ABSTRACT The conservation state of buildings is of increasing interest due to the need to renovate aging building stock and provide a safe and healthy place for end users. Numerous uncertain factors have an impact on building condition, including environmental agents, building age, type of assets and maintenance. Previous studies have focused on identifying these factors, but the relationships among them remain unclear. This paper proposes a Bayesian network (BN) approach to develop a model for assessing a building’s condition. The BN model is based on an extensive review and evaluation of degradation causal factors supported by an analysis of 1974 defects and 5373 maintenance requests in forty buildings. The model was verified by sensitivity analysis, and the proposed approach was tested on an existing building. The model could be used as a supporting tool to identify renovation strategies that can enhance the conservation state of buildings and constructed assets.

中文翻译：

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建筑物和建筑资产的概率性能评估

摘要 由于需要翻新老化的建筑物并为最终用户提供安全和健康的场所，建筑物的保护状态越来越受到关注。许多不确定因素会影响建筑状况，包括环境因素、建筑年龄、资产类型和维护。以前的研究侧重于识别这些因素，但它们之间的关系仍不清楚。本文提出了一种贝叶斯网络 (BN) 方法来开发用于评估建筑物状况的模型。BN 模型基于对退化因果因素的广泛审查和评估，并得到了对 40 座建筑物中 1974 年缺陷和 5373 项维护请求的分析的支持。该模型通过敏感性分析进行了验证，并在现有建筑物上测试了所提出的方法。