Time flies and it is summer now. I used to believe that there wouldn’t be any feeling of summer in UK because according to the weather forecast the highest temperature in July and August is around twenty centigrade. The highest temperature is twenty four in last week reported by BBC, but I felt as hot as in China where the temperature could be as high as forty in the same period. There should be some changes with regard to the parameters that characterize the effects of the weather on people and people’s feelings about the weather.
Coming back to our topic. What we are characterizing is the phenomenon of structural fatigue, risk to fatigue failure and methodologies to mitigate the risk or control the risk under target level. As you may be aware, this relates to material, structure, mechanics and management. Large uncertainties are associated with each of those aspects. My job is to characterize the uncertainties and develop reliable fatigue management methods. We take two steps to achieve that. Firstly, accurate fatigue prediction model is developed. That is to say we should predict the evolution of fatigue cracks accurately, which serves as basis for planning maintenance actions (inspection methods, inspection times, and repair rule). Uncertainties associated with wave environments, stress prediction, material properties and fatigue degradation process are considered by probabilistic modelling techniques. Secondly, maintenance actions are optimised with respect to risk and the associated costs, so that mitigation action can be taken to reduce risk with the minimum costs. In this step, we consider uncertainties in performance of inspection methods and effect of repair actions.
Currently we are concentrating on the first steps, developing fatigue degradation model which is employed to establish optimum maintenance actions. Fatigue itself is a rather complicated and stochastic phenomenon. It is influenced by so many factors such as materials, fabrication, post-welding treatments, local geometry, loading, etc. that it is hard to predict. Thus reliability methods are often employed to deal with the uncertainties involved. Many researchers have developed different models to take into account influence of different factors, but large discrepancies have been found among them. For fatigue life, the difference predicted by different models can be up to 10 times or more. In addition, the parameters in some models are difficult to determine. Some relies on specimen tests while others involve finite element modelling. This hinders their practical applications in engineering structures because specimen tests are expensive and can take a long time while finite element modelling needs profound professional knowledge in fracture mechanics.
In the context of maintenance planning, the fatigue degradation models should not only be accurate but also simple. Optimum maintenance actions are obtained by solving optimization formulations, which requires extensive computational efforts. We thus want the components in the optimization formulations are easy to calculate. An important component is probability of failure, which is calculated based on fatigue degradation model. We are thus targeting on developing accurate and relatively simple model to describe fatigue degradation. It should be noted that our main objective is to develop a reliable model for practical application in maintenance planning for engineering structures, and explaining physical mechanism of fatigue degradation is not a priority.
I hope you have understand the ‘what’ and ‘why’ of the first half part of our project. It is important as it will help you to catch quickly the ideas of my following blogs, in which I will update more on how to obtain the fatigue degradation model.