Correction of prediction model output for structural design and risk-based inspection and maintenance planning

This paper presents a new methodology to calibrate structural reliability models output. The methodology combines data from experience and prediction models to correct the structural reliability models. The paper gives an overview of the techniques used for model calibrations, summarises the methodology in an overall discussion, and proposes data processing to sanitise sensitive information. The proposed methodology is inherently adaptable and can be applied to many other fields that require cost effective maintenance, as well as providing data for calibrating methods and codes.