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Stochastic Petri net-based modelling of the durability of renderings

机译:基于随机Petri网的效果持久性建模

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摘要

In this study, a methodology to model and predict the life-cycle performance of building facades based on Stochastic Petri Nets is proposed. The proposed model evaluates the performance of rendered facades over time, evaluating the uncertainty of the future performance of these coatings. The performance of rendered facades 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 facades, 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 also allows developing future research to consider different environmental conditions, maintenance actions or inspections, amongst other aspects of life-cycle analysis of existing assets.
机译:在这项研究中,提出了一种基于随机Petri网的建模和预测建筑立面生命周期性能的方法。所提出的模型评估了随时间推移渲染的外墙的性能,评估了这些涂料未来性能的不确定性。根据由五个条件级别组成的离散定性等级,根据这些元素的物理和视觉退化来评估渲染立面的性能。在这项研究中,考虑到这些条件状态之间的过渡时间可以建模为具有不同分布的随机变量,从而对恶化进行建模。为此,使用随机Petri网模型作为描述此问题的正式框架。该模型的验证基于使用蒙特卡洛模拟计算的性能概率指标,而导致更好拟合的概率分布参数被定义为那些使用遗传算法计算的使可能性最大化的参数。在这项研究中,分析了位于葡萄牙的99个渲染外墙的样本,并通过现场视觉检查评估了每个案例研究的退化情况。提出的模型可以评估:i)降解条件之间的转化率; ii)一段时间内属于给定降解条件的概率; iii)每种降解条件下的平均持久时间。与基于Markov Chains的传统方法相比,Petri Nets的使用显示出更为准确的方法,而且还可以进行未来的研究,以考虑不同的环境条件,维护措施或检查以及对现有资产进行生命周期分析的其他方面。

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