•DC/AC galvanostatic polarization is used to simulate railway stray DC/AC environments.•Charged electrons can be pushed through discrete steel fibres in SFRC under an external DC or AC voltage.•A ...small amount of chloride increases the stray current induced corrosion in SFRC.
This paper primarily discusses the assessment of stray DC and AC-induced corrosion phenomena on steel fibres and the analysis of the main influencing parameters. Instrumental methods in electrochemistry including Tafel polarization, Cyclic Potentiodynamic (CP) polarization and Electrochemical Impedance Spectroscopy (EIS) were used to assess the corrosion resistance of steel fibres which has great potential to replace conventional steel reinforcement in railway tunnel construction. The analytical model based on electric circuit modelling indicates that concrete containing discrete steel fibres has an inherent corrosion resistance to stray AC interference due to the electrical double layer developed on the surface.
•Mechanical behaviour of BFRC was evaluated by flexural and impact testing.•BFRC was made of (1) basalt bundled fibres and (2) basalt minibars.•Both BFRC increased pre-cracking strength; had little ...effect under impact loading.•Minibars significantly enhanced post-cracking behaviour but bundled fibres did not.•Bundled fibres failed by rupturing, whereas the minibars failed by pulling out.
Chopped basalt fibre has recently gained popularity in concrete reinforcing applications due to its environmentally friendly manufacturing process and excellent mechanical properties. The aim of this research is to evaluate the relative merit of two types of basalt fibre (bundle dispersion fibres and minibars) in enhancing the mechanical behaviour of concrete. Concrete specimens were cast with three different quantities of each fibre, then evaluated based on flexural and drop-weight impact testing. Interfacial properties were also investigated by scanning electron microscopy. The results indicated both types of fibre increased pre-cracking strength, but only minibars enhanced the post-cracking behaviour, likely due to protection from the polymer.
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•A multilayer perceptron neural network is proposed for Fibre Reinforced Concrete.•The post-cracking tensile strength is successfully predicted.•Analytical expressions are provided as ...an alternative tool to traditional testing.•The model has pre-design, quality control and reinforcement optimization purposes.•The model has proved to be coherent with the established knowledge.
Structural fibres are an effective method to improve concrete post-cracking tensile strength (fctR). Currently, the characterization of this property is mainly performed experimentally. This is a source of uncertainties at design stages, which hinders the development of new fibre type and/or optimization of those currently existing. This paper presents a multilayer perceptron neural network to predict fctR of fibre-reinforced concrete (FRC) subjected to the Barcelona Test. The optimal architecture of the predictor is obtained by evaluating 9216 configurations of input dimension and number of hidden layers and neurons. The generalization performance is assessed using repeated random sub-sampling validation with 50 iterations. The final model can predict with high accuracy the fctR of FRC for different cracking stages. A parametric analysis is performed to prove coherence between the results predicted by the model and the established understanding of the FRC behaviour. Finally, numerical expressions are provided as an alternative tool to traditional testing to predict the residual strength of the Barcelona Test for pre-design and quality control purposes based on fibre dosage, concrete strength, specimen type and height and fibre geometric characteristics. These type of approaches are found to be necessary for boosting the development of the FRC technology.
This study examined the effect of steel fiber geometry on the mechanical properties of ultra-high-performance fiber-reinforced concrete (UHPFRC) under cryogenic conditions (approximately −162 °C). ...For this, compressive and tensile tests were performed using UHPFRCs containing three types of straight steel fibers and one type of twisted steel fiber. To investigate the mechanical properties of UHPFRCs under various temperatures, mechanical tests were performed in three different conditions: ambient temperature, cryogenic temperature, and recovered ambient temperature. The test results demonstrated considerable increases in both the compressive strength and tensile performance, including strength and fracture energy, for UHPFRCs with straight fibers at the cryogenic temperature, whereas that containing the twisted fibers demonstrated the poorest energy absorption capacity at the cryogenic temperature, due to the fiber fracturing. Finally UHPFRCs containing longer straight fibers most effectively achieved excellent mechanical properties at the cryogenic temperature, compared to those with short straight and twisted fibers.
This study examined the electrical and self-sensing capacities of ultra-high-performance fiber-reinforced concrete (UHPFRC) with and without carbon nanotubes (CNTs). For this, the effects of steel ...fiber content, orientation, and pore water content on the electrical and piezoresistive properties of UHPFRC without CNTs were first evaluated. Then, the effect of CNT content on the self-sensing capacities of UHPFRC under compression and flexure was investigated. Test results indicated that higher steel fiber content, better fiber orientation, and higher amount of pore water led to higher electrical conductivity of UHPFRC. The effects of fiber orientation and drying condition on the electrical conductivity became minor as sufficiently high amount of steel fibers, 3% by volume, was added. Including only steel fibers did not impart UHPFRC with piezoresistive properties. Addition of CNTs substantially improved the electrical conductivity of UHPFRC. Under compression, UHPFRC with a CNT content of 0.3% or greater had a self-sensing ability that was activated by the formation of cracks, and better sensing capacity was achieved by including greater amount of CNTs. Furthermore, the pre-peak flexural behavior of UHPFRC was precisely simulated with a fractional change in resistivity when 0.3% CNTs were incorporated. The pre-cracking self-sensing capacity of UHPFRC with CNTs was more effective under tensile stress state than under compressive stress state.
Engineering design problems are often multi-objective in nature, which means trade-offs are required between conflicting objectives. In this study, we examine the multi-objective algorithms for the ...optimal design of reinforced concrete structures. We begin with a review of multi-objective optimization approaches in general and then present a more focused review on multi-objective optimization of reinforced concrete structures. We note that the existing literature uses metaheuristic algorithms as the most common approaches to solve the multi-objective optimization problems. Other efficient approaches, such as derivative-free optimization and gradient-based methods, are often ignored in structural engineering discipline. This paper presents a multi-objective model for the optimal design of reinforced concrete beams where the optimal solution is interested in trade-off between cost and deflection. We then examine the efficiency of six established multi-objective optimization algorithms, including one method based on purely random point selection, on the design problem. Ranking and consistency of the result reveals a derivative-free optimization algorithm as the most efficient one.
•Multi-objective optimization (MOO) approaches in general and in Reinforced Concrete (RC) structures are reviewed.•A novel multi-objective model is developed for the optimal design of RC beams.•A set of algorithms are examined and compared through numerical testing.•This paper enlightens the merits of advanced MOO methods in structural engineering problems.
Almost all FRP-reinforced concrete exposed to the marine environment are susceptible to durability deficiencies due to failure of the FRP/epoxy/concrete interface, especially the vulnerable ...epoxy/concrete interface, which is frequently attacked by water and ions. Herein, molecular dynamics simulations of epoxy/CSH interface under different environmental exposures are utilized to specifically elucidate the degradation principles of water and ions on the bonding properties and mechanical responses of the epoxy/concrete interface. The environmental sequences associated with the interfacial bonding degradation are arranged as Na2SO4 + NaCl>NaCl>Na2SO4 > Water>Dry. Remarkably, water molecules weaken the interaction between the epoxy and CSH by robbing interfacial H- and Ca-O bonds, thereby reducing the energy barrier to interfacial peel and shear failure. The weakening effects are exacerbated by the presence of aggressive ions, as Na+ ions attracted to the CSH surface accumulate more water molecules in the interfacial region by forming hydrated ions clusters, which ultimately accelerates the epoxy/CSH interfacial degradation.
•A hybrid artificial intelligence model based on random forest and firefly algorithm is presented.•The proposed model provides an accurate and efficient tool to predict the DIF of SFRC.•The model ...quantifies the effect of matrix strength, fibre dosage and fibre properties on the DIF.
Steel fibre reinforced concrete (SFRC) has been increasingly used in the engineering structures subjected to intense dynamic loads. In structural design and analysis, a dynamic increase factor (DIF) has been usually used to characterize strain-rate effect on the dynamic mechanical behaviour of SFRC. At present, several analytical equations that contain one or two variables have been utilised to predict the DIF values for material strengths of SFRC. However, this may lead to unsatisfactory results as the rate sensitivity of SFRC is influenced by multiple variables. In this study, a hybrid model, integrating random forest (RF) technique and firefly algorithm (FA), is proposed for predicting DIF values for SFRC. RF is utilized to discover the non-linear relationship between the influencing variables and DIF, while FA optimizes the hyper-parameters of RF. A total of 193 and 314 DIF data samples for compressive and tensile strengths of SFRC are retrieved from the reported studies to train and verify the proposed model. The input variables for the predictive model include strain rate, matrix strength, fibre dosage, and fibre properties (i.e. fibre shape, fibre aspect ratio and fibre tensile strength). The predicted results denote that the developed model is an efficient and accurate method to predict the DIF values for SFRC. Additionally, the relative importance of each input variable is investigated. It is found that the DIF values of SFRC are most sensitive to the matrix strength.
•A meshless framework is introduced tmodel fiber reinforced concrete members.•Micropolar peridynamic framework is successfully used in analyzing complex fracture mechanism in fiber reinforced ...concrete.•The proposed analytical approach is able treproduce the complex crack propagation behavior.•The modeling method is highly effective in representing the composite response of notched fiber reinforced beams.
In this study, an effective meshless model is proposed for fracture analysis of cracks in fiber reinforced concrete structures. The cementitious material is modeled using the micropolar peridynamic approach which is a generalized form of the bond-based peridynamics. A semi-discrete approach is incorporated in the micropolar peridynamic framework to study the effect of fiber reinforcement on the fracture analysis of cracks in cementitious materials. Therefore in the proposed fiber reinforced concrete modeling approach, the macro-scale fibers are randomly distributed in the cementitious material, and the forces developed in the fibers are indirectly applied to the cementitious material particles. This fracture analysis method used for fiber-cementitious material composites improves the computational efficiency. Furthermore in contrast to the finite element method, there is no need for mesh refinement and monitoring crack initiations/propagations in the proposed peridynamic framework. The crack development is an inherent feature of the proposed analysis framework. The accuracy of the proposed fracture analysis model is demonstrated through a comparison of available experimental results and simulation outcomes of fiber reinforced concrete beams with a notch at varying locations along the span.
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