Hello everyone,
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.
