A Safety Risk Analysis of a Steel-Structure Building Using an Improved Controlled Interval and Memory Model

Abstract

Scholars and engineers have increasingly focused on the safety of steel-structure buildings. An accurate analysis can substantially reduce the collapse probability of these buildings. This paper proposes a novel risk analysis model to assess the safety of steel-structure buildings. The vector entropy method and weight clustering were used to improve the controlled interval and memory (CIM) model. The proposed model has the advantages of a straightforward modeling approach, strong adaptability, and logical relationships. The new strategy improves the reliability and stability of the CIM model results when the maximum membership principle is not applicable. The Jiangxi Exhibition Center in China, which has a steel truss roof, is used as a case study. The results indicate a high safety risk of the project and the need for maintenance and repair. The improved CIM model has higher stability and adaptability for analyzing the safety risks of steel structure than the standard CIM model.