Influence of input uncertainty on the 1-D hygrothermal simulation of composite walls in China

In hygrothermal simulations, uncertainties in input parameters affect the reliability of outputs, potentially leading to erroneous judgments about building performance. This study proposes a probabilistic method to comprehensively evaluate input uncertainties in the simulated hygrothermal performance of 1-D composite walls in five thermal design zones in China. Specifically, input parameters are categorized into discrete (e.g., insulation type) and continuous (e.g., thermal conductivity) parameters. The discrete parameters form 160 basic simulation scenarios. For each scenario, 400 uniform random samples are generated within given ranges of continuous parameters using Latin hypercube sampling, resulting in 64,000 simulation cases. Heat flux, moisture flux, moisture content, interstitial condensation, mold growth and frost damage are used as indicators for the hygrothermal performance, and multiple linear regression analysis is used to determine the most influential continuous parameters. The results indicate that the thermal conductivity of insulation materials has the greatest influence on the average heat flux, interstitial condensation risk, mold growth risk, and freeze/thaw cycles. The moisture retention curve and vapor diffusion resistance factor of structural materials significantly influence the average moisture flux. The moisture retention curve of structural materials has the most influence on the average moisture content of the structural layer. This study elucidates the most critical input parameters for different thermal design zones in China and other similar climate regions.