Decay phenomena induced by environmental attacks, aging and/or damage due to long-term heavy loads can strongly influence the superficial and structural durability of stone masonry, including multiple leaves structures, which constitutes a substantial percentage of the historical heritage technique. The lifetime prediction and a precocious recognition of structural critical states would allow designing maintenance and repair strategies so to prevent total or partial damage. Considering the great randomness associated to different physical and mechanical decay processes, a probabilistic approach was successfully applied to model the results of salt decay of historical stone masonry, tested in the laboratory and on-site. Approaching the deterioration development as a stochastic process, the lifetime prediction was performed through the probability assessment for a system of reaching, or exceeding, a given damage threshold over time, thanks to useful applications of appropriate distributions to model the experimental fragility curves.
Service life design of stone masonry structures
Elsa Garavaglia;Giuliana Cardani;Anna Anzani
2018-01-01
Abstract
Decay phenomena induced by environmental attacks, aging and/or damage due to long-term heavy loads can strongly influence the superficial and structural durability of stone masonry, including multiple leaves structures, which constitutes a substantial percentage of the historical heritage technique. The lifetime prediction and a precocious recognition of structural critical states would allow designing maintenance and repair strategies so to prevent total or partial damage. Considering the great randomness associated to different physical and mechanical decay processes, a probabilistic approach was successfully applied to model the results of salt decay of historical stone masonry, tested in the laboratory and on-site. Approaching the deterioration development as a stochastic process, the lifetime prediction was performed through the probability assessment for a system of reaching, or exceeding, a given damage threshold over time, thanks to useful applications of appropriate distributions to model the experimental fragility curves.File | Dimensione | Formato | |
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