This article presents a comprehensive and critical review of the structural performances of reinforced recycled aggregate concrete beams and columns based on experimental results reported in the literature. Extensive data sets collected from the literature are categorized to investigate the effects on the local and global structural behavior. First, the flexural and shear response of reinforced recycled aggregate concrete beams is discussed. The structural performances are reviewed focusing on the main geometric and material variables such as the recycled concrete aggregate replacement ratio, the longitudinal reinforcement ratio, the transverse reinforcement ratio, and the shear span-to-depth ratio. Then, the behavior of reinforced recycled aggregate concrete columns under concentric and eccentric compressive loads and the seismic performance under low cyclic loading are discussed. The similarities and the differences between reinforced recycled aggregate concrete and reinforced natural aggregate concrete beams and columns are highlighted. The need for further research is pointed out at the end of the article. The results reported in this review clearly indicate that reinforced recycled aggregate concrete beams and columns with various recycled concrete aggregate replacement ratios have comparable or slightly lower structural performances to the reinforced natural aggregate concrete ones indicating the feasibility of recycled concrete aggregate for structural applications.
Recycled aggregate concrete (RAC) is a promising solution to address the challenges raised by concrete production. However, the current lack of pertinent design rules has led to a hesitance to accept structural members made with RAC. It would entail even more difficulties when facing application scenarios where brittle failure is possible (e.g., beam in shear). In this paper, existing major shear design formulae established primarily for conventional concrete beams were assessed for RAC beams. Results showed that when applied to the shear test database compiled for RAC beams, those formulae provided only inaccurate estimations with surprisingly large scatter. To cope with this bias, machine learning (ML) techniques deemed as potential alternative predictors were resorted to. First, a Grey Relational Analysis (GRA) was carried out to rank the importance of the parameters that would affect the shear capacity of RAC beams. Then, two contemporary ML approaches, namely, the artificial neural network (ANN) and the random forest (RF), were leveraged to simulate the beams’ shear strength. It was found that both models produced even better predictions than the evaluated formulae. With this superiority, a parametric study was undertaken to observe the trends of how the parameters played roles in influencing the shear resistance of RAC beams. The findings indicated that, though less influential than the structural parameters such as shear span ratio, the effect of the replacement ratio of recycled aggregate (RA) was still significant. Nevertheless, the value of vc/(fc)1/2 (i.e., the shear contribution from RAC normalized with respect to the square root of its strength) predicted by the ML-based approaches appeared to be insignificantly affected by the replacement level. Given the existing inevitable large experimental scatter, more shear tests are certainly needed and, for safe application of RAC, using partial factors calibrated to consider the uncertainty is feasible when designing the shear strength of RAC beams. Some suggestions for future works are also given at the end of this paper.
Recycled concrete aggregates (RCAs) generated from construction and demolition activities have been recognized as a feasible alternative to natural aggregates (NAs). Naturally, the columns fabricated with reinforced recycled concrete (RRC) have been proposed and investigated to promote the structural use of recycled aggregate concrete (RAC). There is still, however, very limited modeling research available to reproduce, accurately and efficiently, the seismic response of RRC columns under lateral cyclic loading; proper evaluations are also lacking on addressing the columns’ seismic behaviors. To fill some of those research gaps, a fiber-based numerical model is developed in this study and then validated with the experimental results published in the literature. Subsequently, the numerical model justified is applied to carry out a comprehensive parametric study to examine the effects of a range of variables on the hysteretic characteristics of RRC columns. Furthermore, a grey relational analysis is conducted to establish quantifiable evidence of key variable sensitivities. The evaluation results imply that the use of the additional water method (AWM) for manufacturing RAC is likely to reduce the lateral load-carrying capacity of the RRC columns (up to 10%), whereas the opposite would occur if a conventional mixing procedure is adopted. Moreover, compared with other factors such as steel area ratio, the content of RCA replacement has a less remarkable effect on the seismic performance of the RRC columns. In general, the RRC columns possess acceptable seismic-resistant properties, and they can be used in earthquake-prone regions with confidence.
The use of composite beams made with traditional concrete and bio-based materials (such as timber and bamboo) is a valuable solution to reduce the environmental impact of the building sector. Timber-Concrete Composite (TCC) beams have been used for decades in structural applications such as new buildings, refurbishment of old timber structures, and bridges. Recently, different researchers suggested composite beams based on engineered bamboo, commonly named Bamboo-Concrete Composite (BCC) beams. This study presents a systematic comparison of structural performances and connection behavior of TCC and BCC beams under short-term static load. TCCs beams are compared to BCC ones using similar shear connectors. The most important aspects of the two composite systems are compared: mechanical behavior of connectors and structural behaviors of full-scale composite beams (e.g., failure modes, connection stiffness, connection shear strength, ultimate load-carrying capacity, maximum deflection and composite efficiency). This comprehensive review indicates that BCC beams have similar or even better structural performances compared with TCC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.