The IDDEA project aims to establish the tools and methods needed to perform safer and cost-efficient production, operation and life extension on topside piping. The project will develop intelligent defect detection and predictive structural integrity assessment tools to support decision-making during various phases of a piping lifetime. The corrosion resistance alloys (CRA) topside piping will be focused. The most critical R&D challenges include the development of 1) acceptance criteria for topside CRA piping, 2) defect detection and classification methods, 3) predictive structural integrity assessment method and 4) engineering tools for engineering critical assessment (ECA). The project will investigate the damage mechanisms of materials under different conditions (e.g., loading and environment), and thus establishing acceptance criteria for assessment of defects. The PAUT method will be further developed for defect detection especially in CRA piping. The digital solutions like machine learning, database and models will be applied to develop engineering tools to support decision-making related to predictive life extension. Finally, the innovation will be demonstrated by relevant industrial case studies such as decision-making regarding repair during piping production. In today's piping production, weld defects are not acceptable, which often leads to unnecessary and expensive repair. The knowledge-based tools developed in the IDDEA project will help the operators to make rational decisions regarding repair and future inspection planning.
Project leader: Solveig Hafstad
Institution: KVÆRNER AS