A non-linear finite element model (FEM) was constructed using a three-dimensional software (ATENA-3D) to investigate the effect of strengthening on the behavior of prestressed hollow-core (PHC) slabs with or without openings. The slabs were strengthened using near surface mounted (NSM)-carbon fiber reinforced polymer (CFRP) strips. The constructed model was validated against experimental results that were previously reported by the authors. The validated FEM was then used to conduct an extensive parametric study to examine the influence of prestressing reinforcement ratio, compressive strength of concrete and strengthening reinforcement ratio on the behavior of such slabs. The FEM results showed good agreement with the experimental results where it captured the cracking, yielding, and ultimate loads as well as the mid-span deflection with a reasonable accuracy. Also, an overall enhancement in the structural performance of these slabs was achieved with an increase in prestressing reinforcement ratio, compressive strength of concrete, external reinforcement ratio. The presence of openings with different dimensions along the flexural or shear spans reduced significantly the capacity of the PHC slabs. However, strengthening these slabs with 2 and 4 (64 and $128mm^2$ that represent reinforcement ratios of 0.046 and 0.092%) CFRP strips was successful in restoring the original strength of the slab and enhancing post-cracking stiffness and load carrying capacity.

In order to research the influence of different recycled aggregate contents on the mechanical properties of pervious concrete, the experimental study and numerical simulation analysis of the mechanical properties of pervious concrete with five kinds of recycled aggregates contents (0%, 25%, 50%, 75% and 100%) are carried out in this paper. The experimental test were first performed on concrete specimens of different sizes in order to determine the influence of recycled aggregate on the compressive strength and splitting tensile strength, direct tension strength and bending strength. Then, the development of the internal cracks of pervious concrete under different working conditions is studied more intuitively by $PFC^{3D}$. The experimental results show that the concrete compressive strength, tensile strength and bending strength decrease with the increase of the recycled aggregate contents. This trend of reduction is not only related to the brittleness of recycled aggregate concrete, but also to the weak viscosity of recycled aggregate and cement paste. It is found that the fracture surface of pervious concrete with recycled aggregate is smoother than that of natural aggregate pervious concrete by $PFC^{3D}$, which means that the bridging effect is weakened in the stress transfer between the left and right sides of the crack. Through the analysis of the development of the internal cracks, the recycled aggregate concrete generated more cracks than the natural aggregate concrete, which means that the recycled aggregate concrete is easier to form a coalescence fracture surface and eventually break.

Numerical approach using finite element method has been used to evaluate the behaviour of reinforced concrete frame structure subjected to fire. The structure is previously designed in accordance with Eurocode standards for the design of structures for earthquake resistance, for the ductility class M. Thermal and structural response are obtained using a commercially available software ANSYS. Temperature-dependent nonlinear thermal and mechanical properties are adopted according to Eurocode standards, with the application of constitutive model for the triaxial behaviour of concrete with a smeared crack approach. Discrete modelling of concrete and reinforcement has enabled monitoring of the behaviour at a global, as well as at a local level, providing information on the level of damage occurring during fire. Critical regions in frame structures are identified and assessed, based on temperatures, displacements, variations of internal forces magnitudes and achieved plastic deformations of main reinforcement bars. Parametric analyses are conducted for different fire scenarios and different types of concrete aggregate to determine their effect on global deformations of frame structures. According to analyses results, the three-dimensional finite element model can be used to evaluate the insulation and mechanical resistance criteria of reinforced concrete frame structures subjected to nominal fire curves.

Adaptive neuro-fuzzy inference systems (ANFIS) can be efficient in modelling non-linear, complex and ambiguous behavior of cement-based materials undergoing combined damage factors of different forms (physical and chemical). The current work investigates the use of ANFIS to model the behavior (time of failure (TF)) of a wide range of concrete mixtures made with different types of cement (ordinary and portland limestone cement (PLC)) without or with supplementary cementitious materials (SCMs: fly ash and nanosilica) under various exposure regimes with the most widely used chloride-based de-icing salts (individual and combined). The results show that predictions of the ANFIS model were rational and accurate, with marginal errors not exceeding 3%. In addition, sensitivity analyses of physical penetrability (magnitude of intruding chloride) of concrete, amount of aluminate and interground limestone in cement and content of portlandite in the binder showed that the predictive trends of the model had good agreement with experimental results. Thus, this model may be reliably used to project the deterioration of customized concrete mixtures exposed to such aggressive conditions.

The purpose of this study was to model and design a concrete catenary shell using a modern computer program without performing experiments. The modeling idea stems from the study by Pendergrast, but he listed supplementary items that should be improved in his paper. This study aims to resolve those issues and overcome the drawbacks of the study by Pendergrast. The process of experiment for the design of a catenary shell was reproduced by Grasshopper script. In order to ensure credibility, two models designed from the Grasshopper script were analyzed using a finite element program, SAP2000; one is a square-based catenary shell and the other is a special catenary shell called as the Naturtheater $Gr{\ddot{o}}tzingen$ shell, which was completed in 1977. First, the developed modeling approach was proved to be reasonable from the analysis of the square-based shell. The reliability was further confirmed by a comparison between the current and previous analysis results for the Naturtheater $Gr{\ddot{o}}tzingen$ shell.

In this paper the behavior of reinforced concrete (RC) beam-column connections under cyclic loading was analyzed. The specimens, manufactured in a reduced-scale were made of (a) recycled aggregate concrete (RAC) by replacing 30% of natural coarse aggregate (NCA) with recycled coarse aggregate (RCA) and (b) RAC incorporating Polyethylene terephthalate (PET) fiber i.e., PET fiber-reinforced concrete (PFRC) at the joint region. PET fiber (aspect ratio=25) of 0.5% by weight of concrete used in the PFRC mix was obtained by hand cutting of post-consumer PET bottles. A reference specimen was also prepared using 100% of NCA and subjected to similar loading sequence. Comparing the results the structural behavior under cyclic loading of RAC specimens are quite similar to the reference specimens. Damage tolerance, load resisting capacity, stiffness degradation, ductility, and energy dissipation of the RAC specimens enhanced due to addition of PET fibers at the joint region. PFRC specimens also presented a lower damage indices and higher principal tensile stresses as compared to the RAC specimens. The results obtained gave experimental evidence on the feasibility of RAC for structural use. Using PET fibers as a discrete reinforcement is recommended for improving the seismic performance of RAC specimens.

This pioneer study investigates the size effect on the compressive and tensile strengths of fiber-reinforced self-compacting concrete (FR-SCC) with different specimens, before and after exposure to elevated temperatures. 432 self-compacting concrete (SCC) specimens with two concrete grades (50 and 80MPa) and three steel fiber ratios (0%, 0.5% and 1%) were prepared and tested. Moreover, based on the experimental results, new formulations were proposed to predict the residual strengths for different specimens. A parametric study was also carried out to investigate the accuracy of proposed formulations. Residual strength results showed that the cylinder specimen with dimensions of $100{\times}200mm$ was the most affected, while the cube with a size of 100 mm maintained a constant difference with the standard cylinder ($150{\times}300mm$). Temperature effect on the cube specimen (150 mm) was the least in comparison to other specimen sizes and types. In general, provision of steel fibers in SCC mixtures resulted in a reduction in temperature effect on the variance of a conversion factor. Parametric study results confirm that the proposed numerical models are safe to be used for all types of SCC specimens.

Compressive strength is one of the most important engineering properties of concrete, and testing of the compressive strength of concrete specimens is often costly and time consuming. In order to provide the time for concrete form removal, re-shoring to slab, project scheduling and quality control, it is necessary to predict the concrete strength based upon the early strength data. However, concrete compressive strength is affected by many factors, such as quality of raw materials, water cement ratio, ratio of fine aggregate to coarse aggregate, age of concrete, compaction of concrete, temperature, relative humidity and curing of concrete. The concrete compressive strength is a quite nonlinear function that changes depend on the materials used in the concrete and the time. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of concrete compressive strength. The training of fuzzy system was performed by a hybrid method of gradient descent method and least squares algorithm, and the subtractive clustering algorithm (SCA) was utilized for optimizing the number of fuzzy rules. Experimental data on concrete compressive strength in the literature were used to validate and evaluate the performance of the proposed ANFIS model. Further, predictions from three models (the back propagation neural network model, the statistics model, and the ANFIS model) were compared with the experimental data. The results show that the proposed ANFIS model is a feasible, efficient, and accurate tool for predicting the concrete compressive strength.

This paper presents an experimentally investigation pertinent to the mechanical properties of rubberized mortar (RM) with styrene-butadiene rubber (SBR). The SBR were used with constant water-to-cement ratio of 0.485 and two different volume proportion of SBR particles were utilized as aggregates. One types of SBR particles with fineness modulus of 4.951 were utilized 0%, 10%, and 20% of aggregate volume. Effectiveness of SBR replacement ratio, curing and aging effect on the compressive strength, flexural strengths as well as load-displacement. Compressive and flexural strength of concrete were investigated at the end of 28-days and 56-days age. Obtained results demonstrated that utilization of SBR reduced the flexural strength of SBR mortar at the earlier curing age while SBR increased. Moreover, mechanical properties of mortar mentioned above were significantly affected by the water cure timing with an increasing proportion of the replacement level of SBR.

Concrete pipelines are the most efficient and safe means for gas and oil transportation over a long distance. The use of nano materials and nono-engineering can be considered for enhancing concrete pipelines properties. the tests show that $SiO_2$ nanoparticles can improve the mechanical behavior of concrete. Moreover, severe hazard for pipelines is seismic ground motion. Over the years, scientists have attempted to understand pipe behavior against earthquake most frequently via numerical modeling and simulation. Therefore, in this paper, the dynamic response of underwater nanocomposite submerged pipeline conveying fluid is studied. The structure is subjected to the dynamic loads caused by earthquake and the governing equations of the system are derived using mathematical model via Classic shell theory and Hamilton's principle. Navier-Stokes equation is employed to calculate the force due to the fluid in the pipe. As well, the effect of external fluid is modeled with an external force. Mori-Tanaka approach is used to estimate the equivalent material properties of the nanocomposite. 1978 Tabas earthquake in Iran is considered for modelling seismic load. The dynamic displacement of the structure is extracted using differential quadrature method (DQM) and Newmark method. The effects of different parameters such as $SiO_2$ nanoparticles volume percent, boundary conditions, thickness to radius ratios, length to radius ratios, internal and external fluid pressure and earthquake intensity are discussed on the seismic response of the structure. From results obtained in this paper, it can be found that the dynamic response of the pipe is increased in the presence of internal and external fluid. Furthermore, the use of $SiO_2$ nanoparticles in concrete pipeline reduces the displacement of the structure during an earthquake.

Crack is the most common typical feature of concrete deterioration, so routine monitoring and health assessment become essential for identifying failures and to set up an appropriate rehabilitation strategy in order to extend the service life of concrete structures. At present, image segmentation algorithms have been applied to crack analysis based on inspection images of concrete structures. The results of crack segmentation offering crack information, including length, width, and area is helpful to assist inspectors in surface inspection of concrete structures. This study proposed an algorithm of image segmentation enhancement, named morphological segmentation based on edge detection-II (MSED-II), to concrete crack segmentation. Several concrete pavement and building surfaces were imaged as the study materials. In addition, morphological operations followed by cross-curvature evaluation (CCE), an image segmentation technique of linear patterns, were also tested to evaluate their performance in concrete crack segmentation. The result indicates that MSED-II compared to CCE can lead to better quality of concrete crack segmentation. The least area, length, and width measurement errors of the concrete cracks are 5.68%, 0.23%, and 0.00%, respectively, that proves MSED-II effective for automatic measurement of concrete cracks.

In this paper, the sensitivity of a plastic-damage-based structural damage index on mesh density is studied. Multiple finite element meshes with increasing density are used to investigate their effect on the damage index values calculated from nonlinear finite element simulations for a reinforced concrete column subjected to cyclic loading. With the simulation results, this paper suggests a correction method for the objective damage index based on nonlinear regression of volumetric tensile damage ratio data. The modified damage index values are presented in the quasi-static cyclic simulation to show the efficacy of the suggested correction method.