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Incorporating pre-existing crack in service life prediction of reinforced concrete structures subjected to corrosion is crucial for accurate assessment, realistic modelling and effective decision-making in terms of maintenance and repair strategies.

An accelerated corrosion test was conducted by using impressed current method on cylindrical specimens with varying cover thickness and crack width. Mechanical properties of the specimens were evaluated by tensile tests.

The results show that, the pre-cracked samples exhibited shorter concrete cover cracking times, particularly with wider cracks when compared to the uncracked samples. Moreover, the load-bearing capacity of the reinforcement bars decreased owing to the pre-cracks, causing structural deflection and a shortened yield plateau. However, the ductility index remained consistent across all sample types, implying that the concrete had good overall ductility. Comparing the results of the non-corroded rebar and corroded rebar samples, the maximum reduction in the yield load was 25.22%, whereas the maximum reduction in the ultimate load was 26.23%. The simple mathematical model proposed in this study provides a reliable method for predicting the chloride ion diffusion coefficient in cracked concrete of existing reinforced concrete structures.

A simple mathematical model was proposed for evaluation of the equivalent chloride ion diffusion coefficient considering crack width, average crack spacing and crack extending lengths for cracked reinforced concrete structures, which is used to incorporate existing crack in service life prediction models.

The purpose of this paper was to prepare a ternary hierarchical rough particle to accelerate the anti-corrosive design for coastal concrete infrastructures.

A kind of micro-nano hydrophobic ternary microparticles was fabricated from SiO₂/halloysite nanotubes (HNTs) and recycled concrete powders (RCPs), which was then mixed with sodium silicate and silane to form an inorganic slurry. The slurry was further sprayed on the concrete surface to construct a superhydrophobic coating (SHC). Transmission electron microscopy and energy-dispersive X-ray spectroscopy mappings demonstrate that the nano-sized SiO₂ has been grafted on the sub-micron HNTs and then further adhered to the surface of micro-sized RCP, forming a kind of superhydrophobic particles (SiO₂/HNTs@RCP) featured of abundant micro-nano hierarchical structures.

The SHC surface presents excellent superhydrophobicity with the water contact angle >156°. Electrochemical tests indicate that the corrosion rate of mild steel rebar in coated concrete reduces three-order magnitudes relative to the uncoated one in 3.5% NaCl solution. Water uptake and chloride ion (Cl^-) diffusion tests show that the SHC exhibits high H₂O and Cl^- ions barrier properties thanks to the pore-sealing and water-repellence properties of SiO₂/HNTs@RCP particles. Furthermore, the SHC possesses considerable mechanical durability and outstanding self-cleaning ability.

SHC inhibits water uptake, Cl^- diffusion and rebar corrosion of concrete, which will promote the sustainable application of concrete waste in anti-corrosive concrete projects.

Existing deterministic models that predict the capacity of corroded reinforced concrete (RC) beams have limited applicability because they were based on accelerated tests that induce general corrosion. This research gap was addressed by performing a combined numerical and statistical analysis on RC beams, subjected to natural corrosion, to achieve a much better forecast.

Data of 42 naturally corroded beams were collected from the literature and analyzed numerically. Four constitutive models and their combinations were considered: the elastic-semi-plastic and elastic-perfectly-plastic models for steel, and two tensile models for concrete with and without the post-cracking stresses. Meanwhile, Popovics’ model was used to describe the behavior of concrete under compression. Corrosion coefficients were developed as functions of corrosion degree and beam parameters through linear regression analysis to fit the theoretical moment capacities with test data. The performance of the coefficients derived from different combinations of constitutive laws was then compared and validated.

The results showed that the highest accuracy (R² = 0.90) was achieved when the tensile response of concrete was modeled without the residual stresses after cracking and the steel was analyzed as an elastic-perfectly-plastic material. The proposed procedure and regression model also showed reasonable agreement with experimental data, even performing better than the current models derived from accelerated tests and traditional procedures.

This study presents a simple but reliable approach for quantifying the capacity of RC beams under more realistic conditions than previously reported. This method is simple and requires only a few variables to be employed. Civil engineers can use it to obtain a quick and rough estimate of the structural condition of corroding RC beams.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

Although separate studies on the influence of corrosion and fire exposure on the constitutive relationship of concrete and steel have been done, there is still a gap in knowledge on the influence of corrosion-temperature superimposition as nonlinear phenomenon. The current study is focused to investigate the response of hot-rolled steel bars subjected to corrosion-temperature superimposition.

Using the accelerated corrosion-impressed-current technique, hot-rolled specimens with different levels of corrosion were obtained. The hot-rolled rebars were first corroded to target levels such as (6, 12, 18, 24, 30 and 36%) and subsequently subjected to target temperatures (250 °C, 400 °C, 550 °C, 800 °C and 950 °C), before tensile tests were carried out to evaluate the residual mechanical response.

The outcomes showed a significant decline in the parameters governing the mechanical properties of steel reinforcement due to the combined damage due to corrosion and fire. Corroded reinforcement still showed ductile failure after exposure to fire. Moreover, the combined loss of load-bearing characteristics due to corrosion and fire has little influence on the modulus of elasticity. The outcomes of this investigation provide a theoretical database for the assessment of aged structural elements exposed to combination after exposure to fire.

The information concerning structural material's response to corrosion-temperature combined damage is still limited. The cover of the reinforcement is designed to safeguard the reinforcing bars from foreign agencies but is often damaged and spalled off due to corrosion, rendering the reinforcing bars directly exposed. The study aims at the experimental production of fire conditions in a corrosion-damaged infrastructure to cover the aforementioned research gap. The effects of corrosion being superimposed by exposure to elevated temperatures on key parameters affecting mechanical behavior were examined.

1. Influence of corrosion-temperature superimposition on the mechanical properties of hot-rolled rebars.

2. Influence of corrosion-temperature superimposition on the macro and microstructure properties of hot-rolled rebars.

3. Influence of corrosion-temperature superimposition on stress-strain curves of hot-rolled rebars.

4. Influence of corrosion-temperature superimposition on tensile strength, modulus of elasticity and elongation of hot-rolled rebars.

Influence of corrosion-temperature superimposition on the mechanical properties of hot-rolled rebars.

Influence of corrosion-temperature superimposition on the macro and microstructure properties of hot-rolled rebars.

Influence of corrosion-temperature superimposition on stress-strain curves of hot-rolled rebars.

Influence of corrosion-temperature superimposition on tensile strength, modulus of elasticity and elongation of hot-rolled rebars.

The combination of an Engineered Cementitious Composite (ECC) layer and steel plate to reinforce RC beams (ESRB) is a new strengthening method. The ESRB was proposed based on the steel plate at the bottom of RC beams, aiming to solve the problem of over-reinforced RC beams and improve the bearing capacity of RC beams without affecting their ductility.

In this paper, the finite element model of ESRB was established by ABAQUS. The results were compared with the experimental results of ESRB in previous studies and the reliability of the finite element model was verified. On this basis, parameters such as the width of the steel plate, thickness of the ECC layer, damage degree of the original beam and cross-sectional area of longitudinal tensile rebar were analyzed by the verified finite element model. Based on the load–deflection curve of ESRB, ESRB was discussed in terms of ultimate bearing capacity and ductility.

The results demonstrate that when the width of the steel plate increases, the ultimate load of ESRB increases to 133.22 kN by 11.58% as well as the ductility index increases to 2.39. With the increase of the damage degree of the original beam, the ultimate load of ESRB decreases by 23.7%–91.09 kN and the ductility index decreases to 1.90. With the enhancement of the cross-sectional area of longitudinal tensile rebar, the ultimate bearing capacity of ESRB increases to 126.75 kN by 6.2% and the ductility index elevates to 2.30. Finally, a calculation model for predicting the flexural capacity of ESRB is proposed. The calculated results of the model are in line with the experimental results.

Based on the comparative analysis of the test results and numerical simulation results of 11 test beams, this investigation verified the accuracy and reliability of the finite element simulation from the aspects of load–deflection curve, characteristic load and failure mode. Furthermore, based on load–deflection curve, the effects of steel plate width, ECC layer thickness, damage degree of the original beam and cross-sectional area of longitudinal tensile rebar on the ultimate bearing capacity and ductility of ESRB were discussed. Finally, a simplified method was put forward to further verify the effectiveness of ESRB through analytical calculation.

The durability of concrete containing recycled aggregates, sourced from concrete specimens that have been tested in laboratory testing facilities, remains understudied. This paper aims to present the results of experiments investigating the effect of incorporating such type of concrete waste on the strength and durability-related properties of concrete.

A total of 77 concrete cylinders sized Ø100 × 200 mm with varying amount of recycled concrete aggregate (RCA) (0%–100% by volume, at 25% increments) and maximum aggregate size (12.5, 19.0 and 25.0 mm) were fabricated and tested for slump, compressive strength, sorptivity and electrical resistivity. Disk-shaped specimens, 50-mm thick, were cut from the original cylinders for sorptivity and resistivity tests. Analysis of variance and post hoc test were conducted to detect statistical variability among the data.

Compared to regular concrete, a reduction of slump (by 18.6%), strength (15.1%), secondary sorptivity (31.5%) and resistivity (17.0%) were observed from concrete containing 100% RCA. Statistical analyses indicate that these differences are significant. In general, an aggregate size of 19 mm was found to produce the optimum value of slump, compressive strength and sorptivity in regular and RCA-added concrete.

The results of this study suggest that comparable properties of normal concrete were still achieved by replacing 25% of coarse aggregate volume with 19-mm RCA, which was processed from laboratory-tested concrete samples. Therefore, such material can be considered as a potential and sustainable alternative to crushed gravel for use in light or nonstructural concrete construction.

This study investigated the potential of partially replacing cement with red mud (RM) in concrete and examined its effects on its mechanical properties and microstructure. This study aims to explore sustainable alternatives to traditional cement and evaluate the performance of concrete mixtures with varying percentages (%) of RM as cement replacement.

This research aims to comprehensively understand the impact of RM on concrete, aiming for both environmental sustainability and improved construction materials. Subsequently, concrete mixtures were prepared with varying RM contents, ranging from 0% to 21% in increments of 3%, replacing cement. The workability of these mixtures was evaluated using the Slump Cone Test, whereas their mechanical properties (compressive strength, flexural strength and split tensile strength) were assessed through standardized tests. The durability was further investigated via water absorption, acid attack, rapid chloride permeability tests, open porosity test and Sorptivity test. To gain deeper insights into the internal structure of concrete, microstructure analysis was conducted using X-ray diffraction and scanning electron microscopy. Finally, the results were analyzed and quantified.

The finding demonstrates that substituting 12% of cement with RM not only boosts the mechanical characteristics of concrete but also mitigates waste disposal. The microstructural analysis identified a denser cement matrix and improved bonding between the cement paste and the aggregates, suggesting potential improvements in strength and durability.

These results suggest that RM can be efficiently used to produce sustainable concrete with potential applications in construction projects with environmental considerations.

This study aims to investigate the corrosion inhibitor effect of migrating corrosion inhibitor (MCI) on Q235 steel in high alkaline environment under cathodic polarization.

This study investigated the electrochemical characteristics of Q235 steel with and without MCI by polarization curve and electrochemical impedance spectroscopy. Besides, the surface composition of Q235 steel under different environments was analyzed by X-ray photoelectron spectroscopy. In addition, the migration characteristic of MCI and the adsorption behavior of MCI under cathodic polarization were studied using Raman spectroscopy.

Diethanolamine (DEA) and N, N-dimethylethanolamine (DMEA) can inhibit the increase of Fe(II) in the oxide film of Q235 steel under cathodic polarization. The adsorption stability of DMEA film was higher under cathodic polarization potential, showing a higher corrosion inhibition ability. The corrosion inhibition mechanism of DEA and DMEA under cathodic polarization potential was proposed.

The MCI has a broad application prospect in the repair of damaged reinforced concrete due to its unique migratory characteristics. The interaction between MCIs, rebar and concrete with different compositions has been studied, but the passivation behavior of the steel interface in the presence of both the migrating electric field and corrosion inhibitors has been neglected. And it was investigated in this paper.

The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength development. This study aims to predict the compressive strength of normal concrete and high-performance concrete using four datasets.

In this paper, five established individual Machine Learning (ML) regression models have been compared: Decision Regression Tree, Random Forest Regression, Lasso Regression, Ridge Regression and Multiple-Linear regression. Four datasets were studied, two of which are previous research datasets, and two datasets are from the sophisticated lab using five established individual ML regression models.

The five statistical indicators like coefficient of determination (R²), mean absolute error, root mean squared error, Nash–Sutcliffe efficiency and mean absolute percentage error have been used to compare the performance of the models. The models are further compared using statistical indicators with previous studies. Lastly, to understand the variable effect of the predictor, the sensitivity and parametric analysis were carried out to find the performance of the variable.

The findings of this paper will allow readers to understand the factors involved in identifying the machine learning models and concrete datasets. In so doing, we hope that this research advances the toolset needed to predict compressive strength.