Stochastic Petri net-based modelling of the durability of renderings

Abstract

In this study, a methodology to model and predict the life-cycle performance of building façades based on Stochastic Petri Nets is proposed. The proposed model evaluates the performance of rendered façades over time, evaluating the uncertainty of the future performance of these coatings. The performance of rendered façades is evaluated based on a discrete qualitative scale composed of five condition levels, established according to the physical and visual degradation of these elements. In this study, the deterioration is modelled considering that the transition times between these condition states can be modelled as a random variable with different distributions. For that purpose, a Stochastic Petri Nets model is used, as a formal framework to describe this problem. The model's validation is based on probabilistic indicators of performance, computed using Monte-Carlo simulation and the probability distribution parameters leading to better fit are defined as those maximizing the likelihood, computed using Genetic Algorithm. In this study, a sample of 99 rendered façades, located in Portugal, is analysed, and the degradation condition of each case study is evaluated through in-situ visual inspections. The model proposed allows evaluating: i) the transition rate between degradation conditions; ii) the probability of belonging to a given degradation condition over time; and iii) the mean time of permanence in each degradation condition. The use of Petri Nets shows to be more accurate than a more traditional approach based on Markov Chains, but

Nanomaterials’ Influence on the Performance of Thermal Insulating Mortars—A Statistical Analysis

“…In order to analyse, compare, and optimise new products, different approaches have been used [40,41], with one of these approaches being related to the use of multivariate statistical techniques [42][43][44][45]. These techniques have also been used to study cement-based products [46,47], allowing for the simplification of the interpretation of their performance, with particular emphasis on cluster analysis and Principal Components Analysis (PCA) [43,44,48,49].…”

Performance assessment of milk processing system using Petri nets

“…The failure pattern is considered to follow Weibull distribution and repair rate exponential distribution. Whereas in relevant studies performance analysis carried out by Sachdeva et al [14,15], Gupta and Tewari [3], Kumar et al [17,18] and more recently Gupta et al [11] used exponential failure as well as repair rates to formulate the mathematical performance model and evaluated system availability measures. For validation the approaches presented in mentioned studies have also been considered for modeling of the system under study.…”

“…These are assigned firing rates just as in SPN. Singh and Garg [9], Sachdeva et al [10,11], Thangamani [12], Kumar et al [13], Tavana [14], Ferreira et al [15] applied GSPN for modeling and availability analysis of different industrial systems.…”

Critical Analysis about Emerging Technologies for Building’s Façade Inspection

“…1 data sourced from References [42,47]. Figure 2 describes another case study, a natural stone cladding, directly adhered to the substrate, which was inspected using the global inspection system.…”