TAILIEUCHUNG - Handbook of Corrosion Engineering Episode 1 Part 9

Tham khảo tài liệu 'handbook of corrosion engineering episode 1 part 9', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 268 Chapter Four Modeling and Life Prediction The complexity of engineering systems is growing steadily with the introduction of advanced materials and modern protective methods. This increasing technical complexity is paralleled by an increasing awareness of the risks hazards and liabilities related to the operation of engineering systems. However the increasing cost of replacing equipment is forcing people and organizations to extend the useful life of their systems. The prediction of damage caused by environmental factors remains a serious challenge during the handling of real-life problems or the training of adequate personnel. Mechanical forces which normally have little effect on the general corrosion of metals can act in synergy with operating environments to provide localized mechanisms that can cause sudden failures. Models of materials degradation processes have been developed for a multitude of situations using a great variety of methodologies. For scientists and engineers who are developing materials models have become an essential benchmarking element for the selection and life prediction associated with the introduction of new materials or processes. In fact models are in this context an accepted method of representing current understandings of reality. For systems managers the corrosion performance or underperformance of materials has a very different meaning. In the context of life-cycle management corrosion is only one element of the whole picture and the main difficulty with corrosion knowledge is to bring it to the system management level. This chapter is divided into three main sections that illustrate how corrosion information is produced managed and transformed. The bottom-up approach Scientific models can take many shapes and forms but they all seek to characterize response variables through relationships with appropriate factors. Traditional models can be divided into two main categories mathematical or theoretical models and .

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