Due to the corrosion problem in reinforced concrete structures, the use of fiber-reinforced polymer (FRP) bars may be preferred in place of traditional reinforcing steel. FRP bars are used in concrete constructions to boost the strength of structural elements and retain their longevity. In this study, the axial load carrying capacity (ALCC) of the FRP-reinforced concrete columns has been evaluated using analytical, as well as machine learning, models. A total of fourteen popular analytical models and one proposed machine learning-based model were used to estimate the ALCC of the concrete columns. The proposed machine learning model is based on an artificial neural network (ANN) method. The performance of the ANN, as well as the analytical models, are assessed using six different performance indices. The R-value of the developed ANN model is 0.9758, followed by an NS value of 0.9513. It has been found that the mean absolute percentage error of the best-fitted analytical model is 328.71% higher than the ANN model, and the root-mean-square error value of the best-fitted analytical model is 211.97% higher than the ANN model. The evaluated data demonstrate that the proposed ANN model performs better than the other analytical models. The developed model is quick and easy-to-use to estimate the axial capacity of the FRP-reinforced concrete columns.

The skew slabs possess a broad range of applications in bridges as well as in buildings because of severe space constraints in the congested urban localities and in locations, when there are some other architectural constraints and geographical obstacles, such as mountainous terrains, etc. The available design guidelines/codes give a set of design moment coefficients for a particular set of the skew angles and the slab aspect ratio only; these are based on the empirical formulae and the related performance studies conducted on such slabs in the past. This paper presents an improved theoretical formulation to predict the ultimate flexural capacity of laterally loaded reinforced concrete (RC) skew slabs. The study reveals the effect of the skew angle and aspect ratio on the moment field induced in the slab. The proposed formulation, therefore helps the analyst to proportionate the skew slab having any set of design constraints. A working example is also presented to demonstrate the validity and efficiency of the simplified approach presented therein.

Skew slab is the most common structural element that finds numerous applications in practice, especially when there is any space constraint that prevents the selection of either square or rectangular slab. Due to its geometry, this type of slab behaves differently in comparison to the rectangular slabs and it is a very time-consuming process to predict the moment field in such type of slabs. It becomes still more complicated when some beam system is used to meet the prescribed serviceability criterion. A set of mathematical expressions is presented in the paper that could be of help to predict the moment field being induced in skew slabs under external loads. The outcome of the proposed expressions is validated experimentally as well as numerically; a good agreement is observed in the results. An illustrative example is also presented in the paper to demonstrate the efficiency of the proposed expressions.