In the present study, exterior beam-column sub-assemblage from a regular reinforced concrete (RC) building has been considered. Two different types of beam-column sub-assemblages from existing RC building have been considered, i.e., gravity load designed ('GLD'), and seismically designed but without any ductile detailing ('NonDuctile'). Hence, both the cases represent the under-designed structure at different time frame span before the introduction of ductile detailing. For designing 'NonDuctile' structure, Eurocode and Indian Standard were considered. Non-linear finite element (FE) program has been employed for analysing the sub-assemblages under cyclic loading. FE models were developed using quadratic concrete brick elements with embedded truss elements to represent reinforcements. It has been found that the results obtained from the numerical analysis are well corroborated with that of experimental results. Using the validated numerical models, it was proposed to correlate the energy dissipation from numerical analysis to that from experimental analysis. Numerical models would be helpful in practice to evaluate the seismic performance of the critical sub-assemblages prior to design decisions. Further, using the numerical studies, performance of the sub-assemblages with variation of axial load ratios (ratio is defined by applied axial load divided by axial strength) has been studied since many researchers have brought out inconsistent observations on role of axial load in changing strength and energy dissipation under cyclic load.

In this study 72 different high strength concrete (HSC) mixes were produced according to the Taguchi design of experiment method. The specimens were divided into four groups based on the range of their compressive strengths 40-60, 60-80, 80-100 and 100-125 MPa. Each group included 18 different concrete mixes. The slump and air-content values of each mix were measured at the production time. The compressive strength, splitting tensile strength and water absorption properties were obtained at 28 days. Using this data the Genetic Programming technique was used to construct models to predict mechanical properties of HSC based on its constituients. These models, together with the cost data, were then used with a Genetic Algorithm to obtain an HSC mix that has minimum cost and at the same time meets all the strength and workability requirements. The paper describes details of the experimental results, model development, and optimization results.

A proposed topology method is introduced to measure the air content of fresh cement paste and hardened concrete. The method takes advantage of chromatographic analysis in void areas that are highlighted using different color schemes and later calculated using built-in computer software. The air content measured by the topology method is compared with results obtained from the conventional ASTM methods. It is concluded that the proposed method is reliable, and costs less and is easier to operate compared with the ASTM methods. In addition, 3 dimensional pore models can be created using image post-processing techniques. The proposed method helps researchers in understanding the formation and existence of concrete pores. This paper reports a detailed test program demonstrating the standard operating procedure used for the proposed method and presents a comparison of results between the proposed method and conventional ASTM Specifications. It is also concluded that the air content increases with increasing size of pores and increasing percentage of coarse aggregates.

Managing and reusing knowledge in engineering and construction sectors can lead to greater competitive advantage, improved designs, and more effective management of constructed facilities. The use of Information Technology (IT) in design and construction can exploit strategic opportunities for new ways of integration, sharing and facilitating information and knowledge in any field of engineering. The integrating of separate areas of IT can be used to bring a group of experts and specialists in any field of engineering closer together by allowing them to communicate and exchange information and expertise that facilitate knowledge capture, sharing, and reuse. A lack of an advisory management system and a need to marshal all available data in a common format has indicated the need for an integrated engineering computing environment to investigate concrete repair problems. The research described in this paper is based upon an evaluation management system (EMS) which comprising a database management system (REPCON) alongside visualisation technologies and evaluation system (ECON) is developed to produce an innovative platform which will facilitate and encourage the development of knowledge in educational, evolution and evaluation modes of concrete repair. This allows us to create assessment procedures that will allow the current condition of the concrete structure and its components to be expressed numerically using a confidence level (CL) so as to take the best course of action in the repair and maintenance management. The explained rating system, which is related to structural integrity and serviceability of the structure, allows the confidence level to be determined by visual inspection and the descriptive information and pictures taken from an available REPair of CONcrete (REPCON) database.

Testing of ultrasonic pulse velocity (UPV) is one of the most popular and actual non-destructive techniques used in the estimation of the concrete properties in structures. In this paper, artificial neural network (ANN) approach has been proposed for the evaluation of relationship between concrete compressive strength, UPV, and density values by using the experimental data obtained from many cores taken from different reinforced concrete structures with different ages and unknown ratios of concrete mixtures. The presented approach enables to find practically concrete strengths in the reinforced concrete structures, whose records of concrete mixture ratios are not yet available. Thus, researchers can easily evaluate the compressive strength of concrete specimens by using UPV values. The method can be used in conditions including too many numbers of the structures and examinations to be done in restricted time duration. This method also contributes to a remarkable reduction of the computational time without any significant loss of accuracy. Statistic measures are used to evaluate the performance of the models. The comparison of the results clearly shows that the ANN approach can be used effectively to predict the compressive strength of concrete by using UPV and density data. In addition, the model architecture can be used as a non-destructive procedure for health monitoring of structural elements.