Asian journal of civil engineering
Volume:13 Issue: 1, Feb 2012

In this study, an efficient method is introduced to predict the stability of soil-structureinteraction (SSI) system subject to earthquake loads. In the procedure of the nonlineardynamic analysis, a number of structures collapse and then lose their stability. Theprediction of failure probability is considered as stability criterion. In order to achieve thispurpose, a modified adaptive neuro fuzzy inference system (ANFIS) is proposed by a hybrid of fuzzy c-means (FCM) and fuzzy particle swarm optimization (FPSO). To train themodified ANFIS, the input–output data are classified by a hybrid algorithm consisting ofFCM-FPSO clustering. The optimum number of ANFIS fuzzy rules is determined bysubtractive algorithm (SA). Results of illustrative examples demonstrate high performanceof the modified ANFIS in comparison with the single ANFIS.

This paper presents the results of experimental, analytical and numerical studies concerning the flexural strengthening of RC beams using externally bonded High Performance Fiber Reinforced Cementitious Composites (HPFRCCs) like Slurry Infiltrated Fibre CONcrete (SIFCON) and Slurry Infiltrated Mat CONcrete (SIMCON). A total of ten reinforced concrete beams were cast and tested in the laboratory over an effective span of 3000 mm.Eight beams were strengthened with bonded SIFCON and SIMCON laminates at the bottom under virgin condition and tested until failure; the remaining two beams were used as control specimen. Static responses of all the beams were evaluated in terms of strength, stiffness, ductility ratio, energy absorption capacity factor, compositeness between laminate and concrete, and the associated failure modes. Comparisons were made betweenexperimental, analytical and numerical results of SIFCON and SIMCON. The results show that the strengthened beams exhibit increased flexural strength, enhanced flexural stiffness, and composite action until failure.

Concrete is not an environmentally friendly material due to its destructive resourceconsumption nature and severe environmental impact. However it is one of the major construction materials being utilized globally. For development, the concrete industry has to plan and implement the better use of recycled materials in concrete making. Even though the utilization of recycled aggregates in the concrete industry has been taking place for many years, the promotion of this recycled material as an alternative has never been easy in the industry. Though lot of research has been reported on RAC, very little information is available about the effect of using recycled aggregate in the production of Fiber Reinforced High Performance Concrete (FRHPC). This paper presents the results of experimentation conducted to evaluate the strength and permeability characteristics of FRHPC produced with recycled coarse and fine aggregates. Three types of fibers viz., steel, glass and poly propylene fibers are used in the production of FRHPC. Compressive, tensile, flexural and shear strengths of Fiber Reinforced High Performance Recycled Aggregate Concrete (FRHPRAC) have been evaluated from the experimentation. Chloride ion permeability has been determined as measure of permeability of FRHPRAC. The results of the study show that recycled coarse and fine aggregates can be successfully used in the production of fiber reinforced high performance concrete.

Due to growing environmental concerns of the cement industry, alternative cementtechnologies have become an area of increasing interest. It is now believed that new binders are indispensable for enhanced environmental and durability performance. Geopolymer concrete (GPC) is an innovative method and is produced by complete elimination of ordinary Portland cement by fly ash. Geopolymer concrete has two limitations such as delay in setting time and necessity of heat curing to gain strength. Present research aimed to rectify these two limitations of GPC by replacing 10% of fly ash by OPC on mass basis. This paper presents the results of an experimental investigation on the mechanical properties of Geopolymer Concrete Composites (GPCC) containing 90% Fly ash (FA), 10% Ordinary Portland Cement (OPC) and alkaline liquids. The study analyses the impact of replacement of 10% of fly ash by OPC in the GPC mix on the mechanical properties such as density, Compressive Strength, Split Tensile strength and Flexural strength both in ambient curing at room temperature and heat curing at 60o C for 24 hours in hot air oven. Mixtures were prepared with alkaline liquid to fly ash ratio of 0.4. Based on the test results, empirical expressions were developed to predict split tensile strength and flexural strength of GPC as well as GPCC in terms of their compressive strength.

A parametric experimental study was carried out to analyse the local load carrying capacity and behaviour of hollow cylindrical RC specimens. This topic is part of a research program of shearbending behaviour of hollow cylindrical members. Local load carrying capacity is important in the case of partially loaded members. The parameters of loading setup and specimens under research were: the loaded area, distance between support elements, angle of loading/support elements, wall thickness, length of specimen, transversal and longitudinal reinforcement.Local failure modes of specimens were analysed through crack patterns and loaddisplacement diagrams. A mechanical model was created for calculation of the localbehaviour of members. The model is able to calculate the resistance of hollow cylindricalmembers against partial loads. Analysis of the effect of local resistance utilization on shearbending behaviour is possible using the proposed model.

The main objective of this study is to hybridize particle swarm optimization (PSO) and antcolony optimization (ACO) algorithms to propose an efficient algorithm for optimal designing of truss structures. Two types of serial integration of the algorithms are studied. In the first one, PSO is employed to explore the design space, while ACO is utilized to achieve a local search about the best solution found by PSO. This is denoted as serial particle swarm ant colony algorithm (SPSACA). In the second one, ACO works as the global optimizer while PSO acts as the local one. This is called as serial ant colony particle swarm algorithm (SACPSA). A number of structural optimization benchmark problems are solved by the proposed algorithms. Numerical results indicate that the SPSACA possesses better computational performance compared with the SACPSA and other existing algorithms.

The area of Constantine being located in a seismic zone, the management on the parameter of seismicity requires a precise micro zoning. The compilation of the historical seismic data of the area of Constantine, as those of the neighbouring areas will make it possible to determine the impact of the historical seismicity on the maximal establishment on the ground which will be an essential data for the establishment of the response spectrum for the study area.