Structural Engineering Research Centre

About: Structural Engineering Research Centre is a facility organization based out in Chennai, India. It is known for research contribution in the topics: Finite element method & Fracture mechanics. The organization has 520 authors who have published 703 publications receiving 7298 citations.

Condition evaluation of existing reinforced concrete bridges using fuzzy based analytic hierarchy approach

Abstract: There is an urgent need for a systematic methodology for condition assessment of the bridges because the old bridges of most of the countries are inadequate to carry current-day traffic and satisfy the present codal provisions and even in newer bridges, deterioration caused by unforeseen service condition and deferred maintenance is of great concern. In view of this, an attempt has been made in this study to develop a systematic procedure and formulations for condition evaluation of existing bridges using Analytic Hierarchy Process in a fuzzy environment. Analytic Hierarchy Process (AHP) is an efficient decision making tool for complicated problems with multiple evaluation criteria and uncertainty. Fuzzy logic approach has been used to take care of the uncertainties and imprecision in the bridge inspector's observations. In this paper, first, a methodology has been proposed for condition ranking of number of reinforced concrete (RC) bridges. Then, based on the results obtained from prioritization, rating of the most deserved bridge has been carried out using MADM based fuzzy logic. Computer programs have been developed based on the formulations presented in this paper for evaluating condition of existing bridges and the details are presented in the paper. The methodology and its application are demonstrated through a case study. This methodology would certainly help the engineers and policy makers concerned with bridge management to overcome the problem related to prioritization and decision on funding related to rehabilitation of bridges.

Effect of fly ash and slag on the fracture characteristics of high performance concrete

Abstract: The premature deterioration of concrete structures in aggressive environments has necessitated the development of high performance concrete (HPC). The major difference between conventional concrete and HPC is essentially the use of chemical and mineral admixtures. The improved pore structure of HPC achieved by the use of chemical and mineral admixtures causes densification of paste-aggregate transition zone, which in turn affects the fracture characteristics. Hence, studies were taken up to investigate the effect of fly ash and slag on the fracture characteristics of HPC. Beam specimens (geometrically similar and single size variable notch) with locally available fly ash (25%) and slag (50%) as cement replacement materials were prepared and tested in a servo-controlled Universal Testing Machine (UTM) under displacement control. From the value of the peak load for each beam, various fracture parameters were calculated. The results show that there is a reduction in the fracture energy due to addition of fly ash or slag, which can be attributed to the presence of unhydrated particles of size larger than that of normal flaws in concrete. Also due to densification, the post peak behaviour is steeper for the fly ash or slag based HPC mixes. The results of the investigation are presented in this paper.

Optimal placement of sensors for structural system identification and health monitoring using a hybrid swarm intelligence technique

Abstract: Setting up a health monitoring system for large-scale civil engineering structures requires a large number of sensors and the placement of these sensors is of great significance for such spatially separated large structures. In this paper, we present an optimal sensor placement (OSP) algorithm by treating OSP as a combinatorial optimization problem which is solved using a swarm intelligence technique called particle swarm optimization (PSO). We propose a new hybrid PSO algorithm by combining a self-configurable PSO with the Nelder–Mead algorithm to solve this rather difficult combinatorial problem of OSP. The proposed algorithm aims precisely to achieve the best identification of modal frequencies and mode shapes. Numerical experiments have been carried out by considering civil engineering structures to evaluate the performance of the proposed swarm-intelligence-based OSP algorithm. Numerical studies indicate that the proposed hybrid PSO algorithm generates sensor configurations superior to the conventional iterative information-based approaches which have been popularly used for large structures. Further, the proposed hybrid PSO algorithm exhibits superior convergence characteristics when compared to other PSO counterparts.