A Proposed Model for Accelerated Ageing Cycles in Durability Research

As part of a National research project the various research units examined problems and phenomena in the design of the various components used in the external “enclosures” of buildings: the logical approach in this project was to attempt to simulate, in the laboratory, the ambient actions which are active in the various climatic contexts, differentiating them for purposes of customized re-scaling. The Naples research unit therefore proposed to the other units a model for determining the aging cycle. This model uses an algorithm in which the input data comprises a series of climatic data which can be obtained from various sources (principally the air force). The output provides the duration of the subcycles (each one of which represents, and reproduces, a climatic season), temperatures, humidity, sunlight radiation, and rainfall to which the sample is subjected. In this way we obtain a kind of “virtual year” comprising the four seasons in succession, with different values for temperature, humidity, sunlight radiation and rainfall, with the values inserted those for the region and the time of year which represents the season in question. Climatic data was collected in advance from various official sources, covering a period no longer than the last 5 years, on account of the extreme variability in recent times. The final output is provided by a special simulation software. The model proposed is to be considered helpful: • to refine general principles of service life prediction tests, because in this manner, it is possible to have simulations specifically made for re-scaling, and homogeneity for all the researchers, in all contexts; • to compare data obtained from accelerated ageing tests, external exposure, or existing buildings. The test method is not bound to a specific service life prediction method. It is being possible to use it with the same goal and the same effectiveness in the Factor Method, in Engineering Methods and in Stochastic Methods, also. Data on performance over time of building components can be provided only after a reliable period of trialling, and so, experimentations on different components are needed for testing the method.