A Fuzzy model for studying degradation kinetics of Genna Maria nuragic building

Marta Cappai

First

;Ulrico Sonna

Second

;Giorgio Pia

Last

2023-01-01

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Abstract

The Nuragic Sardinian civilization (ca. 1600–1020 BC) represents one of the most important Bronze Age cultures of the Western Mediterranean area. Today, the built heritage of this period can be found in the megalithic tombs, temples, villages and Nuraghi. These, with an estimated number ranging between 7.000 and 10.000, represent the distinctive prehistorical buildings and constitute a prominent feature of Sardinia's landscape. At present, a large number of Nuraghi are exposed to a series of pathogenic factors which substantially influence degradation kinetics (DGRK). Currently, only effective conservation and protection strategies could slow down the degradation process. The behaviour of structures and materials over time, the incompleteness of materials characterisation, the complexity of relationships and the randomness of future environmental and cultural conditions are all remarkable obstacles to the preservation of these structures. However, according to holistic approaches, some conceptual tools are now available to develop predictive models on the complex 'life' of an ancient building. In the present work, a new fuzzy model has been formalised in order to estimate DGRK of the Genna Maria site. It considers environmental parameters, properties of materials, weathering phenomena, anthropic action such as numerical and linguistic variables derived from instrumental measurements as well as direct observations. The modelling procedure has been carried out by considering the variables month per month. The results highlight that DGRK accelerates and slows down in different parts of the year. For April, May and December, model calculated a relevant degradation risk, while a lower possibility to have a significant decay has been recorded for August, September and October. Overall, the proposed model represents a tool that can usefully and explicitly encode uncertain knowledge and empirical experience and thus provide support for future decisions on site conservation.