Abstract
Corrosion and corrosion fatigue are well recognized as principal causes for the aging of engineered systems and the attendant reduction in their reliability and safety. To meet the challenges of designing for a modern, competitive global market and for the life-cycle management of aging systems, it is essential to develop science-based methods for predicting the evolution of damage through corrosion and corrosion fatigue, and other time-dependent mechanisms, and incorporating them into a new paradigm for design. To this end, the use of a mechanistically based probability (versus statistically based parametric) approach is presented, and illustrated through considerations of corrosion and corrosion fatigue in airframe aluminum alloys. Its efficacy in predicting damage evolution and distribution is demonstrated through a comparison with long-term service data from an aircraft that had been in commercial service for 24 years.
