Applications of nanotechnology in the pavement industry have increased rapidly during the last decade in order to enhance a pavement’s sustainability and durability. Conventional asphalt binder generally does not provide sufficient resistance against rutting at high temperatures. Carbon black nano-particles (CBNPs, produced by perennial mountain trees’ carbonization) were mixed into the performance grade (PG) 58 asphalt binder in this study. Conventional asphalt binder tests (penetration, ductility and softening point), frequency sweep, performance grading, and bitumen bond strength tests were conducted to study the enhancement in the properties of asphalt binder. Dynamic modulus and wheel tracking tests were also performed to investigate the effect of CBNPs on asphalt mixture properties. Experimental results demonstrated that preferred dosage of CBNPs in asphalt is 10% by weight of the bitumen. Results of scanning electron microscopy (SEM) and storage stability tests validated homogenous and stable dispersion of CBNPs in the asphalt binder. Asphalt mixtures became stiffer and resistant to rutting at high temperatures by addition of CBNPs in asphalt binder. Significant improvement in bitumen aggregate bond strength was also observed by incorporating CBNPs. It is concluded that CBNPs can be used to effectively enhance the high-temperature performance and consequently the sustainability of flexible pavements.

This article deals with the study of predicting the confinement effect of carbon fiber reinforced polymers (CFRPs) on concrete cylinder strength using metaheuristics-based artificial neural networks. A detailed database of 708 CFRP confined concrete cylinders is developed from previously published research with information on eight parameters, including geometrical parameters like the diameter (d) and height (h) of a cylinder, unconfined compressive strength of concrete (f_co^'), thickness (nt), the elastic modulus of CFRP (Ef), unconfined concrete strain (?_co), confined concrete strain (?_cc) and the ultimate compressive strength of confined concrete (f_cc^'). Three metaheuristic models are implemented, including particle swarm optimization (PSO), grey wolf optimizer (GWO), and bat algorithm (BA). These algorithms are trained on the data using an objective function of mean square error, and their predicted results are validated against experimental studies and finite element analysis. The study shows that the hybrid PSO model predicted the strength of CFRP-confined concrete cylinders with a maximum accuracy of 99.13% and GWO predicted the results with an accuracy of 98.17%. The high accuracy of axial compressive strength predictions demonstrated that these prediction models are a reliable solution to the empirical methods. The prediction models are especially suitable for avoiding full-scale, time-consuming experimental tests that make the process quick and economical.

Dynamic properties such as natural frequencies and mode shapes are directly affected by damage in structures. In this paper, changes in natural frequencies and mode shapes were used as the input to various objective functions for damage detection. Objective functions related to natural frequencies, mode shapes, modal flexibility and modal strain energy have been used, and their performances have been analyzed in varying noise conditions. Three beams were analyzed: two of which were simulated beams with single and multiple damage scenarios and one was an experimental beam. In order to do this, SAP 2000 (v14, Computers and Structures Inc., Berkeley, CA, United States, 2009) is linked with MATLAB (r2015, The MathWorks, Inc., Natick, MA, United States, 2015). The genetic algorithm (GA), an evolutionary algorithm (EA), was used to update the damaged structure for damage detection. Due to the degradation of the performance of objective functions in varying noisy conditions, a modified objective function based on the concept of regularization has been proposed, which can be effectively used in combination with EA. All three beams were used to validate the proposed procedure. It has been found that the modified objective function gives better results even in noisy and actual experimental conditions.

This paper presents the bond–slip models for deformed and plain bar types in low-strength concrete. The newly developed bond-strength models were used to account for the effect of different deficient variables typically found in non-engineered reinforced-concrete structures in developing countries, such as low-strength concrete, insufficient development length and low concrete cover. Residual bond strength was evaluated from experimental bond–slip curves by defining approximate criteria for calculating residual slip. Suitable bond–slip relationships are identified to define local bond–slip relations for both bar types in low-strength concrete. Based on the experimental findings, the strain distribution profile over the development length is proposed, which can be used to evaluate the bar elastic slip in low-strength concrete by employing the macro model. The proposed bond–slip models can be used in the inelastic analysis of non-engineered reinforced concrete structures.

Reinforced concrete corbels were examined in this study for the cracking behavior and strength evaluation, focusing on defects typically found in these structures. A total of 11 corbel specimens were tested, including healthy specimens (HS), specimens with lower concrete strength (LC), specimens with less reinforcement ratio (LR), and specimens with more concrete cover than specifications (MC). The HS specimens were designed using the ACI conventional method. The specimens were tested under static loading conditions, and the actual strengths along with the crack patterns were determined. In the experimental tests, the shear capacity of the HS specimens was 28.18% and 57.95% higher than the LR and LC specimens, respectively. Similarly, the moment capacity of the HS specimens was 25% and 57.52% greater than the LR and LC specimens, respectively. However, in the case of the built-up sections, the shear capacity of the HS specimens was 9.91% and 37.51% higher than the LR and LC specimens, respectively. Likewise, the moment capacity of the HS specimens was 39.91% and 14.30% higher than the LR and LC specimens, respectively. Moreover, a detailed nonlinear finite element model (FEM) was developed using ABAQUS, and a more user-friendly strut and tie model (STM) was investigated toward its suitability to assess the strengths of the corbels with construction defects. The results from FEM and STM were compared. It was found that the FEM results were in close agreement with their experimental counterparts.