No abstract

No abstract

A general procedure to evaluate future trends in snow loads on structures is illustrated aiming to study influences of climate change at European scale, to assess its impact on the design of new structures as well as on the reliability levels of existing ones, also in view of definition of updated snow maps for new generation of Eurocodes. Starting from reliable and high quality registered meteorological data of daily temperatures, rain and snow precipitations at nine Italian weather stations, conditional probability functions of occurrence of snow precipitation, accumulation and melting have been preliminarily determined as functions of daily maximum and minimum air temperatures. Based on the above mentioned conditional probability functions, an innovative numerical procedure has been setup, that, starting from daily outputs of climate models in terms of maximum and minimum temperatures and water precipitation, allows, by means of Monte Carlo simulations, to determine the yearly maxima of snow loads for a convenient time interval, 40 years, and then, via the extreme value theory, the characteristic ground snow load. The proposed procedure has been preliminarily validated reproducing data series measured in the above mentioned weather stations in the period 1950–1990 and, subsequently, it has been applied to simulate the evolution of characteristic ground snow loads at these sites in the period 1981–2100. In the analysis, which considered 40 year time windows shifted ten years each time, they have been taken into account not only the forecast data derived by different climate models, but also the reference data, in the period 1981–2005, pertaining to the so-called historical experiments. Finally, the proposed procedure has been implemented in a more general methodology for snow map updating, in such a way that the influence of gridded data, predicted by global climate models, on extreme values of snow loads is duly assessed. Preliminary results demonstrate that the outlined procedure is very promising and allows to estimate the evolution of characteristic ground snow loads and to define updated ground snow load maps for different climate models and scenarios

No abstract

No abstract

Featured Application: This study provides a general methodology for the assessment of the impact of climate change on reliability of structures, combining observations and climate projections, to the aim of giving guidance for the adaptation of climatic load maps in structural Codes.Abstract: Climatic loads on structures are commonly defined under the assumption of stationary climate conditions; but, as confirmed by recent studies, they can significantly vary because of climate change effects, with relevant impacts not only for the design of new structures but also for the assessment of the existing ones. In this paper, a general methodology to evaluate the influence of climate change on climatic actions is presented, based on the analysis of observed data series and climate projections. Illustrative results in terms of changes in characteristic values of temperature, precipitation, snow, and wind loads are discussed for Italy and Germany, with reference to different climate models and radiative forcing scenarios. In this way, guidance for potential amendments in the current definition of climatic actions in structural codes is provided. Finally, the influence of climate change on the long-term structural reliability is estimated for a specific case study, showing the potential of the proposed methodology.

The evaluation of seismic performance of existing masonry buildings is a critical issue in assessing the seismic vulnerability of the built environment. With this aim, non-linear static analysis is commonly used, but results are influenced significantly by the collapse criteria adopted, as well as by the assumptions about material properties and drift capacity of masonry walls. A methodology for the probabilistic assessment of the seismic risk index is proposed by means of an original non-linear pushover type algorithm developed by the authors. The main sources of uncertainties related to masonry parameters and their influence on seismic risk indices are identified by means of sensitivity analysis. Response surfaces for the seismic risk indices are thus defined through general polynomial chaos expansion in order to quantify the uncertainties in the resulting seismic risk index. Finally, a seismic performance classification is presented to help stakeholders to manage risks and define priorities for seismic retrofit. The methodology together with the outcomes is illustrated for a set of existing masonry buildings that are part of the school system in the Municipality of Florence.

In consideration of the high vulnerability of the built environment, the assessment of seismic behavior of existing masonry buildings is a key topic in view of their retrofitting and reuse. Because masonry's behavior depends on complex nonhomogeneous, anisotropic, asymmetric, and nonlinear properties, the definition of suitable mechanical models is still a critical issue, especially for stone masonry. Structural analyses of existing masonry buildings in seismic-prone areas are thus significantly influenced by the adopted mechanical models and assumptions about their relevant masonry properties, which are characterized by large uncertainty. In this study, a procedure for the definition of masonry classes and probability density functions of relevant mechanical parameters, such as elastic modulus and shear modulus, is proposed. The general procedure is illustrated referring to a significant number of in situ double-flat-jack test results on stone masonry obtained by the authors during an ad hoc experimental campaign. Finally, combining information on masonry quality obtained by visual inspection with results of in situ tests, a Bayesian methodology is proposed for the updating of masonry mechanical parameters, thereby providing the basis for a more refined probabilistic assessment of the seismic risk index.