Smart multiple attribute decision analysis framework for automatic fire damage level evaluation of concrete structures

Abstract

To achieve fire damage level evaluation of concrete structures under uncertainties, a smart multiple attribute decision analysis framework is proposed in this investigation by fusing evidential reasoning and particle swarm optimization. Based on the framework, multiple attributes can be aggregated together for fire damage level evaluation based on the chosen multi-source data directly. The framework has an excellent generality and a wide engineering application range, in which fire damage evaluation rules can be generated automatically without complex modeling. Two numerical examples of a concrete block and a concrete frame structure under high temperature are utilized to support the multiple attributes-based fire damage level evaluation framework. The evaluation results match well with the experimental results, which show that the framework can achieve reasonable fire damage level evaluation of concrete structures with an excellent convergence.