Verification of existing structures based on updated design values

Assessment of existing structures is becoming a more and more important and frequent engineering task. Continued use of existing structures is of great significance due to environmental, economic and socio-political assets, growing larger every year. These aspects are particularly relevant to heritage buildings that always constitute a great historical, social and economic value. In common cases of existing structure reliability verification, or designing its reconstruction, the partial factor method is applied because it is possible to proceed based on common procedures for designing new structures. However, a problem can occur with existing structures: it's not always obvious if it is necessary to apply the same values of partial factors as when designing new structures. Sure enough during construction process and subsequent life, the structure may have undergone alteration, deterioration, misuse, and other changes to its as-built state. So one of the most important step of the whole assessment procedure of existing structures is performing inspection and tests, and evaluating results. With those information is possible to remove some uncertainties related to variables that define structure characteristics. This work investigates on Bayesian technique of reducing uncertainties in the field of structural engineering, and on how it's possible, applying those techniques, improving our knowledge about the reliability especially of existing structures. In order to do this, several steps are required: first of all, the basic knowledge about reliability analysis and safety concepts is presented. Then a new method of estimation of design values is showed. This method depends on statistical parameter of the variables considered and the reliability index $ \beta $, through which it's possible to assign a certain reliability to the structure. Criteria used to assess reliability index are fully illustrated. After this preparatory part, the main issue of the thesis, that is how it's possible to reduce variable uncertainties and perform verification with updated design values, will be deeply discussed. Finally this procedure will be applied to several examples and case studies, in order to perform verification with updated design values. Conclusions will be drawn from verification results