrate the superiority of the ANN models. It was found that combining one or more concrete mix constituents and treating them as an independent input variable is not advantageous when using regression but can be very useful when using ANNs for modeling concrete slump. Sensitivity analyses based on the ANN models were carried out to evaluate the impact of different concrete mix constituents on the slump values. It was found that the slump attains a minimum value at the critical levels of mortar and coarse aggregates, and tends to increase with paste content and decrease with sand content in the concrete mix.