Reassessment of Operating Engineering Steel Structures with the First Order Reliability Method and Bayesian Inference

Abstract

AbstractSince the commencement of regulations and standards, the sustainability of civil engineering structures has been a recurrent issue for the construction industry and society at large. The practical design process of engineering structures, in accordance with national guidelines, addresses uncertainties related to the stochastic nature of parameters such as climate loads, structural materials, or model limits. These uncertainties are taken into consideration through initial probabilistic assumptions and safety factors. However, safety factors derived mathematically based on code‐driven presumptions often fail to accurately represent the unique conditions of an individual structure. Although the development of structural health monitoring (SHM) techniques allows for a significant reduction in the uncertainty of the action and resistance, the ability to transform monitoring information to reevaluate the design capacity of existing structures is limited at the practical level. This paper provides an example of how design can be enhanced by incorporating sensor data and using the Bayesian inference and First Order Reliability Method (FORM), tailored to accurately reflect the current structural condition.