Stochastic Petri-net models to predict the degradation of ceramic claddings

Abstract

In this study, a stochastic Petri net formalism is proposed to predict the degradation of ceramic claddings over time to understand how different environmental exposure conditions contribute to the overall degradation of these claddings. For that purpose, the degradation condition of 195 ceramic claddings located in Lisbon (Portugal) is evaluated through in situ visual inspections. In the first part of the study, a stochastic deterioration Petri net model is proposed to the entire sample. In the second part, the original sample is divided according to the environmental exposure conditions, evaluating the influence of these conditions on the deterioration process of ceramic claddings. Four main degradation agents are analysed: exposure to moisture; distance from the sea; orientation; and the wind-rain action. The results obtained reveal that Petri nets can accurately describe the deterioration process of ceramic claddings, providing relevant information regarding the performance of these claddings through their life-cycle and according to the environmental exposure conditions to which they are subject to. These results are extremely relevant for different practitioners, allowing adopting more sustainable and durable solutions in a design stage, as well as improving the durability of the ceramic claddings by carrying optimised maintenance plans and strategies.

Impact of Environmental Exposure Conditions on the Maintenance of Facades’ Claddings

“…Among the four constructive solutions, the main observations are different, and it is concluded that solar exposure has different impacts according to the solution adopted. This is in line with the results obtained in previous studies [7,17,39,40,[73][74][75]:…”

“…The optimal parameters of the degradation process are presented in Table 1, in terms of mean and standard deviation of the sojourn time in each degradation condition. The fit of the degradation process to the historical data (collected through in-situ visual inspections) was performed through a degradation model based on stochastic Petri nets, in which the choice of the best probability distribution that describes the degradation process is performed through the maximization of the logarithm of the likelihood [17]. The information presented in this table can be read in the following way: For a CTS, for the situation without impact of the environmental exposure conditions, a transition between conditions A and B, T A , takes, on average, 6.6 years to occur, with a standard deviation of 6.5 years.…”

“…Durability problems are likely to result from the simultaneous occurrence of different climate loads. The combined action of environmental agents should be considered, to deepen the knowledge on the real-life degradation phenomena [17]. For example, the orientation of the façade influences the action of several climate agents, such as solar radiation, temperature, damp, wind, and rain [2,16,18], on the surface of the cladding.…”

“…Reliable information on the service life of building materials and components is not only relevant to support decision-making, but also the base for practicing sustainable construction [24] and to develop effective maintenance strategies [25]. Service life prediction methodologies [7,26] have been developed to provide useful information on the degradation phenomena of building components, in real service conditions, and to know "how" and "when" to intervene [17].…”

“…The degradation of building components is a complex phenomenon [7] that presents a high level of randomness and uncertainty, whose stochastic nature should be recognized in the building management system research [17]. The climate, a significant aspect in the degradation process, is a complex system too.…”