International Concrete Abstracts Portal

Integrating real-time sensor data with physics-based models enhances the accuracy and efficiency of structural simulation and prognosis. In this study, a sensing-based simulation method is introduced to compute bending moments in reinforced concrete bridge columns subjected to seismic motions, based on the measured strains continuously fed to plasticity models. The experimental program included hybrid testing of scaled reinforced concrete bridges under consecutive seismic events. The experimental columns were instrumented with embedded as well as surface-adhered fiber-optic Bragg grating (FBG) sensors for real-time monitoring of strains reflecting degradation of the columns during the formation of damage. The fundamental assumption of strain compatibility in reinforced concrete members was investigated for the successive progression of damage in the cross sections of the columns. The stress distributions within the concrete core and cover were computed through the confined and unconfined concrete stress-strain relations for loading, unloading, and reloading scenarios. The bending moments in the cross-section were computed and compared with the corresponding experimental values calculated based on direct measurements of forces. The results from this study revealed that the cross-sectional strains exhibit three primary features during the seismic events that need to be considered for the accurate calculation of bending moments. Computation of the bending moments requires considering the shifts in cyclic reference, post-event residual strains, and the real steel strains. By using these features, the computed bending moments during the column tests mimicked the experimental results based on the measured seismic forces on the columns.

This study investigates the bonding behavior of large-diameter steel bars (D43 and D57) embedded in concrete using pull-out tests coupled with acoustic emission (AE) monitoring. These large bars, commonly used in nuclear containment structures from the 1970s, were compared with conventional steel bars (D19 and D32) across three concrete strength levels. All tests were performed under displacement-controlled loading using an MTS testing machine. Results indicate that ACI 408R provisions remain valid for large-diameter reinforcing bars. The test results showed that when specimens reached ultimate bond stress, the D57 bar developed only 12 to 16% of its yield strength, whereas the D19 bar reached at least 70%. AE monitoring effectively captured the debonding process, and cumulative AE hit counts correlated with the strain energy released at each loading stage, offering insight into bond failure mechanisms.

Portland Limestone Cement (PLC) has gained widespread use as the most accessible and sustainable blended cement in the market. However, in many African countries, including Ghana, the use of clay pozzolana in the concrete industry has primarily relied on Ordinary Portland Cement (OPC). In this study, PLC Type II/B-L was partially replaced with clay pozzolana at levels ranging from 10% to 50% by weight. The investigation included compressive strength testing, non-destructive evaluations using electrical surface resistivity, pulse velocity, and chloride penetration tests, targeting a characteristic strength of 30 MPa. Additionally, an environmental impact assessment based on the carbon footprint of both control and clay pozzolana concretes was conducted. The mix design followed the EN 206 standard. A total of 72 cubic moulds were produced for the strength test. The results showed that clay pozzolana concretes with between 10 and 20% replacement achieved strength values of 35 and 33 MPa, respectively, higher than the target of 30 MPa (4351.13 psi) strength at 28 days. However, mixtures with 30% to 50% replacement required extended curing periods of 60 to 90 days to reach the desired strength. At extended curing, 10-50% clay pozzolana replacement attained strength between 32 and 41 MPa. Non-destructive test results showed no direct correlation with compressive strength, confirming that different factors govern strength, resistivity, and pulse velocity. The environmental impact assessment revealed a 14 to 51% reduction in CSi and a 19 to 36% increase in CRi with 10 to 50% clay pozzolana (for CSi) and 10 to 40% (for CRi). The thermodynamic modelling also revealed that pozzolana contents below 30% primarily promoted pozzolanic reactions, enhancing performance compared to the control mix. Based on these results, 20–30% clay pozzolana replacement is recommended to ensure reliable performance, while higher levels (>30%) require further durability evaluation for long-term use.

The durability of reinforced concrete is often compromised by chloride penetration, leading to corrosion of reinforcing steel and reduced structural strength. To improve the sustainability and longevity of concrete structures, it is crucial to model and predict chloride permeability (CP) accurately, thereby minimizing the time and resources required for extensive experimental testing. This paper presents a proof-of-concept study applying Artificial Neural Networks (ANN) to predict CP in concrete structures. The model was trained on a small but carefully controlled experimental dataset of 10 concrete mixtures, considering four key parameters: water-to-cementing materials ratio, silica fume content, cementing materials content, and air content. Despite the limited dataset size, which constrains generalizability and statistical robustness, the ANN captured nonlinear relationships among the input parameters and CP. The comparison between experimental and simulated CP values showed reasonable agreement, with errors ranging between –242 and 420 Coulombs. These results establish the trustworthiness and reliability of the proposed model, providing a valuable tool for predicting CP and informing the design of durable and sustainable concrete structures.

Previous research studies have been conducted to study the seismic response of low-aspect-ratio RC shear walls when designed using normal-strength reinforcement (NSR) versus high-strength reinforcement (HSR). Such studies demonstrated that the use of HSR has the potential to address several constructability issues in nuclear construction practice by reducing the required steel areas and subsequently rebar congestion. However, the response of nuclear RC shear walls (i.e., aspect ratios of less than one) with both HSR and axial loads has not yet been evaluated under ground motion sequences. As such, most nuclear design standards restrict the use of HSR in nuclear RC shear wall systems. Such design standards do not consider the influence of axial loads when the shear strength capacity of such walls is calculated. To address this gap, the current study investigates the influence of axial load on the performance of nuclear RC shear walls with HSR when subjected to ground motion sequences using hybrid simulation testing and modelling assessment techniques. In this respect, two RC shear walls (i.e., W1-HSR and W2-HSR-AL), with an aspect ratio of 0.83, are investigated. Wall W2-HSR-AL had an axial load of 3.5% of its axial compressive strength, while wall W1-HSR had no axial load. The test walls were subjected to a wide range of ground motion records, from operational basis earthquake (OBE) to beyond design basis earthquake (BDBE) levels. The experimental results of the walls are discussed in terms of their damage sequences, cracking patterns, ductility capacities, effective periods, and rebar strains. The test results are then used to develop and validate a numerical OpenSees model that simulates the seismic response of nuclear RC shear walls with different axial load levels. Finally, the experimental and numerical results are compared to the current ASCE 41-23 backbone model for RC shear walls. The experimental results demonstrate that walls W1-HSR and W2-HSR-AL showed similar crack patterns and subsequent shear-flexure failures; however, the former had wider cracks relative to the former during the different ground motion records. In addition, the axial load reduced the displacement ductility of wall W2-HSR-AL by 18% compared to wall W1-HSR. Moreover, the ASCE 41-23 backbone model was not able to adequately capture the seismic response of the two test walls. The current study enlarges the experimental and numerical/analytical database pertaining to the seismic performance of low-aspect-ratio RC shear walls with HSR to facilitate their adoption in nuclear construction practice.