International Concrete Abstracts Portal

A machine learning (ML) model is developed using a gradient-boosted decision-tree algorithm to estimate the drift capacity of reinforced concrete (RC) columns. A reliable estimate of the drift capacity of a structure is critical to both its design and assessment. The drift capacity of a structure is also broadly interpreted as a measure of its seismic vulnerability. The estimated drift capacity from the ML model is compared against that of existing methods using test results from a dataset of 341 RC columns subjected to cyclic loading. The mean of the ratio of measured to estimated drift capacity for the developed ML model was 1.0 with a coefficient of variation (CV) of 0.31. In comparison, the regression equation currently adopted in New Zealand and the US to estimate the drift capacity of RC columns has a mean of 3.13 and a CV of 1.07. Other empirical methods assessed in this study also led to large scatter and no discernible correlation between estimated and measured drift capacity. The developed ML model provides more accurate results than existing methods and can estimate the drift capacity for a broad range of RC columns. The developed model is published under an open-source license and is freely available to practitioners and researchers.

Ultra-high performance concrete (UHPC) is a forward-looking material ideal for use in large-scale civil infrastructure systems. However, due to its unique mix, when UHPC is used in actual structures in conjunction with materials like steel reinforcement, it may lead to unexpected behavior. Therefore, this study analyzed the behavior of reinforced UHPC (R-UHPC) for use in actual structures, focusing specifically on beams among various structural components, with a particular emphasis on their flexural behavior. For this purpose, the study collected and comprehensively analyzed experimental data from flexural tests of R-UHPC beams conducted to date, identifying basic mechanics, peculiarities, and considerations in structural design. This study highlights that, besides the commonly known longitudinal reinforcement ratio, numerous factors such as beam length, height, number of tension reinforcement layers, strength, etc., can influence the flexural behavior of R-UHPC beams and demonstrate how these elements impact the performance.

This study uses six large-scale experimental tests to investigate the seismic behavior of external socket connections for reinforced concrete columns. The tests evaluated the effects of key design parameters, including socket height and grout strength, on the performance of these connections under reverse cyclic lateral loads. The results indicate that socket height significantly affects whether the plastic hinge forms in the column above the connection or inside the socket and influences the required strength of the structural components. Shorter socket heights required higher grout strengths and increased shear capacity to avoid undesirable failure modes. Three primary failure modes were observed: grout crushing, shear failure, and flexural failure above the socket. Regardless of socket height, all tests showed that external socket connections effectively protect adjoining structural members by limiting plastic strain demands. These findings provide valuable insights into optimizing the design and performance of external socket connections in seismic regions.

Precast concrete (PC) moment-resisting frame systems with wide beam sections have been increasingly adopted in the construction industry due to their advantages in reducing the span length of PC slabs perpendicular to wide beam members and improving the constructability of precast construction. To further facilitate fast-built construction, this study introduces a novel PC wide beam-column connection system, where the solid panel zone is prefabricated and integrated into the PC column, allowing the upper floor to be quickly constructed without delay due to the curing time of cast-in-place concrete. Meanwhile, the current ACI CODE-318-19 code imposes strict allowable limits on the width of wide beams and complex reinforcement details as part of a seismic force-resisting system to effectively transfer forces into the joint, considering the shear lag effect. To address this, two full-scale PC wide beam-column test specimens were carefully designed, fabricated, and tested to explore the impact of large beam width and simplified reinforcement details beyond the code limit. The seismic performance was evaluated in terms of lateral strength, deformation capacity, stiffness degradation, failure mechanism, and energy dissipation. Based on the evaluation, the proposed PC wide beam-column connections demonstrated equivalent, or even better, seismic performance than the reinforced concrete control specimen. Additionally, it was found that the presence of corbels can mitigate the shear lag effect in PC wide beam-column connections, and that the current effective beam width limit imposed by ACI CODE-318-19 is conservative for PC wide beam-column connections with corbels.

This article presents a robust mathematical framework for computing centroidal polar moments of inertia in a standardized manner, applicable to both regular- and irregular-shaped sections, for use with the traditional ‘ACI Commentary Jc Method.’ The article also showcases with mathematical rigor why, for over 60 years, the standard (traditional) expressions used to compute polar moments of inertia for planar sections embedded in three-dimensional space have been incorrectly derived, and explores the implications of not adopting the correct expressions in design. The mathematical framework for computing polar moments of inertia is developed using advanced calculus, and primitive sections are integrated into the formulation to derive with ease the necessary expressions for the most common sections used in design, namely: rectangular, circular, C-shaped, L-shaped, and regular polygon-shaped sections. Finally, a numerical example is provided to demonstrate the practical implementation of the proposed mathematical framework.