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Special Session: Semi-probabilistic approach for performance assessment of existing structures
Conference: IPW 2020. International Probabilistic Workshop 2020 September 23-25, 2020, at University of Minho, GuimarĂ£es, Portugal.
Organizers: AndrĂ© Orcesi, Salvatore Di Bernardo

 

Papers
Special Session (SS8) Semi-probabilistic approach for performance assessment of existing structures IPW International Probabilistic Workshop 2020.

The application of design-orientated methods to the assessment of existing structures often leads to a high degree of conservatism, which may have severe economic, environment and socio-political consequences when it results in satisfactory structures being condemned as unsafe, thereby leading to an unnecessary investment of resources in replacement or retrofitting, with its associated dismantling (JRC report of CEN/TC250/WG2, 2015). The effects of the construction process and subsequent life of the structure, during which it may have undergone alteration, deterioration, misuse and other changes to its as-built (as designed) state, need to be taken into account. It is thus possible to obtain and gain more or less detailed information on a specific structure.

The partial safety approach considers the application of statistics and probability in the evaluation of the input data, the formulation of assessment criteria, and the determination of load and resistance factors. This approach allows easy calculations, while covering the variability in structural behaviour and loading. However, semi-probabilistic formats are not able to efficiency and correctly manipulate information obtained from measurements and inspections and their use for performance assessment of structures still represents a challenge. To overcome this limitation, a probabilistic approach has to be considered to re-calibrate partial factors. The Mini-Symposium intends to provide a broad forum for discussions about a semi-probabilistic framework for assessment of existing structures, recent developments and associated assumptions.







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