RESPONSE OF RC ELEMENTS EXPOSED TO FIRE

Abstract

Performance of concrete at high temperatures is of great importance, in particular for safety evaluation of concrete structures in building fires or in thermal hazard situations. In building, structural members are to be designed to satisfy the requirement for serviceability and safety limit states. One of the major safety requirements in the building design is the provision of appropriate fire safety measures for structural members. Analyzing structural elements i.e., beams and columns separately gives an insight of thermal profile and strength & stiffness degradation. Simulating the behaviour of boundary conditions has been a challenging task in order to reckon the behaviour of structural elements in the building assembly. Considerable amount of work has been done on material properties at elevated temperatures. There exists a large variation in these properties: Some of these properties have been codified. There is a need for comparative study of these properties available in literature and judge their suitability. In the age of advanced computational technology, computational methods prove supreme to model the job mathematically. This modelling may be done either by using commercially available finite element analysis packages or generating customized computer program. But the most important job lies in validating the modelling technique and the results obtained from these computational methods. In this dissertation, a detailed study has been made to compare the effect of different boundary conditions on thermal analysis of reinforced concrete structural members. Effect of cooling phase on structural members has also been studied. It presents studies showing the effect of fire scenario, load level and concrete models (unconfined concrete/confined concrete/preloaded concrete). Sequentially coupled thermal stress analyses were conducted on various RC elements using FEM based computational package ABAQUS to study their response during fire. An attempt was made to reduce the discrepancies between the simulated results and experimental results thus making them more accurate.