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Fatigue is a phenomenon of gradual, permanent internal changes in a material due to repeated or cyclic loading. The fatigue failure of structural elements may decreases the life of infrastructures, therefore the fatigue life of those structures should be considered. Highway and airfield pavements, bridge decks, offshore supporting structure, machinery foundation etc. are subjected to high cycle repeated loading. The randomness in parameters due to the heterogeneous nature of concrete due to fatigue loading leads to complexities in analysing fatigue failure of reinforced concrete. Probabilistic approach is more dependable for the prediction of fatigue life of reinforced concrete than deterministic approach as it can include variations and uncertainties. In recent years, artificial neural network emerged as a new promising computational tool which adopts a probabilistic approach for modelling complex relationships. The purpose of this study is to extract the data from fatigue tests conducted on reinforced concrete beam to create an artificial neural network predictive model. The developed model can able to predict the critical crack length of reinforced concrete members at which failure occurs by considering the fracture mechanics properties and material properties accountable for the softening behaviour of concrete as input. The developed ANN model and analytical model is capable of predicting the fatigue life of reinforced concrete with reasonable accuracy and in a faster approach.

Reactive Powder Concrete (RPC) is an ultra-high strength concrete composite prepared by the replacement of natural aggregates with quartz powder, silica fume and steel fibers. The use of RPC yields high strength, high ductile concrete with optimized material use and contributes to economic, sustainable and ecofriendly constructions. Past research has indicated that RPC offers significant improvement in the mechanical and physical properties owing to its homogenous composition with less defects of voids and microcracks. This leads to enhancement of ultimate load capacity of RPC members and results in superior ductility, energy absorption, tensile strain-hardening behavior, crack control capability and durability. Geo-polymer concrete (GPC) is a type of concrete that is made by reacting aluminate and silicate bearing materials with a caustic activator. Usually, waste materials such as fly ash or slag from iron and metal production are used, which helps lead to a cleaner environment. This paper attempts to review the effect of steel fibers on the shear strength of steel fiber reinforced RPC and compare the results with those of geopolymer concrete.

Under fatigue loading, concrete like quasi-brittle materials exhibit softening behaviour since an inelastic zone will be formed in front of the crack tip called the fracture process zone (FPZ). There are various toughening mechanisms that exhibiting in this region. Current design practices for reinforced concrete assumes a zero tensile strength for concrete which is actually overly conservative. In fact, concrete can bear significant tensile stress and strain. Therefore, the tension softening response of RC member should consider in the study. Under fatigue loading, strength and stiffness decrease progressively according to the maximum amplitude and the number of cycles of loading. Fracture plays an important role in failure of normally and lightly reinforced beam. Since FPZ mechanisms and fibre bridging action resist crack propagation, we have to consider these mechanisms while assessing remaining life of RC member. Fatigue failure occurs when applied load is much less than the moment capacity. Such structures susceptible to fatigue load need to be monitored and residual life is to be predicted. This paper is presenting a review on the residual strength assessment on plain and reinforced concrete. The review includes the influence of various tension-softening models in predicting the residual life of plain and reinforced concrete. A comparative study is also conducted in order to assess the residual life by considering various tension softening laws.

Many infrastructures like Bridge decks, airfield and highway pavements, offshore structure and machinery foundation are subjected to fatigue loading. This cyclic loading induces gradual, permanent internal changes in a material and thereby affecting the remaining life of the infrastructure. The heterogeneities in concrete add complexities in analysing fatigue failure of reinforced concrete. This review paper discuss about fatigue life prediction models for both plain and reinforced concrete structural member. This review paper comprises various deterministic and probabilistic models used in predicting the fatigue life of plain and reinforced concrete. Deterministic approach is dependent on some initial parameters and conditions and is unreliable to accurately determine the fatigue life of concrete. This results in the development of a more generalized model based on a probabilistic approach that accounts for the stochasticity in fatigue failure of concrete. In recent years, artificial neural network emerged as a new promising computational tool which adopts a probabilistic approach for modelling complex relationships.

Structural insulated panels (SIPs) made by sandwiching an insulating material from both sides have been used in buildings to enhance thermal resistance without loss in structural integrity. New innovations to improve its compositeness are also being explored. One method is to use shear connector made of high thermal resistant and ductile materials. This connects two outer wythes through insulation layer. The outer material can be of any type of high compressive strength concrete. These are usually reinforced with steel or carbon or glass fiber. The use of light weight and high strength materials helps to reduce the overall thickness of the structure. As the material of shear connector acts as a thermal bridge across the outer wythes, materials with low U value (thermal transmittance) are preferred. In this paper, an attempt has been made to carry out a comparative study on the performance of SIPs with shear connectors manufactured using different materials.

Masonry infill walls are commonly used as external walls and partition walls in RC frame buildings. RC frames in earthquake regions are usually designed with higher ductility and hence undergo large displacements under horizontal loading which lead to a rapid activation of the significantly stiffer infills. This activation generates an undesired interaction between the frame and the infill resulting in the participation of the masonry infills for load transfer. The seismic performance of masonry infill walls under earthquake loading have been studied experimentally and analytically. Damages under in-plane loading are found to escalate the out-of plane response. Over the years the studies have been extended from steel frames to RC frames and the infill materials have been varied from masonry infill to concrete panels. However, the studies are particularly focused on masonry infill units. With the rising concern for environmental pollution control, alternative green materials are also being recommended as infills. This paper presents a review on the techniques that have been developed to improve the seismic performance of infilled frames. It can be achieved by providing a rigid connection between the infill and the frame or by completely isolating the infill walls from the surrounding frame and by using seismic isolation elements.

The fatigue failure of structural elements subjected to repeated cyclic loading may reduce the life of infrastructures. Heterogeneous nature of concrete and random factors in fatigue testing lead to great variability in fatigue life of concrete. As deterministic approach depends on certain parameters and initial conditions, it is not reliable for the prediction of fatigue life of concrete. In this study, a probabilistic approach using artificial neural network is utilised to predict the fatigue life of plain concrete. An artificial neural network predictive model was developed utilising the data from fatigue tests conducted on plain concrete beams of three different sizes mainly small, medium and large. The model is trained using the available experimental data of small and medium specimen and is validated using available experimental data reported on large specimens. The developed model is able to predict the number of cycles of failure of concrete by considering material and fracture mechanics properties responsible for the softening behavior of concrete as input. This approach is advantageous over other methods as it includes the randomness in the fatigue of concrete and will be able to predict the fatigue life of concrete with reasonable accuracy.

The effect of microcracks ahead of a macrocrack on the post-peak behavior of concrete-like quasi-brittle material is studied. The critical length of a microcrack is estimated by considering a small element near the macrocrack tip and defining the critical crack opening displacement of the microcrack that exist in the interface region between the aggregate and cement paste. A fracture model is proposed to predict the post-peak response of plain concrete. This model is validated using the experimental results for normal-strength, high-strength and self-consolidating concretes available in the literature. Through a sensitivity analysis, it is observed that the elastic modulus of concrete and the fracture toughness of the interface have a substantial influence on the critical microcrack length.

Simulation has become a prerequisite in engineering and science today for visualization of ideas and concepts. In non-destructive evaluation, simulation is increasingly used to show how an inspection method functions with regard to the component to be inspected and is even used for determining the probability of detection of a respective flaw with regard to the inspection method applied. Probability of detection in non-destructive evaluation is optimized in a way that the best sensor positions, as well as sensor tracking paths, can be found through simulation. In classical non-destructive evaluation, a transducer or transducer array can be virtually moved over the surface of a component to be inspected until a full capture of the component's surface and hopefully volume is achieved in terms of the inspection process. However, with structural health monitoring, no movement of the transducers is possible in case those become an integral and hence fixed part of the component considered. Determining the optimum position of a respective structural health monitoring transducer network can therefore only be achieved through optimization procedures, where numerical simulation is possibly the only viable solution to get this done. Establishing a numerical simulation platform for structural health monitoring purposes has been the major objective of the recently completed INDEUS (Integration of Non-Destructive Evaluation-based Ultrasonic Simulation) project, which is described in this article. The open simulation platform includes different simulation tools, where the requirements and options for further extension of those tools and different test cases applied for validation so far are described. The target is to even simulate real complex structures such as applied in civil, aeronautical, and other engineering disciplines made of metallic and polymer-based monolithic and composite materials where the digital models are inherited from traditional computer-aided design and finite element-based designs. This lays the ground for determining the probability of damage for a given loading condition and structure, and the propagation of guided waves in the structure considered for an undamaged and a damage tolerant condition. From those simulation results, the determination of an optimum configuration of sensing transducers for a given set of actuating transducers is then shown for a guided wave-based structural health monitoring system solution to be designed allowing the tolerable damage to be detected reliably.

Concrete is considered as a homogeneous material from a design perspective. However, on a close examination, it is observed that concrete is heterogeneous, which consist of coarse aggregate and fine aggregate embedded in cement paste. Further, there exists an interfacial region, which bonds the aggregate with the cement paste. The strength of this interfacial transition zone (ITZ) depends on its microstructural characteristics. This interfacial region neither possesses the properties of aggregate nor of the cement paste. Interface being the weakest zone, the microcracks are likely to initiate here when the local major principal stress exceeds the initial tensile strength of the interface. When these microcracks reach certain critical length, it propagates and coalesces with the existing macrocrack to form a major crack resulting in the failure of the bond. The microstructural character of the interfacial zone governs the mode I crack propagation in conventional concrete . The material behavior of concrete is influenced by the geometry, the spatial distribution, and the material property of the individual constituents and their interactions. This study aims at estimating the critical microcrack length using the principles of linear elastic fracture mechanics (LEFM) by analyzing the crack opening displacement at different scales. Also, a procedure to determine the material properties such as the elastic modulus and fracture toughness at the interface by knowing the concrete mix proportion is explained.

Damage tolerant structures subjected to fatigue loading require inspection at regular intervals for detection and reporting of possible damages such as fatigue cracks. SHM systems integrated into those structures consisting of a sensor network combined with data analysis algorithms can further enhance the effectiveness of monitoring either by automating the inspection process or by adaptively changing the inspection intervals. To implement such a SHM system, a network of ultrasonic guided wave actuators and sensors including the electronics will have to be deployed to or integrated into the structure. Design of such a system should consider the probable location of damages that have to be monitored and the ways to enhance the sensitivity of detecting those damages. When a damage approaches its tolerable size limit, it should be detected with a higher accuracy compared to when the damage is first detected at an earlier stage and smaller size. Several probabilistic factors can alter the nature of damage and hence can affect the damage detection sensitivity as a consequence of factors like the specific sensor network algorithms applied, the type of damage and the zone of inspection. This is one of the major challenges to achieve reliable monitoring of some evolving wide spread fatigue damage using an integrated SHM system. In this paper, a specific example of fatigue crack initiation from the rivet holes in a stiffened structural component has been simulated considering a probabilistic sequence of fatigue loading. A scheme of determining the probability of damage growth up to a specific size is studied considering the progressive changes in the load path and randomness in the loading sequence. Our present effort is to develop a scheme of modeling and analysis that uses information regarding variability in the loading and relates those to the probability of a critical damage. Detailed understanding of these relationships is considered useful in arriving at design specifications for an integrated SHM system for improving the system’s reliability

A linearized stress intensity factor (SIF) is derived for concrete through a multiscale approach by considering the predominant process zone mechanisms such as aggregate bridging and microcracking. This is achieved by considering a bridging zone and a microcrack at the macrocrack tip. The bridging zone resists the crack growth through aggregate bridging mechanism. The SIF thus derived is further used in developing an analytical model which predicts the entire crack growth curve for plain concrete by making use of the concepts of dimensional analysis and self similarity in conjunction with the human population growth model. This model is validated using experimental data reported on normal strength, high strength and self consolidating concrete. Through sensitivity analyses it is shown that the specimen size plays an important role in the fatigue crack growth process of concrete. (C) 2017 Elsevier Ltd. All rights reserved.

The fracture process of concrete is characterized by various toughening mechanisms that exist at the macro crack tip. In this study, the crack growth resistance due to the bridging of aggregates (defined as bridging stress) is evaluated by relating the crack opening displacements at the macroscopic scale to the mesoscopic one by considering the fracture toughness and the elastic modulus of the interface between the coarse aggregate and the mortar. The influence of specimen size and the stress ratio on the bridging stress is studied. The effect of the bridging stress on the fatigue crack growth rate is predicted and the results are found to agree well with the experiments for normal and micro concrete. The residual strength of a damaged beam is computed in terms of the moment carrying capacity by considering the bridging resistance offered by the coarse aggregates. (C) 2016 Elsevier Ltd. All rights reserved.