Five previously-tested reinforced concrete frames were modelled using a nonlinear finite element analysis procedure to demonstrate the accurate response simulations for seismically-deficient frames through pushover analyses. The load capacities, story drifts, and failure modes were simulated. This procedure accounts for the effects of shear failures and the shear-axial force interaction, and thus is suitable for modeling seismically-deficient frames. It is demonstrated that a comprehensive analysis method with a capability of simulating material constitutive response and significant second-order mechanisms is essential in achieving a satisfactory response simulation. It is further shown that such analysis methods are invaluable in determining the expected seismic response, safety, and failure mode of the frame structures for a performance-based seismic evaluation. In addition, a new computer program was developed to aid researchers and engineers in the direct displacement-based seismic design process by assessing whether a frame structure meets the code-based performance requirements by analyzing the analysis results. As such, the proposed procedure facilitates the performance-based design of new buildings as well as the numerical assessment and retrofit design of existing buildings. A sample frame analysis was presented to demonstrate the application and verification of the approach.

This study reports the results of nondestructive monitoring of macro void developments in mortars manufactured with both ordinary Portland cement and sulfate resistant cement. Two types of curing were utilized; tap water curing and another curing environment that contains 5% $Na_2(SO_4)$ solution. Being the primary objective of this study, macro void developments of the mortar specimens were monitored by X-ray Medical Computerized Tomography. Compressive strength tests and water absorption tests were conducted on specimens that were kept in both curing environments for a duration of 560 days. Data analyses yielded consistent results among the three tests used in this experimental study. Macro void ratios of mortars decreased at the beginning of experiments for a certain period; afterwards, macro void ratios increased. The objective of this study was accomplished as anticipated since X-CT image analysis was able to nondestructively monitor macro void development process in cement mortars.

The accelerated increase of the population growth rate in the world and the current lifestyle based on consumerism considerably increased the amount of waste generated by the human activity. Specifically, e-plastic waste causes significant damage to the environment because of its difficult degradation process. This paper aims to establish the feasibility of using e-plastic waste in concrete as a partial replacement of coarse mineral aggregate. Considering a control mix without e-plastic waste designed for a compressive strength of 21 MPa, tests on concrete mixes with 40, 50 and 60% of e-plastic waste aggregate to determine the fresh and hardened properties were carried out. A reduction in the compressive strength as the percentage of e-plastic waste increases was observed, the maximum reduction being 44% with respect to the control mix. In addition, a significant reduction as much as 22% in the density of the concrete mixes with e-plastic waste was recorded, which means that lighter elements can be produced with this type of concrete. Two new equations based on regression analysis of the experimental data from this study were proposed. These equations estimate the reduction in the compressive strength of concrete mixes with e-plastic waste aggregate at 14 and 28 days. A cost analysis and a practical alternative to introduce this waste material into the market are also presented.

This study is focused on the investigation for similitude the requirements between prototype and scaled models to determine the structural behavior of concrete load bearing systems. The scaling concept has been utilized in many engineering branches, has been assisted to engineers and scientists for obtain the behavior of the prototype by using scaled model. The scaling can be done for two purposes, either scaling up or scaling down depending upon the application. Because, scaled down models are the experimentation on scaled models is cheaper than huge structures. These models also provide facilities for experimental work. Similarity relationships between systems are created either by field equations of the system or by dimensional analysis. Within this study, similarity relationships were obtained by both methods. The similarity relations obtained are applied to different load bearing systems and it is determined that the similarity relation is a general expression. In this study, as an example, column, frame, cantilever beam and simple beam are chosen and 1/2, 1/5 and 1/10 scales are applied. The results are compared with the analytical results which are obtained by creating of the finite element models with SAP2000 software of different scaled load bearing systems. The analysis results of all systems are examined and it is determined that the scale factors are constant depending on the scale types for different load bearing systems.

The present study focuses on the performance of basalt fiber reinforced concrete (BFRC) lining in tunnel situated in sandstone rock when subjected to internal blast loading. The blast analysis of the lined tunnel is carried out using the three-dimensional (3-D) nonlinear finite element (FE) method. The stress-strain response of the sandstone rock is simulated using a crushable plasticity model which can simulate the brittle behavior of rock and that of BFRC lining is analyzed using a damaged plasticity model for concrete capturing damage response. The strain rate dependent material properties of BFRC are collected from the literature and that of rock are taken from the authors' previous work using split Hopkinson pressure bar (SHPB). The constitutive model performance is validated through the FE simulation of SHPB test and the comparison of simulation results with the experimental data. Further, blast loading in the tunnel is simulated for 10 kg and 50 kg Trinitrotoluene (TNT) charge weights using the equivalent pressure-time curves obtained through hydrocode simulations. The analysis results are studied for the stress and displacement response of rock and tunnel lining. Blast performance of BFRC lining is compared with that of plain concrete (PC) and steel fiber reinforced concrete (SFRC) lining materials. It is observed that the BFRC lining exhibits almost 65% lesser displacement as compared to PC and 30% lesser displacement as compared to SFRC tunnel linings.

Concrete which is a composite material is one of the most important construction materials. Compressive strength is a commonly used parameter for the assessment of concrete quality. Accurate prediction of concrete compressive strength is an important issue. In this study, we utilized an experimental procedure for the assessment of concrete quality. Firstly, the concrete mix was prepared according to C 20 type concrete, and slump of fresh concrete was about 20 cm. After the placement of fresh concrete to formworks, compaction was achieved using a vibrating screed. After 28 day period, a total of 100 core samples having 75 mm diameter were extracted. On the core samples pulse velocity determination tests and compressive strength tests were performed. Besides, Windsor probe penetration tests and Schmidt hammer tests were also performed. After setting up the data set, twelve artificial intelligence (AI) models compared for predicting the concrete compressive strength. These models can be divided into three categories (i) Functions (i.e., Linear Regression, Simple Linear Regression, Multilayer Perceptron, Support Vector Regression), (ii) Lazy-Learning Algorithms (i.e., IBk Linear NN Search, KStar, Locally Weighted Learning) (iii) Tree-Based Learning Algorithms (i.e., Decision Stump, Model Trees Regression, Random Forest, Random Tree, Reduced Error Pruning Tree). Four evaluation processes, four validation implements (i.e., 10-fold cross validation, 5-fold cross validation, 10% split sample validation & 20% split sample validation) are used to examine the performance of predictive models. This study shows that machine learning regression techniques are promising tools for predicting compressive strength of concrete.

Climate changes, such as increasing of $CO_2$ concentration and global warming, will impact on the carbonation service life of concrete structures. Moreover, slag blended concrete has a lower carbonation resistance than control concrete. This study presents a probabilistic numerical procedure for evaluating the impact of climate change on carbonation service life of slag blended concrete. This numerical procedure considers both corrosion initiation period and corrosion propagation period. First, in corrosion initiation period, by using an integrated hydration-carbonation model, the amount of carbonatable substances, porosity, and carbonation depth are calculated. The probability of corrosion initiation is determined through Monte Carlo method. Second, in corrosion propagation period, a probabilistic model is proposed to calculate the critical corrosion degree at surface cracking, the probability of surface cracking, and service life. Third, based on the service life in corrosion initiation period and corrosion propagation period, the whole service life is calculated. The analysis shows that for concrete structures with 50 years service life, after considering climate changes, the service life reduces about 7%.

Fluid velocity analysis on the instability of pipes reinforced by silica nanoparticles ($SiO_2$) is presented in this paper. Mori-Tanaka model is used for obtaining the effective materials properties of the nanocomposite structure considering agglomeration effects. The well known Navier-Stokes equation is used for obtaining the applied force of fluid to pipe. Based on the Reddy higher-order shear deformation theory, the motion equations are derived based on energy method and Hamilton's principal. The frequency and critical fluid velocity of structure are calculated using differential quadrature method (DQM) so that the effects of different parameters such as volume fractions of SiO2 nanoparticles, SiO2 nanoparticles agglomeration, boundary conditions and geometrical parameters of pipes are considered on the nonlinear vibration and instability of the pipe. Results indicate that increasing the volume fractions of SiO2 nanoparticles, the frequency and critical fluid velocity of the structure are increased. Furthermore, considering SiO2 nanoparticles agglomeration, decreases the frequency and critical fluid velocity of the pipe.

FE models for complex or large-scaled structures that need detailed modeling of structural components are usually constructed using commercial analysis softwares. Updating of such FE model by conventional sensitivity-based methods is difficult since repeated computation for perturbed parameters and manual calculations are needed to obtain sensitivity matrix in each iteration. In this study, an FE model updating procedure avoiding such difficulties by using response surface (RS) method and a Pareto-based multiobjective optimization (MOO) was formulated and applied to FE models constructed with a commercial analysis package. The test building is a low-rise reinforced concrete building that has been seismically retrofitted. Dynamic properties of the building were extracted from vibration tests performed before and after the seismic retrofits, respectively. The elastic modulus of concrete and masonry, and spring constants for the expansion joint were updated. Two RS functions representing the errors in the natural frequencies and mode shape, respectively, were obtained and used as the objective functions for MOO. Among the Pareto solutions, the best compromise solution was determined using the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) procedure. A similar task was performed for retrofitted building by taking the updating parameters as the stiffness of modified or added members. Obtained parameters of the existing building were reasonably comparable with the current code provisions. However, the stiffness of added concrete shear walls and steel section jacketed members were considerably lower than expectation. Such low values are seemingly because the bond between new and existing concrete was not as good as the monolithically casted members, even though they were connected by the anchoring bars.

Present study is mainly concerned about the idea of innovative utilization of bamboo in modern construction. Owing to its compatible mechanical properties, a beneficial effect of its use in reinforced concrete (RC) frame infills has been observed. In this investigation, finite element analyses have been performed to examine the failure pattern and stress distribution pattern through the infills of a moment resisting RC frame. To validate the pragmatic use of bamboo reinforced components as infills, earthquake loading corresponding to Nepal earthquake had been considered. The analysis have revealed that introduction of bamboo in RC frames imparts more flexibility to the structure and hence may causes a ductile failure during high magnitude earthquakes like in Nepal. A more uniform stress distribution throughout the bamboo reinforced wall panels validates the practical feasibility of using bamboo reinforced concrete wall panels as a replacement of conventional brick masonry wall panels. A more detailed analysis of the results have shown the fact that stress concentration was more on the frame components in case of frame with brick masonry, contrary to the frame with bamboo reinforced concrete wall panels, in which, major stress dispersion was through wall panels leaving frame components subjected to smaller stresses. Thus an effective contribution of bamboo in dissipation of stresses generated during devastating seismic activity have been shown by these results which can be used to concrete the feasibility of using bamboo in modern construction.

In the present study, soft computing i.e., machine learning techniques and regression models algorithms have earned much importance for the prediction of the various parameters in different fields of science and engineering. This paper depicts that how regression models can be implemented for the prediction of compressive strength of concrete. Three models are taken into consideration for this; they are Gaussian Process for Regression (GPR), Multi Adaptive Regression Spline (MARS) and Minimax Probability Machine Regression (MPMR). Contents of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate and age in days have been taken as inputs and compressive strength as output for GPR, MARS and MPMR models. A comparatively large set of data including 1030 normalized previously published results which were obtained from experiments were utilized. Here, a comparison is made between the results obtained from all the above mentioned models and the model which provides the best fit is established. The experimental results manifest that proposed models are robust for determination of compressive strength of concrete.

Refined analysis depicting mass transportation and physicochemical reaction and reasonable computing load with acceptable DOFs are the two major challenges of numerical simulation for concrete durability. Mesoscopic numerical simulation for chloride diffusion considering binder, aggregate and interfacial transition zone is unable to be expended to the full structure due to huge number of DOFs. In this paper, a multiscale approach of combining both mesoscopic model including full-graded aggregate and equivalent macroscopic model was introduced. An equivalent conversion of chloride content at the Interfacial Transition Layer (ITL) connecting both models was considered. Feasibility and relative error were discussed by analytical deduction and numerical simulation. Case study clearly showed that larger analysis model in multiscale model expanded the diffusion space of chloride ion and decreased chloride content in front of rebar. Difference for single-scale simulation and multiscale approach was observed. Finally, this paper addressed some worth-noting conclusions about the chloride distribution and rebar corrosion regarding the configuration of rebar placement, rebar diameter, concrete cover and exposure period.