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Damage to reinforced concrete (RC) structural elements is inevitable. Such damage can be the result of several factors, including aggressive environmental conditions, overloading, inadequate design, poor work execution, fire, storm, earthquakes etc. Therefore, repairing and strengthening is one way to improve damaged structures, so that they can be reutilized. In this research, the use of an ultra high-performance fibre-reinforced concrete (UHPFRC) layer is proposed as a strengthening material to rehabilitate damaged-RC beams. Different strengthening schemes pertaining to the structural performance of the retrofitted RC beams due to the flexural load were investigated.

A total of 13 normal RC beams were prepared. All the beams were subjected to a four-point flexural test. One beam was selected as the control beam and tested to failure, whereas the remaining beams were tested under a load of up to 50% of the ultimate load capacity of the control beam. The damaged beams were then strengthened using a UHPFRC layer with two different schemes; strip-shape and U-shape schemes, before all the beams were tested to failure.

Based on the test results, the control beam and all strengthened beams failed in the flexural mode. Compared to the control beam, the damaged-RC beams strengthened using the strip-shape scheme provided an increase in the ultimate load capacity ranging from 14.50% to 43.48% (or an increase of 1.1450 to 1.4348 times), whereas for the U-shape scheme beams ranged from 48.70% to 149.37% (or an increase of 1.4870–2.4937 times). The U-shape scheme was more effective in rehabilitating the damaged-RC beams. The UHPFRC mixtures are workable, as well easy to place and cast into the formworks. Furthermore, the damaged-RC beams strengthened using strip-shape scheme and U-shape scheme generated ductility factors of greater than 4 and 3, respectively. According to Eurocode8, these values are suitable for seismically active regions. Therefore, the strengthened damaged-RC beams under this study can quite feasibly be used in such regions.

Observations of crack patterns were not accompanied by measurements of crack widths due to the unavailability of a microcrack meter in the laboratory. The cost of the strengthening system application were not evaluated in this study, so the users should consider wisely related to the application of this method on the constructions.

Rehabilitation of the damaged-RC beams exhibited an adequate structural performance, where all strengthened RC beams fail in the flexural mode, as well as having increment in the failure load capacity and ductility. So, the used strengthening system in this study can be applied for the building construction in the seismic regions.

Aside from equipment, application of this strengthening system need also the labours.

The use of sand blasting on the surfaces of the damaged-RC beams, as well as the application of UHPFRC layers of different thicknesses and shapes to strengthen the damaged-RC beams, provides a novel innovation in the strengthening of damaged-RC beams, which can be applicable to either bridge or building constructions.

The current study mainly focuses on the effect of varying diameter recycled steel fibers (RSF) on mechanical properties of concrete prepared with 25 and 50% of recycled coarse aggregate (RCA) as well as 100% natural aggregate (NA). Two types of RSF with 0.84 mm and 1.24 mm diameter having 30 mm length were incorporated into normal and recycled aggregate concrete (RAC).

The fresh behavior, compressive, splitting tensile, flexural strengths and modulus of elasticity of all the mixes were investigated to evaluate the mechanical properties of RACs. In addition, specimen crack and testing co-relation were analyzed to evaluate fiber response in the RAC.

According to the experimental results, it was observed that mechanical properties decreased with the increment replacement of NA by RCA. However, the RSF greatly improves the mechanical properties of both normal concrete and RACs. Moreover, mixes containing 1.24 mm diameter RSF had a more significant positive impact on mechanical properties than mixes containing 0.84 mm diameter RSF. The 0.84 mm and 1.24 mm RSF addition improved the mixes' compressive, splitting tensile and flexural strength by 10%–19%, 19%–30% and 3%–11%, respectively when compared to the null fiber mix. Therefore, based on the mechanical properties, the 1.24 mm diameter of RSF with 25% replacement of RCA was obtained as an optimum solution in terms of performance improvement, environmental benefit and economic cost.

The practice of RCA in construction is a long-term strategy for reducing natural resource extraction and the negative ecological impact of waste concrete.

This is the first study on the effects of varying size (0.84 mm and 1.24 mm diameter) RSF on the mechanical properties of RAC. Additionally, varying sizes of RSF and silica fume added a new dimension to the RAC.

This paper aims to reduce waste management and generate wealth by investigating the novelty of combining chicken feather fiber and bamboo particles to produce hybrid biocomposites. This is part of responsible production and sustainability techniques for sustainable development goals. This study aims to broaden animal and plant fiber utilization in the sustainable production of epoxy resins for engineering applications.

This research used two reinforcing materials [chicken feather fiber (CFF) and bamboo particles (BP)] to reinforce epoxy resin. The BPs were kept constant at 6 Wt.%, while the CFF was varied within 3–15 Wt.% in the composites to make CFF-BP polymer-reinforced composite (CFF-BP PRC). The mechanical experiment showed a 21% reduction in densities, making the CFF-BP PRC an excellent choice for lightweight applications.

It was discovered that fabricated composites with 10 mm CFF length had improved properties compared with the 15 mm CFF length and pristine samples, which confirmed that short fibers are better at enhancing randomly dispersed fibers in the epoxy matrix. However, the ballistic properties of both samples matched. There is a 40% increase in tensile strength and a 54% increase in flexural strength of the CFF-BP PRC compared to the pristine sample.

According to the literature review, to the best of the authors’ knowledge, this is a novel study of chicken fiber and bamboo particles in reinforcing epoxy composite.

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 main aim of the current study is to investigate the effect of Anti-Crack HP 67/36 glass fibre on the mechanical performance of mortars made of cement, with a focus on post-cracking evaluations using the digital image correlation (DIC) technique.

Experimental tests were carried out on 36-mm long fibres at 0.8% by volume and added to the normal strength (NSM), high strength (HSM) and high strength mortar with fly ash (HSMFA) mortars. CEM I 52.5 CP2 NF, CEM II/A-L 42.5 NF and CEM III/C 32.5 N-SR PM were used for each series of mortar to assess the performance of the glass fibres with the types of cement. F-class fly (FA) ash was used to reduce global CO₂ emissions.

The mortar’s strength decreased as the cement types changed from CEM I to CEM II and III. However, due to changes in the portlandite content of the cement, water porosity increased for both types of mortar, without and with fibre. It was also found that using glass fibre increased flexural strength more than compressive strength, regardless of the type of cement used. For all the strength classes, it was found that the mortar mixes with CEM I had the highest critical crack opening (w_c) and fracture energy (G_F), followed by CEM II and III. No significant effects were observed in the mortar’s property by replacing fly ash (12%).

Only mortars were formulated in this study, but the results must be verified at the concrete scale.

Validation of the DIC technique to characterize the post-cracking behaviour of cement-based material. Use of glass fibres to improve the material’s resistance to cracking.

Use of CEM II and CEM III cements with low CO₂ footprint instead of CEMI without altering the mechanical performance of the material.

The work is a further contribution to studying the cracking behaviour of several series of variable mortars depending on the resistance class and the type of cement used.

Polymethyl methacrylate (PMMA) is a remarkable biocompatible material for bone cement and regeneration. It is also considered 3D printable but requires in-depth process–structure–properties studies. This study aims to elucidate the mechanistic effects of processing parameters and sterilization on PMMA-based implants.

The approach comprised manufacturing samples with different raster angle orientations to capitalize on the influence of the filament alignment with the loading direction. One sample set was sterilized using an autoclave, while another was kept as a reference. The samples underwent a comprehensive characterization regimen of mechanical tension, compression and flexural testing. Thermal and microscale mechanical properties were also analyzed to explore the extent of the appreciated modifications as a function of processing conditions.

Thermal and microscale mechanical properties remained almost unaltered, whereas the mesoscale mechanical behavior varied from the as-printed to the after-autoclaving specimens. Although the mechanical behavior reported a pronounced dependence on the printing orientation, sterilization had minimal effects on the properties of 3D printed PMMA structures. Nonetheless, notable changes in appearance were attributed, and heat reversed as a response to thermally driven conformational rearrangements of the molecules.

This research further deepens the viability of 3D printed PMMA for biomedical applications, contributing to the overall comprehension of the polymer and the thermal processes associated with its implementation in biomedical applications, including personalized implants.

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.

Durability of concrete can be enhanced by reducing the pore size/volume of pores or by entrapping the pores. This can be achieved by adding concrete admixtures that have particle size finer than cement. In this study, GNP, having particle size much smaller than cement, has been introduced/added to concrete mix to control the pore size in concrete to tape out the contribution of GNP in the durability enhancement of concrete.

Different concrete mixes, at various water–cement ratios and amounts of graphene, have been manufactured to produce concrete containing three different %ages of GNP, i.e. 0%, 0.05% and 0.1%. To demonstrate the effect on durability of the concrete through the addition of GNP, these concrete samples have been subjected to repeated Freeze-Thaw cycles. Followed by testing after 28 days of curing, including weight loss, water absorption and strength, which are directly related to the durability aspect of concrete.

It has been observed that the addition of GNP to concrete mixes reduces the weight loss and pore size distribution and enhances tensile and compressive strength of concrete, thereby increasing the durability of concrete in unfavorable circumstances like freeze-thaw i.e. alternate hot and cold weather conditions.

This investigation presents original piece of experimental work conducted on modified concrete (GNP-based concrete). The aim is to construct the civil infrastructure in deep-cold region with increased life span and better performance.

The current bending test method can only test the bending performance of fabric in one direction at a time. It is not possible to directly observe the bending morphology of fabrics in different directions, and it is necessary to cut samples and repeat the test several times, which takes more time. For this situation, a multidirectional visualization of the fabric bending test method is proposed, using which multiple results can be obtained at one time and the fabric bending can be visualized.

About 17 fabrics are tested using a self-designed device. The fabrics are cut into special triangles and multiple sets of results in three directions are obtained at once using the device. The experimental specimens are photographed from the above and the transverse elongation length, bending projection area and circumference are extracted after image processing.

The results show that the correlation coefficients of transverse elongation, bending projected area and circumference are good with the bending length measured by the cantilever method. In which, all three indicators are positively correlated with the bending length. This indicates the good feasibility of the new method.

This method can get the bending index of fabrics in three directions, with five samples in each direction at one time. Meanwhile, it can also visualize the flexural differences between different fabrics and directions of the same fabric. It can provide more efficient testing means for the textile testing field, and the testing efficiency is 15 times of the existing method, which has better theoretical significance and practical values.

Near-fault pulse-like ground motions have distinct and very severe effects on reinforced concrete (RC) structures. However, there is a paucity of recorded data from Near-Fault Ground Motions (NFGMs), and thus forecasting the dynamic seismic response of structures, using conventional techniques, under such intense ground motions has remained a challenge.

The present study utilizes a 2D finite element model of an RC structure subjected to near-fault pulse-like ground motions with a focus on the storey drift ratio (SDR) as the key demand parameter. Five machine learning classifiers (MLCs), namely decision tree, k-nearest neighbor, random forest, support vector machine and Naïve Bayes classifier , were evaluated to classify the damage states of the RC structure.

The results such as confusion matrix, accuracy and mean square error indicate that the Naïve Bayes classifier model outperforms other MLCs with 80.0% accuracy. Furthermore, three MLC models with accuracy greater than 75% were trained using a voting classifier to enhance the performance score of the models. Finally, a sensitivity analysis was performed to evaluate the model's resilience and dependability.

The objective of the current study is to predict the nonlinear storey drift demand for low-rise RC structures using machine learning techniques, instead of labor-intensive nonlinear dynamic analysis.