The deterioration of existing bridges has become a major problem around the world. In the paper, a new model and an associated stress checking method are proposed for concrete box girders strengthened by external prestressing. The new model called the spatial grid model can analyze all the spatial behaviors clearly by transforming the box girder into discrete orthogonal grids which are equivalent to plate elements. Then the three-layer stresses are employed as the stress checking indices to evaluate the stress state of the plate elements. The initial stress check before strengthening reveals the cracked and potential cracking areas for existing bridges, making the strengthening design more targeted and scientific; the subsequent stress check after strengthening evaluates the strengthening effect and ensures safety. A deficient bridge is selected as the practical example, verifying the accuracy and applicability of the proposed model and stress checking method. The results show that principal stresses in the middle layer of plate elements reflect the main effects of external prestressing and thus are the key stress checking indices for strengthening. Moreover, principal stresses check should be conducted in all parts of the strengthened structure not only in the webs. As for the local effects of external prestressing especially in the areas near anchorage and deviator, normal stresses check in the outer and inner layers dominates and local strengthening measures should be taken if necessary.

This paper deepens the finite element modeling (FEM) method to reproduce the compressive behavior of partially steel-jacketed (PSJ) RC columns by means of the Concrete Damaged Plasticity (CDP) Model available in ABAQUS software. Although the efficiency of the CDP model is widely proven for reinforced concrete columns at low confining pressure, when the confinement level becomes high the standard plasticity parameters may not be suitable to obtain reliable results. This paper deals with these limitations and presents an analytically based strategy to fix the parameters of the Concrete Damaged Plasticity (CDP) model. Focusing on a realistic prediction of load-bearing capacity of PSJ RC columns subjected to monotonic compressive loads, a new strain hardening/softening function is developed for confined concrete coupled with the evaluation of the dilation angle including effects of confinement. Moreover, a simplified efficient modeling approach is proposed to take into account also the response of the steel angle in compression. The prediction accuracy from the current model is compared with that of existing experimental data obtained from a wide range of mechanical confinement ratio.

Accelerators are used to speed up the construction by accelerating the setting time which helps in early removal of formwork thus leading to faster construction rate. Admixtures are used in mortar and concrete during or after mixing to improve certain properties of material which cannot be achieved in conventional cement mortar and concrete. The various industrial by products make nuisance and are hazardous to ecosystem as well. These wastes can be used in the construction industries to reduce the consumption of cement/aggregates, cost; and save the energy and environment by utilising waste and eliminate their disposal problem as well. The effect of calcium nitrate and triethanolamine (TEA) as accelerators and marble powder (MP) as waste material on the various properties of cement paste and mortar has been studied in the present work. The replacement ratio of MP was 0-10% @ 2.5% by weight of cement. The addition of calcium nitrate was 0% and 1%; and variation of addition of TEA was 0-0.1@ 0.025% and 0.1-1.0@ 0.1% by weight of cement. On the basis of setting time, some mix proportions were selected and further investigated. Setting time and soundness of cement paste; compressive strength and microstructure of mortar mix of selected mix proportions were studied experimentally at 3, 7 and 28 days aging. Results showed that use of MP, calcium nitrate, TEA and their combination reduced setting time of cement paste for all the mixes. Addition of calcium nitrate increased the compressive strength at all curing ages while MP and TEA decreased the compressive strength. The mechanism of additives was discussed through scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDS) analysis of the specimens.

This paper deals with the instability analysis of concrete pipes conveying viscous fluid-nanoparticle mixture. The fluid is mixed by $AL_2O_3$ nanoparticles where the effective material properties of fluid are obtained by mixture rule. The applied force by the internal fluid is calculated by Navier-Stokes equation. The structure is simulated by classical cylindrical shell theory and using energy method and Hamilton's principle, the motion equations are derived. Based on Navier method, the critical fluid velocity of the structure is calculated and the effects of different parameters such as fluid velocity, volume percent of nanoparticle in fluid and geometrical parameters of the pipe are considered. The results present that with increasing the volume percent of nanoparticle in fluid, the critical fluid velocity increase.

The modeling of loss of bond between reinforcing bars (rebars) and concrete due to corrosion is useful in studying the behavior and prediction of residual load bearing capacity of corroded reinforced concrete (RC) members. In the present work, first the possibility of using different methods to simulate the rebars-concrete bonding, which is used in three-dimensional (3D) finite element (FE) modeling of corroded RC beams, was explored. The cohesive surface interaction method was found to be most suitable for simulating the bond between rebars and concrete. Secondly, using the cohesive surface interaction approach, the 3D FE modeling of the behavior of non-corroded and corroded RC beams was carried out in an ABAQUS environment. Experimental data, reported in literature, were used to validate the models. Then using the developed models, a parametric study was conducted to examine the effects of some parameters, such as degree and location of the corrosion, on the behavior and residual capacity of the corroded beams. The results obtained from the parametric analysis using the developed model showed that corrosion in top compression rebars has very small effect on the flexural behaviors of beams with small flexural reinforcement ratio that is less than the maximum ratio specified in ACI-318-14 (singly RC beam). In addition, the reduction of steel yield strength in tension reinforcement due to corrosion is the main source of reducing the load bearing capacity of corroded RC beams. The most critical corrosion-induced damage is the complete loss of bond between rebars and the concrete as it causes sudden failure and the beam acts as un-reinforced beam.

The rheological behaviour of high strength self compacting concrete (HS-SCC) studied through an experimental investigation is presented in this paper. The effect of variation in supplementary cementitious materials (SCM) $vis-{\grave{a}}-vis$ four different types of processed crushed sand as fine aggregates is studied. Apart from the ordinary Portland cement (OPC), the SCMs such as fly ash (FA), ground granulated blast furnace slag (GGBS) ultrafine slag (UFS) and micro-silica (MS) are used in different percentages keeping the mix -paste volume and flow of concrete, constant. The combinations of rheology, strength and durability are equally important for selection of mixes in respect of high-rise building constructions. These combinations are referred to as the rheo-strength and rheo-durability which is scientifically linked to performance based rating. The findings show that the fineness of the sands and types of SCM affects the rheo-strength and rheo-durability performance of HS-SCC. The high amount of fines often seen in fine aggregates contributes to the higher yield stress. Further, the mixes with processed sand is found to offer better rheology as compared to that of mixes made using unwashed crushed sand, washed plaster sand, washed fine natural sand. The micro silica and ultra-fine slag conjunction with washed crushed sand can be a good solution for high rise construction in terms of rheo-strength and rheo-durability performance.

In the present study, group method of data handling networks (GMDH) are adopted and evaluated for shear strength prediction of both FRP-reinforced concrete members with and without stirrups. Input parameters considered for the GMDH are altogether 12 influential geometrical and mechanical parameters. Two available and very recently collected comprehensive datasets containing 112 and 175 data samples are used to develop new models for two cases with and without shear reinforcement, respectively. The proposed GMDH models are compared with several codes of practice. An artificial neural network (ANN) model and an ANFIS based model are also developed using the same databases to further assessment of GMDH. The accuracy of the developed models is evaluated by statistical error parameters. The results show that the GMDH outperforms other models and successfully can be used as a practical and effective tool for shear strength prediction of members without stirrups ($R^2=0.94$) and with stirrups ($R^2=0.95$). Furthermore, the relative importance and influence of input parameters in the prediction of shear capacity of reinforced concrete members are evaluated through parametric and sensitivity analyses.

In order to evaluate the effect of hybrid fibers on the flexural performance of tunnel segment at room temperature, twelve reinforced self-consolidating concrete (SCC) symmetric inclination beams containing steel fiber, macro polypropylene fiber, micro polypropylene fiber, and their hybridizations were studied under combined loading of flexure and axial compression. The results indicate that the addition of mono steel fiber and hybrid fibers can enhance the ultimate bearing capacity and cracking behavior of tested beams. These improvements can be further enhanced along with increasing the content of steel fiber and macro PP fiber, but reduced with the increase of the reinforcement ratio of beams. The hybrid effect of steel fiber and macro PP fiber was the most obvious. However, the addition of micro PP fibers led to a degradation to the flexural performance of reinforced beams at room temperature. Meanwhile, the hybrid use of steel fiber and micro polypropylene fiber didn't present an obvious improvement to SCC beams. Compared to micro polypropylene fiber, the macro polypropylene fiber plays a more prominent role on affecting the structural behavior of SCC beams. A calculation method for ultimate bearing capacity of flexural SCC symmetric inclination beams at room temperature by taking appropriate effect of hybrid fibers into consideration was proposed. The prediction results using the proposed model are compared with the experimental data in this study and other literature. The results indicate that the proposed model can estimate the ultimate bearing capacity of SCC symmetric inclination beams containing hybrid fibers subjected to combined action of flexure and axial compression at room temperature.

In this paper, vibration analysis of concrete foundations resting on soil medium is studied. The soil medium is simulated by Winkler model considering spring element. The concrete foundation is modeled by thick plate elements based on classical plate theory (CPT). Utilizing energy method consists of potential energy, kinetic energy and external works in conjunction with Hamilton's principle, the motion equations are derived. Assuming the simply supported boundary condition for the concrete foundation, the Navier method is used for calculating the frequency of the structure. The effect of different parameters such as soil medium, mode numbers, length to width ratio and length to thickness ratio of the concrete foundation are shown on the frequency of the structure. At the first, the results are validated with other published works in order to show the accuracy of the obtained results. The results show that considering the soil medium, the frequency of the structure increases significantly.

Today, the modeling of concrete as a material within finite element simulations is predominantly done through nonlinear material models of concrete. In current sophisticated computational systems, there are a number of complex concrete material models which are based on theory of plasticity, damage mechanics, linear or nonlinear fracture mechanics or combinations of those theories. These models often include very complex constitutive relations which are suitable for the modeling of practically any continuum mechanics tasks. However, the usability of these models is very often limited by their parameters, whose values must be defined for the proper realization of appropriate constitutive relations. Determination of the material parameter values is very complicated in most material models. This is mainly due to the non-physical nature of most parameters, and also the large number of them that are frequently involved. In such cases, the designer cannot make practical use of the models without having to employ the complex inverse parameter identification process. In continuum mechanics, however, there are also constitutive relations that require the definition of a relatively small number of parameters which are predominantly of a physical nature and which describe the behavior of concrete very well within a particular task. This paper presents an example of such constitutive relations which have the potential for implementation and application in finite element systems. Specifically, constitutive relations for modeling the plane stress state of concrete are presented and subsequently tested and evaluated in this paper. The relations are based on the incremental theory of elastic strain-hardening plasticity in which a non-associated flow rule is used. The calculation result for the case of concrete under uniaxial compression is compared with the experimental data for the purpose of the validation of the constitutive relations used.

TBM penetration rate is a function of intact rock properties, rock mass conditions and TBM operational parameters. Machine rate of penetrationcan be predicted by knowledge of the ground conditions and its effects on machine performance. The variation of TBM operational parameters such as penetration rate and thrust plays an important role in its performance. This study presents the results of the analysis on the TBM penetration rates in schistose rock types present along the alignment of Golab tunnel based on the analysis of a TBM performance database established for every stroke through different schistose rock types. The results of the analysis are compared to the results of some empirical and theoretical predictive models such as NTH and QTBM. Additional analysis was performed to find the optimum thrust and revolution per minute values for different schistose rock types.

This paper presents Artificial Neural Network (ANN) models for evaluating bond strength of deformed, plain and cold formed bars in low strength concrete. The ANN models were implemented using the experimental database developed by conducting experiments in three different universities on total of 138 pullout and 108 splitting specimens under monotonic loading. The key parameters examined in the experiments are low strength concrete, bar development length, concrete cover, rebar type (deformed, cold-formed, plain) and diameter. These deficient parameters are typically found in non-engineered reinforced concrete structures of developing countries. To develop ANN bond model for each bar type, four inputs (the low strength concrete, development length, concrete cover and bar diameter) are used for training the neurons in the network. Multi-Layer-Perceptron was trained according to a back-propagation algorithm. The ANN bond model for deformed bar consists of a single hidden layer and the 9 neurons. For Tor bar and plain bars the ANN models consist of 5 and 6 neurons and a single hidden layer, respectively. The developed ANN models are capable of predicting bond strength for both pull and splitting bond failure modes. The developed ANN models have higher coefficient of determination in training, validation and testing with good prediction and generalization capacity. The comparison of experimental bond strength values with the outcomes of ANN models showed good agreement. Moreover, the ANN model predictions by varying different parameters are also presented for all bar types.