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A novel diagnostic prognostic approach for rehabilitated RC structures based on integrated probabilistic deterioration models

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  • Ahmed Mohammed Abdelalim

Abstract

The task of maintaining the huge stock of structures provides both owners and engineers with financial and technical challenges. Building managers are increasingly faced with having to maintain their building assets more efficiently whilst reducing the short and long-term cost of rehabilitation. Several approaches employing a Markovian model have been adapted to the bridge structure domain; fewer in the domain of concrete buildings. The present paper describes a parallel approach to maintenance management used in bridge structures, but adapted to the maintenance of reinforced concrete buildings. The maintenance of several components of a concrete structural system is considered in the context of both yearly and longer-term maintenance planning. The significance of different components in relation to others in the system is determined by first conducting a failure mode effect and criticality analysis (FMECA) on all structural/non-structural elements. The FMECA permits developing a component criticality index from which their relative importance is assigned amongst the different building components. An optimisation of different possible maintenance actions is considered in relation to the cost of specified actions or replacement of components based on a multi-objective index (MOI). This index provides a means of relating competing maintenance objectives; that of controlling maintenance intervention costs and maintaining component condition ratings. It provides yearly maintenance costs of individual components for a given structural system over a long-term horizon that spans the life of the building.

Suggested Citation

  • Ahmed Mohammed Abdelalim, 2019. "A novel diagnostic prognostic approach for rehabilitated RC structures based on integrated probabilistic deterioration models," International Journal of Decision Sciences, Risk and Management, Inderscience Enterprises Ltd, vol. 8(3), pages 119-134.
  • Handle: RePEc:ids:ijdsrm:v:8:y:2019:i:3:p:119-134
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