Uncertainty exists in many aspects of building simulation. A deterministic hygrothermal analysis may not sufficiently give a reliable guidance if a number of input variables are subject to uncertainty. In this paper, a probabilistic-based method was developed to evaluate the hygrothermal performance of building components. The approach accounts for the uncertainties from model inputs and propagates them to the outputs through the simulation model, thus it provides a likelihood of performance risk. Latin hypercube sampling technique, incorporated with correlation structure among the inputs, was applied to generate the random samples that follows the intrinsic relations. The performance of an internally insulated masonry wall was evaluated by applying the proposed approach against different criteria. Thermal performance, condensation and mould growth potential of the renovated wall can overall satisfy the requirements stipulated in multifold standards. The most influential inputs were identified by the standardized regression sensitivity analysis and partial correlation technique. Both methods deliver the same key parameters for the single and time-dependent output variables in the case study. The probabilistic method can provide a comprehensive risk analysis and support the decision-maker and engineer in the design and optimization of building components.

建筑物模拟的许多方面都存在不确定性。如果许多输入变量存在不确定性，确定性的湿热分析可能不足以提供可靠的指导。在本文中，开发了一种基于概率的方法来评估建筑构件的湿热性能。该方法考虑了来自模型输入的不确定性，并通过仿真模型将其传播到输出，因此提供了性能风险的可能性。拉丁超立方体采样技术结合了输入之间的相关结构，被用于生成遵循内在关系的随机样本。通过针对不同标准应用建议的方法来评估内部隔热砌体墙的性能。热性能 翻新墙的凝结和霉菌生长潜力总体上可以满足多重标准中规定的要求。通过标准化回归敏感性分析和偏相关技术，确定最具影响力的输入。在案例研究中，这两种方法为单个和随时间变化的输出变量提供相同的关键参数。概率方法可以提供全面的风险分析，并支持决策者和工程师进行建筑构件的设计和优化。在案例研究中，这两种方法为单个和随时间变化的输出变量提供相同的关键参数。概率方法可以提供全面的风险分析，并支持决策者和工程师进行建筑构件的设计和优化。在案例研究中，这两种方法为单个和随时间变化的输出变量提供相同的关键参数。概率方法可以提供全面的风险分析，并支持决策者和工程师进行建筑构件的设计和优化。